Turkish journal of

GERIATRICS
Volume: 27

Number: 2

Year: 2024

The Official Scientific Journal of Turkish Geriatrics Society
e-ISSN: 1307-9948

www.turkgeriatri.org

Volume: 27 • Issue: 2 • Year: 2024

www.turkgeriatri.org
e-ISSN: 1307-9948
The official scientific journal of Turkish
Geriatrics Society
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of
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On Behalf of Turkish Geriatrics SocietyYeşim GÖKÇE KUTSALTECHNICAL ASSISTANCE
Pelin ŞAHİN
BAYT Publishing Services

Turkish Journal of Geriatrics is indexed in: Thomson
Reuters Science Citation Index Expanded (SCI-Exp)and Social Sciences Citation Index (SSCI) since 2008.
And also in Scientific and Technological ResearchCouncil of Turkey (TÜBİTAK), Turkish Academic
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Published four times (March, June,
September, December) a year

CORRESPONDANCE
Turkish Geriatrics Society
www.turkgeriatri.org
info@geriatri.org
www.geriatri.dergisi.org
editor@geriatri.dergisi.org

Date of Publication: 30 June 2024

		 EDITOR-IN-CHIEF
		Yeşim GÖKÇE KUTSAL		EDITORIAL BOARD

Alfonso CRUZ-JENTOFTPeter FERRYÖnder İLGİLİ

Murat KOÇSercan ÖZYURT

Clemens TESCH-ROEMER		INTERNATIONAL ADVISORY BOARD
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TURKISH JOURNAL OF GERIATRICS

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TURKISH JOURNAL OF GERIATRICS

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Piers R, Albers G, Gilissen J, et al. Advance care planning in dementia: recommendations for healthcare
professionals. BMC Palliative Care 2018;17(88):1-17.(DOI:10.1186/s12904-018-0332-2).
2-More than 6 authors will be mentioned with the three authors’ names
Groessl EJ, Kaplan RM, Rejeski WJ et al. Physical Activity and Performance Impact Long-term Quality of Lifein Older Adults at Risk for Major Mobility Disability. Am J Prev Med 2019; 56 (1): 141-146. (DOI: 10.1016/j.
amepre.2018.09.006).
3-Books
BG Katzung. Special Aspects of Geriatric Pharmacology, In:Bertram G. Katzung,Susan B. Masters, Anthony J.
Trevor (Eds). Basic and Clinical Pharmacology. 10th edition, Lange, Mc Graw Hill, USA 2007, pp 983-90.
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nih.gov/search)v

TURKISH JOURNAL OF GERIATRICS

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V. Copy of “Certificate of Language Control and Correction”.

viEDITORIAL

FROM THE EDITOR IN CHIEF
Yeşim GÖKÇE KUTSAL

IX

ORIGINAL ARTICLE

THE PREDICTIVE POWER OF SIMPLE SYSTEMIC INFLAMMATORYPARAMETERS FOR IN–HOSPITAL MORTALITY IN
ELDERLY PATIENTS
Adem AZ, Yunus DOĞAN, Özgür SÖĞÜT, Tarık AKDEMİR
Volume: 27 • Issue: 2 • Year: 2024

CONTENTS

127

THE IMPACT OF MALNUTRITION AND FRAILTY ON MORBIDITY AND
MORTALITY IN GERIATRIC INTERNAL INTENSIVE CARE PATIENTS:
A PROSPECTIVE STUDY
135
Özlem ÖNER, Volkan HANCI, Mehmet Çağatay GÜRKOK, Hakan AKTUNA, Merve BALCIOĞLU,Bişar ERGÜN, Ferhan DEMİRER, Begüm ERGAN, Ali Necati GÖKMEN, Erdem YAKAA SINGLE-CENTER COMPARATIVE STUDY OF ENDARTERECTOMY
AND STENTING FOR SYMPTOMATIC CAROTID ARTERY DISEASE:DECISION-MAKING PROCESSES AND EARLY TO
MID-TERM OUTCOMES
Ömer Faruk ÇİÇEK, Hakan AKBAYRAK, Gökhan ÖZDEMİR, Fettah EREN, Mücahit Tahsin DEMİRTAŞ,Gözde ÖNGÜN, Atilla ORHAN, Mustafa BÜYÜKATEŞ

146

IS RED CELL DISTRIBUTION WIDTH CORRELATED WITH MORTALITYIN GERIATRIC PATIENTS UNDERGOING HIP FRACTURE SURGERY:
A PROSPECTIVE OBSERVATIONAL STUDY
157
Funda ATAR, Gülsen KESKİN, Burhan KURTULUŞ, Reyhan POLAT, Aslı DÖNMEZ
VARIABLES AFFECTING MORTALITY IN PATIENTS IN
PALLIATIVE CARE UNITS: OR IS IT STILL JUST ALBUMIN?
168
Abdullah YEŞİLKAYA, Müge ARIKAN, Büşra Nur TAŞDELEN, Emre MERİÇ, Ayşe AKHAN, Murat DİNDAR,
Arda ULUTAŞ, Didem ADAHAN, Ufuk KARADAVUT, Mehmet Murat ŞAHİN
TURKISH ADAPTATION, VALIDITY AND RELIABILITY STUDY OF
TREATMENT BURDEN QUESTIONNAIRE IN GERIATRIC PATIENTS
Figen AKAY, Tuba ERYİĞİT, Mehmet Fatih ÖS, Kamile SILAY, Güler Balcı ALPARSLAN

178

TRENDS IN CARBAPENEM RESISTANCE FROM 2018-2023
IN HOME HEALTH CARE: THE BOTTOM OF THE ICEBERG
Semiha SOLAK GRASSIE, Tuğçe ÜNALAN ALTINTOP

189

A POPULATION-BASED CROSS-SECTIONAL STUDY ON PHYSICALINTIMATE PARTNER VIOLENCE AFFECTING OLDER WOMEN IN
A PROVINCE OF NORTHERN TURKEY: PREVALENCE, ASSOCIATED
FACTORS, AND INTERGENERATIONAL TRANSMISSION OF
VIOLENCE
Raziye ÖZDEMİR, Elnaz KARAMELİKLİ, Merve AFACAN SATIOĞLU, Merve AKINCI, Zühal ÇAMUR

198

THE PREVALENCE OF SKIN DISEASES AMONG THE ELDERLY PATIENTSAPPLYING A TERTIARY DERMATOLOGY OUTPATIENT CLINIC:A RETROSPECTIVE ANALYSIS OF 2400 PATIENTS
211
Fatma ETGÜ, Yeliz KASKO ARİCİ
COMPARISON OF THE EFFICACY OF LUMBAR ERECTOR SPINAE PLANEBLOCK FOR CHRONIC AXIAL LOW BACK PAIN IN GERIATRIC ANDYOUNGER PATIENTS: RESULTS OF A RETROSPECTIVE STUDY
220
Ezgi CAN, Gökhan YILDIZ, Ömer Taylan AKKAYA, Rasime Pelin KAVAK, Gevher Rabia GENÇ PERDECİOĞLU,Damla YÜRÜK, Hüseyin Alp ALPTEKİN

www.turkgeriatri.org

The multiple problems of older individuals in this aging world are
well defined. Approaches to these problems can only achieve
success if they are based on the results of scientific researches
conducted in this field. Unfortunately, there is still concern thatolder persons are underrepresented in scientific researches,
which is considered a form of discrimination.

FROM THE EDITOR IN CHIEF

Although there are some barriers for the elderly to enroll inclinical researches, factors that facilitate their participation
include: 1) approval of family members, 2) the positive attitudeof the medical team toward the research, 3) the approach of theperson who communicates with the patient about the study, and
4) factors such as the patient’s high level of education, which
positively affect participation.
Unfortunately, there is no “standardized methodology” forincluding older patients with comorbidities and disabilities inclinical trials. It is important to design a protocol which is carefully
prepared and equipped with sufficient references that takes
ethical aspects into account.
In terms of compliance with the research, study protocols should
be appropriate for the admission of the elderly. They should
not include complex and difficult applications, and the researchshould not impose an economic burden on the patient.
The approach to be applied after the research should bedesigned at the very beginning of the study and approved by
the ethics committee. At the end of the study, elderly patientsshould be informed about the results of the research, monitored
for unwanted side effects for a while longer, and referred for
medically necessary treatments.
Yeşim GÖKÇE KUTSAL

www.turkgeriatri.org

ix

ORIGINAL ARTICLE

Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.386

THE PREDICTIVE POWER OF SIMPLE
SYSTEMIC INFLAMMATORY PARAMETERS
FOR IN–HOSPITAL MORTALITY IN
ELDERLY PATIENTS

2024; 27(2):127−134
 Adem AZ1. . . . . . . . . . . . . . . . . . . 
 Yunus DOĞAN2 . . . . . . . . . . . . . . 

 Özgür SÖĞÜT1. . . . . . . . . . . . . . . 

 Tarık AKDEMİR1. . . . . . . . . . . . . . 

ABSTRACTIntroduction: We evaluated the predictive power of systemic inflammatory
parameters, including the neutrophil/lymphocyte ratio, C-reactive protein/
albumin ratio, monocyte/eosinophil ratio, and platelet/lymphocyte ratio, for allcause in-hospital mortality in elderly.
Materials and Method: This single–center and retrospective study enrolled
46,563 patients aged ≥65 years who presented to the emergency department
due to various complaints from June 2019 to June 2022. We evaluated thedemographics, clinical characteristics, laboratory data, and clinical outcomesof the patients.

CORRESPONDANCE
1Adem AZ

Phone
e-mail: +905301007117: adem.aaz@gmail.com

Received : Apr 12, 2024
Accepted : May 19, 2024

1 Haseki Training and Research Hospital,

Department of Emergency Medicine,İstanbul, Turkey

2 Muş State Hospital, Department ofEmergency Medicine, Muş, Turkey

Results: A total of 3,385 hospitalized patients, 1,808 males and 1,577
females, were included in the study. The average age was 76.25±7.35 years.
The overall mortality rate was 11.73%. Nonsurvivors had significantly elevatedneutrophil/lymphocyte, C-reactive protein/albumin, monocyte/eosinophil, andplatelet/lymphocyte ratios compared to survivors (p=0.0001 for all comparisons).
Elevated neutrophil/lymphocyte and C-reactive protein/albumin ratios were
determined as independent predictors of mortality. A neutrophil/lymphocyte
ratio ≥9.41 had 46.97% sensitivity and 79.99% specificity for predicting mortality.
While the positive predictive value was 23.7%, the negative predictive value was
91.9%. Additionally, a C-reactive protein/albumin ratio ≥13.18 was identified as
the cut-off for mortality, with 57.07% sensitivity and 69.91% specificity. Its positive
and negative predictive values were 20.1% and 92.5%, respectively.
Conclusion: Mean serum neutrophil/lymphocyte and C-reactive protein/
albumin ratios on hospital admission were associated with all-cause mortality
in hospitalized patients aged ≥65 years. However, their sensitivity and positive
predictive value were relatively low. Nevertheless, negative predictive value forboth were significantly high. This implies that these parameters could be used
to determine the elderly at a lower risk of mortality.
Keywords: Aged; Biomarkers; Decision Making; Mortality.

1272024; 27(2):127−134

INTRODUCTION
The global population is gradually aging. Agedpatients visit the emergency department (ED) more
frequently than young people do (1). The elderly
typically presents to the ED with atypical complaints
and findings. Due to comorbidities and polydrug
use, the diagnosis and treatment of these individuals
may be delayed (1, 2). Furthermore, older patientsare at high risk of recurrent ED visits, hospitalization,
morbidity, and mortality (3). Although numerous
risk scores have been developed to identify at-risk
individuals, none offer highly accurate predictions.
Infective parameters, such as neutrophil/lymphocyte ratio (NLR), C-reactive protein/albumin(CRP/Alb) ratio, monocyte/eosinophil ratio (MER),
and platelet/lymphocyte ratio (PLR), are simple,
rapidly accessible, and widely available markers ofinflammatory status. NLR has been linked to the
prognosis of infectious disorders, such as sepsis
and bacteremia (4). NLR has also been associatedwith the clinical outcomes of noncommunicablediseases, such as acute myocardial infarction andstroke (5, 6). In a study of 5,166 elderly patients,
CRP/Alb ratio was indicative of all-cause in-hospitalmortality (7). Chen et al. reported that a low MER
is linked to mortality and a poor prognosis in casesof acute ischemic stroke (8). Age-related chronic
inflammation is a risk factor for morbidity andmortality in the elderly (9). Infective parameters,such as NLR, PLR, MER, and CRP/Alb ratios, may be
predictive of mortality and morbidity in the elderly.
We investigated the predictive power of NLR,
PLR, MER, and CRP/Alb serum administration atadmission with respect to all-cause in-hospitalmortality in elderly patients presenting to the ED.

MATERIALS AND METHOD
Ethics committee approval and patientconsent
This study was conducted in accordance with the
1989 Declaration of Helsinki and was approved by128

the institutional review board of Haseki Research
and Training Hospital, Istanbul, Türkiye (approval
no. 2022/198). The institutional review board did not
request patient consent to access medical records
since there were no potentially identifiable markers
or patient identifiers.
Study design and settingThis single-center, retrospective, and observational
study enrolled 46,563 consecutive patients aged ≥65 years who presented to the ED from June 2019
to June 2022. Data on patients aged ≥ 65 years
who visited the ED with any medical problem werecollected from the hospital’s automated records andarchives. We assessed the patients’ demographic
information (age and sex), initial complaints anddiagnoses, comorbidities, vital signs, laboratory
parameters (leukocyte, neutrophil, lymphocyte,
eosinophil, monocyte, and platelet counts and CRP
and albumin levels), clinical outcomes (discharge,
hospitalization, intensive care unit admission,and mortality), and Glasgow Coma Scale (GCS)
and quick Sequential Organ Failure Assessment(Q-SOFA) scores. The patients were divided
into survivors and nonsurvivors, and the serum
systemic inflammatory markers of the two groups
at admission were compared to identify factors
associated with mortality.
Outcome definition
We evaluated the abilities of the NLR, PLR, MER,
and CRP/Alb values to predict all-cause in-hospitalmortality in elderly patients.
Study population and sampling
To reduce selection bias, all patients who met theeligibility criteria during the study period were
included. We enrolled 46,563 consecutive adultpatients aged ≥ 65 years who visited the ED withany medical problem. Of these individuals, 35,087
discharged patients were excluded. A further 3,316

THE PREDICTIVE POWER OF SIMPLE SYSTEMIC INFLAMMATORYPARAMETERS FOR IN–HOSPITAL MORTALITY IN ELDERLY PATIENTS

were excluded because their data could not be
accessed. A total of 3,936 patients were excluded
because of trauma-related injuries and 839 patients
because of a history of hematological diseases,
such as leukemia or myelodysplastic syndrome.
Ultimately, 3,385 patients were analyzed (Figure 1).

Statistical analysis
Data analysis was conducted using SPSS software(version 15.0 for Windows; SPSS Inc., Chicago, IL).
Categorical variables (sex and age) are expressed
as numbers (n) and percentages (%). Numerical
data are expressed as means, standard deviations,Figure 1. Flowchart.

median, and interquartile range (IQR). Intergroupcomparisons (survivors vs. non–survivors) wereconducted by chi–squared and Student’s
independent t–tests for normally distributed
variables (e.g., sex and age) and Mann–Whitney
U–test for non–normally distributed variables(e.g., leukocyte, neutrophil, lymphocyte, andthrombocyte counts). Logistic Regression analysis
was conducted to determine the factors associatedwith mortality. Receiver operating characteristic
analysis was performed to determine the NLR,
PLR, MER, and CRP/Alb cut–off values. The alphasignificance level was set at p < 0.05.

RESULTSThis study involved 3,385 hospitalized patients,
comprising 1,808 males (53.41%) and 1,577 females(46.59%), with an average age of 76.25 ± 7.35 years.
The overall mortality rate was 11.73% (n = 397).
Table 1 lists the patients’ demographic and clinicalcharacteristics. The sex and age of the survivors
and nonsurvivors differed significantly (p = 0.025
and p = 0.0001, respectively). The nonsurvivors hada significantly higher Q-SOFA score and a lower
GCS score than the survivors (p = 0.0001 for bothcomparisons). Moreover, the nonsurvivors had
significantly elevated NLR, MER, PLR, and CRP/Alb
values compared with the survivors (p = 0.0001 for
all comparisons).
Multivariate logistic regression analysis identified
increased age (odds ratio [OR]: 1.05, 95% confidence
interval [CI]: 1.03–1.07; p = 0.0001), male gender (OR:1.52, 95% CI: 1.14–2.01; p = 0.009), higher Q-SOFA(OR: 4.72, 95% CI: 3.68–6.03; p = 0.0001) score, and129

2024; 27(2):127−134

Table 1. Comparison of demographic, clinical and laboratory characteristics in surviving and non–surviving patients.

Characteristic
Sex

Male

FemaleAge, years

Survivors(n = 2,988)

Non–survivors(n = 397)

n (%)

n (%)

1,575 (52.71)

233 (58.69)

1,413 (47.29)

164 (41.31)

mean ± SD

mean ± SD

p*
0.025

75.97 ± 7.25

78.29 ± 7.85

0.0001

Lengths of stay

11.56 ± 6.00

8.62 ± 7.10

0.00010.62 ± 0.90

2.38 ± 0.73

0.0001GCS

13.46 ± 2.80

7.95 ± 3.48

0.000113.37 ± 2.62

12.97 ± 2.81

0.004

WBC (10^3/uL)

11.14 ± 5.11

13.71 ± 6.77

0.00018.44 ± 4.88

10.92 ± 6.46

0.0001

Lymphocyte (10^3/uL)

1.86 ± 1.25

1.88 ± 1.99

0.736

Q-SOFA

Hemoglobin (g/dL)

Neutrophil (10^3/uL)

Thrombocyte (10^3/uL)

244.67 ± 87.12

236.69 ± 97.75

0.091

Monocyte (10^3/uL)

0.68 ± 0.37

0.77 ± 0.54

0.016

Eosinophil (10^3/uL)

0.12 ± 0.16

0.07 ± 0.13

0.000152.15 ± 77.54

99.99 ± 103.91

0.0001

Median (IQR)

Median (IQR)

CRP (mg/L)
NLR

4.41 (2.55–8.38)

8.02 (3.55–16.61)

0.00018.60 (3.56–38.05)

44.37 (8.5–144.29)

0.0001144.17 (98.47–220.7)

173.24 (98.1–314.95)

0.0001

4.16 (1.26–18.31)

17.70 (3.58–56.75)

0.0001MER

PLR

CRP/Alb

Note: Data are expressed as numbers (n) and percentages (%), means, standard deviations (SD), median, and interquartile range (IQR). *Intergroup comparisons (Survivors vs. non–survivors) were conducted using chi–squared and Student’s independent t–tests for normally distributed
data (e.g., sex and age) and the Mann–Whitney U test for non–normally distributed data (e.g., leukocyte, hemoglobin neutrophil, lymphocyte,
thrombocyte counts, and etc.).
Abbreviations: Q–SOFA, quick Sequential Organ Failure Assessment; GCS, Glasgow Coma Scale; WBC, white blood cell; CRP, C–reactive protein; NLR, neutrophil/lymphocyte ratio; MER, monocyte/eosinophil ratio; PLR, platelet/lymphocyte ratio; CRP/Alb, C–reactive protein/albumin
ratio.

Table 2. Multivariate logistic regression analysis to determine mortality.
Age, yearspOR

95% CI

0.00011.05

1.03–1.07

0.009

1.52

1.14–2.01

Q-SOFA

0.0001

4.72

3.68–6.03

0.127

0.92

0.88–1.02

NLR

0.003

1.03

1.01–1.05

MER

0.004

1.00

1.00–1.01

0.241

1.00

0.98–1.01

CRP/Alb

0.00011.02

1.01–1.03

Sex (male)

GCS

PLR

Abbreviations: OR, odds ratio; CI, confidence interval; Q–SOFA, quick Sequential Organ Failure Assessment; GCS, Glasgow Coma Scale; NLR,
neutrophil/lymphocyte ratio; MER, monocyte/eosinophil ratio; PLR, platelet/lymphocyte ratio; CRP/Alb, C–reactive protein/albumin ratio.

130THE PREDICTIVE POWER OF SIMPLE SYSTEMIC INFLAMMATORYPARAMETERS FOR IN–HOSPITAL MORTALITY IN ELDERLY PATIENTS

elevated NLR (OR: 1.03, 95% CI: 1.01–1.05; p =0.003) and CRP/Alb (OR: 1.02, 95% CI: 1.01–1.03; p =0.0001) values as independent predictors of mortality
in hospitalized patients aged ≥ 65 years admitted to
the ED with any medical problem (Table 2).
An NLR ≥ 9.41 had 46.97% sensitivity and 79.99%
specificity for predicting mortality, with an area
under the curve (AUC) of 0.651 (95% CI: 0.635–

0.667). While the positive predictive value (PPV)
was 23.7%, the negative predictive value (NPV) was
91.9%. In addition, a CRP/Alb ≥ 13.18 was identified
as the cutoff for mortality, with 57.07% sensitivity and69.91% specificity (AUC: 0.769, 95% CI: 0.741–0.796).
Its PPV and NPV were 20.1% and 92.5%, respectively(Table 3 and Figure 2).

Table 3. Systemic inflammatory parameters for determining mortality in elderly.
Criterion

AUC

SE

95% CI

Sensitivity

Specificity

PPV

NPV

LR (+)

NLR ≥ 9.41

0.651

0.016

0.635-0.667

46.97

79.99

23.7

91.9

2.35

MER ≥ 31.11

0.689

0.015

0.673-0.704

57.32

73.09

22.0

92.8

2.13

PLR ≥ 199.71

0.564

0.016

0.547-0.581

44.19

71.65

17.1

90.6

1.56

CRP/Alb ≥ 13.18

0.668

0.016

0.652-0.684

57.07

69.91

20.1

92.5

1.90

Abbreviations: AUC, Area under the curve; SE, Standard error; CI, Confidence interval; PPV, Positive predictive value; NPV, Negative predictive
value; LR (+), Likelihood Ratio; NLR, neutrophil/lymphocyte ratio; MER, monocyte/eosinophil ratio; PLR, platelet/lymphocyte ratio; CRP/Alb,
C–reactive protein/albumin ratio.

Figure 2. Specificity and sensitivity of the serum
systemic inflammatory parameters
including NLR, PLR, MER, and CRP/Alb
values, for determining the mortality in
hospitalized patients aged 65 and olderusing ROC curves.

Abbreviation: NLR, neutrophil/lymphocyte ratio; MER, monocyte/eosinophil ratio;
PLR, platelet/lymphocyte ratio; CRP/Alb, C–reactive protein/albumin ratio.

1312024; 27(2):127−134

DISCUSSION
Our findings demonstrate the possibility of using
NLR, PLR, MER, and CRP/Alb to predict all-cause
in-hospital mortality in elderly patients admitted to
the ED.
Elderly patients frequently present to the EDwith unusual symptoms, comorbidities, drug use,and delayed diagnosis (1, 2). Emergency physiciansneed fast, simple, low-cost, repeatable, and widely
available markers of medical conditions in theelderly. Ratio indices are increasingly used to predictthe clinical outcomes of patients who present to the
ED. For example, NLR, PLR, MER, and CRP/Alb are
easily calculated and predictive of clinical outcomes(4–11). The key finding of this study was that NLR
and CRP/Alb values were independent predictorsof mortality in hospitalized patients aged ≥ 65
years; however, their sensitivity and PPV values wererelatively low.
NLR has been linked to the clinical outcomesof various diseases and may be a prognostic
indicator of infectious disorders (4–6, 10, 11). NLR
was independently associated with 28-day mortality
in patients with severe sepsis and septic shock(10). In addition, NLR was associated with a highmortality rate in acute myocardial infarction cases(5). In a study with 5,056 patients, NLR was related
to poor outcomes in unspecified critical illnesses(11). Similarly, our study demonstrated that NLR
at ED admission was independently predictive of
all–cause mortality in patients aged ≥ 65 years. The
mechanism underlying the relationship between
NLR and noncommunicable disease mortality
is unclear. Song et al. hypothesized that NLR isassociated with mortality because it represents an
imbalance in the inflammatory response triggeredby acute illness (9). Chronic inflammation, which
has been linked to aging, is another possibility (12).
Although NLR was found to be associated withmortality in the hospitalized elderly in our study, itssensitivity and PPV were relatively low. In a study bySong et al., an NLR > 6 demonstrated a sensitivity
132

of 62.86% and a specificity of 69.93% for predicting
mortality (9). Reflecting our findings, the sensitivity
and specificity of NLR in their study were notsufficient for clinical decision-making.
PLR and MER values are associated withprognosis and clinical outcomes in various clinicalconditions (8, 13–15). In a study involving 280
patients with acute ischemic stroke, a high MER
was related to poor clinical outcomes and mortality(8). MER has been correlated with short- and longterm mortality in ST-elevation myocardial infarction(13). In addition, an elevated MER predicts longterm mortality in pulmonary embolism patients (14).
Moreover, mortal patients with acute exacerbationof chronic obstructive pulmonary disease had
elevated NLR and PLR values (15). Similarly, in
our study, nonsurvivors had significantly elevated
MER and PLR values compared with survivors,
suggesting that these markers may be useful for
predicting clinical outcomes. However, multivariate
logistic regression analysis indicated that neither
PLR nor MER can reliably and independently predictmortality in hospitalized elderly patients.
An elevated level of CRP, an acute-phase reactant,
has been linked to the prognosis of ischemic
diseases, infections, and malignancies (16). Serum
albumin level is a sensitive indicator of nutritional
status. Hypoalbuminemia is associated withincreased hospital mortality among older patients(17). CRP and albumin are prognostic markers invarious clinical scenarios, but their combination can
provide inflammatory and nutritional information.
Among 811 elderly patients, CRP/Alb ratio wasfound to be predictive of all-cause mortality (7).
Kaplan et al. (18), Sogut et al. (19), and Bai et al.
(20) reported that CRP/Alb value is a significant
predictor of a poor clinical outcome in patientswith acute pancreatitis, acute coronary syndrome,and neurocritical illness, respectively. In our study, amean CRP/Alb ≥ 13.18 was identified as the cutoff
for predicting mortality, with 57.07% sensitivity and69.91% specificity among patients aged ≥ 65 years
admitted to the ED with any medical condition.

THE PREDICTIVE POWER OF SIMPLE SYSTEMIC INFLAMMATORYPARAMETERS FOR IN–HOSPITAL MORTALITY IN ELDERLY PATIENTSThe strength of our study is the large sample size
(46,563 patients). However, this study also has several
limitations. This was a retrospective observational
study conducted at a single center, which increases
the possibility of undiscovered confounding factors
and restricts the generalizability of the findings. In
addition, the primary outcome was all-cause inhospital mortality. Despite the large sample size,
there were only 397 mortalities, and we could notanalyze the causes of mortality. These issues should
be considered in future studies.

REFERENCES
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Funding Sources: The author(s) received nofinancial support for this work, authorship, and/or
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133-137. (DOI: 10.1016/j.ajem.2020.01.044).

Data Availability Statement: The data
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septic patients. Am J Emerg Med 2017; 35 (2): 234239. (DOI: 10.1016/j.ajem.2016.10.055)

CONCLUSIONS
Our study identified elevated NLR and CRP/
Alb values as potential systemic inflammatory
parameters for predicting in-hospital mortality inpatients aged ≥ 65 years. However, the PPV for both
NLR and CRP/Alb was found to be low, suggestingthat these parameters may not be strong indicatorsof mortality. Moreover, the sensitivity and specificity
values for both parameters were not reliable enoughfor use in clinical decision-making. Nevertheless, theNPVs for NLR and CRP/Alb were significantly high.
This implies that NLR values < 9.41 and CRP/Alb
values < 13.18 might be safely used by clinicians to
identify elderly patients at a lower risk of in-hospitalmortality.
Statement of Ethics: This study was approvedby the Institutional Review Board of Haseki Research
and Training Hospital, Istanbul, Turkey (approval no.
2022/198).
Conflict of interest statement: The authors
declare no competing interests.

1332024; 27(2):127−134

11. Salciccioli JD, Marshall DC, Pimentel MA, Santos
MD, Pollard T, Celi LA, et al. The association between the neutrophil–to–lymphocyte ratio and mortality in critical illness: an observational cohort study.
Crit Care 2015; 19 (1): 13. (DOI: 10.1186/s13054-0140731-6).

16. Emerging Risk Factors Collaboration; Kaptoge S, Di
Angelantonio E, et al. C–reactive protein concentration and risk of coronary heart disease, stroke, andmortality: an individual participant meta–analysis.
Lancet 2010; 375 (9709): 132-140. (DOI: 10.1016/
S0140-6736(09)61717-7).

12. Bandeen–Roche K, Walston JD, Huang Y, Semba
RD, Ferrucci L. Measuring systemic inflammatory
regulation in older adults: evidence and utility. Rejuvenation Res. 2009; 12 (6): 403-410. (DOI: 10.1089/
rej.2009.0883).

17. Hannan JL, Radwany SM, Albanese T. In–hospitalmortality in patients older than 60 years with very low
albumin levels. J Pain Symptom Manage 2012; 43 (3):631-637. (DOI: 10.1016/j.jpainsymman.2011.04.009).

13. Deng X, Wang X, Shen L, et al. Association of eosinophil–to–monocyte ratio with 1–month and long–term
all–cause mortality in patients with ST–elevation myocardial infarction undergoing primary percutaneous coronary intervention. J Thorac Dis 2018; 10 (9):5449-5458. (DOI: 10.21037/jtd.2018.09.27).
14. Külahçıoğlu Ş, Tokgöz HC, Akbal ÖY, et al. Eosinophil–to–Monocyte Ratio as a Candidate for a Novel
Prognostic Marker in Acute Pulmonary Embolism:
Is it a Consumptive Mechanism? Anatol J Cardiol
2022; 26 (9): 717-724. (DOI: 10.5152/AnatolJCardiol.2022.1780).
15. Yao C, Liu X, Tang Z. Prognostic role of neutrophil–lymphocyte ratio and platelet–lymphocyte ratio
for hospital mortality in patients with AECOPD. Int
J Chron Obstruct Pulmon Dis 2017; 12: 2285-2290.
(DOI: 10.2147/COPD.S141760).

134

18. Kaplan M, Ates I, Akpinar MY, et al. Predictive valueof C–reactive protein/albumin ratio in acute pancreatitis. Hepatobiliary Pancreat Dis Int 2017; 16 (4): 424430. (DOI: 10.1016/S1499-3872(17)60007-9).
19. Söğüt Ö, Akdemir T, Can MM. Prognostic value of
the C–reactive protein to albumin ratio in patients
undergoing primary percutaneous coronary intervention for ST–segment elevation myocardial infarction. Turk J Med Sci 2021; 51 (3): 1281-1288. (DOI:
10.3906/sag-2003-188).
20. Bai M, Wu Y, Ji Z, et al. Prognostic value of C–reactive protein/albumin ratio in neurocritically ill patients. Minerva Anestesiol 2019; 85 (12): 1299-1307.
(DOI: 10.23736/S0375-9393.19.13625-5).

ORIGINAL ARTICLE

Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.387

THE IMPACT OF MALNUTRITION ANDFRAILTY ON MORBIDITY AND MORTALITYIN GERIATRIC INTERNAL INTENSIVE CARE
PATIENTS: A PROSPECTIVE STUDY

2024; 27(2):135−145 Özlem ÖNER1. . . . . . . . . . . . . . . .

 Volkan HANCI1 . . . . . . . . . . . . . . 

 Mehmet Çağatay GÜRKOK2 . . . . 
 Hakan AKTUNA2. . . . . . . . . . . . . .

 Merve BALCIOĞLU3. . . . . . . . . . . 
 Bişar ERGÜN3 . . . . . . . . . . . . . . . 
 Ferhan DEMİRER3. . . . . . . . . . . . 

 Begüm ERGAN4. . . . . . . . . . . . . . 

 Ali Necati GÖKMEN1 . . . . . . . . . . 
 Erdem YAKA5. . . . . . . . . . . . . . . . 

CORRESPONDANCE
1Özlem ÖNERPhone
e-mail: +905062876951: namdaroner@gmail.com

Received : Apr 13, 2024
Accepted : May 21, 2024

1 Dokuz Eylul University, Department

Of Anesthesiology And Reanimation,
Subdivision of Critical Care Medicine, Izmir,
Turkey2 Dokuz Eylul University, Department ofGeneral Surgery, Subdivision of Critical
Care Medicine, Izmir, Turkey

3 Dokuz Eylul University, Department of

ABSTRACTIntroduction: This study aims to assess the impact of malnutrition and frailty
on morbidity and mortality in geriatric patients in the internal intensive care unit.
Materials and Method: The study is prospective, descriptive, and crosssectional in design, conducted at intensive care unit. Demographic data,
anthropometric measurements, clinical evaluations, and laboratory parameters
are recorded for each patient. Various nutritional screening tools such as
the modified NUTRIC score, Subjective Global Assessment, Nutritional Risk
Screening, Mini Nutritional Assessment - Short Form, and frailty assessment
scales like Edmonton Frailty Scale and Clinical Frailty Scale are used.
Results: The patients were divided into two groups: survivors and nonsurvivors. The mean Nutritional Risk Screening -2002 score was 5.20±0.70 for thesurvivors group and 6.15±0.57 for the non-survivors group (p<0.001). The mean
Mini Nutritional Assessment - Short Form score was 8.20±0.82 for the survivors
group and 6.46±1.02 for the non-survivors group (p<0.001). According to themodified NUTRIC score, 40 patients (97.6%) in the non-survivors group were athigh risk of malnutrition (p<0.001). According to the Edmonton Frailty Score, inthe non-survivors group, 1 patient (2.4%) was classified as light frail, 21 patients(51.2%) as mild frail, and 19 patients (46.3%) as severe frail (p<0.001). The mean
Clinical Frailty Score was 5.89±0.99 for the survivors group and 8.0±0.0 for the
non-survivors group (p<0.001).
Conclusion: Due to the significant prevalence of malnutrition and frailty inthe critical patient population being monitored in the intensive care unit, bothconditions should be regularly assessed.
Keywords: Intensive Care Unit; Malnutrition; Frailty; Mortality; Geriatrics.

Internal Medicine, Izmir, Turkey

4 Dokuz Eylul University, Department of

Pulmonary, Subdivision of Critical Care
Medicine, Izmir, Turkey

5 Dokuz Eylul University, Department of

Neurology, Subdivision of Critical Care
Medicine, Izmir, Turkey

1352024; 27(2):135−145

INTRODUCTION
The global demographic landscape is undergoinga notable shift with a marked increase in the elderly
population, as highlighted by data from the World
Health Organization. Projections suggest that the
proportion of individuals aged 60 and above will
escalate from 12% in 2015 to 22% by 2050 (1). This
demographic trend translates into a corresponding
rise in admissions of vulnerable and frail elderly
individuals to Intensive Care Units (ICU) (2). Notably,alongside the surge in patient numbers, there is adiscernible elongation in the duration of ICU stays.
Specifically, individuals aged seventy-five and older
account for a staggering 70-fold increase in ICU bed
days per annum compared to their counterparts
under sixty-five years old (3). The utilization ofsubstantial ICU resources, encompassing bed
occupancy and financial outlays, by the elderly
population underscores the persistent challenge
confronting ICU personnel in managing geriatricpatients (4).
In the elderly patient population, various factors
such as cognitive impairment, comorbidities,
polypharmacy, depression, and anorexia cancompromise oral intake and disrupt nutrition (5).
Moreover, this demographic is particularly susceptible
to the detrimental effects of malnutrition, attributed
to both the depletion of the body’s homeostatic
reserves due to chronic illnesses and the heightened
stress levels associated with acute ailments (5).
While elderly patients in ICU receive treatment
for their primary conditions, the significance ofadequate nutrition may be overlooked, exposing
them to the risk of malnutrition upon ICU admission
and throughout subsequent care periods (6). The
catabolic processes induced by inadequate nutrition
can exacerbate existing risks of morbidity andmortality (4). These factors underscore the necessityof conducting regular nutritional risk assessments ingeriatric ICU patients.
Despite the availability of various nutrition
screening tools to identify malnutrition risk,
136

determining the “ideal choice” for assessing
inadequate nutrition remains unclear (7).
Nonetheless, the practical utility of these tools
in clinical settings continues to be investigated,particularly in the elderly patient population, wherechallenges related to cooperation may arise (8).
Frailty stands out as a significant concern
rendering the geriatric population vulnerable (9). It
manifests as a multidimensional biological syndrome
characterized by a decline in the organism’s
resilience to stress and physiological reserves
due to cumulative impairment across multiple
physiological systems (10) . Diagnosis of frailty ina patient necessitates meeting three criteria fromdecreased grip strength, diminished energy levels
in daily activities, slowness in walking, reduced
physical activity, and unintended weight loss (9).
Despite extensive study, the relationship between
frailty and inadequate nutrition in the elderly
remains ambiguous (11). Regular assessments forboth malnutrition and frailty in geriatric patients are
crucial for early diagnosis and intervention for bothconditions (11).
We have two main aims in this research. First;
The aim is to determine before ICU malnutrition
and frailty rates in patients who do not have surgicalpathology and are admitted to the internal medicine
ICU. Our second aim is to determine the relationshipbetween malnutrition and frailty detected in theinternal medicine patient group and mortality andmorbidity. Thus, we aim to overcome the difficulties
in assessing the impact of the pre-intensive carehealth status of geriatric patients on intensive careoutcomes by assessing the risk of malnutrition andfrailty.

MATERIALS AND METHOD
Study design
This study is a prospective, descriptive, and crosssectional investigation. Approval for the study was
obtained from the Local Ethics Committee (approvalTHE IMPACT OF MALNUTRITION AND FRAILTY ON MORBIDITY AND MORTALITYIN GERIATRIC INTERNAL INTENSIVE CARE PATIENTS: A PROSPECTIVE STUDY

number: 2022/40-02). Among the geriatric patients
followed in a three-month period at the Faculty of
Medicine, Internal Medicine ICU, ninety six patients
who met the inclusion criteria were accepted into
the study. Exclusion criteria comprised patients
under 65 years old, individuals with psychiatricconditions or difficulties in cooperation, thoseunable to provide a nutritional history due toimpaired consciousness, and patients receiving
enteral or parenteral nutrition before ICU admission.
Informed consent was obtained from eligible
patients before their participation in the study.
The cases were divided into two groups: survivors
and non-survivors. Throughout their ICU stay,patients’ nutritional regimens were administeredin accordance with the primary physician’s orders
based on their clinical status, with no modifications
made for the study.
Study population
Demographic information including age, gender,and comorbidities of consenting patients were
documented. Patient heights were measured by the
ICU team. Patients’ weights upon ICU admission,weight fluctuations, and percentage changes
over the previous six months were obtained fromconscious patients directly and from their relatives
in the case of unconscious individuals. The clinicalstatus of each patient within the first 24 hours of ICU
admission was assessed using the Acute Physiology
and Chronic Health Evaluation II (APACHE II),
Sequential Organ Failure Assessment (SOFA)
scoring systems and Charlson comorbidity index.
Additionally, pre-ICU hospitalization duration,
ICU length of stay, and ICU mortality rates wererecorded.
Evaluation of biochemical parameters andscreening malnutrition
Hospital records and laboratory data for eachpatient were reviewed, and the following laboratory

parameters upon initial admission to the ICU
were documented: complete blood count, serum
electrolyte levels (sodium, potassium, calcium),arterial blood gas analysis (including PaO2, PaCO2,
FiO2, PO2/FiO2, HCO3, lactate levels, and SpO2
values). Furthermore, C-Reactive Protein(CRP),
procalcitonin, alanine aminotransferase (ALT),
aspartate aminotransferase (AST), serum creatinine(Cr), and blood urea nitrogen (BUN) values wererecorded.
In this study, in addition to anthropometricmeasurements, Modified NUTRIC score, Subjective
Global Assesment (SGA), Nutritional Risk Screening(NRS-2002) and Mini Nutrition Evaluation Screening
Form (MNA-SF) were used for screening patientsfor malnutrition.
The Edmonton Frailty Scale (EFS)The Edmonton Frailty Scale comprises 9
components, encompassing cognitive function,
overall health status, self-perception of health,functional
independence,socialsupport,polypharmacy, mood, urinary incontinence, andfunctional performance, with a maximum score of
17 (12). In our study, two components requiring
patient performance were adapted to suit ICU
patients. Unlike the frailty phenotype, it also
assesses cognitive function. Based on the total
score obtained, individuals were categorized
regarding frailty as follows: 0-5 points: Robust,
not frail; 6-7 points: Vulnerable; 8-9 points: Mildly
frail, pre-frail; 10-11 points: Moderately frail; 12-17
points: Severely frail. The suitability and validity of
the EFS for assessing frailty in hospitalized patients
have been demonstrated (12).
Clinical Frailty Scale (CFS)
Frailty phenotype and cumulative frailty index
models pose challenges for bedside evaluations
and critical patients (13). One of the scales
developed in response is the Clinical Frailty Scale,1372024; 27(2):135−145

which correlates with frailty assessment based on
the Fried frailty phenotype criteria. Clinicians scoreelderly individuals from 1 (very fit) to 9 (terminallyill) based on their clinical judgment. As the scoreincreases, the degree of frailty escalates. A score ≥5
indicates “frailty” (13).
Evaluation of complications
Following admission to the ICU, the presence, type,and severity of various complications occurring
during patient follow-up were documented. These
complications were defined based on objective
criteria, including pulmonary complications(excluding pneumonia and atelectasis), sepsis(with positive culture), pneumonia (evidenced by
infiltration on new chest X-ray, purulent sputum ±positive culture), and delirium (characterized byacute-onset neuropsychiatric symptoms and signs
disrupting global brain function). Additionally,
patients’ ICU length of stay and ICU mortality wererecorded.
Statistical analysis

terms of weight, the mean weight of the survivors
group was 73.09±8.64, while the non-survivors
group was 68.5±6.33 (p=0.004). The mean APACHE
II score was 13±3.11 for the survivors group and23.68±3.04 for the non-survivors group (p<0.001).
Non-survivors had longer hospital stays before ICU
admission and longer ICU length of stay (p=0.004,
p=0.001, respectively). The characteristics of theentire cohort are given in Table 1. There was no
statistically significant difference in laboratory
findings between the survivors and non-survivors
groups (Table 2).
Evaluation of anthropometric measurements
When both groups were evaluated in termsof anthropometric measurements, statisticallysignificant differences were found in TSF (triceps
skinfold thickness), MAC (mid-arm circumference),and MAMC (mid-arm muscle circumference)
between the survivors and non-survivors groups(p<0.001) (Table 3).
Evaluation of nutritional tools

SPSS 24.0 (Chicago, IL) software was utilized forstatistical analysis. Data with categorical values(BMI, TSF, MAMC, age, weight, height) were
presented as mean ± standard deviation (SD). The
Mann-Whitney U test was employed to compare
anthropometric and systemic evaluation methods
in the study. Frequency data were presented as
number and percentage (%), and the chi-square
test was used to compare malnutrition status andfrequency data. Spearman’s correlation test was
employed to determine correlations. A p-value<0.05 was considered statistically significant.

The mean NRS-2002 score was 5.20±0.70 for thesurvivors group and 6.15±0.57 for the non-survivors
group (p<0.001). The mean MNA-SF score was
8.20±0.82 for the survivors group and 6.46±1.02 forthe non-survivors group (p<0.001). The mean SGA
score was 5.87±0.66 for the survivors group and
3.51±1.09 for the non-survivors group (p<0.001).
The mean mNUTRIC score was 3.49±0.63 for thesurvivors group and 5.68±0.65 for the non-survivors
group (p<0.001) (Table 1 and Table 3).

RESULTS

The mean Edmonton Frailty Score was 8.22±1.95
for the survivors group and 11.37±0.88 for the
non-survivors group (p<0.001). The mean Clinical
Frailty Score was 5.89±0.99 for the survivors groupand 8.0±0.0 for the non-survivors group (p<0.001)(Table 1 and Table 3).

Ninety six patients who met the inclusion criteria
were accepted into the study. In the survivors
group, the mean age was 75.5±7.29, while in the
non-survivors group, it was 78.6±8.36 (p=0.74). In

138

Evaluation of frailty assessment tools

THE IMPACT OF MALNUTRITION AND FRAILTY ON MORBIDITY AND MORTALITYIN GERIATRIC INTERNAL INTENSIVE CARE PATIENTS: A PROSPECTIVE STUDY

Table 1. Characteristics of the patients, nutrition screening tools and frailty assessment index
Characteristic

All Patients(n =96 )Survivors(n = 55)

Non-survivors(n = 41)

p- valueAge (mean±standart deviation)

76.9±7.87

75.5±7.29

78.6±8.36

0.740*

45 (46.9%)
34 (35.4%)
17(17.7%)

30 (54.5%)
18 (32.7%)
7 (12.7%)

15 (36.6%)
16 (39%)10 (24.4%)

0.159*

Weight (mean±standart deviation)

71.15±8.03

73.09±8.64

68.5±6.33

0.004*Height (cm) (mean±standart deviation)

167±5.47

166.75±5.73

167.61±5.120.432*BMI (mean±standart deviation)

25.5±2.98

26.29±2.99

24.44±2.640.002*

48 (50 %)48 (50 %)

27 (49.1%)
28 (50.9%)

21 (51.2%)
20(48.8%)

0.837*

APACHE II

17.56±6.21

13±3.1123.68±3.04<0.001**

SOFA score

7.56±2.91

5.44±1.61

10.41±1.46<0.001**

Length of hospital stay before ICU (days)

5.81±3.37

4.95±3.45

6.98±2.92

0.004**

Length of ICU days

11.31± 5.54

9.38±3.74

13.9±6.49<0.001**Age (range)

Sex

Youngest old (65-74 years)
Middle old (75-84 years)
Oldest old (over 85 years)

Female
Male

BMI

< 25
25-30
> 30

47 (49%)41 (42.7%)
8 (8.3%)22(40%)
27 (49.1%)
6 (10.9%)25 (61%)14 (34.1%)
2 (4.9%)0.109**

NRS malnutritionYesNo

95 (99%)1 (1%)

54 (98.2%)
1 (1.8%)41 (100%)
0 (0%)

0.573**

MNA malnutritionYesNo

46 (47.9%)0 (52.1%)

9 (16.4%)
46 (83.6%)

37 (90.2%)-4 (9.8%)<0.001**SGA

No malnutrition risk
Mild malnutrition
Severe malnutrition

42 (43.8%)
45 (46.9%)9 (9.4%)41 (74.5%)
14 (25.5%)
0 (0%)

1 (2.4%)31 (75.6%)
9 (22%)<0.001**

mNutrıc score

Low risk
High risk

55 (57.3%)
41 (42.7%)

54 (98.2%)
1 (1.8 %)

1 (2.4%)-40 (97.6%)<0.001**

Edmonton Frailty Scale

Non frail
PrefrailLight frail
Mild frail
Severe frail

2 (2.1%)18 (18.8%)
23 (24%)33 (34.4%)
20 (20.8%)

2 (3.6%)18 (32.7%)
22 (40%)12 (21.8%)
1 (1.8%)0 (0%)
0 (0%)
1 (2.4%)21 (51.2%)
19 (46.3%)<0.001**

Clinic Frail Score

4
5
6
7
8

1 (1%)
23 (24%)16 (16.7%)
11 (11.5%)
45 (46.9%)

1 (1.8%)23 (41.8%)
16 (29.1%)
11 (20%)4 (7.3%)0 (0%)
0 (0%)0(0%)
0 (0%)
41 (100%)<0.001**

All values are expressed as numbers (percentages) or median (interquartile range).
Abbreviations:BMI: Body mass index, 1. APACHE II: Acute physiology and chronic health evaluation II, 2. CCI: Charlson Comorbidity Index, SOFA:Sequential Organ Failure
Assessment score, MNA-SF=Mini Nutritional Assessment—Screening Form, NRS-2002=Nutritional Risk Screening
1. On the day of ICU admission
2. Includes hematological and solid organ malignancies*: Mann–Whitney U test, Data presented as median ± standard deviation**: Chi Square test. Data presented as frequency and percentance1392024; 27(2):135−145

Table 2. Laboratory findings of patients
Laboratuary Findings

All Patients (n =96 )Survivors (n = 55)

Non-survivors (n = 41)

White blood cell count, 103 /mL

12069.47±6131.84

11656.36±6653.53

12637.5±5370.7

0.086

12.13±2.05

12.33±2.1111.5±1.98

0.166

300812.5±205127.5

321690.9±256484.8

272804.88±98596.5

0.795

142.9±6.85142.7±6.65

143.1±7.20

0.758

4.43±0.77

4.51±0.82

4.32±0.70

0.280

Hemoglobin, g/dL

Platelet, 103 /mL
Sodium, mmol/L

Potassium, mmol/L

Calcium, mmol/L

p- value*

7.86±0.62

7.84±0.60

7.89±0.66

0.719

AST, IU/L

82.85±102.29

86.05±114.44

78.56±84.48

0.932

54.35±70.15

58.13±85.91

49.29±40.95

0.747

Blood urea nitrogen, mg/dL

42.19±30.91

41.4±30.16

43.24±32.23

0.994

2.09±0.98

1.06±0.65

3.37±1.12

0.356

146.42±60.57

143.89±67.3

149.8±50.76

0.257

1.64±0.78

1.48±0.61

1.84±0.94

0.350

165.68± 107.52

149.73±100.40

187.07± 114.16

0.108

3.82±11.25

3.91±10.74

3.70±12.06

0.131

pH

7.35±0.13

7.37±0.14

7.38±0.12

0.703

pO2

70±27.63

71.38±32.75

68.66±18.99

0.813

38.01±13.14

36.93±11.48

39.46±15.13

0.830

2.86±1.41

2.39±1.59

2.13±1.11

0.472

22.11±4.87

22.15±5.4322.18±4.05

0.824

90.55±5.58

90.85±5.11

90.15±6.19

0.885

ALT, IU/L

Creatinine, mg/dL

Glucose, mg/dL

Albumin, g/dL

C-reative protein

Procalsitonin

pCO2

LactatHCO3
SpO2

Abbreviations: ALT: Alanine aminotransferase, AST: Aspartate aminotransferase, LDH:Lactate dehydrogenase. PaO2 : Arterial partial oxygenpressure, PaCO2:Arterial partial carbon dioxide pressure, HCO3: Serum Bicarbonate,* (Mann–Whitney U test). Data presented as median ± standard deviation

Table 3. Values of Nutrition screening tools, Fraility assessment index, Anthropometric measurements.
NRS

MNA-SF
SGA

mNUTRIC score

Edmonton Fraility score
Clinic fraility score
TSF

MAC

MAMC
CCI

All Patients (n=96)

Survivors (n=55)

Nonsurvivors (n=41)

p value*5.60±0.81

5.20±0.70

6.15±0.573<0.0017.46±1.25

8.20±0.82

6.46±1.02

4.86±1.46

5.87±0.66

3.51±1.09

4.43±1.20

3.49±0.63

5.68±0.65

9.56±2.23

8.22±1.95

11.37±0.88

6.79±1.28

5.89±0.99

8.0±0.00

119.26±106.8

128.39±110.92

107.24±101.29

27.60±3.9629.50±3.10

25.03±3.54202.23±28.61

214.8±23.99

202.23±28.61

8.64±2.23

7.16±1.39

10.51±1.51<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001

MNA-SF=Mini Nutritional Assessment—Screening Form, NRS-2002=Nutritional Risk Screening, MAC=mid-arm circumference, MAMC=mid-arm
muscle circumference (in cm), TSF=triceps skin fold.
∗: Mann-whitney U test

140THE IMPACT OF MALNUTRITION AND FRAILTY ON MORBIDITY AND MORTALITYIN GERIATRIC INTERNAL INTENSIVE CARE PATIENTS: A PROSPECTIVE STUDY

Correlations of nutrition screening tools withcomplications

Clinical Frailty Score (0.303), APACHE II (r=0.403),
SOFA (r=0.405), and CCI (r=0.397), and a negative
correlation with SGA (r=-0.813) (p<0.05). Delirium
showed positive correlations with mNUTRIC score(r=0.272), Edmonton Frailty Score (r=0.264), Clinical
Frailty Score (r = 0.278), SOFA (r=0.208), and CCI(r=0.289), and a negative correlation with SGA(r=-0.813) (p<0.05). The correlations of nutrition
screening tools, frailty assessment scores, andcritical illness scores with ICU complications are
given in Table 4.

Positive correlations were found between NRS-2002(r = 0.614), mNUTRIC score (r=0.866), Edmonton
Frailty Score (r=0.763), Clinical Frailty Score (r =0.848), APACHE II (r=0.854), and CCI (r=0.778) withICU mortality, and a negative correlation was foundbetween SGA (r=-0.312) and ICU mortality (p<0.05).
ICU length of stay showed positive correlations with
NRS-2002 (r = 0.322), mNUTRIC score (r=0.310),

Table 4. Corelations of Nutrition screening tools, Frailty assessment index with complications.

NRS-2002

SGA

MNA-SFmNUTRIC score

Edmonton Fraility score
Clinic Frail score
APACHE II

SOFA Score
CCI

SepticShockMortality
in ICU

Lengthof Stay ICU

Delirium

Pressure
Ulcer

0.614**

0.322**

0.128

0.399**

0.246*

0.516*

0.243*-0.312**-0.813**-0.251*-0.496**-0.307**-0.574**-0.381**

0.000

0.002

0.014

0.000

0.002

0.000

0.000

0.866**

0.310**

0.272**

0.494**

0.384**

0.617**

0.443**

0.763**

0.194

0.264**

0.343**

0.283**

0.491**

0.387**

0.848**

0.303**

0.278**

0.416**

0.329**

0.552**

0.387**

0.854**

0.403**

0.163

0.432**

0.350**

0.625**

0.361**

0.841

0.405**

0.208*

0.420**

0.337**

0.602**

0.392**

0.778**

0.397**

0.289**

0.464**

0.311**

0.535**

0.393**ARF

ARDS∗p<0.05 (Spearman correlation test).
∗∗p< 0.001 (Spearman correlation test).

Table 5. Corelations of Nutritional screening tools, Frailty assesment index and Critical ilness scores with each others.

NRS-2002

SGA

MNA-SFmNUTRIC score

Edmonton Fraility score
Clinic Frailty score
APACHE II

SOFA score
CCI

NRS-2002

SGA

MNA-SFmNUTRIC
Score

Edmonton
Fraility
Score

ClinicFrailty
Score

APACHE
II

SOFA
scoe

CCI

-----

-0.653**-0.744**

0.598**

0.443**

0.500**

0.634**

0.537**

0.533**-0.633**-----0.770**-0.797**-0.690**-0.741**-0.681**-0.620**-0.573**-0.744**0.770**------0.716**

0.579**-0.640**-0.642**-0.584**-0.607**0.598**-0.797**-0.716**----

0.667**

0.783**

0.802**

0.752**

0.674**

0.443**-0.690**-0.579**0.667**----

0.786**

0.626**

0.620**

0.507**

0.500**-0.741**-0.640**0.783**

0.786**----

0.705**

0.727**

0.638**

0.634**-0.681**-0.642**0.802**

0.626**

0.705**-----

0.912**

0.653**

0.537**-0.620**-0.5840.772

0.620**

0.727**

0.912**-----

0.661**

0.533**-0.573**-0.607**0.674**

0.507**

0.638**

0.653**

0.661**-----∗p<0.05 (Spearman correlation test).
∗∗p< 0.001 (Spearman correlation test).

1412024; 27(2):135−145

Correlations of nutritional screening tools,
Frailty assessment scores, and Critical illness
scores with each other
NRS-2002 showed a positive correlation withmNUTRIC score (r=0.598) and negative correlations
with SGA (r=-0.653) and MNA-SF (r=-0.744) (p<0.05).
SGA showed positive correlations with MNA-SF(r=0.770) and negative correlations with mNUTRIC
score (r=-0.797) (p<0.05). MNA-SF showed anegative correlation with mNUTRIC score (r=-0.716)(p<0.05). The Edmonton Frailty Score showed apositive correlation with the Clinical Frailty Score(r=0.786) (p<0.05). The correlations among nutrition
screening tools, frailty assessment scores, andcritical illness scores are presented in Table 5.

DISCUSSION
In this study, we explored the correlation between
malnutrition and frailty scores with morbidity andmortality among 96 geriatric patients admitted tothe internal medicine ICU for non-surgical reasons
during a three-month period. Our findings revealed
a statistically significant relationship between
disease severity, body mass index, anthropometricmeasurements, and intensive care mortality rates.
Moreover, we observed a significant association
between malnutrition rates, as assessed by MNASF, SGA, and mNUTRIC score, and ICU mortality
rates. Utilizing the Edmonton Frailty Scale, we
identified a notable correlation between moderateand severe frailty and mortality rates. Likewise, there
was a statistically significant association between
increasing clinical frailty index scores and mortality
rates. These results underscore the importanceof considering both malnutrition and frailty
assessments in the management and prognosis ofgeriatric patients in intensive care settings.
One of the primary objectives of this research
was to ascertain the prevalence of malnutrition
upon admission of elderly patients to ICU andto investigate its association with ICU mortality.

142

Malnutrition has been linked to various adverse
health outcomes, including declines in functional
status, muscle strength, bone mass, immunity,
cognitive function, wound healing, surgicalrecovery, as well as elevated hospital readmission
rates and mortality (14). According to our study
findings, 47.9% of geriatric patients admitted to
the ICU were identified as malnourished basedon the Mini Nutritional Assessment (MNA), 56.3%
according to the Subjective Global Assessment(SGA), and 42.7% according to the modified
Nutrition Risk in the Critically ill (mNUTRIC) score.
Consistent with our findings, previous study
reported malnutrition rates ranging from 37% to
50% among patients admitted to medical andsurgical ICUs using SGA classifictions (3). However,
it is noteworthy that this study encompassed acohort with younger patients. Malnutrition rates
can vary according to the clinical characteristics ofpatients followed ICU. In another previous study,
they classified 26% of ICU patients as moderately
malnourished and 11% as severely malnourishedbased on SGA and found SGA to be applicablein critically ill patients (15). One of the reasonsfor the different results between our study andthis study is that the study population consistedof younger patients with predominantly surgicalpathologies rather than geriatric internal medicine
patients. Evaluating the nutritional status of elderly
patients is challenging. In a study by Atalay et al.
(16), the prevalence of malnutrition assessed using
SGA in patients over 70 years old was found to
be 33.6%. According to the authors’ knowledgeof the literature, no study has been found that
demonstrates the prevalence of malnutrition in
the geriatric patient group aged 65 and older who
are admitted to the internal medicine ICU without
any surgical pathologies. However, it is known that
20-50% of all hospitalized geriatric patients areaffected by malnutrition (17). Unfortunately, thenutritional status of critical patients deteriorates
rapidly after admission to the ICU, and the effects
of inadequate nutrition are added to severe stress-

THE IMPACT OF MALNUTRITION AND FRAILTY ON MORBIDITY AND MORTALITYIN GERIATRIC INTERNAL INTENSIVE CARE PATIENTS: A PROSPECTIVE STUDY

induced catabolism (17). This explains the high rateof malnutrition in geriatric patients in our study.
In our study, we observed a significant correlation
between malnutrition rates assessed by the MNA,
SGA, and mNUTRIC scores and ICU mortality rates.
Similarly, a review encompassing 1168 articles
investigating the relationship between malnutrition
and adverse clinical outcomes in the ICU revealed
that malnutrition was associated with an elevatedrisk of prolonged ICU length of stay, readmission,and hospital mortality (18). Furthermore, in critically
ill COVID-19 patients diagnosed with malnutrition
using SGA and NRS-2002, increased mortality rates
were also observed (19). These findings underscorethe clear association between inadequate nutrition
and adverse clinical outcomes among hospitalized
patients (5).
Another objective of our study was to ascertain
the levels of frailty and their association with mortality
among patients aged 65 and older presenting
with internal pathologies upon admission to the
ICU. The impact of frailty on elderly patients has
predominantly been investigated in communitybased studies, with fewer studies focusing on
hospitalized or ICU-bound elderly individuals (20).
A review analyzing studies examining frailty incommunity settings reported a prevalence ranging
from 4% to 59.1% among a total of 61,500 patients(20). Fraility is often undiagnosed condition in
hospitalized elderly patients, with prevalence
ranging from 27% to 80% (21). Failure to consider
and recognize fraility may contribute to the difficultyin diagnosing it.
Our study has demonstrated a lower prevalenceof fraility compared to studies conducted in thecommunity. Particularly among patients followedin the ICU, fraility appears to be more common,as observed this study. In the study we present, 20
patients (20.8%) were categorized as severely frail
according to the Edmonton Frailty Scale, while
45 patients (46.9%) were classified as severely frail
according to the Clinical Frailty Scale. Consistent

with our findings, frailty is more commonly observedin patients under ICU monitoring. A meta-analysis
investigating the impact of frailty on ICU outcomes
reported a frailty prevalence of 33.1% among
3030 geriatric patients with internal and surgicalpathologies, and 30% among all patients (9).
Assessing patients’ frailty alongside critical
illness assessment scores upon ICU admission canbe advantageous in evaluating cognitive, mobility,
functionality, and social aspects (22). In a study
conducted among patients aged 60 and older in the
ICU, the prevalence of frailty was measured at 21.3%
using a frailty index (22). In the United States, among
52 intensive care patients aged 80 and over, theprevalence of frailty according to th e Clinical Frailty
Scale (CFS) was 88.5%, with an average CFS score of
5.8 (23). While aging does not inherently imply frailty,
the prevalence of frailty tends to increase with age(23). The inclusion of patients aged 80 and over may
have contributed to the observed high prevalence.
Moreover, the prevalence can vary depending on
the frailty scale utilized. In a multicenter community
study conducted in our country, the prevalence offrailty was 27.8% according to the frailty index and
10% according to the Frail scale (24). However,significant differences in prevalence among thesame patient group were not observed between
the Edmonton Frailty Scale and the Clinical Frailty
Scale in our study; both scales exhibited statisticallysignificant correlations.
In the presented study, we observed a statisticallysignificant association between the presence offrailty upon admission to the ICU and an elevatedrisk of mortality. Among deceased patients, 46.3%
exhibited severe frailty, and 51.2% displayed
moderate frailty according to the Edmonton Frailty
Scale (p<0.001). Similarly, in a review examining therelationship between frailty and mortality, being frail
was demonstrated to increase the risk of hospitalmortality by 1.71 times, long-term mortality risk
by 1.53 times, and ICU mortality risk by 1.51 times(9). Previous studies have identified frailty as an

143

2024; 27(2):135−145

independent risk factor for ICU mortality, length ofstay, and readmission (4). A study reporting an ICU
mortality rate of 69% found a correlation between
frailty and SOFA and APACHE II scores (25). Given
the association between frailty and mortality,
assessing frailty alongside ICU scores may be crucial
in evaluating these patients.
Our study has certain limitations. Being
conducted in a single center’s ICU, thegeneralizability of the results may be limited. The
utilization of malnutrition and frailty assessment
tools in the geriatric population, which may exhibit
less cooperation, and reliance on information
provided by family members in cases of insufficient
data could introduce bias.
Nonetheless, our study also possesses strengths.
It was conducted in a highly homogeneous patientgroup admitted to the internal ICU without surgicalpathology. We extensively evaluated this patientgroup using clinical, anthropometric measurements,
and comprehensive screening tools. To the best of
our knowledge, this study is the first to address thisissue in this patient population.
Our findings indicate the prevalence ofmalnutrition and frailty in a significant portion of
ICU-monitored patients. In ICU settings, the focus
often centers on conditions such as respiratory
failure, septic shock, and acute kidney injury,
potentially overlooking malnutrition and frailty
in elderly patients and their associated adverse
outcomes. Both conditions may be as critical as oreven more important than the acute issue leading
to ICU admission.
In conclusion, evaluating the impact of preintensive care health status on ICU outcomesamong elderly patients poses challenges. Assessing
the risk of malnutrition and frailty could provide
a method to address this challenge. Therefore,
regular assessment of nutrition status and frailty in
critically ill patients is imperative.

144

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2017;41(5):744-58.(doı:10.1177/0148607115625638).
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20. Collard RM, Boter H, Schoevers RA, Oude Voshaar
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(doı:10.1503/cmaj.150100).
22. Ritt M, Schwarz C, Kronawitter V, et al. Analysis ofRockwood et Al’s Clinical Frailty Scale and Friedet Al’s Frailty Phenotype as Predictors of Mortality
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145

ORIGINAL ARTICLE

Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.388
2024; 27(2):146−156
 Ömer Faruk ÇİÇEK1. . . . . . . . . . . 

 Hakan AKBAYRAK1 . . . . . . . . . . . 
 Gökhan ÖZDEMİR2 . . . . . . . . . . . 
 Fettah EREN2. . . . . . . . . . . . . . . . 

 Mücahit Tahsin DEMİRTAŞ1. . . . . 
 Gözde ÖNGÜN2. . . . . . . . . . . . . . 

 Atilla ORHAN1. . . . . . . . . . . . . . . .

 Mustafa BÜYÜKATEŞ1. . . . . . . . . 

CORRESPONDANCE
1Ömer Faruk ÇİÇEK

Phone
e-mail: +903322245242: farux@hotmail.com

Received : May 06, 2024
Accepted : May 31, 2024

1 Selçuk University Faculty of Medicine,

Dept. of Cardiovascular Surgery, Konya,
Turkey2 Selçuk University Faculty of Medicine,

Dept. of Neurology, Konya, Turkey

A SINGLE-CENTER COMPARATIVE STUDY
OF ENDARTERECTOMY AND STENTING FORSYMPTOMATIC CAROTID ARTERY DISEASE:DECISION-MAKING PROCESSES AND EARLYTO MID-TERM OUTCOMES

ABSTRACTIntroduction: Ischemic stroke constitutes a significant burden on global
health. Carotid artery atherosclerosis is a significant contributor to theoccurrence of ischemic strokes. Both carotid endarterectomy and stenting are
viable treatment options for symptomatic carotid artery disease, yet the optimal
choice between them remains debated, particularly in elderly patients withmultiple comorbidities. This study aims to compare decision-making processes
and early to mid-term outcomes between carotid endarterectomy and carotid
artery stenting in elderly symptomatic carotid artery disease patients.
Materials and Method: A total of 88 symptomatic carotid artery disease
patients (carotid endarterectomy: n=35, mean age: 71.72±7.87 years; carotid
artery stenting: n=53, mean age: 70.64±7.46 years) were retrospectively
analyzed.
Results: No significant differences were observed in demographic
characteristics between carotid endarterectomy and stenting groups. Chronic
renal disease was more prevalent in the carotid endarterectomy group. Carotid
artery stenting patients had a higher prevalence of 50–69% stenosis and lessplaque ulceration. Complication rates were comparable between groups, withlonger intensive care and hospitalization durations in the carotid endarterectomy
group. Mid-term mortality rates and major complications did not significantly
differ between groups.
Conclusion: Both carotid endarterectomy and carotid artery stenting are
effective treatments for symptomatic carotid artery disease. Despite differencesin lesion characteristics, complication rates were similar between carotid
endarterectomy and carotid artery stenting. This study emphasized the efficacy
of a full cooperation between the cardiovascular surgery and neurology teams
through an in-depth evaluation of each of the patients and the creation ofindividualized treatment strategies that optimized overall outcomes.
Keywords: Aged; Endarterectomy; Carotid; Carotid Stenosis; Stents.

146

A SINGLE-CENTER COMPARATIVE STUDY OF ENDARTERECTOMY
AND STENTING FOR SYMPTOMATIC CAROTID ARTERY DISEASE:DECISION-MAKING PROCESSES AND EARLY TO MID-TERM OUTCOMESINTRODUCTION
Stroke, the primary cause of permanent disability
and mortality worldwide, predominantly arises fromischemic etiologies, which account for approximately
88% of cases, while hemorrhagic stroke constitutes
the remaining 12% (1). Large vessel atherosclerosis,
particularly in the extracranial internal carotid
artery, is responsible for a considerable number
of ischemic stroke cases. Indeed, approximately
20% of all ischemic strokes are caused by carotid
artery disease (CAD) and the thromboembolism
associated with atherosclerosis (2). The risk of strokeincreases as the severity of the stenosis in the carotid
arteries increases. Recent studies have found thatin asymptomatic patients with 50% carotid arterystenosis, the occurrence of ipsilateral stroke was
4% in five years, while if the stenosis was 70%, therisk was doubled in the same period (3). High-riskpatients have an advanced level of stenosis andmultiple risk factors, which is why the treatment of
stenoses above 50% is clinically important. Age (65years and older), male gender, smoking, coronary
artery disease, hypertension, and hyperlipidemia are
the most important clinical risk factors for CAD (4, 5).
Medical treatment, balloon angioplasty, stentplacement, and carotid endarterectomy (CEA)
surgery are the current treatment options for CAD.
Since the provision of medical treatment alone
to symptomatic patients does not produce thedesired result, surgical treatment has been a focus
of interest, and given technological developments
in recent decades, carotid artery stent (CAS)placement has become the treatment modalityof choice. CAS was first used in the 1980s but has
become quite common in recent years. The factthat other surgical treatment options have someknown limitations, including wound infection,
peripheral nerve injury, challenging anatomical
localization, and difficult management of patientswith additional comorbidities, has contributed tothe popularization of CAS treatment.
Symptomatic carotid disease is defined as focal
neurological symptoms that may be associated withatherosclerotic CAD and may include one or moretransient ischemic attacks characterized by sudden
onset focal neurological dysfunction, transientmonocular vision loss, or non-specific neurologicalsymptoms (6). The findings of randomized controlled
trials indicate CEA to be a safe and effective
treatment method for reducing the risk of ischemic
stroke in patients with symptomatic CAD (6, 7).
Thus, in recent years, as a result of technologicaladvances, CAS has become a favored technique
due to being less invasive than CEA and having
fewer negative consequences in high-risk patients.
In fact, a number of randomized controlled trials
have compared the results of the CAE and CAS
procedures in symptomatic CAD patients (8, 9).
Given
the
widespread
prevalenceofatherosclerosis in elderly people and the growing
population of older adults worldwide, there willclearly be an increasing need for approaches
to address carotid artery stenosis among thisage group in the coming years. The presence ofadditional comorbidities, anatomical complexities,
higher risk of perioperative complications, andgreater frailty among elderly patient populations
pose challenges when deciding on the suitabilityof endarterectomy, while technical difficulties,
including lesions that are unsuitable for stenting
and vascular access site issues, make it difficult
to decide on stent placement. Currently, there isno clear strategy for choosing the best treatment
option for elderly patients with symptomatic carotid
artery stenosis and multiple comorbidities. However,ischemic stroke is a serious cause of both disability
and mortality, especially in older populations, whichmeans that the diagnosis and treatment of carotid
stenosis are important for stroke prophylaxis. In
this single-center study, we sought to present bothour decision-making processes and the short- to
medium-term outcomes in elderly patients withsymptomatic carotid artery stenosis who underwent
CEA and CAS through an approach that emphasizes
interdisciplinary collaboration and patient-centricassessment.

1472024; 27(2):146−156

MATERIALS AND METHOD
In this study, a total of 88 patients who underwent
CAS (n=53) and CEA (n=35) for the treatment of
CAD were retrospectively analyzed. All the patientsenrolled in this study were symptomatic and were
initially assessed using Doppler ultrasonography
as the primary diagnostic modality. Afterwards,
all the patients underwent evaluation by meansof computed tomography (CT) angiography and/or conventional digital subtraction angiography(DSA) to ascertain the degree of stenosis andthe anatomical extent of the lesion. The stenosis
grade was determined according to the North
American Symptomatic Carotid Endarterectomy
Trial (NASCET) criteria (10). Symptomatic patientswith 50–99% stenosis at the internal carotid artery
according to the NASCET criteria were includedin this study. Patients with totally occluded carotid
artery lesions were excluded from this study. The
patients’ demographic characteristics, including
age, gender, comorbid conditions, side and severityof the carotid artery lesion(s), symptom details,
diameter and length of the stents, patch types used
Table 1.

in endarterectomy, post-procedural complications,and durations of intensive care and hospital staywere obtained from hospital records. The patients’
symptoms were classified as amaurosis fugax,
dizziness, dysarthria, minor cerebrovascular disease(CVD), and/or major CVD.
The study protocol was approved by the Local
Ethics Committee of Selçuk University’s Facultyof Medicine (approval date: 30.12.2020; decision
number: 2020/570). Prior to the procedure, every
patient completed a written informed consent form.
The study was conducted in accordance with theprinciples outlined in the Declaration of Helsinki.
Decision-making process
Our decision-making process regarding CEA and CAS,
which emphasized interdisciplinary collaborationand patient-centric assessment, proceeded asfollows. After each patient’s DSA procedure, theinvasive neurologist extended an invitation to thesurgeon to join them in the angiography unit. In
the meeting held in the angiography unit, thePotential challenges from both the surgeon’s and interventionalist’s perspectives when considering the optimaltreatment strategy for the patient during the council.
Surgeon’s perspective

Interventionalist’s perspective

Lesion extending very distally
Anatomical challenges: High carotid bifurcation
exposure problems
Spinal immobility of the neck

Perioperative
anesthesia issues

Arch anomalies (including bovine arch)
Aortic arch problems

Angulated takeoffs from the arcus

Poor general condition

Tortuosity, elongation

Recent major stroke
Hemodynamic instability
Severe pulmonary disease

Multiple comorbidities

Factors with carotid
arteryAngulation
Severe calcification
Long segment lesion
Plaque with thrombus

Renal insufficiency
Prior neck surgery
Neck radiotherapy

Peripheral artery disease
Femoral access issues

Tracheostomy

Leriche syndrome
Iliac tortuosity

Hyperperfusion syndrome
Distal embolism and procedure-related stroke

148

Aortic arch atheroma

Short neck

Cardiac problems

Surgical difficulties

Tortuosity

A SINGLE-CENTER COMPARATIVE STUDY OF ENDARTERECTOMY
AND STENTING FOR SYMPTOMATIC CAROTID ARTERY DISEASE:DECISION-MAKING PROCESSES AND EARLY TO MID-TERM OUTCOMES

patient’s age, symptoms, comorbid conditions,carotid lesion characteristics (degree of stenosis,
angulation, calcification, ulceration), arcus aorta
anatomy, and contralateral carotid lesion wereconsidered to make the best decision for thepatient. The decision-making factors concerning
surgery or stent implantation are summarized inTable 1. The table outlines the probable challenges
that the surgeon and the interventional neurologist
may encounter throughout the decision-making
process, as considered from both their perspectives.
A consensus-based decision was reached after thesurgical and interventional teams had presented
their arguments during the meeting. If stenting
was decided upon, the procedure was performed
during the same session, whereas if surgery waschosen, the procedure was completed within 3–5
days.
Carotid artery stenting procedure
CAS placement was performed in all patients forwhom it was considered appropriate via the rightcommon femoral artery. First, angiography of thearcus was performed and the aortic anatomy wasdetermined. Bilateral selective carotid angiography
and selective cerebral angiography were
performed. Embolic protection devices (EPDs) were
not routinely used. The positioning of the stent was
adjusted immediately after passing the carotid artery
lesion with the appropriate guide wire. Next, thestent was placed, and if required, balloon dilation
was performed. Finally, control angiography images
were obtained for both the carotid stent and the
distal vascular area. Antiplatelet drugs, which werestarted prior to the procedure, were continued after
the CAS placement for 1–3 months. Following thisperiod, monotherapy was continued.
Surgical technique
CEA was performed under general or local
anesthesia. Following the neck incision, thecommon carotid, external carotid, and internal
carotid arteries were explored. The patient wasthen heparinized and vascular clamps were applied.
Then, longitudinal arteriotomy was performed below
the carotid bifurcation level, and the incision was
extended both proximally and distally. The plaqueinside the carotid artery was carefully separated
and removed. Fixing sutures were placed at boththe proximal and distal ends of the endarterectomy
level to stabilize the incision line of the plaque andprevent any possible dissections that may haveoccurred after the flow was restored. Following the
CEA procedure, the arteriotomy was repaired bymeans of patch angioplasty. The preferred choiceof patch material was an autologous saphenous
vein, but if that was not available, an expanded
polytetrafluoroethylene (ePTFE) was used instead.
Due to the slightly aneurysmatic character of the
carotid artery, a patch was not applied in one
patient included in this study. Finally, the vascularclamps were removed in the appropriate order andthe blood flow was restored.
Statistical analysis
All the analyses in this study were performed
using SPSS 22.0 (SPSS, Chicago, IL). The normal
distribution of the variables was examined using
the Kolmogorov-Smirnov test. Continuous variables
with a normal distribution were presented as themean ± standard deviation. Continuous variables
that did not conform to a normal distribution were
presented as the median (minimum–maximum).
Categorical variables were expressed as thenumber and percentage. Independent groups
with normally distributed continuous variables
were compared using Student’s t-test, while nonnormally distributed variables were compared using
the Mann-Whitney U test. Categorical variables
were compared using the chi-square or Fisher’s
exact test. A p-value less than 0.05 was considered
statistically significant.

1492024; 27(2):146−156

RESULTS
The demographic characteristics of the 88 patients(mean age: 71.72±7.87 years) included in this study
are presented in Table 2. The patients were divided
into two groups: the CEA group (n=35, mean age:

71.72±7.87 years) and the CAS group (n=53, mean
age: 70.64±7.46 years). There were no statisticallysignificant differences between the CEA andCAS groups in terms of the patients’ age, gender,concomitant hypertension, hyperlipidemia, diabetes

Table 2. Demographic data regarding the study population, endarterectomy, and stent groups and comparisons are given

Age (year)
GenderHypertension

73.34±8.2970.64±7.46

0.11

25 (71.4%)

36 (67.9%)

0.91

Female27 (30.7%)

10 (28.6%)

17 (32.1%)

78 (88.6%)

33 (94.3%)

45 (84.9%)

0.30

41 (46.6%)

17 (48.6%)

24 (45.3%)

0.93

33 (37.5%)

13 (37.1%)

20 (37.7%)

1.00

44 (50%)18 (51.4%)

26 (49.1%)

1.00

27 (30.7%)

12 (34.3%)

15 (28.3%)

0.72

COPD

Chronic renal disease

Aortic arch type
Bovine arch
Lesion side
Degree of stenosis, %*Lesion grade
Plaque ulceration
Contralateral carotid

p value

61 (69.3%)

Coronary artery disease

Imaging methods

Stent group(n=53)

71.72±7.87

Diabetes mellitus

Symptoms

Endarterectomy group(n=35)

Male

Hyperlipidemia

Active smoking

All patients(n=88)

9 (10.2%)

7 (20%)

2 (3.8%)0.026

37 (42%)18 (51.4%)

19 (35.8%)

0.22

Amaurosis fugax

7 (8%)

4 (11.4%)

3 (5.7%)

Dizziness

22 (25%)9 (25.7%)

13 (24.5%)

Dysarthria

4 (4.5%)3 (8.6%)

1 (1.9%)Minor CVD

37 (42%)

12 (34.3%)

25 (47.2%)

Major CVD

18 (20.5%)

7 (20%)

11 (20.8%)

CT Angiography

73 (83%)26 (74.3%)

47 (88.7%)

0.14

DSA

86 (97.7%)

33 (94.3%)

53 (100%)

0.15

I

34 (38.6%)

11 (31.4%)

23 (43.4%)

II

38 (43.2%)

13 (37.1%)

25 (47.2%)

III

16 (18.2%)

11 (31.4%)

5 (9.4%)11 (12.5%)5 (14.3%)

6 (11.3%)

Right

37 (42%)

12 (34.3%)

25 (47.2%)

Left

32 (36.4%)

13 (37.1%)

19 (35.8%)

Bilateral

19 (21.6%)

10 (28.6%)

9 (17%)

79.99±15.18

82.74±13.35

78.17±16.14

50-69%

21 (23.9%)

3 (8.6%)18 (34%)70-89%

28 (31.8%)

16 (45.7%)

12 (22.6%)≥90%

39 (44.3%)

16 (45.7%)

23 (43.4%)

33 (37.5%)

20 (57.1%)

13 (24.5%)>%50 stenosis

11 (12.5%)

8 (22.9%)

3 (5.7%)

Total occlusion

8 (9.1%)2 (5.7%)

6 (11.3%)

0.45

0.03
0.75
0.35
0.15
0.008
0.004
0.06

COPD: Chronic obstructive pulmonary disease, CT: Computed tomographic, CVD: Cerebrovascular disease, DSA: Digital subtraction angiography *Based on North American Symptomatic Carotid Endarterectomy Trial (NASCET) criteria

150

A SINGLE-CENTER COMPARATIVE STUDY OF ENDARTERECTOMY
AND STENTING FOR SYMPTOMATIC CAROTID ARTERY DISEASE:DECISION-MAKING PROCESSES AND EARLY TO MID-TERM OUTCOMES

mellitus, coronary artery disease, chronic obstructive
pulmonary disease, active smoking, symptom
characteristics, preoperative imaging modality,side and degree of the carotid artery lesion, andcontralateral carotid lesion (p=0.11, p=0.91, p=0.30,
p=0.93, p=1.00, p=1.00, p=0.72, p=0.22, p=0.45,
p=0.14, p=0.15, p=0.35, p=0.15, and p=0.06,
respectively). However, chronic renal disease wasfound to be significantly elevated in the patients who
underwent CAE (n=7, 20%) when compared with thepatients who underwent CAS (n=2, 3.8%) (p=0.026).

The prevalence of a type III aortic arch was also higher
in the CEA group when compared with the CAS group(p=0.03). The lesion grade distribution significantly
varied between the two groups (p=0.008), with the
CAS group having a higher prevalence of stenosis in
the 50–69% range. Moreover, the plaque ulceration
exhibited a statistically significant increase in the
CEA group (p=0.004).
The characteristics of the CEA and CAS
procedures are provided in Table 3. The mean
proximal diameter of the stents used in the CAS

Table 3. Procedural and post-procedural data are provided for CEA and CAS groups

Proximal diameter (mm)Stent size

Distal diameter (mm)Length (mm)Type of anesthesia
Localization ofendarterectomy
Side of procedure

Type of patch
Shunt usage

X-clamp time (min.)Complications

Endarterectomy group(n=35)

Stent group(n=53)-

8.96±0.92-

6.79±0.88-

36.6±4.78

General31 (88.6%)

-

Local

4 (11.4%)-

Isolated ICA

7 (20%)-ICA+CCA28 (80%)-Right

18 (51.4%)

26 (49.1%)

Left

17 (48.6%)

27 (50.9%)

Saphenous vein

30 (85.7%)

-

ePTFE

4 (11.4%)-

No patchp value

-

1.00

-

1 (2.9%)-4 (11.4%)--

20.69±6.53

-

-

-

3 (5.7%)

Myocardial infarction

1 (2.9%)1 (1.9%)Minor CVD

1 (2.9%)3 (5.7%)Intracranial hemorrhage-

2 (3.8%)Hyperperfusion syndrome

2 (5.9%)7 (13.2%)

Postoperative bleeding

2 (5.9%)-

Hypoglossal nerve injury

2 (5.9%)-1 (1-57)

1 (0-9)4 (2-90)

3 (2-27)

Death

Intensive care unit duration (day)Hospitalization duration (day)0.36<0.001<0.001

CCA: Common carotid artery, ECA: External carotid artery, ePTFE: Expanded polytetrafluoroethylene, ICA: Internal carotid artery, CVD: Cerebrovascular disease1512024; 27(2):146−156

procedure was 8.96±0.92 mm, while the mean
distal diameter was 6.79±0.88 mm and the mean
length was 36.6±4.78 mm. The mean X-clamp time
for the CEA procedure was 20.69±6.53 minutes.
There was no statistically significant difference
between the CEA and CAS groups in terms of thecomplications seen after the procedures (p=0.36).
Two patients (5.9%) in the CEA group required
surgical revision on the first postoperative day due
to local hematoma. The durations of the intensive
care and hospitalization periods were found to bestatistically significantly longer in the CEA groupwhen compared with the CAS group (p<0.001).
There was no procedural mortality or myocardial
infarction in either group. However, in the CAS
group, three deaths (5.7%) and one myocardial
infarction (1.9%) occurred during the intensive careunit follow-up after the procedure, whereas one
myocardial infarction (1.9%) was observed in the
CEA group following the operation.
The median follow-up period was 28.83 (range0–61) months. Within this follow-up period, twopatients in the CAS group required reintervention
due to restenosis. Additionally, CVD occurred inthree patients in the CEA group and five patientsin the CAS group during the follow-up period.
These events were not attributed to the vessel that
previously underwent intervention; rather, they
were associated with either the contralateral side orembolism of cardiac origin. At our mid-term followup, the mortality rates were found to be comparable
between the CAS and CEA groups, with 34 patients(64.2%) in the CAS group and 23 patients (65.7%)in the CEA group experiencing death (p=0.88).
The leading causes of death were cardiac andpulmonary issues, while cancer, general debility,
infection, diabetes complications, and renal andhepatic failure were among the other contributing
factors.
In the subgroup analyses of patients below andabove 75 years of age, no significant difference
was observed between the CEA and CAS groups

152

regarding the major cumulative complications,
including permanent disability and death.

DISCUSSION
CEA and CAS are two effective treatment modalities
for the management of symptomatic CAD. Although
endovascular treatments have made significant
progress in recent years, the easy accessibilityof the cervical carotid artery and the low risk ofcomplications associated with the surgery haveresulted in the continued preference for surgicalapproaches as the primary treatment modalities.
When considering the suitability of CEA for apatient, the surgeon must conduct a comprehensive
evaluation that encompasses various dimensions.
This entails more than merely executing the CEA
procedure, as it necessitates a holistic assessmentof both the patient and the pathology. Factors
such as the presence of multiple comorbidities,
anatomical complexities, anesthetic challenges,
and other potential surgical intricacies must all becarefully considered. With the aging populationand the increasing prominence of geriatricpatients worldwide, healthcare professionals are
increasingly encountering individuals who present
with such complexities. However, there appears
to be a paradigm shift favoring stent placement in
the management of symptomatic CAD, as CAS isless invasive and is now commonly performed innumerous centers. While guidelines offer extensive
information on the topic, it is prudent to approachreal-life situations based on the principle that“there is no disease, there is only the patient.” Thisis because each patient presents with a multitudeof unique conditions beyond CAD. Therefore,
during the patient evaluation, both the surgeon
and the neurologist must strive to make the optimal
decision by considering the factors outlined in Table
1 and beyond. In this study, no attempt was madeto demonstrate the superiority of one procedure
over the other; rather, it was recognized that bothprocedures may be more appropriate, depending

A SINGLE-CENTER COMPARATIVE STUDY OF ENDARTERECTOMY
AND STENTING FOR SYMPTOMATIC CAROTID ARTERY DISEASE:DECISION-MAKING PROCESSES AND EARLY TO MID-TERM OUTCOMES

on the individual patient and their specific situation.
Instead, this study highlighted the achievementof comprehensive collaboration between theneurology and cardiovascular surgery teams by
meticulously evaluating each patient and devisinga treatment plan that was tailored to optimize theoutcomes in all aspects.
The CEA and CAS groups were similar in termsof the patients’ demographic characteristics,
comorbidities, and symptoms, although patientswith chronic kidney disease were statistically moreprevalent in the CEA group. This trend may havearisen due to a preference for surgery, potentiallyinfluenced by patients with chronic kidney disease
opting to avoid additional contrast agent use
during the procedure. While contralateral carotid
stenosis or occlusion may influence the decisionmaking process regarding stenting or surgery due
to perceived impacts on procedural outcomes, ourpatient cohort exhibited comparable occurrences
between the two groups (p=0.06). Additionally,
the study by Deser et al. similarly suggests thatthe presence of contralateral severe internal
carotid artery stenosis does not elevate the riskof postoperative stroke, mortality rates, or bloodpressure fluctuations (11).
Table 1 outlines the factors that present
challenges from both the surgeon’s and theinterventionalist’s perspectives when determining
the optimal treatment strategy for a patient. Aorticarch issues represent significant limiting factors for
CAS because the aortic arch is an important causeof cerebral embolization during both diagnostic
and interventional procedures involving supraaortic vessels (12). The presence of a complex aorticarch anatomy, such as a type III arch or bovine arch,
can render CAS more challenging and increase
the likelihood of neurological problems whenusing the femoral access route (12-14). Indeed, in
our study, a statistically significant difference wasfound between the CEA and CAS groups in termsof the aortic arch structure. More specifically, a typeIII arch was observed more frequently in the CEA
group. We suggest that the preference for surgery
in patients with a type III arch may stem fromconcerns about the risk of cerebral embolization
attributed to the existing anatomy, as discussed
during the decision-making meetings. Still, thelesion severity and plaque morphology also play
crucial roles when deciding between stenting andsurgery. In our cohort, patients with greater levels of
stenosis and ulcerated plaque tended to undergo
CEA.
Two different methods can be used in CEA—
namely, conventional and eversion endarterectomy.
When applying the conventional technique,following the longitudinal arteriotomy of the internal
carotid artery, endarterectomy is performed andthe arteriotomy is repaired or patch angioplasty is
performed. The patch angioplasty technique is mostcommonly applied and has been demonstrated tooffer better results in some studies (15, 16). When
applying the eversion technique, after the internal
carotid artery is obliquely transected from its origin,the artery is turned inside out, plaque excision
is performed, and the internal carotid artery is
reimplanted into the bulbus. Additionally, various
modifications to the eversion method have been
described and found to offer satisfactory results(17). Several studies have reported that both theconventional method and the eversion method areassociated with similar efficacy and reliability (1820). All the patients enrolled in our study underwent
longitudinal arteriotomy followed by conventional
endarterectomy. Patch angioplasty was utilized forthe arteriotomy repair in all the patients except
one, where the primary repair approach was chosen
due to the mildly aneurysmal artery structure.
Another key point that should be emphasizedprocedurally in terms of CAS is the usage of a distal
EPD. The use of EPDs has been limited in the initialstudies concerning CAS. In accordance with thissituation, an EPD was not used in the CAVATAS trial,
where higher rates of stroke and restenosis were1532024; 27(2):146−156

found after eight years of follow-up and only 26%
of patients were treated with stent implantation(21). By contrast, as a combined primary endpoint,
an EPD was used in every technically feasible casein the CREST study, where no significant difference
was found between CAS and CEA with regard to
myocardial infarction, stroke, 30-day mortality, andipsilateral stroke in the first four days (22). In ourstudy, the utilization of EPDs was not favored.
In the vast majority of randomized controlled
trials conducted in the last decade to compare
CAS and CEA, the results obtained using the two
methods have largely been consistent. Amongthese trials, the CEA results were found to be better
when compared with the CAS results in the EVA3S study, which was one of the first studies in thisarea where the use of more sophisticated devices
was limited (23). Although the CAVATAS study did
not have sufficient power for the evaluation of theefficacy and reliability, the SAPPHIRE, CREST, andICSS studies met the non-inferiority criteria for
CAS when compared with CEA, while very similar
results were also obtained in the SPACE study (8, 9,
22, 24). When sub-group analyses of these studies
were analyzed to facilitate patient selection, it
was noteworthy that while the same results wereobtained in general terms, myocardial infarction
was more common in patients who underwent
CEA and stroke was more common in patients
who underwent CAS. The greater occurrence of
myocardial infarction during CEA has been linked
to the emotional stress created by the surgery forthe patient, as well as to possible alterations in the
antiplatelet treatment regimen, whereas the higher
incidence of stroke in CAS has been attributed tothe patients’ more advanced age. In our study, nodifference was detected between the two groups
in terms of the complications, including myocardial
infarction and stroke, during the hospital stay.
Interestingly, in this study, CAS, which represents
a less invasive technique for patients over 70 years ofage, was significantly associated with an increased

154

incidence of stroke when compared with CEA. It has
previously been stated that this situation might beprimarily due to the increased vascular tortuositythat occurs with advancing age. The subgroup
analysis in the NASCET study revealed that patients
aged 75 years and older, and with 50–99% stenosis,
experienced greater benefits following CEA whencompared with younger individuals (25). However,
our subgroup analyses of patients aged below
and over 75 years old did not reveal any significant
difference between the CEA and CAS groups when
it came to the major cumulative complications. We
suggest that the lack of significant findings in our
subgroup analyses may be attributed to the limited
sample size, which potentially constrained ourability to conduct robust subgroup evaluations.
Despite the limited patient population, there wasno significant difference between the two groups
in terms of the patients’ demographic data, postprocedural complications, and mid-term outcomes,
indicating that the two treatment approaches wereused successfully in the appropriate patient groups
in our study. Advancements in stent technology
and the use of sophisticated materials may alter
treatment choices in the future, although surgery
will retain its indispensable role. Large randomized
prospective trials are still required to determine
the most appropriate treatment, particularly forasymptomatic individuals, including symptomaticpatients.
Conflict of Interest: The authors state thatthe study was conducted without any commercial
or financial relationships that could be seen as apotential conflict of interest.

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ORIGINAL ARTICLE

Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.389
2024; 27(2):157−167
 Funda ATAR1 . . . . . . . . . . . . . . . . 

 Gülsen KESKİN1 . . . . . . . . . . . . . 
 Burhan KURTULUŞ2 . . . . . . . . . . 
 Reyhan POLAT1. . . . . . . . . . . . . . 
 Aslı DÖNMEZ1 . . . . . . . . . . . . . . . 

CORRESPONDANCE
1Funda ATAR

Phone
e-mail: +905064927432: fundaatar81@gmail.com

Received : Apr 26, 2024
Accepted : May 23, 2024

1 University of Health Sciences, Etlik City

Hospital , Department of Anesthesiology
and Reanimation, Ankara, Turkey

2 Dışkapı Yıldırım Beyazıt Training and

IS RED CELL DISTRIBUTION WIDTHCORRELATED WITH MORTALITY INGERIATRIC PATIENTS UNDERGOING HIPFRACTURE SURGERY: A PROSPECTIVEOBSERVATIONAL STUDY

ABSTRACTIntroduction: Our study aimed to determine the impact of preoperative red
blood cell distribution width on length of intensive care unit and hospital stays,
and short- and long-term mortality in elderly patients undergoing hip fracture
surgery.
Materials and Method: This prospective cohort study included 414 patients
aged 65 and older who presented with hip fractures between November 2021
and November 2022. Patients’ demographic characteristics, American Societyof Anesthesiologists score, Revised Cardiac Risk Index, comorbidities, andpreoperative complete blood counts (hemoglobin, red blood cell distribution
width, platelet count, etc.) were recorded at the preoperative visit. Lengthof intensive care unit and hospital stays were documented postoperatively.
Patients were followed for one year after surgery in terms of mortality.
Results: Patients with high red blood cell distribution width levels (≥14.25%)
were older, had more comorbidities, and had higher American Society ofAnesthesiologists score and Revised Cardiac Risk Index scores (p<0.001). In
the high red blood cell distribution width group, length of hospital stays was
longer (p<0.001). There was no significant difference between red blood cell
distribution width groups in terms of intensive care unit stay duration andreadmissions (p=0.304 and p=0.664, respectively). According to the multivariate
logistic regression analysis, an red blood cell distribution width of ≥14.25 was
found to increase the risk of 30-day mortality by 4.7 times and 1-year mortality
by 2.74 times.
Conclusion: Red blood cell distribution width is a useful, practical, andcost-effective indicator of short- and long-term mortality in elderly patients
undergoing hip fracture surgery.
Keywords: Aged; Anemia; Hip fracture; Mortality.

Research Hospital, University of Health
Sciences, Department of Orthopedics,
Ankara, Turkey

1572024; 27(2):157−167

INTRODUCTION
Hip fracture, a common problem in geriatricpatients, is linked to significant mortality andmorbidity rates (1). Over 1 million hip fractures occur
annually, imposing a burden on society (1). Even
with treatment, 1-year mortality after hip fracture is
between 8.4% and 36.0% (2). Therefore, a definitive
prognostic parameter is crucial for effective risk
stratification. Comorbidities, age, perioperativecomplications, and various risk prediction models(such as the Charlson Comorbidity Index and theorthopedic version of the Physiologic and Operative
Severity Score) are recognized factors influencing
mortality in hip fracture patients (3). Nevertheless,these models are time-consuming, requiring further
calculations, so a need exists for a simple, costeffective laboratory parameter associated withpostoperative mortality (1).
Red cell distribution width (RDW) measures
heterogeneity in erythrocyte sizes and is a routine
parameter of a complete blood count (CBC) test.
It is calculated automatically or manually with thisformula: (standard deviation of mean corpuscularvolume / mean corpuscular volume) × 100 (4).
Generally used to investigate hematologicaldisorders, RDW has recently been proposed
as a long-term inflammatory biomarker (5). An
association between increased RDW and mortality
has been reported in many diseases, such as
diabetes mellitus (DM), hypertension (HT), coronary
artery disease (CAD), acute pancreatitis, and sepsis(6). In this study, evaluate the impact of RDW on
30-day and 1-year mortality in geriatric patients
undergoing hip fracture surgery.

MATERIALS AND METHOD
The hospital ethics committee approved theresearch on October 4, 2021 (reference no: 121/05),
and a prospective observational study was planned
to include patients aged 65 and older with adiagnosis of hip fracture confirmed by imaging
158

examinations from November 1, 2021, to November
1, 2022. Written consent was obtained from all
patients. The exclusion criteria included declining
participation in the study, absence of preoperative
CBC test, indefinite fracture time, and recent historyof blood transfusion, as exogenous red blood cells
could alter the RDW (7). The patients in the study
were visited preoperatively by an anesthesiologist,
and their demographic data (age, gender, bodymass index [BMI]) comorbidities (such as DM, HT,congestive heart failure [CHF], and chronic renal
failure [CRF]), American Society of Anesthesiologists(ASA) score, and Revised Cardiac Risk Index (RCRI)
were recorded.
Blood samples were collected from thepatients, and CBC parameters were analyzed(hemoglobin, RDW, platelet count, etc.). The CBC
was conducted with the Symex XN-550 automatedhematology analyzer (Sysmex Corp., Kobe, Japan),with reference values for RDW coefficients ofvariation ranging between 12.2% and 16.5%. Other
biochemical tests were performed using standard
techniques with the Beckman Coulter LH 780 device(Beckman Coulter Inc., Brea, New York, USA).
Anemia was classified as follows: mild (11.0-11.9 g/
dL for women, 11.0-12.9 g/dL for men), moderate(8.0-11.0 g/dL), and severe anemia (< 8.0 g/dL) (5).
At the time of discharge, records were taken of theanesthesia method (general or local anesthesia),
surgery duration, postoperative first-day CBC (RDWand hemoglobin levels), in-hospital complications(including hypoxemia, pneumonia, acute coronary
syndrome, arrhythmia, stroke, severe bleeding,infection, and acute renal failure), and length ofintensive care unit (ICU) and hospital stays. Patientswere contacted by phone 1 year after discharge.
The last phone call was conducted on November
1, 2023. The primary endpoint of the study was toinvestigate the impact of RDW on 30-day and 1-year
mortality, and the secondary endpoint focused on
the effect of RDW on readmission and length of ICU
and hospital stays.

IS RED CELL DISTRIBUTION WIDTH CORRELATED WITH MORTALITY IN GERIATRIC PATIENTSUNDERGOING HIP FRACTURE SURGERY: A PROSPECTIVE OBSERVATIONAL STUDY

Statistical analysis
The data were statistically analyzed using IBM SPSS
Statistics for Windows, version 20.0. The study
examining the effect of RDW on mortality used
as a reference the study of Wei-Hsiang et al. (1).
The sample size to detect a significant differenceof 1 unit in RDW averages between deceased andsurviving groups was calculated with a 5% error level
and a minimum 80% power using the two-sided
t-test. Accordingly, the study was planned with aminimum of 87 patients in the mortality group and
114 patients in the surviving group over 1 year.
To determine the statistical methods to be
applied, the Shapiro-Wilk normality test was initiallyconducted. If the assumption of normality was
not met in any of the groups, non-parametric test
methods were selected. In this context, Student’s
t-test and/or the Mann-Whitney U test were used tocompare variables obtained through measurements
between two independent groups. Mean, standard
deviation, and median (minimum–maximum) values
were provided to summarize continuous variables,
and Fisher’s exact test and chi-squared test results
were presented as frequency distributions andpercentages for categorical variables.
The area under the receiver operating
characteristic (ROC) curve provides an estimate of
the overall accuracy of alternative tests. An area of
0.50 indicates that the variable adds no information.
For an alternative test, areas under the ROC and
95% confidence intervals (CIs) were calculated as
defined by Hanley and McNeil (8). For the variables
whose diagnostic powers were found to bestatistically significant, the cutoff points determinedaccording to the Youden index are given together
with the relevant sensitivity and selectivity points.
All variables with statistical significance in theunivariate analyses were considered eligible forinclusion in the multiple analysis and were tested forcollinearity. Cutoff points determined by the Youden
index for variables with statistically significant
diagnostic power are provided along with relevant

sensitivity and specificity scores. Multiple logistic
regression analyses were conducted using the
backward logistic regression approach. Variables
that remained significant (p <.05) in the multivariate
model were considered independent predictors.
Hosmer-Lemeshow goodness-of-fit statistics wereused to evaluate the model fit. Odds ratios (ORs)and 95% CIs were calculated for each predictor.

RESULTS
Figure 1 illustrates the flowchart of patient selection.
A total of 414 geriatric patients with hip fractures,
165 males and 249 females, were included in the
study. The mean age of the patients was 76.37 ±8.52 years, and mean RDW was 14.5 ± 2.07%. Table
1 presents the patients’ basic characteristics.
Table 2 summarizes the study group’s clinicalcharacteristics, comorbidities, and complications
according to RDW levels. Patients with higher RDW
levels were older and had higher ASA and RCRI
scores (p <.001). The percentage of anemia in the
RDW ≥14.25% group was higher than in the RDW<14.25% group (79.13% vs. 48.28%, respectively;
p <.001). The most common complications inhospital were acute kidney injury and pneumonia in
the group with high RDW (4/182, 2.19%, for both).
The length of hospital stays was longer for patientsin the high RDW group (p<.001). No statisticallysignificant difference was observed between thetwo groups regarding the length of ICU stay andreadmissions within the 1-year hospital (p= .304,
p=.664, respectively).
The area under the curve (AUC) for both 30-day
and 1-year mortality were found to be statisticallysignificant in higher RDW patients (p <.001). The
AUC was 0.732 (95% CI: 0.671–0.793) for 30-day
mortality and 0.709 (95% CI: 0.654–0.765) for 1-year
mortality. Accordingly, RDW values of ≥14.25 were
determined to predict 30-day mortality, whereas
values of ≥14.05 were found to predict mortality at
1 year. Figure 2 shows ROC curves illustrating the
AUC for both mortality rates.

1592024; 27(2):157−167

Figure 1. Study cohort flow diagram

Table 1. Demographic and Clinical Characteristics of Patients
Preoperative characteristics of patients (n = 414)

ValuesAge (year)

76.37±8.52

Sex, male, n (%)

165 (39.86)

BMI (kg/m2)

26.99±3.37

RDW (%)

14.5±2.07

Length of hospital stay (days)

5.78±8.85

Length of ICU stay (days)

2.14±6.86

Readmission n (%)

22 (5.31)

30-day mortality n (%)

65 (15.7)

1 year mortality n (%)

94 (22.71)

Values are given as mean ± SD or number (percentage). BMI, body mass index; RDW, red blood cell distribution width; ICU, intensive care unit

160

IS RED CELL DISTRIBUTION WIDTH CORRELATED WITH MORTALITY IN GERIATRIC PATIENTSUNDERGOING HIP FRACTURE SURGERY: A PROSPECTIVE OBSERVATIONAL STUDY

Table 2. Characteristics of the study population by RDW group (n = 414)
RDW value

RDW <14.25% (n=232)

RDW ≥14.25% (n=182)

p valueAge (years)

75.03±7.97

78.08±8.91<0.001

Male n (%)

93 (40.08)

72 (39.56)

0.914

BMI (kg/m2)

26.82±3.3

27.2±3.46

0.261

Comorbidity n (%)

152 (65.51)

151 (82.96)<0.001Diabetes mellitus

59 (25.43)

70 (38.46)

0.004

Systemic Hypertension

115 (49.56)

105 (57.69)

0.1

8 (3.44)

4 (2.19)

0.452

Hyperlipidemia
Heart failure

5 (2.15)

13 (7.14)

0.014

Coronary artery disease37 (15.94)

45 (24.72)

0.026

Peripheral artery disease

1 (0.43)

2 (1.09)

0.585

Atrial fibrillation

14 (6.03)

25 (13.73)

0.008

Asthma14 (6.03)

10 (5.49)

0.815

COPD

11 (4.74)

15 (8.24)

0.145

Cerebrovascular disease

18 (7.75)

17 (9.34)

0.566

History of malignancy

5 (2.15)15 (6.5)

0.004

Chronic renal failure

8 (3.44)

18 (8.24)

0.007

Alzheimer’s disease

16 (6.89)

21 (11.53)

0.1

Thyroid dysfunction

18 (7.75)

21 (11.53)

0.191

Chronic liver disease03 (1.64)

0.084

Rheumatoid arthritis

6 (2.58)

7 (3.84)

0.466

Parkinson’s disease

7 (3.01)2 (1.09)0.309

Heart valve disease0

2 (1.09)0.193

2 (0.86)

1 (0.54)

1

General anesthesia

96 (53.33)

84 (46.67)

Regional anesthesia

136 (58.12)

98 (41.88)

15 (6.46))

17 (9.34)

Acute kidney failure

1 (0.43)

4 (2.19)

Acute coronary syndrome

2 (0.86)

3 (1.64)

Infection

5 (2.15)

3 (1.64)

Pneumonia

3 (1.29)

4 (2.19)

Epilepsy
Anesthesia typen (%)
Complication n (%)

RCRI n (%)

Atrial fibrillation

2 (0.86)0

Embolism

1 (0.43)

1 (0.54)

Bleeding

01 (0.54)

Hypoxemia

1 (0.43)

1 (0.54)

Low risk

142 (61.20)

72 (39.56)

Medium risk

60 (25.86)

64 (35.16)

High risk

30 (12.93)

46 (25.27)

0.331

0.565

<0.001161

2024; 27(2):157−167

Table 2. Continued
RDW value
ASA physicalstatus n (%)

RDW <14.25% (n=232)

RDW ≥14.25% (n=182)

1

67 (28.87)

24 (13.18)

2111 (47.84)

85 (46.70)

3

47 (20.25)

55 (30.21)

47 (3.01)18 (9.89)

p value<0.001

No anemia

120 (51.72)

38 (20.87)

Mild anemia

106 (45.68)

121 (66.48)

Moderate anemia

4 (1.72)

8 (4.39)

Severe anemia

2 (0.86)

15 (8.24)

Hemoglobin (g/dL)

12.39±1.82

10.91±2.05<0.001

Hematocrit, %36.94±5.3333.64±5.72

0.001

Platelet (109/L)

222.91±76.87

250.95±101.05<0.001

MCV (fL)

88.03±4.24

83.97±8.95

0.168

WBC (109/L)<0.001Preoperative
anemia n (%)<0.00110.06±4.15

10.61±4.62

Lymphocyte (109/L)

1.61±0.82

1.38±0.85

0.001

Monocytes (109/L)

0.64±0.27

0.72±0.3

0.040

Neutrophil (109/L)

7.74±3.94

8.5±4.24

0.004

RBC (109/L)

4.22±0.67

4.02±0.74<0.001

MCH (pg)29.64±1.5627.35±3.55<0.001MCHC (g/dL)

33.67±1.3932.42±1.58<0.001Albumin (g/dL)

39.81±9.834.95±9.8

0.034

Alkaline phosphatase (IU/L)

97.33±42.74

120.28±76.19<0.001

C reactive protein (mg/dL)

38.95±67.85

83.22±88.29

0.001

Urea (mg/dl)

41.43±21.71

49.95±29.68

0.009

Serum creatine (umol/L)

0.87±0.37

1.13±1.08

0.314

Sodium (mEq/L)

138.73±3.78138.7±3.71

0.243

Potassium (mEq/L)

4.26±0.45

4.34±0.55

0.009

Calcium (mg/dL)

8.79±0.72

8.59±0.83<0.001INR

1.04±0.1

1.17±0.49<0.001

Length of hospital stay (days)

4.55±3.78

7.34±12.49<0.001

Length of ICU stay (days)

1.24±2.56

3.27±9.83

0.304

Readmission n (%)

10 (45.45)

12 (54.55)

0.664

Operation duration (min)75.47±27.15

74.07±22.44

0.664

30-day mortality n (%)

14 (21.54)

51 (78.46)<0.001

1 Year mortality n (%)

29(30,85)

65(69,15)<0.001

Values are given as mean ± SD or number (percentage). RDW, Red blood cell distribution width; BMI, Body mass index; COPD, chronic obstructive pulmonary disease; RCRI, Revised Cardiac Risk Index, ASA, American Society of Anesthesiologists; MCV, Mean corpuscular volume, WBC,White blood count, RBC, Red blood cells; MCH, Mean corpuscular hemoglobin, MCHC, Mean corpuscular hemoglobin concentration, INR,
International normalized ratio; ICU, Intensive care unit

162

IS RED CELL DISTRIBUTION WIDTH CORRELATED WITH MORTALITY IN GERIATRIC PATIENTSUNDERGOING HIP FRACTURE SURGERY: A PROSPECTIVE OBSERVATIONAL STUDY

Figure 2. Receiver Operating Curve of Red Blood Cell Distribution Width in predicting 30-day mortality (A) and 1-year mortality (B)Table 3. Multivariate analysis to identify factors associated with 30-day mortality

RDW ≥14,25

OR (95% C.I.)(Univariate)pOR (95% C.I.)(Multivariate)p6.06 (3.22-11.38)<0.0014.68 (2.35-9.33)<0.001Age

1.18 (1.08-1.15)<0.0011.09 (1.05-1.14)<0.001

Atrial fibrillation

3.55 (1.76-7.29)

0.001

2.64 (1.14-6.11)

0.023

Alzheimer’s disease

5.10 (2.49-10.43)<0.0012.98 (1.27-6.97)

0.012

CRF

3.78 (1.63-8.76)

0.002

3.42 (1.30-9.03)

0.013

RDW, Red blood distribution width; Chronic renal failure, CRF

According to the multivariate logistic regression
analysis, high preoperative RDW levels wereindependent risk factors for postoperative 30-day
and 1-year mortality. A RDW of ≥14.25 increased
the risk of death within 30 days by approximately
4.7 times; for 1-year mortality, it increased the risk
by 2.74 times. Other independent determinants of
30-day mortality included advanced age (OR 1.09
[1.05–1.14], p<.001), atrial fibrillation (OR 2.64 [1.14–

6.11], p=.023), Alzheimer’s disease (OR 2.98 [1.27–
6.97], p=.012), and chronic kidney disease (OR 3.42
[1.30–9.03], p=.013), (Table 3). Other independent
determinants of 1-year mortality included advancedage (OR 1.09 [1.05–1.13], p<.001), Alzheimer’s
disease (OR 5.35 [2.29–12.46], p=.012), high RCRI
(OR 3.02 [1.45–6.30], p=.003), and uremia (OR 1.01
[1.00–1.02], p=.01).

163

2024; 27(2):157−167

DISCUSSION
Our study demonstrated that high RDW (>14.25%)
in aged patients who have hip surgery correlateswith age and comorbidity burden. This condition
did not increase the duration of ICU stay orrisk of readmission. Nevertheless, we observed
an independent increase in mortality risk overboth short and long periods in patients with apostoperative RDW >14.25%.
It is claimed that RDW levels increase byapproximately 1% per year in individuals aged
60 and above (9). In our study, patients with RDW>14.25 were older compared to those with RDW≤14.25. Therefore, the age distribution between
our groups confirms the association between high
RDW and age. This phenomenon is explained by
the natural decline in the physiological functionsof erythropoiesis with aging (10). Yet, it remains
uncertain whether the elevated RDW in these patientgroups is a result of aging itself or a consequence of
critical illness. Therefore, we are inclined to believethat the reason for high RDW in these patients is not
attributable to age alone.
The causes of elevated RDW are multifactorial.
Several studies suggest that RDW can serve
as a biomarker for assessing mortality risk incomorbidities such as heart disease and cancer(5,11). Nevertheless, it remains unclear whether the
relationship between elevated RDW and mortality iscausal or consequential. In light of all these findings,
we believe that RDW to be an indicator that reflects
the prognosis of frail patients. Therefore, we
emphasize the importance of clinicians considering
RDW when assessing prognosis during preoperative
examinations.
In our study, comorbidities such as DM, CRF,
and CHF were more frequently observed inpatients with high RDW values. Our findings,
in conjunction with previous studies, support
the potential relationship of RDW with adverse
outcomes in chronic diseases (12,13). Although164

the pathophysiological mechanisms between high
RDW and poor prognosis remain uncertain, it has
been proposed that various systemic factors suchas oxidative stress, inflammation, and inadequate
nutrition (deficiencies in iron, folate, vitamine B12,etc.) could explain this relationship (6,14). Oxidative
stress occurring in chronic illnesses may lead toincreased production of reactive oxygen radicals,
disruption of erythrocyte homeostasis, and anincrease in mortality (15). Additionally, inflammation
can affect bone marrow function and disrupt ironmetabolism, thereby influencing the erythropoiesis
process (5).
Although we found an association between
high RDW and length of hospital stay, we did notobserve a difference in terms of postoperativecomplications, length of ICU stays, or risk ofreadmission. In this regard, our findings contradict
previous studies (6,16). In our study, patients withelevated RDW were older than in other studies, andthey had a higher burden of comorbidities. This may
have affected the clinical decision-making processof clinicians and created a reflex to keep patientsin the hospital for a longer period (17). However,
we observed that more objective decisions, suchas ICU stay duration and readmission, were notinfluenced by RDW values. Although we could notdemonstrate the significance of RDW in terms ofcomplications, pneumonia was the most frequently
observed complication in the high RDW group.
This also supports the findings of previous studies(18,19).
In our study, we showed that high RDW is
independently correlated with postoperative
mortality at both 30-day and 1-year periods. Hung
Wei-Hsiang et al. reported that RDW>13.35%
caused an increase in the risk of 30-day mortality
in patients (1). However, this increase in 30-day
mortality is quite slight and contradicts our findings.
This difference may be attributed to variations in thecomposition of populations or matching disparities
between the two studies. Similarly, in a randomized

IS RED CELL DISTRIBUTION WIDTH CORRELATED WITH MORTALITY IN GERIATRIC PATIENTSUNDERGOING HIP FRACTURE SURGERY: A PROSPECTIVE OBSERVATIONAL STUDY

controlled trial involving heart failure patients,
Felker and colleagues report a twofold increase in
the risk of mortality with RDW values above 15.8%
compared to those with RDW values below 13.3%(20). Tonelli et al., meanwhile, reported a twofold
higher probability of mortality in patients with CAD
with RDW greater than 13.8% compared to thosewith RDW less than 12.6% (21). However, Michael
Berry and colleagues assessed the effect of RDW on
mortality in emergency laparotomy patients aged
65 and older and could not establish an association
between anisocytosis and 30-day mortality (14).
In our study, it was observed that an RDW >14.25
was correlated with 4.7 times increased 30-day
mortality and 2.74 times increased 1-year mortality.
The selection of younger patients in comparison
to our study and the inclusion of patients withspecific comorbidities in these studies may havecaused these differences. However, none of thesestudies considered robust adjustment factors suchas nutritional status, immune status, hemoglobin
levels, and multiple diseases that reduce the riskof confusing factors based on a conceptual model.
Finally, although studies support the relationshipbetween high RDW and mortality, the differencein RDW cut-off values affected the mortality risk
prediction rate. This is because there is currently nostandardized threshold value to define high RDWlevels. Formun AltıTherefore, despite the indicationof clinically significant associations between high
RDW and mortality, we believe that future studies
are needed to determine an optimal thresholdvalue.
While attempting to predict postoperative
mortality rates following hip fracture surgery, there
is a need for tests that clinicians can easily apply.
Previous studies have found an association between
high RCRI scores and 30-day mortality in patients
undergoing hip fracture surgery (22). Additionally,Yin et al. suggested that evaluating RDW and ASA
scores together may provide a more powerful andeffective strategy for predicting mortality in hip

fracture patients (23). The findings of our study
suggest that mortality increases as ASA and RCRI
scores increase. However, the availability of RDW
in automated CBC results is a factor that increases
its value. Additionally, RDW assessment is practicaland cost-effective. Nevertheless, there are various
factors that can affect RDW values. Therefore, we
believe that RDW alone may not be used as aneffective and independent factor in predicting
prognosis. However, combining RDW with otherknown prognostic indicators may enhance thepower of risk models. Therefore, in preoperative
assessment, RDW, when used in conjunction withother scoring systems, can facilitate resource
allocation, potentially providing a practicalcontribution to the current risk classification strategy.
The strengths of this study are its prospective
design, unbiased inclusion criteria, and long-term
follow-up of patients. However, various potential
limitations should be considered. Firstly, patientswere treated and followed up in a single tertiary
center, which may not represent other healthcare
centers and ethnicities. Secondly, while theassessment of RDW is quick, straightforward, anddoesn’t demand specialized skills or equipment,
there are various methods available for measuring
red cell size (e.g., impedance or optical techniques)
and RDW (24). This can lead to variations inreference values depending on the device andpopulation. Finally, there was no common opinion
on the optimum threshold value for the prognostic
aim of RDW (25).
This prospective study revealed a strong
association between preoperative RDW andshort-term and long-term mortality in geriatricpatients who have hip surgery. Due to its routine
reporting in CBC, lack of additional cost, andeasy interpretability, RDW may provide a practicalcontribution to predicting patient prognosis.

1652024; 27(2):157−167

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167

ORIGINAL ARTICLEVARIABLES AFFECTING MORTALITY IN
PATIENTS IN PALLIATIVE CARE UNITS:
OR IS IT STILL JUST ALBUMIN?
Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.390
2024; 27(2):168−177
 Abdullah YEŞİLKAYA1 . . . . . . . . . 
 Müge ARIKAN1 . . . . . . . . . . . . . . 

 Büşra Nur TAŞDELEN1 . . . . . . . . 
 Emre MERİÇ1. . . . . . . . . . . . . . . . 
 Ayşe AKHAN1. . . . . . . . . . . . . . . . 

 Murat DİNDAR1 . . . . . . . . . . . . . . 
 Arda ULUTAŞ1 . . . . . . . . . . . . . . . 

 Didem ADAHAN2 . . . . . . . . . . . . . 

 Ufuk KARADAVUT3 . . . . . . . . . . . 

 Mehmet Murat ŞAHİN4. . . . . . . . . 

CORRESPONDANCE
1Abdullah YEŞİLKAYA

Phone : +905327160016
e-mail : dr.abdullahyesilkaya@gmail.com
Received : May 07, 2024
Accepted : Jun 02, 2024

1 Karabuk University Faculty of Medicine,

Department of Anesthesiology, Karabük,
TurkeyABSTRACTIntroduction: This study aimed to evaluate the relationship between
biomarkers, clinical prognostic indexes, and mortality in patients without
malignancy.
Materials and Method: This retrospective study included patients who were
followed up in palliative care units between January 2020 and January 2024.
Data were collected from patients’ digital database records. Demographic
characteristics, clinical features, comorbidities, main reasons, and lengthof hospital stay were recorded. Laboratory parameters were measured atadmission. Patient outcomes were also documented.
Result: The study included 416 patients. The mortality rate was 28.36%(n=118). When survivors and nonsurvivors were compared, variables including
albumin, protein, white blood cells, neutrophils, C-reactive protein, procalcitonin,
CRP/albumin, CRP/protein, neutrophil/lymphocyte, and platelet/lymphocyte
ratios significantly affected mortality. Logistic regression analysis revealed that
only the albumin level was statistically significant (0.010). It was found significant
that the albumin value was below 2.76 g/dL (odds ratio 3.688; the area under
the curve (AUC)=0.670, and P<.000). The sensitivity and specificity of an albumin
cutoff value of 2.05 g/dL were 85% and 97%, respectively.
Conclusion: Our study highlights the pivotal role of hypoalbuminaemia
as the most significant predictor of mortality in patients on the palliative careunit (PCU) without malignancy. To optimise patient care in palliative settingsand better tailor therapeutic interventions, we must recognise the vital role ofhypoalbuminaemia as a critical risk factor.
Keywords: Palliative Care; Mortality; Albumin.

2 LÖSANTE Children\’s and Adult Hospital,

Department of Family Medicine, Ankara,
Turkey3 Karabuk University Faculty of Medicine,

Department of Biostatistics, Karabük,
Turkey4 Karabuk University Faculty of Medicine,

Department of Family Medicine, Karabük,
Turkey168

VARIABLES AFFECTING MORTALITY IN PATIENTS IN
PALLIATIVE CARE UNITS: OR IS IT STILL JUST ALBUMIN?

INTRODUCTION
Palliative care (PC) is a multidisciplinary approachthat improves the quality of life of patients with lifethreatening diseases and their families. The needfor palliative care units (PCU) is rapidly increasing
worldwide owing to the ageing population andrising prevalence of cancer and comorbidities (1,2).
Despite this need, PC applications have still notbeen developed at the desired level in many partsof the world, such as our country.
The standard protocol is unclear in our country,
although PC protocols have been established inmany countries worldwide, such as the UnitedStates, Canada and Germany (3). One of themost important reasons is that PC is not a specificmedical speciality in Turkey. Physicians from various
medical specialities, such as Anaesthesiology andReanimation, Family Medicine, Neurology, andInternal Medicine, provide services. Palliative careand its features are not well-known to society or
general health professionals (1,4).
This study aimed to conduct a descriptive
analysis by evaluating patients admitted to the
PCU. This study also aimed to determine factors
affecting mortality. Our research effectively uses alimited number of PCU beds. We assume this will
help us create a PCU management protocol for our
hospital.

MATERIALS AND METHOD
After obtaining approval from the local ethics
committee(2024/1684),
thissingle-centre
retrospective study was conducted at Karabuk
University Hospital in Karabuk, Turkey. This study
was conducted in accordance with the principles of
the Declaration of Helsinki.
All patients admitted to the PCU between 1
January 2020 and 1 January 2024 were evaluated.
Data were obtained by scanning patients’ hospital
digital database records. Patients who were
hospitalised with a diagnosis of COVID-19, stayed≤ 24 hours, were under the age of 17, and had
insufficient file information were excluded. Only
the first admission was considered for patients withrecurrent PCU. Patients diagnosed with malignancy
were excluded based on the study design.
The PCU is a 14-bed unit staffed by a family
medicine anaesthesiologist on a 24-hour-per-day,
7-days-a-week basis. The following data wererecorded: age, sex, place of admission, includingfrom home, intensive care unit (ICU), emergency
department (ED), and other services; feedingstyle; respiratory pattern, including spontaneous
breathing, tracheostomy, home invasive mechanicalventilation; decubitus status, and comorbidities.
Patient comorbidities were retrospectively analysedby scanning their ICD-10 (International Statistical
Classification of Diseases) codes. They werecategorised as cardiovascular disease, including
hypertension, heart failure, and arrhythmia;
neurological disease, including cerebrovasculardisease, epilepsy, Alzheimer disease, and Parkinson
disease; respiratory disease, including asthma
and chronic obstructive pulmonary disease;metabolic disease, including diabetes mellitus,
hypo/hyperthyroidism, renal failure, and cirrhosis;
psychiatric disease, including depression, bipolar
disorder, schizophrenia, and other diseases suchas peptic ulcer, gastroesophageal reflux disease,
Schögren scleroderma, Behçet disease, benign
prostatic hyperplasia, and osteoporosis.
Charlson Comorbidity Index (CCI) was used asa clinical prognostic index. Charlson Comorbidity
Index (CCI) is used as an index of survival andprognosis, like other prognostic scoring such as
the APACHE II, Palliative Prognostic Index or the
Karnofsky Performance Scale (5,6). We preferred to
use CCI. This index was calculated using the MDcalc
website(https://www.mdcalc.com/calc/3917/
charlson-comorbidity-index-cci) with comorbidities.
The feeding style was classified as parenteral,nasogastric tube (NG), percutaneous endoscopic
gastrostomy (PEG), or oral and percutaneous
1692024; 27(2):168−177

endoscopic jejunostomy (PEJ). The main reasonsfor PCU admission (palliation, nutritional difficulty,
decubitus, and pain) and the length of hospital
stay were recorded. The laboratory values of eachpatient were recorded, including haemogram —haemoglobin, platelet count, neutrophils, andlymphocytes; biochemistry — liver and kidney
function tests, electrolytes, albumin, and protein
values; infection markers — C-reactive protein(CRP) and procalcitonin). CRP/albumin ratio (CAR),
CRP/protein ratio (CPR), neutrophil/lymphocyte
ratio (NLR), and platelet/lymphocyte ratio (PLR)
were calculated. Additionally, the discharge statusof the patients was evaluated, and the mortality rate
was calculated.
Data analysis
In this study, variables that were the primary reasonsfor hospital admission and comorbidities were
proportionally assigned according to the numberof admissions. Descriptive statistics of the variables
used in the data set, number of observations (N),and mean ± SD are given. To determine mortality
rates, data obtained for those who lived and died
were compared. Before comparison, normality
tests were performed using the Kruskal–Wallisand Shapiro-Wilk methods. For comparison, thet-test was used for parametric data, whereas
the Mann–Whitney U test was used for nonparametric data. The significance level was set at
P<.05. Logistic regression analysis was performed
to determine the variables affecting mortality.
Therefore, we attempted to explain the variables
that caused these deaths. The Wald test wasapplied for model selection in logistic regression.
In addition, the Receiver Operating Characteristic(ROC) curve method was applied to distinguishbetween deceased and living individuals based on
the determining factors. The SPSS 22 V statisticalprogramme was used for all analyses.

170

RESULTS
During the study period, 934 patients wereadmitted to a PCU. Data from 269 patients were
excluded due to recurrent PCU admissions otherthan the first admission. A total of 249 patients were
excluded for the following reasons: 128 patientswere diagnosed with COVİD, 90 patients werediagnosed with malignancy, 17 patients had missing
data, and 8 patients stayed ≤24 hours. Six patientsstill hospitalised were excluded from the study.
A total of 416 patients were included in thisstudy. The mean age of the patients was 74.65±
13.58 years, and 228 were men (54.81%). Most
patients were admitted to the ICU and ED. The
clinical and demographic characteristics of patientsare presented in Table 1. The mean length of stay
was 15.84 ± 13.37 days. The mortality rate was
28.36% (n = 118).
The most common comorbidities werecardiovascular and neurological disease; 293
patients had three or more comorbidities (Table 1).
Education of patients’ relatives (for patients
admitted from the ICU for nutrition or homemechanical ventilator training), malnutrition,decubitus, and pain were the main reasons foradmission to the PCU.The most common reason
for admission was palliation with 43.27%. Other
reasons were malnutrition in 25.24%, decubitus in
19.23%, pain in 6.25% and other in 6.01%.
Among them, 118 died, with a mortality rateof 28.36%. There were significant differencesin albumin, protein, WBC, neutrophil, CRP,
procalcitonin, CAR, CPR, NLR, and PLR between
survivors and nonsurvivors. The data obtained fromthe t test of mortality analysis conducted according
to the characteristics examined in this study are
shown in Table 2.
Logistic regression analysis was applied to all
the significant parameters, and the results arepresented in Table 3. The table shows that only thealbumin level was statistically significant among theVARIABLES AFFECTING MORTALITY IN PATIENTS IN
PALLIATIVE CARE UNITS: OR IS IT STILL JUST ALBUMIN?

Table 1. The demographic and clinical features of the patients

Age

Sex

n

Mean ± SD

416

74.65 ± 13.58

188

77.16 ± 12.95

Men

228

72.57 ± 13.75

Women

n

%

188

54.81%

Total

Women

Men

ICU

Place of acceptanceED

ServiceHome

Tracheostomy
Home mechanical ventilator

Yes

26.20%

75

18.03%

73

17.55%

88

21.15%
78.85%

79

18.99%

No

337

81.01%

NG

PEG
Oral
Yes

No

81

19.47%

132

31.73%

124

29.81%

78

18.75%

1

0.24%

285

68.51%

131

31.49%
Mean ± SD
15.84 ± 13.37

CCI

7.45 ± 2.60
Neurological diseasen366

Cardiovascular disease

438

Metabolic disease

217

Pulmonary disease

Psychiatric disease
Postoperative
Others1 and lessNumber of Comorbidity

109

328

LOS

Comorbidity

38.22%No

PEJ

Decubitus

45.19%

159

Yes
Parenteral

Feeding style

228

2
3

4

5 and more

68
36
9
107
43
80
110
102
81

ICU: Intensive Care Unit, ED: Emergency Department, NG: Nasogastric Tube, PEG: Percutaneous Endoscopic Gastrostomy, PEJ: Percutaneous
Endoscopic Jejunostomy, LOS: Length of Stay, CCI: Charlson Comorbidity Index.

1712024; 27(2):168−177

Table 2. A comparison of survivors and nonsurvivors
Mortality analysis
Survivors (n=298)

Nonsurvivors (n=118)

Age, years

74.45 ± 14.25

75.12 ± 11.74

P values.624

LOS, day15.04 ± 11.39

17.92 ± 17.30.097

Sodium, mEq/L

138.34 ± 5.17

138.21 ± 6.52

.838

Albumin, mg/dL

3.12 ± 0.62

2.76 ± 0.52.000*

Protein, mg/dL

5.85 ± 0.97

5.44 ± 1.05.000*

WBC, 10’9/L

8.96 ± 4.27

10.57 ± 6.12.010*

Haemoglobin, g/dL

10.34 ± 2.11

9.91 ± 1.95

.051

283.69 ± 127.77

258.99 ± 144.76.107

Neutrophil count, 10’9/L

8.69 ± 12.32

13.53 ± 18.56.010*

Lymphocyte count, 10’9/L

1.77 ± 2.53

2.08 ± 4.59

.502

Platelet, 10’9/L

CRP, mg/L

75.74 ± 73.61

114.26 ± 72.09.000*

Procalcitonin, ng/mL

0.69 ± 1.55

1.57 ± 4.23

.030*

CAR

26.84 ± 27.99

42.32 ± 25.80

.000*

CPR

13.79 ± 14.06

21.42 ± 13.27

.000*

NLR

6.42 ± 5.87

10.94 ± 10.70

.000*

PLR

245.04 ± 176.17

301.66 ± 281.02.043** Statistically significant; WBC: white blood cell; CRP: C-reactive protein; CAR: C-reactive protein/albumin ratio; CPR: C-reactive protein/protein
ratio; NLR: neutrophil/lymphocyte ratio; PLR: platelet/lymphocyte ratio.

Table 3. Logistic regression mortality analysis of all parameters
Parameters

B

SE

Wald

Sig.

Odds Ratio

Albumin

1.305

0.667

3.828

0.010

3.688

Protein-0.388

0.412

0.888

0.346

0.678

WBC

-0.043

0.050

0.732

0.392

0.958

Neutrophil

0.002

0.025

0.005

0.945

1.002

CRP

-0.018

0.017

1.188

0.276

0.982

Procalcitonin-0.041

0.103

0.155

0.694

0.960

CAR

0.102

0.412

2.662

0.105

0.981

CPR

0.089

0.090

0.982

0.322

1.093

NLR

-0.012

0.029

0.163

0.686

0.988

PLR

0.156

0.389

1.093

0.518

0.771

WBC: white blood cell; CRP: C-reactive protein; CAR: C-reactive protein/albumin ratio; CPR: C-reactive protein/protein ratio; NLR: neutrophil/lymphocyte ratio; PLR: platelet/lymphocyte ratio.

172

VARIABLES AFFECTING MORTALITY IN PATIENTS IN
PALLIATIVE CARE UNITS: OR IS IT STILL JUST ALBUMIN?

Figure 1. Receiver Operating Characteristic(ROC) curve for mean albumin value

Table 4. Cut off between survivor and nonsurvivor groups and albumin values based on ROC analysis.
Area Under the curve

Test Result Variable(s): Albumin
Area Std. Error Asymptotic Sig.
Albumin

.670

.028

.000

Asymptotic 95% Confidence Interval
Lower Bound

Upper Bound

.614

.726

Cuttoff Value
2.05

Positive Likelihood Ratio

2.81

1.56-4.12

Negative Likelihood Ratio

0.01

0.00-0.015

Sensitivity

0.85

0.77-0.93

Specificity

0.97

0.91-0.99

mortality variables (P=.010). The other variables
were not significant. Accordingly, albumin levels
were the main variable that explained mortality.
The receiver operating characteristic (ROC)
curve method was applied to distinguish between
survivors and nonsurvivors based on albumin

level, which was significant after logistic regression
analysis. The results are shown in Figure 1, and theother test results for albumin are shown in Table 4.
According to the ROC analysis, the cutoff value formean albumin was 2.05 mg/dL. The sensitivity andspecificity of the albumin cutoff value of 2.05 mg/dL
were 85% and 77%, respectively.

173

2024; 27(2):168−177

DISCUSSION
In this study, we concurrently evaluated laboratory
values and clinical prognostic indexes that affectmortality rates in PCU patients without malignancy.
The mortality rate in this study was 28.36%. We
found that only hypoalbuminaemia was strongly
associated with mortality.
The majority of patients were men, andtheir mean age was 74.65 ± 13.58 years. Most
patients were admitted to the ICU and ED; themajority were administered NG and PEG, and 88
patients underwent a tracheostomy. Our patients’demographic and clinical features were consistent
with those reported in the literature (2, 7-10).
Factors affecting mortality rates in PCUs havebeen reported in various studies. Several laboratory
values and ratios, such as protein, sodium, WBC,
CRP, procalcitonin, CAR, CPR, and NLR, have been
widely studied as prognostic markers in patients on
the PCU (1, 7, 9-11).
C reactive protein (CRP) is a classical acutephase protein that increases rapidly. There are manyfactors (infection, rheumatological disease, cancer,etc.) that affect the CRP value. It is a laboratory
parameter whose relationship with mortality andprognosis has been studied in the literature (1,12,
13). It has been shown in studies that high serum
CRP concentrations are associated with organ failure
and mortality. (14, 15) Karaşahin et al. stated in theirstudy that evaluating CRP in the first 24 hours of
hospitalization would be important in determining
prognosis (16).
The CRP/albumin ratio, a combination ofsystemic inflammation and nutritional status markers, has been studied as an independent prognostic marker in critically ill patients (17-18). Oh et al.
reported that a one-unit increase in CAR resulted
in an 11% increase in the risk of 30-day mortality in
critically ill ICU patients (19). Ranzani et al. conducted a study in an intensive care unit and found that
CRP level and CAR were independent risk factors
174

for mortality (12). In their study, Sargın et al. analysed laboratory values (such as neutrophils, PLT,
CRP, CAR, and NLR) that affect patient mortality (1).
None of these factors was significant.
Neutrophil-lymphocyte ratio (NLR) is a marker
that shows systemic inflammation in clinical practiceand can be easily measured and repeated with ablood count device. Increased NLR has been shown
to be an independent prognostic risk factor in many
types of cancer and its association with mortality rate
(17, 20). However, studies conducted on patients
followed in the palliative service are limited.
However, the results of these studies remain
controversial. There are significant differences
between survivors and nonsurvivors regarding
protein, WBC, neutrophil, CRP, procalcitonin, CAR,
CPR, and NLR. However, when logistic regression
analysis was applied, we found that only the effectof hypoalbuminaemia on mortality rates was
significant.
Hypoalbuminaemia is associated with short-term
mortality, hospital stay, and other complications (21,22). In a study conducted by Akirov et al., mortality
was 12% in patients with mild hypoalbuminaemia
and 34% in those with significant hypoalbuminemia(23). Sargın et al. reported in their study that
hypoalbuminaemia is a risk factor for mortality (1).
However, they did not use a clinical index in theirstudy and presented this as a limitation. Taşar et al.
stated that hypoalbuminaemia is an independentrisk factor for mortality (24). Aung et al. foundthat albumin values < 3.1 mg/dL were the mostimportant determinant of mortality (25). We studied
mortality markers in a specific group of patients
without malignancy. In our study, albumin values< 2.76 mg/dL were significant in mortality, and thesensitivity and specificity values were 85% and 97%,
respectively.
Current studies have focused on determining
the factors affecting mortality, especially in
critically ill patients who are followed up in the ICU
and PCU (1, 2, 11, 13, 22, 26-28). Apart from theVARIABLES AFFECTING MORTALITY IN PATIENTS IN
PALLIATIVE CARE UNITS: OR IS IT STILL JUST ALBUMIN?

laboratory values of the patients, comorbidities
also affect mortality. The scoring systems usedin the ICU and PCU were based on organ failureand comorbidities such as APACHE II, SOFA, PPI
and CCI. The Charlson Comorbidity Index (CCI)
is a widely used comorbidity index for critically illpatients (29, 30). Vural et al. They determined high
CCI, high APACHE II score and low albumin values​​
as indicators of mortality. However, they studied aheterogeneous patient group (31). We used this toevaluate effects on mortality but it did not affecton mortality.
Palliative care requires a multidisciplinary
approach. It is still essential as a health policy
to develop PCU services both in our country andglobally.
Our study was conducted in a specific patientgroup and included a relatively large number ofpatients. Additionally, the effects of laboratory
parameters and clinical features on the mortality
rate of the patients were investigated. We believethese are the strengths of the present study.
This study had several limitations. The mostimportant limitations of our study are its retrospective
and single-centre nature, and the fact that the
study was conducted in a patient group with a highaverage age and high comorbidities. We did not use
other widely used and accepted prognostic scales
for PCU patients, such as the Palliative Prognostic
Index or the Karnofsky Performance Scale.
We believe more prospective studies should be
conducted by grouping patients according to age
and main disease. In particular, we plan to evaluatepatients diagnosed with malignancy.

CONCLUSION
Our study highlights the pivotal role ofhypoalbuminaemia as the most significant
predictor of mortality in PCU patients without
malignancy. By recognising and addressing
this critical risk factor, healthcare providers

can better tailor therapeutic interventions andoptimise patient care in palliative settings. Further
research is warranted to elucidate the underlying
mechanisms linking hypoalbuminemia to adverse
outcomes, and to explore targeted therapeuticstrategies aimed at mitigating its detrimental
effects on patient survival.
Acknowledgements: We, the authors, wish toacknowledge and appreciate Dr. Ufuk Karadavut,
Dr. Didem Adahan and Dr. M. Murat Şahin and theentire family medicine and anaesthesiology teamof PCU, who provided us with the necessary data
and all the support for the successful completionof this article. No other journal has reviewed thismanuscript.
Financial disclosure: Authors declare they haveno financial support.
Conflict of interest: Authors declare no conflictsof interest.
Authors‘ contributions: The first author isthe lead and the corresponding author. All theother authors are listed in alphabetical order.
Conceptualisation: AY MA and BT; Methodology:
AY MA BT and AA; Validation: MA EM AA;
Investigation: EM AA MD and AU; Writing – originaldraft: MA AY; Visualisation: BT; Writing – review andediting: AY MA and BT.

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177

ORIGINAL ARTICLE

TURKISH ADAPTATION, VALIDITY ANDRELIABILITY STUDY OF TREATMENT BURDENQUESTIONNAIRE IN GERIATRIC PATIENTS
Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.391
2024; 27(2):178−188
 Figen AKAY1. . . . . . . . . . . . . . . . . 

 Tuba ERYİĞİT2 . . . . . . . . . . . . . . 
 Mehmet Fatih ÖS3 . . . . . . . . . . . . 
 Kamile SILAY4 . . . . . . . . . . . . . . . 

 Güler Balcı ALPARSLAN5. . . . . . . 

CORRESPONDANCE
1Figen AKAY

Phone
e-mail: +905368561105: fig1907@hotmail.com

Received : May 09, 2024
Accepted : May 31, 2024

1 T.R. Ministry of Environment, Urbanization

and Climate Change, Institutional
Medicine, Ankara, Turkey

2 Istanbul Topkapı University Plato

Vocational School, Department of Medical
Documentation and Secretariat, Istanbul,
TurkeyABSTRACTIntroduction: This study aimed to adapt the Turkish Treatment Burden
Questionnaire, test its validity and reliability, and predict the treatment burdenin the geriatric population.
Materials and Method: This methodological study included individuals aged
65 years and older from the geriatric population attending routine outpatient
clinic examinations at the Ankara Bilkent City Hospital Geriatrics Department
between June 1, 2022, and June 1, 2023. The sample consisted of 150 geriatricindividuals who spoke and understood Turkish, could managed their illness, had
no disease complications, were communicative, and did not have any physicalor mental illnesses that would hinder their participation. The study data werecollected using the ‘Individual Information Form’ and the Turkish version of the‘Treatment Burden Questionnaire.’ Descriptive and confirmatory factor analysis
were performed, and Cronbach’s α coefficient was calculated for the Turkish
version of the scale.
Results: Analyzing the factor structure of the Treatment Burden
Questionnaire, a three-factor, 11-item structure with an eigenvalue above 1
explained 53.227% of the variance. In the assessment of the internal consistencyof the scale, four items were eliminated because of low item-total correlations
and inter-item correlations. The reliability analysis for the 11-item Treatment
Burden Scale yielded a Cronbach’s α coefficient of 0.645.
Conclusion: The Turkish adaptation of the Treatment Burden Questionnairedemonstrated validity and reliability in for assessing the extent of treatment
burden in the geriatric population.
Keywords: Treatment; Geriatrics; Chronic Disease; Questionnaire.

3 T.R. Ministry of Health, Ankara Bilkent

City Hospital, Department of Nephrology,
Ankara, Turkey

4 T.R. Ministry of Health, Ankara Bilkent City

Hospital, Department of Geriatrics, Ankara,
Turkey5 Eskişehir Osmangazi University, Facultyof Health Sciences, Internal Medicine
Nursing, Eskisehir, Turkey

178

TURKISH ADAPTATION, VALIDITY AND RELIABILITY STUDY OF
TREATMENT BURDEN QUESTIONNAIRE IN GERIATRIC PATIENTSINTRODUCTION
Non-communicable diseases (NCDs), also called
chronic illnesses, are characterized by a gradualand progressive deviations in various physiological
functions that do emerge suddenly, often featuring
remissions and relapses and necessitating
irreversible medical care and treatment (1,2).
Globally, 76.4% of all deaths are attributed to NCDs.
NCDs, encompass a broad range of conditions,
including
cardiovasculardiseases,
cancer,respiratory diseases, and metabolic disorders(3). According to the World Health Organization(WHO) 2014 NCD data for Turkiye, cardiovasculardiseases account for 47% of deaths, cancer for
22%, respiratory diseases for 8%, diabetes for 2%,
and other diseases for 21% (4). The proportion ofthese deaths in geriatric individuals is 38% due tocirculatory system diseases, 19% due to malignant
tumours, and 12% due to respiratory systemdiseases (3).
Considering epidemiological research conducted in Turkiye, it is evident that the incidenceof chronic diseases increases with age, particularlyin the geriatric population, requiring enhanced
treatment, specialized care, and rehabilitation (5).
Risk factors such as poverty, poor living conditions,
unhealthy nutrition, exposure to ultraviolet rays,
viruses, physical inactivity, tobacco and alcoholuse, overweight/obesity, and high blood sugar
and pressure create a conducive environment
for the development of chronic diseases (3). As
individuals age in the geriatric population, various
structural changes occur in the chest cavity andlung parenchyma, abnormalities in lung function
tests, ventilation and gas exchange abnormalities,
decreased exercise capacity, decreased respiratory
muscle strength (6), reduction in lean mass such asmuscles and bones, increase in fat mass, decreasein muscle functions, strength, and mass (7),decreased blood flow in the liver, decreased activityof liver enzymes, increased stiffness in the vascularwall, impaired circulation, structural changes in
the heart, increased insulin resistance, decreased
beta-adrenergic response leading to decreased
vasodilationofcatecholamines,
decreased
glomerular filtration rate, renal artery stenosis, anddecreased renin levels are among the many factors
contributing to the increased prevalence of chronic
diseases (8).
The burden of treatment encompasses theimpact of the disease, specific treatments, and theirside effects, as well as the functioning of healthcare
services and their effects on patient well-being (9).
Another definition involves the patients’ efforts toaccess and use healthcare services and performself-care activities, expressing the adverse effectsof these efforts on patients. In short, the treatment
burden focuses on the individualized load oftreatment and care experienced by individuals
with chronic illnesses during treatment, excluding
any consideration of the burden on the healthcare
system (10). Based on these definitions, the burdenof treatment encompasses all the healthcare
activities undertaken by patients to maintain theirhealth. These include doctor visits, blood pressure
monitoring, self-monitoring, laboratory tests,
treatment management, the use of medical devices,bearing certain costs in particular situations, accessto care, and the ability to coordinate care. Treatment
burden in the context of an acute illnesses may
be temporary. The patient could easily tolerate
it while temporarily achieving a healthcare goal.
Likewise, the burden of multiple oral medications
may be acceptable in chronic diseases. However,self-injection, taking new medications, undergoing
additional laboratory tests, and making lifestylechanges will begin to increase the burden oftreatment and care on patients (11). Harmony
between geriatric individuals and healthcare
professionals is crucial during treatment. In geriatricpatients, in addition to the pharmacologicaltreatment approach to manage the disease, avoid
disability, and maintain their quality of life, lifestyle1792024; 27(2):178−188

changes such as diet, exercise, smoking cessation,
and alcohol abstinence are also recommended.
These care activities increase the burden on geriatricpatients (12).
Regular monitoring of elderly individuals at
appropriate intervals, as specified by healthcare
professionals, should be performed using
appropriate techniques and documentation. The
importance of paying attention to regular healthcheck-ups (eye, kidney, cardiovascular, etc., andorgan/system examinations) in this patient groupshould be emphasized. The group of medications
used by these patients as well as the possible side
effects of these medications should be discussed(8). There may be differences in the skills of
individuals to manage health problems, definedas health capacity, and follow these treatments.
Factors such as geriatric individuals’ medicationuse, treatment follow-up situations, sociocultural
status, cognitive functions, and overall health statusneed to be considered, especially the presence ofproblems such as the excessive use of medications(13). When the number of healthcare activities
required to manage chronic diseases increases, thetreatment burden on patients will also increases. As
a result, a decrease in therapeutic adherence, anincrease in hospitalization rates, and mortality may
occur. These conditions indicate that patients must
invest effort, attention, and time in managing theirdiseases (9,11).
In the literature, a measurement tool for assessing
the burden experienced by individual patientsduring treatment in Turkiye has yet to be developed.
This study was conducted to determine the content
validity, construct validity, and internal consistency
reliability coefficient of the Treatment Burden
Questionnaire AU1.1 version and to contribute to
the literature by establishing its characteristics forthe valid and reliable measurement of the treatment
burden and predicting the treatment burden in thegeriatric population.

180

MATERIALS AND METOD
Study design
This is a methodological study.
Participants
The study population was comprised of geriatricpatients aged 65 years and older who attended
routine outpatient clinic examinations at theGeriatrics Department of Ankara City Hospital,
Bilkent Campus, between June 2022 and June
2023. The sample size was determined based on therecommendation in the literature that at least 5-10
times the number of items in validity and reliability
studies should be included (14). Considering this,150 geriatric individuals were included in the study,
ten times the number of items in the 15-item scale.
The sample was selected using a non-probability
random sampling method, and participants wererequired to be aged 65 years or above, able tomanage their disease, free of disease complications,
physically and mentally healthy enough toparticipate, speak and understand Turkish, andwilling to participate in the study.
Data collection
Research data, along with patient demographic
characteristics, were collected using face-to-faceinterviews with the Treatment Burden Questionnaire.
Each Scale took approximately 15-20 minutes tocomplete.
Data collection tools
The data collection form included the Individual
Introduction Form and the Treatment Burden
Questionnaire.
Individual Introduction Form: The Individual
Introduction Form, consisting of 12 questions ina single section, was designed by the researchers
inspired by the studies of Değer and Ordu (2022)(15). It included demographic information such as

TURKISH ADAPTATION, VALIDITY AND RELIABILITY STUDY OF
TREATMENT BURDEN QUESTIONNAIRE IN GERIATRIC PATIENTSage, gender, marital status, education, occupation,
income status, smoking and alcohol use, exercise,and diet-related characteristics (lifestyle andhabits); disease and disease durations (diseasecharacteristics) were also queried for each geriatricindividual.
Treatment
Burden
Questionnaire: The
Treatment Burden Questionnaire (TBQ-AU1.0
version), developed in France, consists of 15 items
and a single dimension. There are no reverse itemson the scale. Each item on the scale is scored ona scale ranging from ‘0-10’ (‘not a problem’ to, ‘asignificant problem’). The lowest possible scoreon the scale was ‘0,’ and the highest score ranged
between ‘0’ and ‘150.’ A high score indicated thatan individual was experiencing a high level oftreatment burden. The Cronbach’s α coefficient forthe scale was found to be 0.89 (16). As no validity
and reliability studies have been conducted for the
TBQ-AU1.1 version in Turkiye, the Turkish language
and context adaptation for this version weretranslated, and validity and reliability tests were
performed within the scope of this study.
Language and content validity
The translation-back-translation method was used totest the language validity of the Treatment Burden
Questionnaire. In the first stage, the researchers
appropriately adapted the English version of theTreatment Burden Questionnaire into Turkish. The
English form and the Turkish-translated form of
the scale were presented to seven expert faculty
members in the nursing field who were both familiar
with the scale and fluent in English. After adjustments
were made based on expert opinions, the entire
scale was reviewed again. The translation basedon the original version was then presented to theresearchers, and the final Turkish version of the scale
was created according to their suggestions. A pilot
study was conducted with 50 patients in this study.

Internal consistency
The Treatment Burden Questionnaire showedhomogeneous relationships, and Cronbach’s αcoefficients were examined.
Construct validity‘Explanatory and Confirmatory Factor Analysis’ wasperformed to determine the construct validity of
the Treatment Burden Questionnaire. The KaiserMeyer-Olkin (KMO) value and Bartlett’s sphericity
test were used for the exploratory factor analysis.
After determining the suitability of the data for
exploratory factor analysis, the fit criteria for
confirmatory factor analysis, including root meansquare error of approximation (RMSEA), comparative
fit index (CFI), goodness of fit index (GFI), adjusted
goodness of fit index (AGFI), incremental fit index(IFI), non-normed fit index (TLI), and chi-square/degrees of freedom (x2/df) tests, were evaluated,and varimax rotation methods were used.
Statistical analysis
The data and analyses of the scale were performed
using IBM SPSS (Statistical Package for Social
Sciences) version 27.0 and Amos 26.0 statisticalpackage program. Continuous data were calculated
as mean, standard deviation, minimum, andmaximum, whereas categorical data were calculated
as percentages. Kolmogorov-Smirnov, skewness,
and kurtosis tests were used to investigate thenormal distribution of the data. Since the data
showed a normal distribution, one-way analysis ofvariance (ANOVA) and independent sample T test
were used. Statistical significance was set at p <0.05.
Ethical dimension
Official permissions to conduct this study was
obtained by signing a license agreement via email
with the authors who developed the scale and its
owner. This study was conducted in accordance with181

2024; 27(2):178−188

the principles of the Declaration of Helsinki. This
study was reviewed and approved by the ClinicalResearch Ethics Committee of the Ministry of Healthof Ankara City Hospital 1 (Approval Number: E.
Kurul-E1-22-2671). Informed consent was obtained
from the geriatric individuals participating in the
research in advance to provide information about
the study procedures at each stage.

RESULTsignificant difference was found between females(42.77±16.24) and males (49.10±14.72) (p=0.014).
Assessing the Treatment Burden Questionnairescores based on chronic diseases revealed nosignificant differences between the diseases(p=0.386). Upon examining the scores, it wasdetermined that patients with respiratory systemdiseases (58.00±18.57) experienced the highest
burden.

Sociodemographic Characteristics ofGeriatric Individuals

Validity of the Treatment Burden
Questionnaire

The average age of geriatric individuals (n=150)
was 77.79 ± 8.19 years (min=65, max=98), 54% werefemale, 83.3% were married, 34.7% had elementary
school education, and 80.7% had income matching
their expenses. It was found that 5.3% of geriatricindividuals used cigarettes, and 0.7% used alcohol.
While 22.7% of the geriatric patients engaged inphysical activity, 27.3% followed a diet. The mostcommon diseases among geriatric individuals werea combination of cardiovascular and endocrine
diseases (40.0%). The average duration of geriatricindividuals’ diseases was 8.31 ± 4.76 years (min=1,
max=20).

Data were collected from a study group of 150
individuals to assess the validity and reliability of
the Treatment Burden Questionnaire. Initially, theKMO Index and Bartlett’s tests were employed toassess the adequacy of the sample size and theappropriateness of the data. The KMO value wasfound to be 0.661, and the results of the Bartlett
Sphericity test were x2=278.372, p=0.000 (Table 1).

Treatment Burden Questionnaire Results
The treatment burden score for geriatric individuals
was calculated as 45.68±15.83 (min=2, max=95),
indicating that they experienced a low levelof treatment burden. Among the components
contributing to treatment burden in geriatricpatients, the most significant feature was thefinancial burden (7.57±2.62). In contrast, the least
impactful factor on treatment burden was theburden related to appointments (frequency ofvisits, problems encountered when going to visits,
inability to undergo examination after attending theappointment) (0.40±1.39).
When evaluating the Treatment Burden
Questionnaire scores based on gender, a statistically182

Exploratory Factor Analysis (EFA)
EFA was applied to a 15-item scale within the scopeof the study. After confirming the suitability of thedata for analysis, a varimax rotation was performed
using principal components analysis to examine
the scale’s factor structure. Rotation was applied tothe scale, and a five-factor structure was identified
by reviewing the results. However, four scale items
that overlapped and had low factor loadings were
excluded from the analysis. After excluding these
items, factors with eigenvalues exceeding one
were included in the study. A three-factor structure
emerged using a Scree Plot (Figure 1).
For factors with eigenvalues exceeding 1,
the factorization of the scale was consideredappropriate for the study, and as a result of the
Exploratory Factor Analysis (EFA), a three-factor
factor matrix was obtained, explaining 53.227% of
the total variance. According to the EFA results,
the Treatment Burden Questionnaire yielded a

TURKISH ADAPTATION, VALIDITY AND RELIABILITY STUDY OF
TREATMENT BURDEN QUESTIONNAIRE IN GERIATRIC PATIENTS

Figure 1. Slope gradient graph of the EFA result

Table 1. Factor Analysis Results of Treatment Burden Questionnaire Items
Treatment Burden Questionnaire (TBQ) Items:

TBQ 1(Economic and Social
Context)

1. Financial burden related to your healthcare

0.815

2. Administrative burden related to healthcare

0.747

3. Burden related to diet changes

0.621

4. Burden related to engaging in physical activity

0.579

TBQ 2
(Treatment)

5. Daily medication intake burden

0.721

6. Burden related to the taste, shape, etc., oftablets/medications

0.715

7. Burden related to laboratory tests

0.625

8. Burden related to the need for regular
medical care

0.562

TBQ 3
(Medical
Follow-ups)

9. Burden related to doctor appointments

0.843

10. Burden related to interactions withhealthcare professionals

0.662

11. Burden related to self-monitoring

0.657

Eigenvalue

2.825

1.826

1.525

Explained Variance Ratio

19.07917.74116.408

KMO = 0.661, Χ2 = 278.372; Bartlett Sphericity Test (p) = 0.000
Total Explained Variance Ratio = 53.227

183

2024; 27(2):178−188

Confirmatory Factor Analysis (CFA)

three-factor structure comprising 11 items. In thisstudy, factor loadings ranged from 0.562 to 0.843
in the factor analysis. All items gathered from thefactor, Factor 1 (TBQ 1), with an eigenvalue of 2.825,
consisted of four items and explained 19.079% of
the variance. Factor 2 (TBQ 2), with an eigenvalueof 1.826, comprised of four items and explained
17.741% of the variance. Factor 3 (TBQ 3), with an
eigenvalue of 1.525, consisted of three items andexplained 16.408% of the variance (see Table 1).

CFA was applied to determine the fit indices of thestructure consisting of 11 items and three factors
obtained from the results of the EFA, and to assess
its appropriateness. The fit indices obtained from the
CFA results of the Treatment Burden Questionnaire
are presented in Table 2.
The Treatment Burden Questionnaire CFA results
yielded the following goodness-of-fit indices: x2/

Table 2. CFA Results of the Treatment Burden Questionnaire
Index

Excellent Fit Criterion

Acceptable Fit Criterion

Treatment Burden Questionnaire/sd0≤χ2/df≤3

3≤χ2/df≤5

1.792

RMSEA

0.000.05

0.05

0.073

CFI

0.95≤CFI

0.85≤CFI

0.863

GFI

0.90≤GFI

0.85≤GFI

0.922

AGFI

0,90≤AGFI

0.85≤AGFI

0.871

IFI

0.901.00

0.80

0.872

TLI

0.90≤TLI

0.80≤TLI

0.812

Chi-Square/Degrees of Freedom (X^2/df), Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Non-Normed Fit
Index (NNFI) or Tucker-Lewis Index (TLI), Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI)

Figure 2. Path Diagram for the Treatment Burden
Questionnaire

184

TURKISH ADAPTATION, VALIDITY AND RELIABILITY STUDY OF
TREATMENT BURDEN QUESTIONNAIRE IN GERIATRIC PATIENTSTable 3. Total Correlations and Cronbach a Coefficients of the Burden of Treatment Questionnaire (n=150)
Scale and Subdimension

Cronbach α coefficient

TBQ 1

0.673

TBQ 2

0.589

TBQ 3

0.549

Treatment Burden Questionnaire

0.645

df=1.792, RMSEA=0.073, CFI=0.863, GFI=0.922,
AGFI=0.871, IFI=0.872, TLI=0.812. In this instance,
Figure 2 shows a Path Diagram tailored to theTreatment Burden Questionnaire.

was sent to experts, who evaluated the clarity andcultural appropriateness of the questions, providing
scores as follows: “1 point: Not appropriate; 2points: Slightly appropriate (items/expressions
need to be shaped appropriately); 3 points: Quite
appropriate (appropriate, but minor changes areneeded); 4 points: Very appropriate (no need forchanges, can remain as is)” (17). Kappa’s coefficientof agreement (K.G.I.) was used to evaluate eachquestion by dividing the number of experts whoscored three and four points by the total number ofexperts (18). The K.G.I. for the 15 items on the scale
was greater than 0.80. The scale was reviewed in its
entirety based on expert suggestions. Following
the analysis of expert recommendations, necessary
adjustments were made to the scale without
removing any items.

Reliability Analysis of the Treatment Burden
Questionnaire
The Cronbach’s α coefficient was calculated basedon the data obtained from 150 geriatric individuals
in this study. The analysis resulted in a Cronbach’s
α internal consistency coefficient of 0.645 for theTreatment Burden Questionnaire (Table 3).

DISCUSSION
This study aimed to translate and adapt a scalemeasuring the treatment burden of individuals into
Turkish and conduct reliability and validity analyses
to determine the dimensions in which geriatricindividuals experience treatment burden. Language
and content validity were assessed according tothese objectives, and EFA was applied. After the
EFA, four overlapping items were excluded, and thevalidity and reliability findings of the scale consistingof 11 items with three factors were discussed.
Discussion of Language and Content Validity
According to the literature, it is recommended toconsult expert opinions, with at least three experts,
to determine the language and content validity. The
opinions of seven faculty members were obtained
for this study. Using the Davis technique, the scale

In scale adaptation studies, conducting apilot application with at least 30-40 people isrecommended to test the understandability ofthe questions (17). In the planned study, a pilot
application was conduct with 50 participants toassess their language, expression, comprehensibility,
and application difficulties. At the end of theapplication, the questionnaire items were found to
be understandable and did not require correction.
Discussion of the Construct Validity of theTreatment Burden Questionnaire
KMO value and Bartlett’s sphericity tests wereused to evaluate the appropriateness of the data
and adequacy of the sample size. The literature

185

2024; 27(2):178−188

suggests that the KMO value should be> 0.60, andthe Bartlett’s test should be significant, indicating
good factor analysis and a sufficient sample size
(19). According to this information, our study’s
sample size was sufficient (KMO = 0.661) (Bartlett
sphericity test; x2 = 278.372, p = 0.000).
Discussion of the Reliability Analysis of theTreatment Burden Questionnaire
Reliability is the first condition that mustbe satisfied in scaled studies. The most important
method to assess the reliability is to calculate Cronbach’s α coefficient. This allowed us to determine
the scale’s degree of consistency. If this α value isbelow 0.40, the scale is not reliable. Values between
0.40 and 0.60 indicate low reliability, 0.60 and 0.80
are moderately reliable, and 0.80 and 1.00 are highly reliable (19). In the study, the Cronbach’s α internal consistency coefficient of the Treatment Burden
Questionnaire was found to be 0.645, indicatingthat the scale is moderately reliable.
EFA
The literature emphasizes that the total explained
variance should be 40-60% (20). Consistent withthe literature, the 3-factor scale structure explained
53.227% of total variance. This finding is further
supported by a similar 3-factor structure obtainedin a Spanish validity and reliability study where
the Treatment Burden Questionnaire (TBQ_AU1.1
version) was administered to patients with Multiple
Sclerosis (10).
When selecting scale items in EFA, the factor
loads should be at a certain level. Tabacknick and
Fidell defined this threshold value as 0.32 (21).
Another study stated that the factor loads of scale
items should be at least 0.30 or higher (22). In ourstudy, when examining the factor loads in the EFA,
it was observed that they varied between 0.562 and
0.843. According to the results, the factor loadingsof the included items were sufficient.

186

CFA
The critical values that CFA must satisfy are x2/
df, RMSEA, CFI, GFI, AGFI, IFI, and TLI, which are
shown in Table 2 (20). In our study, the obtained fit
indices were calculated as x2/df = 1.792, RMSEA =0.073, CFI = 0.863, GFI = 0.922, AGFI = 0.871, IFI=
0.872, TLI = 0.812. These results showed that the fit
indices examined with CFA were at sufficient levels,
confirming the 3-factor 11-item structure.
Limitations of the study
In our study, the KMO values and Bartlett’s sphericity
tests were applied, and it was observed that the
sample size needed to be at a sufficient level but not
excellent (20). This situation led to the Cronbach’s αcoefficient being 0.645 (quite reliable) which is not ahigh level of reliability (0.80-1.00).

CONCLUSION
As a result of this research,- Geriatric individuals experience a low treatment burden.
- There was a statistically significant differencein treatment burden between female (42.77±16.24)
and male (49.10±14.72) geriatric individuals(p=0.014).
- When evaluated according to chronic diseases,
there was no significant difference in the treatment
burden questionnaire scores (p=0.386).
- Among the chronic diseases, it was determined that patients with respiratory system diseases (58.00±18.57) experienced the highest-burden
according to treatment burden scores.
Validity and reliability analyses of the Turkish
version of the Treatment Burden Questionnaire(Version A.U1.1) indicated sufficient validity and reliability. Based on the results obtained at the end of
the study, it can be clearly stated that the 3-factor
11-item Treatment Burden Questionnaire is high-TURKISH ADAPTATION, VALIDITY AND RELIABILITY STUDY OF
TREATMENT BURDEN QUESTIONNAIRE IN GERIATRIC PATIENTS

ly reliable for evaluating the treatment burden on
geriatric individuals in Turkey. We recommend conducting this validity and reliability studies in othersample groups with a larger sample sizes.
Funding: The authors declared that this study
had received no financial support.
Competing interest: There is no conflict ofinterest among the authors.

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ORIGINAL ARTICLE

TRENDS IN CARBAPENEM RESISTANCEFROM 2018-2023 IN HOME HEALTH CARE:
THE BOTTOM OF THE ICEBERG
Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.392
2024; 27(2):189−197
 Semiha SOLAK GRASSIE1 . . . . . 

 Tuğçe ÜNALAN ALTINTOP2 . . . . 

ABSTRACTIntroduction: There has been a shift in the care of older patients from hospitalsettings to home healthcare. Older patients are more susceptible to infections,and infections associated with home healthcare are often understudied. This
study aimed to investigate the changing trends in carbapenem resistance inthese infections over time.
Materials and Method: Microbiological data of home healthcare patients
between 2018 and 2023 were analyzed using hospital records.

CORRESPONDANCE
1Semiha SOLAK GRASSIE

Phonee-mail: +905325946274: semihasolak@yahoo.com

Received : Feb 29, 2024
Accepted : Apr 25, 2024

Results: The rate of carbapenem resistance increased significantly from
4.17% to 19.53% between 2018 and 2023, particularly in Klebsiella spp.
and Pseudomonas spp. Additionally, an increase in the number of respiratory
and wound tissue samples was observed.
Conclusion: Carbapenem resistance is a growing problem not only in
hospitals but also in home healthcare settings. Effective infection prevention
and control measures should be implemented, given the complexities ofmanaging these infections, especially in geriatric populations.
Keywords: Home Care Services; Carbapenem-Resistant Enterobacteriaceae;
Pseudomonas Aeruginosa; Acinetobacter Baumannii.

1 Yıldırım Beyazıt University Yenimahalle

Training and Research Hospital, Infectious
Diseases Clinics, Ankara, Turkey

2 Yıldırım Beyazıt University Yenimahalle

Training and Research Hospital ,Microbiology Laboratory, Ankara, Turkey

1892024; 27(2):189−197

INTRODUCTION
Healthcare-associated infections (HAI) are among
the most common adverse events and serious
public health threats. This results in prolonged
hospitalization, expensive diagnostic methods,
increased treatment costs, and reduced quality of life(1,2). The geriatric population is disproportionately
affected by HAIs owing to predisposing factors
such as age-related changes, geriatric syndromes,
and comorbidities (3). Additionally, non-hospital
HAIs are frequently overlooked (2). In recent years,
there has been a shift from inpatient to home carein Europe. Home care involves healthcare workers
taking care of individuals to provide a range ofservices, from routine checkups to post-mortem
care. While home care offers benefits such as an
improved quality of life and reduced healthcare
costs, it also carries risks such as the potential for
infection (2,4). Studies on infections linked to homehealthcare services are limited. Infections that arise
48 hours after hospital discharge are defined ashome HAI (5).
Patients receiving home healthcare services
include those with various underlying medical
conditions,invasive
procedures,
frequent
hospitalizations, and intensive care admissions.
Bacterial colonization, including that of resistantbacteria, is frequently observed in these patients.
Consequently, they are more susceptible to infections
caused by resistant bacteria (6, 7). One of theseis carbapenem-resistant Gram-negative bacteriasuch as Klebsiella pneumoniae, Acinetobacterbaumannii, and Pseudomonas aeruginosa (8). In
cases of non-hospitalized infections selecting anappropriate antibiotic can be challenging because ofbacterial resistance (9). In cases of serious infections
requiring hospitalization, empirical antibiotics
should be initiated with a broader spectrum for thispopulation than for other patients (7).
The objective of this study was to investigatechanges in carbapenem resistance rates insamples collected from patients followed up at
190

home healthcare clinics. Additionally, this study
analyzed the types of samples and changes in the
microbiological epidemiology of these patients overtime. The data from our study can aid in determining
empirical treatment approaches for patients, bothat home and during hospitalization. In addition, it
can facilitate the rapid implementation of infection
control measures during hospitalization.

MATERIALS AND METHODThis retrospective study analyzed the microbiologicalsamples of patients who were followed up in thehome healthcare clinics of Yildirim Beyazit University
Yenimahalle Training and Research Hospital
between August 15, 2018, and August 15, 2023.
Data were obtained from the electronic medical
records of the hospital.
Patients who were followed up at the Home
Health Care Clinic and whose samples were sent to
the microbiology laboratory were included in thisstudy. Isolates from these samples were identified
using an automated microbial identification system(Vitek 2, Biomerieux, France) and conventional
methods, such as oxidase, catalase, indole, methyl
red, citrate, mobility, citrate, and urease tests.
Susceptibility testing was performed using the discdiffusion method and interpreted according tocurrent EUCAST guidelines (10).
All samples collected from the patients wereretrospectively examined for microorganisms without
distinguishing between infection and colonization.
Microorganisms and their resistance status wereanalyzed, with a focus on carbapenem resistance.
Sample types were recorded. Microorganisms andtheir carbapenem resistance statuses were classified
annually, and differences in species and resistancestatuses were compared.
SPSS 29.00 software was used for statisticalanalysis. Descriptive statistics is used to demonstrate
the study population, clinical sample, and bacterial
distribution. Differences in bacterial species,

TRENDS IN CARBAPENEM RESISTANCE FROM 2018-2023
IN HOME HEALTH CARE: THE BOTTOM OF THE ICEBERG

carbapenem-resistant bacteria, and culture types
over the years were analyzed using the Chi-Square
test. The Kruskal -Wallis test was used to analyze
the relationship between age and carbapenem
resistance rates.

Of the 922
microorganisms,
resistance.

samples containing growing
119
showedcarbapenem

The incidence of carbapenem-resistant bacteria
increased in parallel with age (p 0.02). Specifically,
there were 77 urine cultures, 15 pressure ulcers,
26 tracheal aspirates, and one sputum sample.
Changes in carbapenem resistance rates andmicroorganisms are shown in Table 1. The samples
were grouped into five periods in Figure 1: August
2018-2019, August 2019-2020, August 20202021, August 2021-2022, and August 2022-2023.
Carbapenem resistance rates showed a statisticallysignificant increase over the years (p < 0.01).

RESULTSA total of 1243 samples taken from patients followed
up at home health care clinics at Yenimahalle
Training and Research Hospital were analyzed inthis study. No microbial growth was detected in anyof the 321 samples. The mean patient age was 71.3
± 14.8 (26-102) years.

Table 1. The change in carbapenem resistance rates between 2018 and 2023.
Carbapenem resistance raten (%)

Klebsiella spp.
n (%)

Pseudomonas spp.
n (%)

Acinetobacter spp.
n (%)

2018-2019

4 (4,17)

1 (1,04)

2 (2,08)

1 (1,04)

2019-2020

1 (2,32)

1 (2,32)--

2020-2021

4 (7,14)

1 (1,18)

3 (5,36)-2021-2022

61 (12,68)

28 (5,94)

23 (4,88)

10 (2,12)2022-2023

49 (19,53)

33 (12,89)

15 (5,86)

1 (0,39)

119

64

43

12

Date

Total

Figure 1. Change in carbapenem resistance over time.

191

2024; 27(2):189−197

Table 2. The change in sample types between 2018 and 2023.
Date

Urine n (%)

Wound n (%)

Aspirate n (%)

Sputum n (%)

Total n (%)

2018-2019104 (97.20)

1 (0.93)02 (1.87)107

2019-2020

84 (96.55)

1 (1.15)

1 (1.15)

1 (1.15)87

2020-2021

76 (90.48)

7 (8.33)

1 (1.19)0842021-2022

482 (81.97)

65 (11.05)

40 (6.80)

1 (0.17)588

2022-2023

259 (82.48)

34 (10.83)

20 (6.37)

1 (0.32)

314

Total

1005 (85.17)

108 (9.15)

62 (5.25)

5 (0.42)1180** other samples (n=63) were not included in the table

Figure 2. Change in sample types overtime.

Figure 3. Carbapenem resistance rates inhome health care patients.

192

TRENDS IN CARBAPENEM RESISTANCE FROM 2018-2023
IN HOME HEALTH CARE: THE BOTTOM OF THE ICEBERG

Table 2 and Figure 2 summarize the distributionof samples received by the laboratory and theirchanges over the years. The majority of thesamples from home healthcare patients sent to
the microbiology laboratory were urine cultures(85.17%). The rest of the samples were wound(9.15%), tracheal aspirated (5.25%), sputum (0.42%),and other (n=63). Wound and tracheal aspirate
samples showed an increasing trend over time p<0.01.
The resistance rates are summarized in Figure 3.
Carbapenem resistance rates were 23.02 % (64/278)
for Klepsiella spp., 66.67 % (12/18) for Acinetobacter
spp., and 21.60 % (43/199) for Pseudomonas spp. inall samples. Distribution of the carbapenemresistant bacteria type between the years wasn’t
statistically significant p 0.09.

DISCUSSION
Our
study
detectedanincreaseincarbapenem
resistance,
particularly
in Klebsiella and Pseudomonas spp. in-home
HAI. We also observed a significant change after the
COVID-19 pandemic and an increase in the numberof pressure ulcers and tracheal aspirate samples.
This increase could be attributed to an increase in
the number of bedridden and intubated patients
receiving home healthcare services. The worldwide
incidence and prevalence of carbapenem-resistantGram-negative bacteria have increased alarmingly
over the past decade. In Europe, in 2015, populationweighted means of carbapenem resistance for P.
aeruginosa, K. pneumonia, and A. baumanii were
17.8%, 8.1%, and 0.1%, respectively (11). The national
healthcare-associated infection surveillance reportfor 2022 reveals that the carbapenem resistance
rate in A. baumanii was 92.18%, K. pneumonia was
66.56%, and P. aeruginosa was 67.60% among HAI(12). In 2018, the A. baumanii rate was 70.90% and
the P. aeruginosa rate was 33.99% (13). As seen inthese two reports, there has been a very significant
increase in the incidence of carbapenem-resistantbacteria in HAIs over the past several years. A
study reported even higher rates of carbapenem
resistance than reported for 2018; carbapenem
resistance was A. baumanii 93%, K. pneumonia 78%,
and P. aeruginosa 76% (14). Another study
examined bloodstream infections in the ICUs of 24
hospitals in Turkey in 2021, highlighting the rise in
carbapenem-resistant bacteria and high mortality
rates despite the initiation of appropriate treatment(15). A simulation study reported that carriers ofcarbapenem-resistant Gram-negative bacteria had
a 1.8-fold higher possibility of re-admission within
1 year. Additionally, 30% of carriers sustain life-long
infections. Implementing contact precautions can
reduce transmission risk by 40%, yet only 10% of
carriers adhere to these precautions (16).
Older people are much more likely to sufferfrom infectious diseases than younger people.
Organ dysfunctions that increase with age, changes
in the immune system, nutritional problems, andunderlying diseases that increase over the years
lead to an increased risk of infection among older
patients. Infections in older people are one of the
primary causes of death (17). A very large proportionof home healthcare patients are geriatric patientswith multiple hospitalizations and even ICU stays(18). Previous studies have shown that advanced age
is an important risk factor for carbapenem-resistantbacteria. Some studies reported a 20–30% mortality
rate increase with carbapenem-resistant bacteria
infections (17, 19). Our study, like other studies,observed a significant increase in carbapenem
resistance with increasing age.
These results suggest that carbapenem
resistance is a growing problem not only in hospitalsettings but also in long-term care facilities. Olderadults are particularly susceptible to colonization
by carbapenem-resistant Gram-negative bacteria
because of extended hospital stays, catheter ormechanical ventilation use, and comorbidities (3,19).
Following discharge, these colonizing bacteria cancause outbreaks in long-term care facilities. A report1932024; 27(2):189−197

from West Virginia identified a long-term care facility
as the primary source of a carbapenem-resistant K.
pneumoniae outbreak (20). Furthermore, the rates
of carbapenem-resistant Gram-negative bacteria
were found to be significantly higher in long-termcare facilities than in communities and hospitals (21).
However, despite the lack of research on patients
followed up in home healthcare settings, our study
highlights the need for epidemiological studies onthese infections as well as infection prevention andcontrol strategies.
Infection rates among patients who received
home healthcare have been reported to range from
5% to 80%. Common infections reported in thesepatients include respiratory tract infections, urinary
tract infections, skin and soft tissue infections, andthose associated with intravenous catheters (6). The
samples analyzed in our study were predominantly
from the urinary system, with respiratory tract
samples obtained through tracheal aspiration being
less frequent. This discrepancy may stem fromthe possibility patients with tracheostomies weremore prone to having respiratory tract specimens
collected, whereas other patients might not haveundergone sputum culture assessments. However,an increase in the number of respiratory and woundsamples was observed in this study. Infections are theleading cause of hospitalization in these patients,
with respiratory tract infections being the mostcommon. Infection was detected in 45% of patients
who required admission in a previous study (6, 22).
The rise in respiratory and wound infections overtime is noteworthy for home healthcare patients,
considering the need for re-admission because of
these infections.
This study found a significant increase in the rateof carbapenem-resistant bacteria in the samples,particularly after the COVID-19 pandemic. Postpandemic era studies have demonstrated anincrease in carbapenem-resistant Gram-negative
bacteria due to impaired infection prevention andcontrol practices resulting from a high workload (23-194

26). It is worth noting that the significant rise in theuse of polymixin antibiotics, particularly in empiricalcases, may have exerted selection pressure onthese species (26-28). The high antibiotic use rates,
the highest among the region, at hospitals andoutpatients caused one of the highest resistance
rates in the region, especially carbapenem
resistance (29, 30).
Treatment options for carbapenem-resistantbacterial infections are limited, particularly in casesthat do not require hospitalization and can be
managed on an outpatient basis (31). Therefore,
when considering empirical treatment options,
it is crucial to be aware of the resistance profile,particularly the likelihood of carbapenem-resistantbacteria in patients being managed at home, when
considering empirical treatment options (9,31). Dataon the epidemiology of home healthcare infections
are scarce, and this study highlights the need for
epidemiological research on home healthcare
infections to develop better management strategies.
Owing to the increasing rates of resistance inthese patients, it is crucial for the healthcare staff
to implement precautionary measures to prevent
infection transmission among patients. Additionally,
they should monitor the growth of resistant bacteria
and the onset of infections in patients. Healthcare
personnel should demonstrate equal vigilance
to inpatients in isolating patients, separating
equipment, practicing hand hygiene, and using
protective gear (32,33). Home healthcare workers
must receive training in infection control proceduresto prevent outbreaks among patients (22,32).
However, in cases where patients are admitted to a
hospital without prior information on their bacterial
growth, such as those transferred from anotherhospital, it is advisable to place them in contact
isolation until culture results are available. Thismeasure helps ensure infection control within thehospital. Additionally, upon discharging patientswith nosocomial infections to home healthcare
facilities, there should be a mechanism in place toTRENDS IN CARBAPENEM RESISTANCE FROM 2018-2023
IN HOME HEALTH CARE: THE BOTTOM OF THE ICEBERG

promptly notify home healthcare workers about
infection control measures (33,34).
The limitations of this study include the absenceof patient clinical data and the lack of differentiation
between infection and colonization as the cause
in our laboratory data. However, we aimed todemonstrate changes in carbapenem resistancetrends among home healthcare patients, regardlessof whether the microorganism was a cause of
infection or colonization, or if it was clinically
relevant. This is because infection prevention andcontrol practices should be implemented regardlessof the clinical relevance to prevent the spread ofthese microorganisms.
This study showed an increasing trend in
carbapenem resistance rates among home healthcare
patients, particularly after the COVID-19 pandemic.
The incidence of carbapenem resistance increases
in parallel with age. The negative contributionof this increasing prevalence to morbidity andmortality in older patients has also increased.
Therefore, prevention and control strategies shouldbe implemented in home healthcare settings tomanage these infections. These infections arechallenging to manage, especially in geriatricpatients, and may cause hospital readmission oroutbreaks in vulnerable older patients.
Conflict of Interest: The authors declare no
conflict of interest regarding this manuscript.
Funding: None.
Ethics approval: This study was approved by the
Yildirim Beyazit University Clinical Studies EthicalCommittee with the registration number E-2023-40.

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ORIGINAL ARTICLE

Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.393
2024; 27(2):198−210
 Raziye ÖZDEMİR1 . . . . . . . . . . . . 

 Elnaz KARAMELİKLİ1 . . . . . . . . . 

 Merve AFACAN SATIOĞLU1 . . . . 
 Merve AKINCI1. . . . . . . . . . . . . . . 

 Zühal ÇAMUR1. . . . . . . . . . . . . . . 

CORRESPONDANCE
1Raziye ÖZDEMİR

Phone
e-mail: +905425660818: raziyeozdemir@karabuk.edu.tr

Received : May 13, 2024
Accepted : May 31, 2024

1 Karabuk University, Faculty of Health

Science Midwifery Department , Karabuk,
TurkeyA POPULATION-BASED CROSS-SECTIONALSTUDY ON PHYSICAL INTIMATE PARTNER
VIOLENCE AFFECTING OLDER WOMENIN A PROVINCE OF NORTHERN TURKEY:PREVALENCE, ASSOCIATED FACTORS, AND
INTERGENERATIONAL TRANSMISSION OF
VIOLENCE

ABSTRACTIntroduction: This study aimed to estimate the prevalence of physicalintimate partner violence among older women, identify factors associated withvictimization, and gather information on the intergenerational transmission ofviolence.
Materials and Method: This population-based cross-sectional study was
conducted in Karabuk Province and included 399 ever-married women aged
65 years and older. The dependent variable was exposure to physical violenceby a current or former spouse. Independent variables included women’ssociodemographic and reproductive characteristics, their experience ofviolence in childhood, and some characteristics of their husbands and parents.
The crude and adjusted prevalence ratios were estimated to explore therelationship between the dependent and independent variables using robust
Poisson regression analysis.
Results: The prevalence of physical intimate partner violence was 62.9%
for the lifetime and 7.6% for the past year. Lifetime prevalence increased 1.2fold with low household income, 1.4-fold with seven or more pregnancies,
1.3-fold with daily or weekly alcohol consumption by the husband, 1.3-foldwith witnessing father-to-mother violence in childhood, and 1.5-fold withexperiencing physical violence by parents in childhood. Women were more
likely to use violence against their children if they had experienced violence inchildhood and adulthood.
Conclusion: This study’s finding of high lifetime and past-year prevalenceof exposure to intimate partner violence highlights the need for more efforts
to address intimate partner violence among older women. More research isneeded to better understand older women’s experiences of intimate partner
violence and identify health and social policy approaches to meet their support
and assistance needs.
Keywords: Intimate Partner Violence; Domestic Violence, Physical Abuse;
Prevalence; Aged; Women.

198

A POPULATION-BASED CROSS-SECTIONAL STUDY ON PHYSICAL INTIMATE PARTNER
VIOLENCE AFFECTING OLDER WOMEN IN A PROVINCE OF NORTHERN TURKEY: PREVALENCE,ASSOCIATED FACTORS, AND INTERGENERATIONAL TRANSMISSION OF VIOLENCEINTRODUCTION
Intimate partner violence (IPV) against women isa global public health problem and human rights
violation with a wide range of short- and longterm health consequences and high economic
costs (1). IPV is defined as behaviors that cause
physical, psychological, or sexual harm, including
acts of physical assault, sexual coercion, emotional
abuse and controlling behaviors by a current orformer partner (2). Target 5.2 of the United Nations
Sustainable Development Goals calls for ending all
forms of violence against women and girls. One of
the indicators defined to monitor progress toward
this target is the measurement of IPV among everpartnered women aged 15 and over (5.2.1) (3).
Although this indicator includes older women,
most studies on IPV focus on women aged 15-49
years. Inadequate knowledge about older women’s
experiences of IPV leads to the invisibility andneglect of violence-related problems. Around theworld, older women face discrimination due torigid gender norms and cultural values that placea premium on youth and women’s reproductivefunctions. This discrimination can make older
women more vulnerable to age- and gender-based
violence. Violence against older women not only
harms them but also undermines their ability tocontribute to their families and communities (4).
Understanding older women’s experiences with IPV
is critical for identifying and addressing this problem
and developing effective social policy responses.
This is particularly important because of the risk ofsocial isolation, cognitive and functional decline,
deteriorating health, and potential dependence on
a spouse or caregiver for care in old age (5).
Physical violence, a common and visible formof IPV, refers to any aggressive behavior aimed
at causing physical harm using force. The limited
evidence on the physical IPV experiences of women
aged 65 and older comes from high-income
countries. According to a 2013 World HealthOrganization (WHO) study, the lifetime prevalenceof physical and/or sexual IPV in ever-partnered
women aged 15 and over was 30%; violence
increased with age, reaching its highest level (38%)
in the 40–44 age group, and then decreased atolder ages (20% in the 60–64 age group, 22% in
the 65–69 age group). The WHO study emphasizes
that the available data on IPV against older womenare limited to a small number of studies from highincome countries and that the low frequency of
IPV should not be interpreted as indicating thatolder women are less exposed to partner violencebut, rather, as patterns of violence among older
women being less understood (6). According toa meta-analysis of the WHO Global Database on
Prevalence of Violence Against Women, 23% of
women aged 65 years and older had experienced
physical, sexual, or both forms of IPV in their lifetime,with 4% having experienced it in the past year. This
study also highlights the need for more research to
fully understand the prevalence, as estimates forolder women were based on a limited number ofstudies (7). Although there are differences in themeasurement of physical violence among studies,
the lifetime prevalence of physical IPV among older
women is approximately 36% in Spain (8), 17% in
the United States (9), and 7% in Canada (10). In
Germany, the lifetime prevalence of physical andsexual IPV was 23% for women aged 50-65 and 10%
for women aged 66-86 (11). Studies have reported
that 0.3-4% of older women had been exposed tophysical IPV in the past year (7, 9, 11). According
to nationwide surveys in Turkey, the prevalence ofphysical IPV among women ranges from 30–39%
lifetime (12, 13, 14, 15) and 8–10% in the past year
(14, 15). These surveys did not provide information
on IPV exposure among older women. Additionally,
population-based domestic studies have focused
primarily on elder neglect and abuse rather than
IPV. A study conducted in Canakkale found that 4%of women aged 65 years and older had experienced
physical violence in the past year, with husbands
being the perpetrators in 43% of cases (16).

199

2024; 27(2):198−210

IPV is a socially produced phenomenon and isfueled by poverty, social and gender inequalities
and patriarchal ideology. In low- and middle-income
countries, women may be more vulnerable to IPV
due to various factors, such as economic insecurity,
gender inequalities, social stigma, inadequate
legal regulations, and insufficient social support
services, which are shaped by social, economic andpolitical determinants (7). Studies have shown that
exposure to IPV among older women is associatedwith several factors, including educational level (11),spousal alcohol use (11, 17), a history of childhood
abuse (11, 17, 18), inadequate social support (17, 19),
financial difficulties (18, 19), ethnic minority status,
cognitive or physical impairment, dependence on
one’s partner, and caregiving stress (18). Gerinio
et al. (2018) reported that social support, helpseeking behavior, and community-based services
addressing abuse are major protective factors
against IPV in elderly people (18).
The global elderly population is growing, which
may lead to an increase in the incidence of IPV and
IPV-related adverse health outcomes. Currently,
there is insufficient evidence on the experience of
IPV among older women in Turkey, and no studies
on this topic have been conducted in Karabuk
Province. Therefore, this study aimed to estimate
the prevalence of physical IPV among women aged
65 years and older, identify factors associated with
IPV victimization, and collect information on theintergenerational transmission of violence.

MATERIALS AND METHOD
Study design and settingThis population-based cross-sectional study was
conducted in 2022 in Karabuk Province, which islocated in the Black Sea region of Turkey. According
to 2021 data from the Turkish Statistical Institute,
Karabuk has a population of 249,287 people, 14%of whom are over 65 years old and 22% of whom
live in rural areas.

200

Study population and sampling
The sample size was calculated to be 377 womenbased on a population size of 19652 (women
aged 65 and older living in Karabuk in 2021), an
expected proportion of lifetime physical IPV of
50% (we assumed that lifetime exposure in older
women would be higher than the prevalence (3639%) found in younger women in national studies(14, 15) using the same method of measuringphysical violence as in this study), a 95% confidence
interval, and a 5% margin of error. A multistage
sampling procedure was used to select the women
who composed the sample group. First, the study
sample was proportionally distributed among therural (village) and urban (city and district centers)
populations. Urban neighborhoods and villages
were listed. Eight urban neighborhoods and 12
villages were then randomly selected. Households
were visited every ten houses, starting with arandom household on a street in the selected
settlements. If there was more than one evermarried older woman in the household, only one
woman was interviewed. If there was no older
woman in the household or if the woman refused
to participate in the study, the researchers moved
on to the next house.
Measures
Dependent variable: The dependent variable
was women’s exposure to physical violence from
intimate partners. We measured physical violenceusing the acts of physical violence identified in the
WHO Multi-country Study (20) and asked women
if they had experienced any of the following actsby their current or former spouse: a) slapped heror thrown something at her that could hurt her; b)
pushed or shoved her or pulled her hair; c) hit her
with his fist or something else that could hurt her;d) kicked, dragged, or beaten her up; e) choked orburned her on purpose; and f) threatened to use or
used a gun, knife, or another weapon against her.

A POPULATION-BASED CROSS-SECTIONAL STUDY ON PHYSICAL INTIMATE PARTNER
VIOLENCE AFFECTING OLDER WOMEN IN A PROVINCE OF NORTHERN TURKEY: PREVALENCE,ASSOCIATED FACTORS, AND INTERGENERATIONAL TRANSMISSION OF VIOLENCE

The lifetime prevalence of physical IPV was
calculated as the proportion of ever-married
women who reported experiencing at least one actof physical violence by a current or former spouseat any point in their lives. We also determined the
1-year prevalence of IPV among currently married
women by calculating the proportion of women
who reported at least one act of physical violence
that occurred in the 12 months before the interview.
The acts of physical violence were categorized into
two groups based on their severity: ‘slapping or
throwing something that could hurt’ and ‘pushing,shoving, or pulling hair’ were classified as moderate,
while all other acts were considered severe violence(20). A woman who experienced both moderate andsevere violence was classified as having experienced
severe violence. Additionally, the frequency ofphysical violence was classified as occurring onceor twice, occasionally, or frequent.
Independent variables: The independent
variables included women’s sociodemographic
characteristics (age, marital status, place ofresidence, level of education, monthly householdincome); women’s reproductive characteristics(age at first marriage, total number of pregnancies,
abortions, number of living children); somecharacteristics of their husbands and parents (levelof education, husband’s alcohol consumption);and childhood (aged ≤15) experiences of violence(childhood witnessing of physical violence fromfather-to-mother and childhood victimization ofparental physical violence).
Data collection tool and method
The data were collected through face-to-faceinterviews using a questionnaire that included 45
questions. The questionnaire was pretested on ten
older women in the city center who were not partof the study population. Before the data collection
stage, a meeting was held with all the researchers
to clarify the rules and ethical precautions to befollowed during the interviews. The interviews

lasted approximately 35 minutes in an isolated
place, mostly in the women’s homes. Some women
requested that a family member (daughter ordaughter-in-law) be present during the interview.
Therefore, a few interviews could not ensure an
isolated atmosphere (n= 8). Informed consent
was obtained from all women for their voluntary
participation in the study. Data collection wascompleted between June and September 2022.
Data analysis
The characteristics of the study group weresummarized as frequency and percentage
distributions. Chi-squared tests were used tocompare the proportions of lifetime physical IPV
among the categories of explanatory variables.
Prevalence ratios (PRs) were calculated for thevariables found to be significant according to the chisquare test. Crude and adjusted prevalence ratios(CPR and APR) and corresponding 95% confidence
intervals (CIs) were estimated to explore therelationships between dependent and independent
variables using univariable and multivariable robust
Poisson regression analyses. Due to the small
number of women exposed to physical IPV in thepast year, separate analyses were not performed
for them. All analyses were performed using SPSS
v20. For all comparisons, p <0.05 was considered toindicate statistical significance.
Ethical approval: Ethical approval for the
conduct of the study was granted by Karabuk
University (date: 07.06.2022, No. 2022/916).

RESULTS
Data were collected from 399 ever-marriedolder women in the study. The study’s results arepresented under three headings: 1) the prevalenceof physical IPV; 2) characteristics of the study groupand factors associated with lifetime physical IPV;and 3) intergenerational transmission of physicalviolence.

2012024; 27(2):198−210

1) The prevalence of physical intimate partner violence
The lifetime prevalence of physical IPV was 62.9%,
with 30.3% experiencing only moderate violence and32.6% experiencing severe violence. The prevalenceof physical IPV among currently married women in
the past year was 7.6%. All of these women reported
being subjected to severe violence (Figure 1).

Figure 2 shows the frequency of physical violenceacts. Women were most frequently subjected to‘slapping or throwing things’ and least frequently
to ‘threatening or using a weapon’. As the severityof the violence increased, its frequency decreased.
Women reported that most acts of violence wereoccasional and frequent (Figure 2).

Figure 1. Women’s experiencesof physical intimate
partner violence in
Karabuk, Turkey* If both moderate and severe physicalviolence were reported, these cases
were classified as severe violence.
**The denominator is currently married
women (n= 264).

Figure 2. Frequency ofphysical violence
acts

202

A POPULATION-BASED CROSS-SECTIONAL STUDY ON PHYSICAL INTIMATE PARTNER
VIOLENCE AFFECTING OLDER WOMEN IN A PROVINCE OF NORTHERN TURKEY: PREVALENCE,ASSOCIATED FACTORS, AND INTERGENERATIONAL TRANSMISSION OF VIOLENCEb) Characteristics of the study group andfactors associated with lifetime physical intimate partner violence
More than half of the women (54.6%) were aged
65-69 years, and 9.0% were aged 80 years or older.
The marital status of the women was 66.2% married,
32.6% widowed and 1.3% divorced. The proportionof households with a monthly income less than $200
was 39.1%. Most women (45.1%) were married duringadolescence, and one in five (20.1%) had sevenor more pregnancies. Almost half of the women(46.4%) and 10.8% of their husbands had no formal
education. Most of the women’s parents also had
no formal education (84.7% of mothers and 59.1%
of fathers). The proportion of women who witnessed
physical violence from father-to-mother duringchildhood was 47.1%. More than half of the women(56.9%) reported experiencing physical violencefrom their parents during childhood (Table 1).
All variables examined were associated withlifetime physical IPV exposure (p < 0.05), except
for four variables (woman’s age, place of residence,

Table 1. Characteristics of the study group according to exposure to lifetime physical intimate partner violence
Lifetime physicalintimate partner violenceTotaln (%)*

Yesn (%)**

Non (%)**

65-69

218 (54.6)

129 (59.2)

89 (40.8)

70-74

87 (21.8)

56 (64.4)

31 (35.6)

χ²= 3.546

75-79

58 (14.5)

41 (70.7)

17 (29.3)

p = 0.315≥ 80

36 (9.0)25 (69.4)

11 (30.6)

Urban

299 (74.9)

188 (62.9)

111 (37.1)

Rural

100 (25.1)

63 (63.0)

37 (37.0)

p = 0.982

Married264 (66.2)

163 (61.7)

101 (38.3)

χ²= 0.454

Widow or divorced

135 (33.8)

88 (65.2)

47 (34.8)

p = 0.501

No formal education

185 (46.4)

137 (74.1)

48 (25.9)

Primary school

173 (43.4)

93 (53.8)

80 (46.2)

Secondary school and above

41 (10.3)

21 (51.2)

20 (48.8)≤ 199

156 (39.1)

119 (76.3)

37 (23.7)

χ²= 19.637
p <0.001

VariableAge group

Place of residence
Current marital status
Education level
Household monthly income(USD)#First marriage age

Total number of pregnancies
Abortion (at least one)
Number of living children

Chi-squaretest

χ²= 0.000

χ²= 20.649
p <0.001≥ 200

243 (60.9)

132 (54.3)

111 (45.7)≤ 17

180 (45.1)

126 (70.0)

54 (30.0)

18-24

201 (50.4)

121 (60.2)

80 (39.8)≥ 25

18 (4.5)

4 (22.2)

14 (77.8)≤3127 (31.8)

54 (42.5)

73 (57.5)

4-6

192 (48.1)

131 (68.2)

61 (31.8)≥780 (20.1)

66 (82.5)

14 (17.5)

Yes

184 (46.1)

132 (71.7)

52 (28.3)

χ²= 11.415
p <0.001

No

215 (53.9)

119 (55.3)

96 (44.7)≤3247 (61.9)

140 (56.7)

107 (43.3)

4-6

134 (33.6)

94 (70.1)

40 (29.9)≥7

18 (4.5)

17 (94.4)

1 (5.6)

χ²= 17.281
p <0.001
χ²= 38.114
p <0.001

χ²= 14.789
p = 0.001

203

2024; 27(2):198−210

Table 1. Continued.

Totaln (%)*

Variable

Lifetime physicalintimate partner violenceYesn (%)**

Non (%)**

Chi-square
test

Yes

342 (85.7)

217 (63.5)

125 (36.5)

χ²= 0.303

No

57 (14.3)

34 (59.6)

23 (40.4)

p= 0.582

No formal education

43 (10.8)

31 (72.1)

12 (27.9)

Primary227 (56.9)

156 (68.7)

71 (31.3)

Secondary school and above

129 (32.3)

64 (49.6)

65 (50.4)

Every day/every week

92 (23.1)

72 (78.3)

20 (21.7)

1-2 times a month or less frequently

110 (27.6)

73 (66.4)

37 (33.6)

Never

197 (49.4)

106 (53.8)

91 (46.2)

No formal education

338 (84.7)

222 (65.7)

116 (34.3)

χ²= 7.287

Primary school and above

61 (15.3)

29 (47.5)

32 (52.5)

p = 0.007

No formal education

236 (59.1)

164 (69.5)

72 (30.5)

χ²= 11.485

Primary school and above

163 (40.9)

87 (53.4)

76 (46.6)

p = 0.003

Childhood witnessing of father- Yes
to-mother physical violenceNo

188 (47.1)

146 (77.7)

42 (22.3)

χ²= 33.157

211 (52.9)

105 (49.8)

106 (50.2)

p < 0.001

Yes

227 (56.9)

177 (78.0)

50 (22.0)

χ²= 51.226

No

172 (43.1)

74 (43.0)

98 (57.0)

p < 0.001

399 (100.0)

251 (62.9)

148 (37.1)

Diagnosed chronic disease

Husband’s education level

Husband’s alcohol usage

Mother’s education level
Father’s education level

Childhood victimization ofparental physical violenceTotal

χ²= 14.693
p = 0.002

χ²= 16.849
p < 0.001*Column percentage. **Row percentage. #Calculated according to the exchange rate of the Central Bank of the Republic of Turkey on 01/08/2022.

marital status, and diagnosed chronic disease).
Women with low education and low householdincome were more exposed to physical IPV.
Exposure to violence gradually decreased as
marriage age declined but increased as the numberof pregnancies and living children increased.
Women who had at least one abortion were more
likely to have experienced physical IPV than those
who had never had an abortion (71.7% and 55.3%,
respectively). The low levels of education of thewomen, their husbands and their parents increased
the likelihood of exposure to physical IPV. While thephysical IPV percentage was 53.8% among women204

whose husbands had never consumed alcohol, itrose to 78.3% among women whose husbands werecurrent or former daily or weekly drinkers. Lifetime
exposure to physical IPV was greater among women
who had witnessed father-to-mother violence andthose who had experienced physical violence fromtheir parents (Table 1). Although not shown in thetable, 29.1% of all women and 75% of women who
experienced violence in the past year reported
being injured by physical violence at least once intheir lifetime.
Multivariable analysis revealed a greater lifetime
prevalence of physical IPV among women with a

A POPULATION-BASED CROSS-SECTIONAL STUDY ON PHYSICAL INTIMATE PARTNER
VIOLENCE AFFECTING OLDER WOMEN IN A PROVINCE OF NORTHERN TURKEY: PREVALENCE,ASSOCIATED FACTORS, AND INTERGENERATIONAL TRANSMISSION OF VIOLENCE

Table 2. Factors associated with exposure to lifetime physical intimate partner violence
Univariable analysis
Variable
Education level

CPR

No formal education

Primary school

Secondary school

High school and above (ref)Household monthly income (USD)
First marriage age

Total number of pregnancies
Abortion (at least one)
Number of living children≤ 199≥ 200 (ref)

≤ 17

18-24

≥ 25 (ref)≤ 3 (ref)Yes≤ 3 (ref)4-6

Husband’s alcohol usage
Mother’s education level
Father’s education level
Childhood witnessing of physicalviolence from father-to-mother

APR

95%CI

p

1.1

0.6-2.1

0.756

1.5

0.7-3.1

0.263

1.0

0.5-1.9

0.961

1.7

0.8-3.6

0.197

1.4

0.8-2.7

0.268

1.0

-

-

1.0

-

-

1.4

1.2-1.6<0.0011.2

1.1-1.4

0.005

1.0

-

-

1.0

-

-

3.1

1.3-7.5

0.010

2.4

0.8-7.1

0.113
0.137

2.7

1.1-6.5

0.025

2.2

0.8-6.5

1.0

-

-

1.0

-

-

1.0

-

-

1.0

-

-

1.3-2.0<0.001

1.3

1.5-2.4

1.1-1.5<0.001

1.0

-

-

1.0

-

-

1.2

≥7

1.7

No formal education

Husband’s education level

0.043

1.9

No (ref)p

1.0-4.2

1.6

4-6
≥7

95%CI

2.1

Multivariable analysis

1.5

1.1-1.4

0.001

0.007

1.3

1.0-1.6

0.060

1.4

1.1-1.9

0.012

1.1

0.9-1.2

0.421

1.0

-

-

1.0

-

-

1.0

0.9-1.2

0.939

1.4-1.9<0.001

1.2

0.9-1.6

0.134

1.1-2.0

0.014

1.0

0.7-1.4

0.823

Primary

1.4

1.1-1.9

0.011

1.2

0.9-1.5

0.332

1.0

0.7-1.5

0.789

1.0

0.7-1.4

0.840High school and above (ref)

1.0

-

-

1.0

-

-

1.5

1.2

1.2-1.7

1.0-1.5<0.0011.3

1.1-1.6<0.001

1.2

0.9-1.4

0.059

1.0

-

-

1.0

-

-

No formal education

1.4

1.0-1.8

0.021

1.0

0.8-1.4

0.754

1.0

-

-

1.0

-

-

No formal education

1.1

0.8-1.6

0.513

0.7

0.5-1.1

0.125

0.8

0.6-1.2

0.363

0.7

0.4-1.0

0.050

1.0

-

-

1.0

-

-

1.6

1.3-1.8<0.0011.3

1.1-1.5

0.002

SecondaryEvery day/every week

1-2 times a month or less frequently

Never (ref)Primary school and above (ref)Primary school

Secondary school and above (ref)Yes

No (ref)

Childhood victimization of parental Yes
physical violence
No (ref)

0.027

1.0

-

-

1.0

-

-

1.8

1.5-2.2<0.0011.5

1.3-1.8<0.001

1.0

-

-

1.0

-

-

ref: reference value. CPR: crude prevalence ratio. APR: adjusted prevalence ratio.

monthly household income of less than $200 (APR=
1.2), women with seven or more pregnancies (APR=
1.4), and women whose husbands used alcohol daily
or weekly (APR= 1.3). In addition, lifetime prevalence
was significantly greater among women who had

witnessed father-to-mother violence (APR= 1.3)
and those who had experienced physical violencefrom their parents (APR = 1.5) during childhood
than among those who had no such experiences(Table 2).
2052024; 27(2):198−210

Table 3. Intergenerational transmission of physical violence

Experience with physical violenceChildhood witnessing ofphysical violence fromfather-to-motherChildhood victimizationof parental physicalTotal
violence
n
Yes
No
n (%)
n (%)

Yes
n (%)

No
n (%)

Yes
n (%)

No
n (%)

188

150 (79.8)

38 (20.2)

146 (77.7)

42 (22.3)

131 (69.7)

57 (30.3)

No

211

77 (36.5)

134 (63.5)

105 (49.8)

106 (50.2)

94 (44.5)

117 (55.5)

χ²= 75.984 p<0.001

χ²= 33.157 p<0.001

χ²= 25.533 p<0.001

Yes

227

177 (78.0)

50 (22.0)

168 (74.0)

59 (26.0)

No

172

74 (43.0)

98 (57.0)

57 (33.1)

115 (66.9)

χ²= 51.226 p<0.001

Chi-square test
Victimization of physical
IPV

Inflicting physicalviolence on own childYes

Chi-square test
Childhood victimization ofparental physical violence

Victimization ofphysical IPV

χ²= 66.464 p<0.001

Yes

251

174 (69.3)

77 (30.7)

No148

51 (34.5)

97 (65.5)

Chi-square test

χ²= 46.016 p<0.001

IPV: Intimate partner violence.

c) Intergenerational transmission of physicalviolence

DISCUSSION

violence. Our findings indicate that IPV among older
women is a significant public health problem that
requires serious attention. We found that almost
two out of three (62.9%) of the ever-partnered
women aged 65 years and older had experienced
physical violence from a current or former intimate
partner at least once in their lifetime, and 7.6% of
the currently married women had experienced it in
the past year. Most women were victims of severe
physical violence and were subjected to repeatedacts of violence. This study also provides important
insights into the intergenerational transmission ofviolence and highlights the need for long-term, lifecourse policies to prevent violence against women.

In this study, the experiences of physical IPV amongolder women in a province in northern Turkey was
examined using the WHO standard definitions of

The prevalence of both lifetime and past-year
physical IPV found in this study is much greater thanthat reported in high-income countries. In the 2014

Any experience of physical violence in childhood or
adulthood increased the likelihood of a subsequent
experience of violence. Women who witnessed andwere exposed to parental violence in childhood
were more likely to perpetrate violence against theirchildren, in addition to being exposed to IPV (p <0.001). The majority of women (69.3%) exposed tophysical IPV perpetrated physical violence against
their children (p < 0.001) (Table 3).

206

A POPULATION-BASED CROSS-SECTIONAL STUDY ON PHYSICAL INTIMATE PARTNER
VIOLENCE AFFECTING OLDER WOMEN IN A PROVINCE OF NORTHERN TURKEY: PREVALENCE,ASSOCIATED FACTORS, AND INTERGENERATIONAL TRANSMISSION OF VIOLENCE

nationwide survey in Turkey, the lifetime prevalenceof physical IPV increased with age, while the pastyear prevalence decreased with increasing age. It isan expected finding that the lifetime prevalence ofphysical IPV found in this study is greater than that in
the national study due to the age-related cumulative
effect. In addition, the women in our study group,
who had reached a certain age and approximately athird of whom were widowed, may have been more
likely to report their past experiences. However, thepast-year prevalence, which would be expected
to be lower in older women, is almost the sameas that reported in younger women in the national
survey (8%). The high past-year prevalence in the
study might have been affected by the ongoing
effects of the COVID-19 epidemic in the year
before data collection. The pandemic has had
negative socioeconomic and psychological effects
on society, including a dramatic increase in cases ofdomestic violence. On the other hand, all women
who reported experiencing violence in the past year
reported that they had been exposed to violencemany times, and 15 of them reported being injured
by violence at least once in their lives. Therefore,
our findings can be interpreted as indicating thatwomen’s past exposure to violence continues
into old age. A systematic review of 52 qualitative
studies investigating advanced-age women’s
experiences of violence revealed that IPV is often
experienced in the context of a lifetime of exposure
to IPV, that physical and mental health effects are
cumulative, that health effects are exacerbated byaging processes, and that age-related changes insocial status are often exacerbated (5).
Despite the process of modernization that
Turkey has undergone since the establishment of
the republic, patriarchal values that determine thesubordinate position of women are still entrenchedin society. Patriarchal control over women is
exercised through restrictive codes of behavior,gender segregation and the association of family
honor with female virtue (21). Islamic religious beliefs

reinforce patriarchal ideology, and power relations
based on widespread gender inequalities expose
women of all ages to various forms of violence. In
Turkey, however, women’s access to education andemployment opportunities has increased over theyears, and the issue of women’s rights has begun
to feature more prominently on the public agenda.
These changes are also reflected in women’s
attitudes toward violence. For example, the level ofagreement with the statement that a husband canbeat his wife for some reason was 39.9% in 2003 (22)and 9% in 2018 (23); the percentage of women who
agreed that children can be beaten for education
was 42.4% in 1995 (12) and 27.3% in 2014 (15). It is
more difficult for older women to access modern
values than for younger women, and the acceptanceof violence may be more prevalent among older
women. Women with no formal education, earlymarriage and excess fertility composed most of
our study group. The gender roles and norms thatgive men more power and expect women to be
self-sacrificing and obedient may shape the lifetime
violence experiences of our study group, reflecting
the more traditional face of Turkey.
In this study, exposure to lifetime physical IPV
increased 1.3-fold with daily or weekly alcohol
consumption by the husband, 1.2-fold with low
household income, and 1.4-fold with seven or
more pregnancies. Similar associations between
low income and alcohol consumption and IPV
have been found in other studies (11, 17, 18, 19).
Heavy alcohol use can lead to spousal violenceby increasing marital conflict, increasing individuallevels of aggression, and impairing cognitive
functioning (11). Traditional and patriarchal values
may contribute to greater exposure to IPV among
women with seven or more pregnancies. These
values confine women to traditional family roles,
encourage excessive fertility, and may increase therisk of exposure to violence to control women.
Our findings on the intergenerationaltransmission of violence confirm that “violence2072024; 27(2):198−210

begets violence”. Women who witnessed IPV fromfather-to-mother and women who experienced
violence from their parents in childhood had a highprevalence of IPV (APR= 1.3 and 1.5, respectively).
Women’s violent experiences in childhood andadulthood increased the likelihood of violenceagainst their children. Children who witness violence
between parents may perceive it as a normal partof family life, leading to greater acceptance of such
violence and aggression. In this way, boys learn touse violence, and girls learn to tolerate violence orat least to tolerate aggressive behavior (24). Other
studies have also shown that negative childhood
experiences, particularly witnessing violence fromfather-to-mother, increase the risk of becoming an
IPV victim in adulthood (11, 24, 25).
Limitations
This study has limitations. First, due to thecross-sectional design of this study, causality
cannot be proven. Second, the study asked
women retrospectively about their lifetime
experiences of violence based on women’s selfreports. Retrospective reporting may lead tounderreporting or overreporting. In addition,older women’s willingness and ability to disclose
violence perpetrated by their husbands may also
be influenced by their perceptions of their current
economic and social status. Finally, complete privacy
was not assured in all interviews. A family member
was present during a small number of interviews.
Despite these limitations, this study contributes
to the limited body of literature highlighting IPV
in older women as an issue that requires greaterattention. In addition, the standard WHO definitionof physical violence used in the study allows
comparisons between studies, representing an
additional contribution of this study.

CONCLUSION
In conclusion, this study showed that the prevalenceof lifetime and past-year physical IPV among

208

women aged 65 and older was 62.9% and 7.6%,
respectively. The lifetime prevalence increased
with low income, seven or more pregnancies,
husband’s alcohol use, witnessing physical violencefrom father-to-mother in childhood, and exposure
to physical violence from parents in childhood. In
addition, women’s exposure to physical violence inchildhood and adulthood increased the likelihoodof physical violence against their children. Firstand foremost, eliminating violence against womenrequires political commitment and multisectoral
action to address social and gender inequalities.
Older women should be systematically screened
for exposure to violence, and psychosocial support
programs should be established for those affected.
Primary health care facilities are particularly
important for identifying victims and meeting theirservice needs. Further research focusing on otherforms of IPV and health outcomes is needed tobetter understand older women’s experiences of
IPV.

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ORIGINAL ARTICLE

Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.394
2024; 27(2):211−219
 Fatma ETGÜ1. . . . . . . . . . . . . . . . 

 Yeliz KASKO ARİCİ2 . . . . . . . . . . 

THE PREVALENCE OF SKIN DISEASESAMONG THE ELDERLY PATIENTS APPLYINGA TERTIARY DERMATOLOGY OUTPATIENT
CLINIC: A RETROSPECTIVE ANALYSIS OF
2400 PATIENTSABSTRACTIntroduction: As the population ages, particular health issues affect thissusceptible age group. The aim of this study was to evaluate the incidence,
frequency, age, gender, and season-of-year distribution of dermatologicaldisorders among geriatric patients.
Materials and Method: This was a retrospective, descriptive study. Skindiseases were categorized into 12 different groups and analyzed according to
the age groups, gender, and season of the application.

CORRESPONDANCE
1Fatma ETGÜPhone
e-mail: +905333673667: fatmaetgu@gmail.com

Received : Mar 22, 2024
Accepted : Jun 05, 2024

Results: The study included 2431 patients (1203 were female and 1228 weremale). The mean age of the patients was 74.02±7.07(65-100) years. For 23.1%of these patients, the problems were acute, and for 76.9%, they were chronic.
The ratio of patients with one, two, and more than three complaints was 81.0%,
13.9%, and 5.1%, respectively. The most frequent diagnoses were pruritus(n=424, 17.4%); eczematous dermatitis (n=395, 16.2%); fungal infections (n=372,
15.3%); premalign and malign skin disorders (n=247, 10.2%); bacterial infections(n=147, 6%); viral infections (n=118, 4.9%); papulosquamous diseases (n=95,
3.9%); urticaria and adverse drug reactions (n=96, 3.9%); benign skin tumors(n=79, 3.2%); acneiform disorders (n=40, 1.6%); and vesiculobullous disorders(n=22, 0.9%).
Conclusion: The majority of skin diseases among the elderly are not lifethreatening, and they are preventable. Knowing the prevalence and distributionof skin diseases seen in the elderly can help prevent these disorders and develop
policies for better management of elderly-related health issues.

1 Ordu University, Faculty of Medicine,

Department of Dermatology, Ordu, Turkey

Keywords: Aged; Skin Diseases; Preventive Medicine; Skin Aging.

2 Ordu University, Faculty of Medicine,

Department of Biostatistics and Medical
Informatics , Ordu, Turkey

2112024; 27(2):211−219

INTRODUCTION

MATERIALS AND METHOD

Improvements in health care and the managementof chronic conditions have led to longer life
expectancies, which, in addition to declining fertility
rates, have contributed to population aging (1,2). It has been estimated that by 2025, the global
population will comprise approximately 1,2 billion
individuals aged 60 and over, and this number is
projected to increase to 1,9 billion individuals by
2050 (3).

This retrospective descriptive study was conductedin the Department of Dermatology at the Universityof Ordu, Turkey. All patients over 65 years of age who
attended the dermatology outpatient clinic from
June 2019 to June 2021 were included in the study.
The study was conducted in accordance with theHelsinki Declaration and was approved by the Ordu
University Training and Research Hospital Ethics
Review Board (Number: 2023/214). According to
the World Health Organization classification, thepatients in this study were grouped by gender andage group: 65–74 years, 75–84 years, and 85 years
or older.

According to the Turkish Statistical Institute,from 2020–2022, life expectancy at birth in Turkey
was 77.5 years (4). The elderly population, including
those 65 years of age and older, has increased by
22.6% in the last five years. In 2030, the percentageof the population aged 65 years and over has been
projected to be 12.9%, 16.3% in 2040, 22.6% in 2060,
and 25.6% in 2080 (5).
Because aging is an ongoing biological process,it causes a wide range of changes in all organs,including the skin (6, 7). Aging causes decreased
epidermal hydration and increased transepidermal
water loss, which leads to dry, xerotic skin. The
epidermal turnover rate and the production of lipids
and filaggrin also decline with aging. Consequently,
the epidermal barrier function does not function
properly. Moreover, the immune system, whichenables the body to repair DNA and wounds, aswell as manintain thermoregulatory mechanisms,
sweat production, sebum production, and vitamin
D production, weakens with age (2, 8). In addition
to these changes, reduced functional capacity,
associated chronic conditions, polypharmacia, andpoor skin care and personal hygiene practices,increase the susceptibility of elderly patients to skindiseases and issues (9–11).
This study aimed to evaluate the incidence,
frequency, age, gender, and seasonal distribution ofdermatological disorders among geriatric patients
admitted to the outpatient dermatology clinic at auniversity hospital in the city of Ordu, Turkey.

212

Skin diseases were categorized into 12 different
groups, including pruritus, eczematous dermatitis,
papulosquamous diseases, bacterial infections, viral
infections, fungal infections, benign neoplasms,
precancerous, and malignant lesions, urticaria, andadverse drug reactions, vesiculobullous diseases,
acne, and related diseases, and other diseases(disorders of physical agents, hair disorders, naildisorders, mucosal disorders, vascular diseases,
granulomatous disorders, pigmentation disorders,and connective tissue diseases, metabolic skindiseases, panniculitis, kserosis cutis, and parasitic
infestations).
Statistical Analysis
Categorical data were expressed as frequency (n)and percentage (%). Pearson’s chi-square test wasused to determine the relationships between the
categorical variables. Continuous variables wereexpressed as mean±standard deviation (minimummaximum value). In the chi-square tests, if the
expected frequencies were below 5, the likelihood
ratio test statistic was calculated instead ofPearson’s test statistic. All statistical analyses were
performed using SPSS v28 (IBM Inc., Chicago, IL,
USA) statistical software.

THE PREVALENCE OF SKIN DISEASES AMONG THE ELDERLY PATIENTS APPLYING A TERTIARY
DERMATOLOGY OUTPATIENT CLINIC: A RETROSPECTIVE ANALYSIS OF 2.400 PATIENTS.

RESULTS

presented with a chronic complaint. Only 11.2% of
the patients had xerosis. Overall, the most frequentdiagnoses were pruritus (n = 424, 17.4%); eczematous
dermatitis (n = 395, 16.2%); fungal infections (n =372, 15.3%); premalign and malign skin disorders(n = 247, 10.2%); bacterial infections (n = 147, 6%);
viral infections (n = 118, 4.9%); papulosquamous
diseases (n = 95, 3.9%); urticaria and adverse
drug reactions (n = 96, 3.9%); benign skin tumors(n = 79, 3.2%); acneiform disorders (n = 40, 1.6%);and vesiculobullous disorders (n = 22, 0.9%). The
group with other disorders included the following:vascular disorders (n = 95, 3.9%); disorders due tophysical agents (n = 83, 3.4%); parasitic infestations(n = 92, 3.8%); mucosal disorders (n = 12, 0.7%); hairdisorders (n = 12, 0.5%); nail disorders (n = 6, 0.2%);
and pigmentation disorders (n = 8, 0.3%). The
frequency distribution of the disease diagnoses ofthe patients is shown in Table 1.

This retrospective cross-sectional study used asample of 2,431 patients who presented to the
Ordu University Training and Research Hospital
Dermatology Polyclinic between 2019 and 2021.
Of these patients, 49.5% (n = 1203) were female,and 50.5% (n = 1228) were male. The distributionof the patients according to the seasons showedthat the highest number of applications were in
winter (n = 787, 32.4%), followed by autumn (n =670, 27.6%), summer (n = 632, 26.0%), and spring(n = 342, 14.1%). The mean age of the patients was
74.02±7.07 (65–100) years; 1,412 (58.1%) patientswere in the 65–74 age group, 940 (38.7%) patientswere in the 75–89 age group; and 79 (3.2%) patientswere in the ≥ 90 age group.
Of the patients in the study sample, 23.1%
presented with an acute complaint, and 76.9%

Total
%

Acneiform
disordersWinter

Vesiculobullous
diseasesAutumnUrticaria andadverse drug
reactions

SummerPremalign andmalign diseases

Seasons

Benign skintumorsSpringOther disorders≥90

Fungal infections

75-89

Viral infections

AgegroupsBacterial
infections

65-74

Papulosquamous
diseases

Male

n
%
n
%
n
%
n
%
n
%
n
%
n
%
n
%
n
%
n
%

Eczematous
dermatitis

GenderFemalePruritus

Table 1. The distribution of diagnosis of the patients’ according to gender, age groups, and seasons

212
17.6
212
17.3
185
13.1
216
23.0
23
29.1
60
17.5
118
18.7
112
16.7
134
17.0
424
17.4

167
13.9
228
18.6
252
17.8
135
14.4
8
10.1
63
18.4
104
16.5
109
16.3
119
15.1
395
16.2

43
3.6
52
4.2
64
4.5
28
3.0
3
3.8
18
5.3
15
2.4
19
2.8
43
5.5
95
3.9

79
6.6
68
5.5
85
6.0
57
6.1
5
6.3
15
4.4
46
7.3
48
7.2
38
4.8
147
6.0

57
4.7
61
5.0
72
5.1
45
4.8
1
1.3
24
7.0
23
3.6
38
5.7
33
4.2
118
4.9

200
16.6
172
14.0
242
17.1
122
13.0
8
10.1
50
14.6
116
18.4
102
15.2
104
13.2
372
15.3

215
17.9
181
14.7
255
18.1
131
13.9
10
12.7
41
12.0
97
15.3
112
16.7
146
18.6
396
16.3

41
3.4
38
3.1
41
2.9
33
3.5
5
6.3
10
2.9
17
2.7
20
3.0
32
4.1
79
3.2

101
8.4
146
11.9
121
8.6
113
12.0
13
16.5
33
9.6
57
9.0
73
10.9
84
10.7
247
10.2

56
4.7
40
3.3
60
4.2
36
3.8
0
0.0
16
4.7
20
3.2
24
3.6
36
4.6
96
3.9

14
1.2
8
0.7
9
0.6
10
1.1
3
3.8
4
1.2
6
0.9
6
0.9
6
0.8
22
0.9

18
1.5
22
1.8
26
1.8
14
1.5
0
0.0
8
2.3
13
2.1
7
1.0
12
1.5
40
1.6

213

2024; 27(2):211−219

Table 2. The difference in the diagnosis of the disease of the patients according to the gender
GenderFemaleDiagnosis of the disease

Total

Male

n

%

n

%

n

%

Pruritus

212

17.6

212

17.3

424

17.4

Eczematous dermatitis

167

13.9

228

18.6

395

16.2

Papulosquamous diseases

43

3.6

52

4.2

95

3.9

Bacterial infections

79

6.6

68

5.5

147

6.0

Viral infections

57

4.7

61

5.0

118

4.9

Fungal infections

200

16.6

172

14.0

372

15.3

Benign skin tumors

41

3.4

38

3.1

79

3.2

Premalign and malign diseases

101

8.4

146

11.9

247

10.2

Urticaria and adverse drug reactions

56

4.7

40

3.3

96

3.9

Vesiculobullous diseases

14

1.2

8

0.7

22

0.9

Acneiform disorders

18

1.5

22

1.8

40

1.6

Other disorders

215

17.9

181

14.7

396

16.3

Total

1203

100.0

1228

100.0

2431

100.0

p

0.002 (χ2: 29.020)

χ2: Pearson’s chi-square test statistic

Table 3. The difference in the diagnosis of the disease of the patients according to the age groups
Age groups
65-74

Diagnosis of the disease

75-89

Total

≥90

n

%

n

%

n

%

n

%

Pruritus

185

13.1

216

23.0

23

29.1

424

17.4

Eczematous dermatitis

252

17.8

135

14.4

8

10.1

395

16.2

Papulosquamous diseases

64

4.5

28

3.0

3

3.8

95

3.9

Bacterial infections

85

6.0

57

6.1

5

6.3

147

6.0

Viral infections

72

5.1

45

4.8

1

1.3

118

4.9

Fungal infections

242

17.1

122

13.0

8

10.1

372

15.3

Benign skin tumors

41

2.9

33

3.5

5

6.3

79

3.2

Premalign and malign diseases

121

8.6

113

12.0

13

16.5

247

10.2

Urticaria and adverse drug reactions

60

4.2

36

3.8

0

0.0

96

3.9

Vesiculobullous diseases

9

0.6

10

1.1

3

3.8

22

0.9

Acneiform disorders

26

1.8

14

1.5

0

0.0

40

1.6

Other disorders

255

18.1

131

13.9

10

12.7

396

16.3

Total

1412

100.0

940

100.0

79

100.0

2431

100.0

p
LRχ2: Likelihood Ratio chi-square test statistic

214<0.001 (LRχ 2:91.800)

THE PREVALENCE OF SKIN DISEASES AMONG THE ELDERLY PATIENTS APPLYING A TERTIARY
DERMATOLOGY OUTPATIENT CLINIC: A RETROSPECTIVE ANALYSIS OF 2.400 PATIENTS.

The analysis of disease distribution according togender showed statistically significant differences
between the groups (p = 0.002), as shown in
Table 2. The female patients were predominantly
diagnosed with other disorders, pruritus, and fungal
infections. The male patients were predominantly
diagnosed with eczematous dermatitis, pruritus,
and other disorders. Premalignant and malignant
diseases were more prevalent among males,
accounting for 11.9% and 8.4%, respectively. The
incidence of benign skin tumors was comparable inboth females and males.

drug reactions, acneiform disorders, and otherdisorders became less frequent as the age groupincreased. The disease group with other disorders
was the most frequently encountered in the 64–74
age group. Patients between 75 and 89 years andpatients over 90 years were diagnosed with pruritus.
The prevalence of some diseases variee according
to season (Table 4). Eczematous dermatitis was themost frequently observed disease in the spring,followed by pruritus in the summer and fall, andother disorders in the winter. Fungal infections werethe most frequently diagnosed in the summer, whileviral infections were the most frequent in the spring.

The disease distribution varied according to age
group, which was statistically significant (p < 0.001),
as shown in Table 3. As expected, there was anotable increase in the prevalence of premalignant
and malignant diseases as the age of the patients
increased. Additionally, benign skin tumors werethe most frequently observed in patients older
than 90 years. In contrast, eczematous dermatitis,
viral infections, fungal infections, urticaria, adverse

The rate of patients with only one complaint
was 81.0%, the rate of patients with two complaints
was 13.9%, and the rate of patients with morethan three complaints was 5.1%. When a patientpresented with multiple complaints, the primary
diagnosis related to the primary complaint was
taken into account. The differences in the number

Table 4. The difference in the diagnosis of the disease of the patients according to the seasons
Seasons
SpringDiagnosis of the disease

SummerAutumnTotal

WinterPruritus

n

%

n

%

n

%

n

%

n

%

60

17.5

118

18.7

112

16.7

134

17.0

424

17.4

63

18.4

104

16.5

109

16.3

119

15.1

395

16.2

Papulosquamous diseases

18

5.3

15

2.4

19

2.8

43

5.5

95

3.9

Bacterial infections

15

4.4

46

7.3

48

7.2

38

4.8

147

6.0

24

7.0

23

3.6

38

5.7

33

4.2

118

4.9

Fungal infections

50

14.6

116

18.4

102

15.2

104

13.2

372

15.3

Benign skin tumors

10

2.9

17

2.7

20

3.0

32

4.1

79

3.2

33

9.6

57

9.0

73

10.9

84

10.7

247

10.2

Urticaria and adverse drug reactions

16

4.7

20

3.2

24

3.6

36

4.6

96

3.9

Vesiculobullous diseases

4

1.2

6

0.9

6

0.9

6

0.8

22

0.9

8

2.3

13

2.1

7

1.0

12

1.5

40

1.6

Other disorders

41

12.0

97

15.3

112

16.7

146

18.6

396

16.3

342

100.0

632

100.0

670

100.0

787

100.0

2431

100.0

Eczematous dermatitis

Viral infections

Premalign and malign diseases

Acneiform disorders

Total

p

0.023 (χ 2: 51.035)

χ2: Pearson’s chi-square test statistic

215

2024; 27(2):211−219

Table 5. The differences in number of patients’ complaints according to gender, age groups, and seasons
Number of complaints
1nGenderAge groups

Seasons

2
%

n

≥3
%

n

p
%

Female

976

81.1

169

14.0

58

4.8

0.858

Male

994

80.9

169

13.8

65

5.3

(χ2: .306)

65-74

1143

80.9

203

14.4

66

4.7

75-89

768

81.7

121

12.9

51

5.4

0.421
(χ2: 3.888)

≥90

59

74.7

14

17.7

6

7.6

Spring

273

79.8

48

14.0

21

6.1

Summer

535

84.7

75

11.9

22

3.5

0.004
(χ2:19.420)

Autumn

547

81.6

100

14.9

23

3.4

Winter

615

78.1

115

14.6

57

7.2

χ2 : Pearson’s chi-square test statisticof patients’ complaints according to gender, agegroups, and seasons are examined in Table 5. The
number of patients’ complaints did not significantly
change according to gender (p = 0.858). The rates
of complaints were similar for women and men. The
number of complaints increased as age increased,
but this increase was not statistically significant(p = 0.421). The number of patients’ complaints
showed a statistically significant change according
to the seasons (p = 0.004). The rate of those with≥3 complaints was approximately 2 times higher inspring and winter than in summer and fall (6.1% and7.2% vs. 3.5% and 3.4%, respectively).

DISCUSSION
In this study, there was a similar number of female
and male patients. In some previous studies, female
patients outnumbered male patients (7, 12, 13).
In other previous studies, there were more malepatients than female patients (14-17). In this current
study, the majority of the patients were between
the ages of 65 and 74 years, similar to other studies(7, 13-15, 17). Our findings showed that, the mostfrequent diagnoses were in the winter, followedby the autumn. In a study conducted by Yaldız et216

al., patients attended to the hospital in the winter,followed by the spring (14). Another previous study
found that patients most frequently visited thehospital in the autumn and spring (17).
Pruritus,
eczematous
dermatitis,
fungalinfections, premalignant skin diseases, and bacterial
diseases were the most frequently diagnosed in thisstudy, similar to the previous studies (14, 15, 17,18). Bilgili et al. reported the same most common
disease groups as found in our study, with the
exception that urticaria-angioedema was the fourthmost common disease, which was as common in ourcohort. Moreover, there were no patients over 90
years of age diagnosed with urticaria (16). Sarac etal. reported the same most common disease groups
as in our study, but their patients were diagnosed
with a greater number of papulosquamous diseases(7). In our study, more than 75% of the patients had
chronic complaints, and four out of five patients had
only one complaint. In a previous study, more than
90% of the patients had only one complaint in astudy with 209 patients (13).
As people age, their sebaceous and sweat
glands produce less sebum and less sweat, whichleads to the development of xerosis. The waterTHE PREVALENCE OF SKIN DISEASES AMONG THE ELDERLY PATIENTS APPLYING A TERTIARY
DERMATOLOGY OUTPATIENT CLINIC: A RETROSPECTIVE ANALYSIS OF 2.400 PATIENTS.

content of the stratum corneum decreases whenolder people are immobile. Additionally, xerosis
may be caused by the latter stage of renal illness, alack of zinc and critical fatty acids, thyroid conditions,and medications (12). In our study group, xerosis
was present in 11.2% of the patients. Kılıç et al.
conducted a study on elderly patients in nursing
homes, and they reported that 45.3% of thesepatients had xerosis. In a study conducted by Yaldız
et al., 7092 elderly patients were retrospectively
examined, and the ratio of xerosis was found to
be 8.17%, similar to our findings (14). In anotherstudy, the authors analyzed 7722 patients over 65
years, and the prevalence of xerosis was reported
to be 13.8% (15). In another study, 4.7% of the 877
patients had xerosis (7).
In our study, pruritus was the most frequently
observed in both genders. Its prevalence increased
with advancing age and was not affected byseason. Similar to our study, in (7), the prevalenceof pruritus prevalence was found to be the same
in both genders, and its prevalence increased
with advancing age. In the same study, pruritus
was the third most common disease in the patientgroup (7). In another study conducted in Turkey,
pruritus was the third most common disease, andits prevalence increased with advancing age (19).
Most cases of pruritus in the elderly population
have been reported to be related to xerosis
and aging (12, 17). Systemic illnesses, as well
as psychological issues, can also contribute topruritus. Metabolic illnesses that might produce
pruritus include diabetes mellitus (DM), irondeficient anemia, infections, medications, renal,
and hepatic insufficiency, thyroid, and parathyroid
disorders, and malignancies (12).
The prevalence of eczematous dermatitis
steadily declines with age. The reason may bethat there is more contact with environmental andphysical factors in the younger individuals (7, 17). In
this study, eczematous dermatitis was the second
leading cause of elderly attendance at outpatient

clinics, although its prevalence decreases withadvancing ages. Eczematous dermatitis was morecommon in the 65–74 age group in both genders (7).
Yıldız et al. reported that eczematous dermatitis was
the most common disorder seen in elderly patients.
The elderly have increased sensitivity to allergens
and irritants because of a malfunctioning of theepidermal barrier (15). In this study, eczematous
dermatitis is the most frequently observed in spring.
Yaldız et al. reported that eczematous dermatitis
was the most common disease in their patientgroup, and it was more common in patients ages
65–75 years, in the winter, and in females (14).
Bacterial infections were observed in all
age groups, with a prevalence of 6%. Bacterial
infections were more common in females and in
the summer and autumn, but the difference was
not significant. The healing process can be delayedfor several reasons, including reduced blood flow,
compromised immunological function, thinningand dryness of the skin, related systemic disorders,
epidermal damage brought on by itching, anddiminished personal care, all of which contribute toinfections. In a previous study by Yıldız et al. (15),the prevalence of bacterial infections was 5.9 in the
study conducted by Yıldız et al. (15). The authors
reported that the prevalence of bacterial infections
was 7.3%, and they were observed in all age groups
and in both genders (17).
In this study, fungal infections were found tobe the third most common skin disorder in thisstudy. The frequency of these infections declinedwith age. They were more common in the summer
than in the other seasons. In this study, the female
patients had more fungal infections than the malepatients. However, in Yalçın et al., fungal infections
were found to be more common in males and in thesummer (17). In another study, similar to the study
conducted by Yalçın et al. the authers found thatthe fungal infections were more common in males(12). Yaldız et al. reported that fungal infections
were more common in males, in the summer, and217

2024; 27(2):211−219

in older patients (14). Humidity and temperature
may be the reasons for the increased prevalence of
fungal infections in the summer (12, 14, 17).
In this study, it was observed that the rate ofpremalignant and malignant diseases increased
gradually as patient age increased. Aging isaccompanied by an increasing prevalence ofmalign illnesses due to mutations, a decline in DNA
repair ability, and lifelong exposure to carcinogens
and sun exposure. Malign diseases are known to be
more common in male patients (14). In line with thisknowledge, in this study, more males than females
were affected by premalignant and malignant
diseases. However, a previous study found thatpremalignant and malignant skin diseases weremore common in females and people over the ageof 75 years (7).

REFERENCES
1.

Ansorge C, Miocic JM, Schauer F. Skin diseases in
hospitalized geriatrics: a 9-year analysis from a university dermatology center in Germany. Archives ofDermatological Research 2022;314(5):427-437. (DOI:
10.1007/s00403-021-02244-9)

2.

Darjani A, Mohtasham-Amiri Z, Mohammad
Amini K, Golchai J, Sadre-Eshkevari S, Alizade N.
Skin disorders among elder patients in a referral
center in Northern Iran (2011). Dermatol Res Pract.
2013;2013:193205. (DOI: 10.1155/2013/193205)

3.

Kumar D, Das A, Bandyopadhyay D, et al. Dermatoses in the elderly: clinico-demographic profile
of patients attending a tertiary care centre. Indian J Dermatol 2021;66(1):74-80. (DOI: 10.4103/ijd.
IJD_245_20)

4.

Turkish Statistical Institute (TURKSTAT). Life Tables, 2020–2022. . [Internet]. Accessed: 18.09.2023.
ID: 49726 Available from: https://data.tuik.gov.tr/
Bulten/Index?p=Life-Tables-2020-2022-49726

5.

Turkish Statistical Institute (TURKSTAT). Elderly
Statistics, 2022. [Internet]. Accessed: 17.03. 2023.
ID: 49667. Available from: https://data.tuik.gov.tr/
Bulten/Index?p=Elderly-Statistics-2022-49667

6.

Jindal R, Jain A, Roy S, Rawat SD, Bhardwaj N.
Skin disorders among geriatric population at a
tertiary care center in Uttarakhand. J Clin Diagn
Res. Research 2016;10(3):WC06-8. (DOI: 10.7860/
JCDR/2016/17015.7500)

7.

Aksoy Sarac G, Emeksiz MAC, Acar O, Nazlican E,
Tanacan E, Nayir T. Retrospective analysis of dermatological diseases in geriatric patients during dermatology outpatient department visits. Dermatol
Pract Concept. 2022;12(3):e2022145. (DOI: 10.5826/
dpc.1203a145)

8.

Uprety S, Paudel S, Thapa P. Pattern of skin diseases in geriatric population: our year-long experiencefrom Nepal. Indian Dermatol Online J. 2021 Nov
22;12(6):888-891. (DOI: 10.4103/idoj.IDOJ_65_21)

9.

Darjani A, Alizadeh N, Rafiei E, et al. Skin diseases
among the old age residents in a nursing home: a neglected problem. Dermatol Res Pract 2020:8849355.
Published 2020 Nov 5. (DOI: 10.1155/2020/8849355)

Limitations
This study has the following limitations. First of all,because of its retrospective design, the diagnoses
were taken from hospital record. Second, because
the study was conducted in a tertiary health care
hospital, the results cannot be generalized to all
populations. Third, although some patients had
more than one complaint, only the complaint basedon which they were admitted to the hospital wasassessed.

CONCLUSIONAs the percentage of geriatric patients is increases,
special attention should be paid to this age group.
Fortunately, the majority of frequent illnesses among
the elderly are not life-threatening, and they arepreventable. This study fovused on dermatologicalconditions in the elderly. Further epidemiologicalstudies are needed to assess the prevalence ofskin diseases, skin care, treatment, and prevention
strategies for skin disorders in geriatric patients.
218

10. Blume-Peytavi U, Kottner J, Sterry W, et al. Age-associated skin conditions and diseases: current perspectives and future options. Gerontologist 2016;56
Suppl 2:S230-42. (DOI: 10.1093/geront/gnw003)

THE PREVALENCE OF SKIN DISEASES AMONG THE ELDERLY PATIENTS APPLYING A TERTIARY
DERMATOLOGY OUTPATIENT CLINIC: A RETROSPECTIVE ANALYSIS OF 2.400 PATIENTS.

11. Kandwal M, Jindal R, Chauhan P, Roy S. Skin diseases in geriatrics and their effect on the quality of life:
a hospital-based observational study. J Family Med
Prim Care. 2020;9(3):1453-1458. (DOI: 10.4103/jfmpc.
jfmpc_1188_19)

16. Bilgili SG, Karadag AS, Ozkol HU, Calka O, Akdeniz N. The prevalence of skin diseases among geriatric patients in Eastern Turkey. J Pak Med Assoc.
2012;62(6):535-539. PMID: 22755334.

12. Kilic A, Gul U, Aslan E, Soylu S. Dermatologicalfindings in the senior population of nursing homes
in Turkey. Arch Gerontol Geriatr. 2008;47(1):93-98.
(DOI: 10.1016/j.archger.2007.07.007)

17. Yalcin B, Tamer E, Toy GG, Oztaş P, Hayran M, Alli
N. The prevalence of skin diseases in the elderly: analysis of 4099 geriatric patients. Int J Dermatol. 2006;45(6):672-676. (DOI: 10.1111/j.13654632.2005.02607.x)

13. Polat M, Yalcin B, Caliskan D, Alli N. Complete dermatological examination in the elderly: an exploratory study from an outpatient clinic in Turkey. Gerontology 2009;55(1):58-63. (DOI: 10.1159/000129683)

18. Polat M, Ilhan MN. Dermatological complaints of theelderly attending a dermatology outpatient clinic inturkey: a prospective study over a one-year period.
Acta Dermatovenerol Croat. 2015;23(4):277-281.

14. Yaldiz M. Dermatological diseases in the geriatricage group: Retrospective analysis of 7092 patients.
Geriatr Gerontol Int. 2019 Jul;19(7):582-585. (DOI:
10.1111/ggi.13665)

19. Bas Y, Kalkan G, Seckin HY, Takci Z, Sahin S, Demir
AK. Analysis of dermatologic problems in geriatricpatients. Turk J Dermatol. 2014;8(2):95-100. (DOI:
10.4274/tdd.1905)

15. Yıldız H. Prevalence of geriatric dermatoses among
elderly patients treated at the dermatology outpatient clinic in Eskisehir, Turkey. South. Clin. Ist. Euras.
2019;30(1):47-51 (DOI: 10.14744/scie.2019.46855)

219

ORIGINAL ARTICLE

Turkish Journal of Geriatrics
DOI: 10.29400/tjgeri.2024.395
2024; 27(2):220−228
 Ezgi CAN1. . . . . . . . . . . . . . . . . . . . . . .
 Gökhan YILDIZ1 . . . . . . . . . . . . . . . . . .

 Ömer Taylan AKKAYA1. . . . . . . . . . . . .
 Rasime Pelin KAVAK2. . . . . . . . . . . . . .

 Gevher Rabia GENÇ PERDECİOĞLU1. 
 Damla YÜRÜK1 . . . . . . . . . . . . . . . . . .

 Hüseyin Alp ALPTEKİN1. . . . . . . . . . . .

CORRESPONDANCE
1Ezgi CAN

Phone
e-mail: +905348395016: ezgiacarcan89@gmail.com

Received : Apr 28, 2024
Accepted : Jun 12, 2024

COMPARISON OF THE EFFICACY OF
LUMBAR ERECTOR SPINAE PLANE BLOCKFOR CHRONIC AXIAL LOW BACK PAIN INGERIATRIC AND YOUNGER PATIENTS:
RESULTS OF A RETROSPECTIVE STUDY

ABSTRACTIntroduction: The lumbar erector spinae plane block is one of theinterventional procedures for chronic low back pain. This study aimed tocompare the efficacy of lumbar erector spinae plane block for chronic axial lowback pain due to disc protrusion/bulging in geriatric and younger patients andto evaluate clinical, demographic, and radiological characteristics that may be
associated with treatment success.
Materials and Method: The clinical and demographic data of patients who
underwent ultrasound-guided lumbar erector spinae plane block for chronic
axial low back pain between November 2022 and July 2023 were retrospectively
evaluated. Patients were divided into two groups, ≥65 and <65 years of age,and treatment efficacy at the third month after the procedure was evaluatedand compared.
Results: A total of 147 patients (75 patients aged <65 years and 72 patients
aged ≥65 years) were included in the analysis, and a successful treatment
response (at least 50% pain relief) was achieved in 44.4% of geriatric patientsand 62.6% of younger patients (p=0.027). In addition BMI, comorbidity, opioiduse, and lumbar paraspinal fatty infiltration were significantly higher in geriatricpatients than in younger patients (p<0.05).
Conclusion: The results of this study demonstrate that lumbar erector spinae
plane block for chronic axial low back pain provides significantly less pain relief
in geriatric patients than in younger patients at three-month follow-up.

1 Ankara Etlik City Hospital, Algology,

Keywords: Lower back pain; Aged; Injection; Ultrasound imaging

Ankara, Turkey

2 Ankara Etlik City Hospital, Radiology,

Ankara, Turkey

220

COMPARISON OF THE EFFICACY OF LUMBAR ERECTOR SPINAE PLANE BLOCK FOR CHRONIC AXIAL
LOW BACK PAIN IN GERIATRIC AND YOUNGER PATIENTS: RESULTS OF A RETROSPECTIVE STUDYINTRODUCTION
With a prevalence of 21-75%, chronic low back pain
(CLBP) is a common health problem in the geriatricpopulation, frequently leading to disability andfunctional impairment (1). While most cases of low
back pain resolve within a few months, advanced age
is a significant risk factor for chronic pain (1) Herniatedintervertebral discs, facet joint degeneration andspinal canal stenosis are the most common causes of
CLBP in elderly patients (2). Medical treatment andphysical therapy modalities are primarily employed
for these patients. Interventional pain procedures
and surgical treatment are required for patients who
do not respond to these modalities (3).
Lumbar erector spinae plane block (ESPB) is aneffective interventional pain procedure performed
under ultrasound (US) guidance in patients withaxial and/or radicular CLBP refractory to medical
and physical therapy (4). ESPB was first defined asa treatment technique for thoracic pain in 2016 andhas since been widely used for acute and chronic
spinal pain, including pain in the lumbar region (5).
US-guided lumbar ESPB involves injecting local
anesthetic (LA) around the paraspinal muscles
attached to the transverse process of the vertebrae.
This method is effective for pain treatment as the
drug spreads to the paravertebral planes and neuralforamens (6).
The structure of the lumbar paraspinal muscles
has a significant effect on the stability of the lumbar
spine, and increased fat infiltration in the paraspinal
muscles, which are the target sites of lumbar ESPB,
has been associated with sarcopenia, low back pain,
and loss of patient function (7, 8). Recent studies
have associated increased fat infiltration in the
lumbar paraspinal region with poor outcomes after
epidural injections and surgery (8, 9).
To the best of our knowledge, the effectivenessof lumbar ESPB in the treatment of chronic axial
LBP in geriatric patients compared with younger
patients has not been investigated, nor have thefactors influencing treatment success. This study
aimed to investigate the effectiveness of lumbar
ESPB in geriatric patients (≥65 years) comparedwith younger patients and to examine the impactof patient demographic and clinical characteristics,
including the degree of paraspinal fat infiltration,
on treatment success.

MATERIALS AND METHOD
Study design and participantsThis study, designed retrospectively, received
approval from the local ethics committee (number
2023-600) and registered at ClinicalTrials.gov(registration number NCT06208865). Medical
records were retrospectively retrieved and analyzed
from the hospital data of patients who underwent
US-guided lumbar ESPB for axial CLBP between
November 2022 and July 2023. The inclusion
criteria were as follows: (1) patients aged ≥ 18
years, (2) patients with chronic axial low back pain
due to lumbar disc bulging/protrusion withoutcompression of the spinal nerve root; (3) noresponse to medical treatment and physical therapy
for ≥ 3 months; (4) Lomber magnetic resonanceimaging (MRI) within 1 year before injection, (5)no previous lumbar interventional procedure and(6) no paravertebral lumbar facet tenderness andno neurological deficit on examination (patients
without sensory/motor deficit, deep tendon reflex
abnormality). The exclusion criteria were as follows:(1) clinically and radiologically (patients whose
MRI images or reports could not be accessedfrom patient records) inadequate medical records;(2) lost to follow-up within three months after theprocedure; (3) history of surgery for lumbar discherniation or interventional procedure; (4) severe
spinal stenosis (vertebral canal diameter <10 mmin the sagittal plane) and/or foraminal stenosis(foraminal height <15 mm in the axial plane); (5)extruded, sequestered, or migrated hernias on
lumbar MRI, (6) facet hypertrophy on lumbar MRI
221

2024; 27(2):220−228(7) radicular low back pain, (8) paravertebral lumbar
facet tenderness and neurological examination
findings such as sensory/motor deficit, deep tendon
reflex abnormality and (8) history of malignancy.

processes of the lumbar vertebrae which are theattachment sites of the paraspinal muscles (erector
spinae muscle group), a 22-gauge spinal needle
was inserted into the transverse process of the L3
vertebra using the in-plane method (Figure 1). After

Lumbar erector spinae plane block (ESPB)

contacting the transverse process of the L3 vertebra,

All procedures were performed under US guidance.
The patient was placed in the prone position andsterile conditions ensured. The intervention was
performed by two pain specialists with similar
experience of at least three years.

10 mL of drug containing 2 mL dexamethasone,

A 2-6 MHz convex US probe (LOGIQ P9,
GEUltrasound,
Sunhwan-ro,
Jungwon-gu,
Seongnamsi, Gyeonggi-do, Korea) was used during
the procedure. After visualizing the transverse

was performed on the side with the predominant

4 mL 0.025% bupivacaine, and 4 mL saline wasinjected. Lumbar ESPB was performed unilaterally
in all patients using this method and drug volume.
In patients with bilateral axial pain, the procedure
pain. The patients were followed up for possible
adverse events, and no adverse events occurred inany of the patients.

Figure 1. The ultrasound section shows the visualization of the transverse process and needle in lumbar erector spinae
plane block

222

COMPARISON OF THE EFFICACY OF LUMBAR ERECTOR SPINAE PLANE BLOCK FOR CHRONIC AXIAL
LOW BACK PAIN IN GERIATRIC AND YOUNGER PATIENTS: RESULTS OF A RETROSPECTIVE STUDY

Data collection and outcome measures
The intensity of the pain was assessed using a
numerical rating scale (NRS) both before and onemonth and three-months after the treatments. The
NRS is defined as ranging from 0 (no pain) to 10(the worst pain imaginable). Consistent with similar
studies (10), treatment was considered successful
in one patient who experienced a ≥50% reductionin the NRS score at three months post-treatment.
Patients were divided into two age groups, < 65years and ≥ 65 years, and analyzed appropriately.

Figure 2. Bilateral paraspinal muscles were assessed for
fat infiltration on T2-weighted axial sections
at the L3 level. The Goutallier grading was
defined as follows: (a) Goutallier 0, no visible
fat streaks; (b) Goutallier 1, minimal fat
streaks; (c) Goutallier 2, more muscle thanfat; (d) Goutallier 3, equal fat and muscle; (e)Goutallier 4, more fat than muscle.

In addition, demographic data such as gender,
comorbidities (diabetes mellitus (DM), hypertension(HT) and coronary artery disease (CAD)), body massindex (BMI)kg/m2), pain duration and opioid use
were obtained from patient data. NRS scores before
and 3 months after the lomber ESPB were collectedfrom patient data and recorded. Pre-procedure
lumbar magnetic resonance images were obtained
from the patient’s data. Lumbar pathologies causing
chronic axial low back pain (lumbar disc bulging/protrusion without spinal nerve root compression)
was evaluated by a experienced radiologist. Fat
infiltration in the paraspinal muscles was evaluatedat the L3 vertebral level. Paraspinal fatty infiltration
was evaluated using T2-weighted MRI scan,
employing methodologies established in previously
published studies, and the Goutallier classification
was used for grading (11). The grading of fatty
infiltration in the paraspinal muscles on a lumbar MRI
was performed by a experienced radiologist. As weapplied lumbar EPSB at the L3 level, we preferredto perform MRI evaluation at the same level. The
Goutallier Classification is defined as follows: The
Goutallier classification system assesses the amountof fat present in the muscle. Goutallier 0 indicates novisible fat streaks, Goutallier 1 indicates minimum
fat streaks, Goutallier 2 indicates more muscle thanfat, Goutallier 3 indicates equivalent amounts offat and muscle, and Goutallier 4 indicates more fat
than muscle (Fig 2).

223

2024; 27(2):220−228

Statistical analysis
All analyses were conducted using the Jamovi project(2022, Jamovi Version 2.3, Computer Software). The
findings of this study are expressed as frequencies
and percentages. Normality analysis was performed
using the Shapiro–Wilk test, skewness-kurtosis, andhistograms. Categorical variables were presented
as absolute numbers with percentages. Continuous
variables were compared between age groups using
the Mann–Whitney U-test and Kruskal–Wallis H-test
and were presented as medians with interquartile
ranges. Categorical variables were compared using
the chi-square test or Fisher’s exact test. Statisticalsignificance was set at P < 0.05.

RESULTSA total of 196 patients underwent US-guided lumbar
ESPB during the study period, and 49 patients were
excluded in line with the exclusion criteria. There
were 147 patients in the analysis between the agesof 20 between 77 years, including 75 patients aged
<65 years and 72 patients aged ≥65 years. The
treatment response at the post-procedural third
month was successful in 62.6% of patients aged
<65 years and 44.4% of patients aged ≥ 65 years(Fig 3) and the difference was statistically significant(p=0.027). The comparison of the NRS changes
at basal and at the first and third month after theprocedure is shown in Fig. 4.
Figure 3. Study design
and follow-up

224

COMPARISON OF THE EFFICACY OF LUMBAR ERECTOR SPINAE PLANE BLOCK FOR CHRONIC AXIAL
LOW BACK PAIN IN GERIATRIC AND YOUNGER PATIENTS: RESULTS OF A RETROSPECTIVE STUDY

Figure 4. Comparison of the effect of time on NRS in geriatric and younger patients

Table 1. Baseline demographic and clinical characteristics according to age groups (<65 years and ≥65 years)
Variables
BMI (kg/m2)<65 years (n=75)≥65 years (n=72)

median(min-max)

median(min-max)

27(19-37)

29(19-37)

p-value
0.002*

Basal NRS

7(6-9)

8(5-9)

0.020*

Three-month NRS

3(1-9)

5(1-9)

0.030*

24(4-120)

27(4-120)0.988*
p-value

Duration of pain (months)

Sex
Successful treatment
responce
Comorbid medical disease
Opioid use
Fat infiltration grade(Goutallier Classification)

n(%)

n(%)

Female36 (44.4)

45 (55.6)

Male

39 (59.1)

27 (40.9)

Yes

47 (59.4)

32 (40.6)

No

28 (41.1)

40 (58.6)

Yes

14 (21.5)

51 (78.5)

No

61 (75.3)

21 (24.7)

Yes

17 (33.3)

34 (66.7)

No

58 (60.4)

38 (39.6)

Mild (Grade 0,1)

56 (83.5)

11 (16.5)

Moderate(Grade 2 )

12 (29.2)

29 (70.8)

Severe (Grade 3,4)

7 (17.9)32 (82.1)

0.077**
0.027**<0.001**0.003**<0.001**

BMI: Body mass index, NRS: numerical rating scale, *: Mann Whitney U Test,**: Chi Square Test
The values are presented as median (minimum-maximum) and numbers of patients. P values that are written in bold represent statistical. P<0.05
is considered statistically significant

2252024; 27(2):220−228

Table 1 presents the basic demographic
and clinical characteristics and the degree ofparaspinal fatty infiltration, for each patient groupcategorized by age. Successful treatment response
was significantly lower in the geriatric patients(p=0.027). The baseline NRS scores were high inboth age groups (<65 and ≥65 years; median scoresof 7 and 8, respectively), indicating severe pain, andboth the baseline and three-month NRS scores
were significantly higher in the geriatric group(p=0.020 and p=0.030, respectively). The patients
aged ≥65 years had significantly higher BMI values
and more comorbid medical diseases (diabetes
mellitus, hypertension, and coronary artery disease)than the younger patients (p=0.002 and p<0.001,
respectively). The patients in the geriatric groupused more opioids (p=0.003), and the grade ofparaspinal fat infiltration, determined according to
the Goutallier classification at the L3 level on lumbar
MRI, was significantly higher in these patients(p<0.001). Sex (gender), and pain duration weresimilar between the patient groups (p>0.05)

DISCUSSION
In this study, we found significantly less pain relief
with lumbar ESPB for chronic axial low back pain
due to lumbar disc bulging/protrusion in geriatricpatients than in younger patients. Geriatric patients
also have higher BMI, comorbidity, pain severity,
opioid use, and degree of lumbar paraspinal fat
infiltration compared to younger patients. There islimited information in the literature regarding theoutcomes of geriatric patients undergoing lumbar
ESPB and these clinical characteristics.
In ESPB, LA applied to the erector spinae planeand multifidus muscle groups (paraspinal muscles)
can reach the craniocaudal region, paravertebral
muscles, and neural foramen (6). Therefore, lumbar
ESPB is a suitable interventional procedure forthe treatment of CLBP. In a study by Durmus etal., lumbar ESPB was applied to 96 patients with
CLBP aged 25–79 years, and a significant decrease226

in pain scores was reported in the first month (4).
Another study found that patients who underwent
lumbar ESPB before and one month after lumbar
disc surgery had significantly less persistent low
back pain in the sixth postoperative month than thepatients who did not undergo lumbar ESPB (12). In
our study, 147 patients aged 20–77 years with chronic
axial LBP underwent US-guided lumbar ESPB;
62.6% of the patients aged <65 years and 44.4% of
the patients aged ≥65 years showed a significant
reduction in their third-month pain scores. Our
study is the first to investigate the effectiveness oflumbar ESPB in older patients compared to younger
patients. Treatment success was significantly lower
in the geriatric patients (p=0.027).
With aging, the number and size of muscle fibers
decrease, and resulting in loss of muscle mass.
Sarcopenia is characterized by age-related decreases
in muscle strength and physical performance andis common in geriatric patients. This leads to lossof mobility and increases the risk of mortality (13).
Sarcopenia is thought to develop through various
mechanisms, including mitochondrial dysfunction,
protein imbalance, and motor neuron loss (14).
When our patients were analyzed according to age
group, the presence of paraspinal fat infiltration, in
addition to advancing age, which may facilitate thedevelopment of sarcopenia, was significantly higher
in the patient group aged ≥65 years. Similarly,
studies of patients undergoing lumbar epiduralsteroid injections for CLBP have reported thatyounger patients had more successful pain relief(8, 15). The lumbar paraspinal muscles consist of
the multifidus, erector spinae, and psoas muscles,
and their integrity ensures normal spinal function,alignment, and stability (9). Paraspinal muscles
contain a high proportion of type 1 fibers, which
help maintain posture and joint stability owing totheir low tonicity and resistance to fatigue (16). Fatty
infiltration of these muscles is a sign of atrophy andthus sarcopenia, and has been associated withlow back pain (7). Several studies have examined

COMPARISON OF THE EFFICACY OF LUMBAR ERECTOR SPINAE PLANE BLOCK FOR CHRONIC AXIAL
LOW BACK PAIN IN GERIATRIC AND YOUNGER PATIENTS: RESULTS OF A RETROSPECTIVE STUDYchanges in the paraspinal muscles with age inhealthy adults and have found that fat infiltration
increases with age (17-19). Studies have shown that
increased paraspinal fat infiltration is associatedwith loss of muscle strength, poor functioning,
and reduced mobility (16, 17). Dahloqvist et al.
studied fat replacement in the paraspinal and lower
limb muscles of healthy adults and found that theparaspinal muscles had significantly higher mean
fat content and increased fat replacement withaging than the lower limb muscles (20). Similarly,
previous research has investigated the effect ofparaspinal fat infiltration on the efficacy of lumbar
and cervical interventional pain treatment. Kim etal. performed fluoroscopy-guided lumbar epiduralsteroid injections in 245 patients aged ≥65 years
with low back pain and found that severe paraspinal
fat infiltration was associated with poor treatment
outcomes (8). The relationship between the degreeof paraspinal fat infiltration and treatment response
has also been evaluated for lumbar disc surgery,and increased fat infiltration in the erector spinae
muscles has been found to be associated with poor
clinical outcomes following lumbar discectomy (9).
In our study, we found that paraspinal fat infiltrationin older patients (≥65 years) was significantly
higher than that in younger patients (<65 years),consistent with existing findings. This supports thephysiopathological evidence that aging reduces
skeletal muscle mass and replaces it with fat andconnective tissue (21).
In this study, BMI was significantly higher inthe ≥65 years age group (p=0.002). In addition,
comorbidities, such as diabetes mellitus,
hypertension, and coronary artery disease, weresignificantly more common in the patients aged ≥65
years than in the younger patients (p<0.001). Thismay be related to the increased risk of comorbidities
and metabolic syndrome with advancing age,increased sedantary life, less exercise, and increased
sarcopenia due to these factors. In addition,
opioid use was significantly higher in the geriatricpatients (p=0.003). A recent study found a negative
association between the analgesic efficacy of lumbar
epidural steroid injections in geriatric patients andpre-injection opioid use at three months, but it isunclear whether opioid use affects the long-term
analgesic efficacy of the procedure (8).
This study had several limitations. First, ourstudy was retrospectively designed, and NRS scores
three months after injection were available, so it
does not fully reflect the patients’ long-term clinicaloutcomes. In addition, no clinical data on disability,
opioid use, or quality of life were available fromthe patient records. In addition, the degree of fatty
infiltration in the paraspinal muscles was assessed
only in a single multifidus muscle at the L3 level,
making it impossible to draw conclusions about thedegeneration of other lumbar muscles.

CONCLUSION
This study demonstrated that US-guided lumbar
ESPB for chronic axial LBP due to lumbar discbulging/protrusion is less successful in geriatricpatients than in younger patients. Geriatric patientswere found to have significantly higher levels ofhigh-grade paraspinal fat infiltration associatedwith sarcopenia and clinical features such as high
BMI, comorbidity, opioid use and high disease
severity than younger patients. This is the first study
to evaluate the effectiveness of lumbar ESPB in
geriatric patients, and the clinical, demographic
and radiological characteristics associated withtreatment success. Prospective evaluation withlarger participants and longer follow-up is needed
to assess the long-term outcomes in geriatricpatients and their associated factors.
Acknowledgements: None
Conflicts of Interest: All the authors have noconflicts of interest.
Data Availability Statement: The data that
support the findings of this study are available fromthe corresponding author upon reasonable request.

227

2024; 27(2):220−228

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Turkish Journal of Geriatrics
2024; 27(2)FROM THE EDITOR IN CHIEF
Yeşim GÖKÇE KUTSAL

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