Nutrition Therapy in Chronic Kidney Patients
Original
Effectiveness of Medical Nutrition Therapy in Improving Prognostic Nutritional Index
Scoring among Dietitian Referred Chronic Kidney Patients: A Retrospective Study at
Hospital Kuala Lumpur, Malaysia
Jayvikramjit Singh1, Basmawati Baharom1, Zamtira Seman2, Lye Sing Ie1, Nor Fazlyn Zakaria1
1

Department of Dietetics and Food Service, Hospital Kuala Lumpur, Malaysia
2
National Institutes of Health, Selangor, Malaysia

ABSTRACT
Background and purpose: The prognostic nutritional index (PNI) is a simple assessment
tool to determine the nutritional status of patients. The purpose of this study was to assess
the effectiveness of MNT in improving PNI scoring among chronic kidney patients.
Methods: This retrospective study used data of patients seen by Dietitians in 2022.
Descriptive analysis was used to describe patient characteristics, prevalence of CKD
patients and PNI scoring. Analysis of PNI towards factor and parameter associated was doneusing Generalized Estimating Equation (GEE). A p-value of < 0.05 was set as the cutoff forstatistical significance.
Results: There were significant association (p<0.05) for variables such as PNI,
hemoglobin, total protein, albumin and urea. There was also positive improvement for PNI
scoring, hemoglobin, total protein, albumin. There was also reduction in urea, potassium,
phosphate, uric acid, fasting blood sugar and total cholesterol among referred patients todietitian. Significant association of PNI with hypercholesterolemia (p=0.017), albumin(p=0.003), total protein (p=0.003), creatinine (p=0.01), phosphate (p<0.001), uric acid
(p=0.043) and eGFR (p=0.013) among patients referred to dietitian. No significant
association was noted between BMI and PNI.
Conclusion: Results of current study suggests that medical nutrition therapy is an
important aspect of management for chronic kidney patients. Patients with improved PNIscoring which were seen by dietitian showed better nutritional status compared to thosepatients who did not receive dietary consultations from dietitians. Further study with large
coverage may give a concrete or better results in future
Keywords: Prognostic Nutritional Index, Chronic Kidney Disease, End Stage Kidney
Disease, Low Protein Diet, Medical Nutrition Therapy
INTRODUCTION
The prognostic nutritional index (PNI) is a simple
assessment tool to determine the nutritional status ofpatients (1). It is calculated by combining serum
albumin levels and total lymphocyte counts, which
are two indicators of nutritional status or malnutrition
and immune function (2). PNI has been shown to bea useful tool in predicting mortality among many
populations, including end stage renal patients on
dialysis (3).
A study published in the Journal of Renal Nutritionin 2021 investigated the prognostic value of PNI in
predicting mortality in 671 hemodialysis patientswith CKD (4). The study found that lower PNI
values were associated with higher mortality rates,
even after adjusting for other factors such as age,sex, and comorbidities (4). Similarly, a study
published in the Journal of Cachexia, Sarcopenia
and Muscle in 2020 found that PNI was asignificant predictor of mortality among Chronic
Kidney Disease (CKD) patients undergoinghemodialysis (5). The study also found that PNI
was more accurate than other nutritional indicessuch as the geriatric nutritional risk index and thecontrolling nutritional status score (5).
PNI has also been also researched among
peritoneal dialysis patients. A study conducted by
Sijia et al concluded that low PNI levels wereindependently associated with the first occurrenceof pneumonia in PD patients (6-8). PNI was anindependent predictor of new-onset pneumonia in
PD patients (6-8).

*To whom correspondence should be addressed:jayvikramjit@yahoo.co.uk

PNI has been also used as a prognostic tool among
diabetic nephropathy patients. This study aimed at
the long-term effects of prognostic nutritional index(PNI) on renal outcomes in patients with diabetic
nephropathy (DN) and type 2 diabetes mellitus (9-10).

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Asian Journal of Dietetics, 2024
Results from this study proved that PNI correlatedwith eGFR and glomerular injury and was anindependent predictor for DN progression in patientswith T2DM (9-10).

Specific Objectives
To determine the effectiveness of Medical
Nutrition Therapy (MNT) in improving patients’nutritional status
To determine the association between Prognostic
Nutritional Index (PNI) and clinical outcomes(nutritional status and renal function) in patientswith Chronic Kidney Disease (CKD) receiving
dietary counselling.
MATERIALS AND METHODSThis study might help to strengthen the PNI as tool
to determine as a strong prognostic tool for CKD
patients. PNI is a simple tool that can be used todetermine nutritional status of CKD patients. Since
it is easy to use and only requires two variables(albumin and lymphocytes level) to calculatemalnutrition status of CKD patients, it will enableclinicians to better diagnose malnutrition among
CKD patients.

Study Type and Design
This was a retrospective study that was conductedat Hospital Kuala Lumpur. This study used
Malaysian Dietetics Care Notes (DCN) which isthe standard documentation form used by
Dietitians. Sample size targeted for this study was
352 patients. Chronic Kidney Disease patients at
Nephrology outpatient clinic referred to Dietitianand patients not referred to Dietitian from 1st
January 2022 until 31st December 2022 were
included in this study. A minimum of at least two
follow up by dietitian was required for analysis
purposes. The end point of the study was theaccuracy of PNI in determining nutritional statusof CKD patients. Flow chart of this study is
explained as below.

Medical nutrition therapy (MNT) has been provenin effectively improving CKD patients’ nutritional
status (11). However, research on effectiveness of
MNT improving patients PNI scoring among CKD
patients has not done before in Malaysia. We hope
the results of this study will help dietitians andother healthcare personnel to use PNI as adiagnostic tool for better patient outcome in termsof improving nutritional status and patient care.
Objective
General Objective
To assess the effectiveness of MNT in improving
PNI scoring among CKD patients

Identify patientsin inclusion
criteria from DCN

Extraction of data

Data entry into
SPSS

Publication offindings

Presentation ofresearch output

Data cleaning anddata analysis

Figure 1: Flow chart for data collection
Study Tool

from DCN. Laboratory test results was obtained fromLab Information System (LIS) at Nephrology Clinic,
Hospital Kuala Lumpur, Malaysia. All information
included demographic data such as age, gender,
ethnicity, medical history such as hypertension,
diabetes, heart disease, examination data such as

This study used PNI scoring as a nutritional tool. The
PNI was calculated by 5×lymphocyte count (109 /L)+serum albumin (g/L) in this study. Scoring for PNI
was determined by low (<40), moderate (40-45), high>45. Clinical information of patients was collected32

Nutrition Therapy in Chronic Kidney Patientsweight, height, blood pressure, laboratory data suchas serum creatinine, blood urea nitrogen, total serum
uric acid, total cholesterol, HbA1c, fasting blood
sugar, proteinuria.

•

Study Visits and Procedures
The data of concern involved outpatient patients seen
by Dietitian and not seen by Dietitian at Outpatient
Nephrology Clinic from 1st January 2022 until 31st
December 2022. These data were retrieved fromcopies of Dietetic Care Notes (DCN) which wasstored at Dietetic Clinical Store Office. The days ofreferral and follow ups were within the stipulated
time of 1st January 2022 until 31st December 2022.
Dietitians of Hospital Kuala Lumpur retrieved thedata from Dietetic Clinical Store Office and Lab
Information System (LIS) and entered the variablesof concern into SPSS for further analysis. These datacollection period commenced from 1st January 2024
until 31st January 2024.

Medical nutrition therapy based on The National
Kidney Foundation’s Kidney Disease Outcomes
Quality Initiative (KDOQI) Guidelines 2020 was
given to patients that were referred to dietitian (12).
Patients were given a diet comprised of 1) dietary
protein intake of 0.6 to 0.8 g/kg/day from 50% plantbased sources, 2) fiber intake of 25 g/day, 3) lowsodium intake of less than 5 g/d and 4) adequate
caloric intake of 30 to 35 kcal/kg/day. If patient has a
co-morbidity of diabetes and other form of noncommunicable diseases, the MNT shall be
individualized according to the patient’s diseases.
Study Population & Sampling Method

Statistical Analysis

This was a simple random sampling that referred toeligible patients (chronic kidney disease patients)
referred and seen by Dietitian as well as patients notreferred to Dietitians from 1st January 2022 until 31st
December 2022.

The Statistical Package for the Social Sciences (SPSS,
IBM, Chicago, IL) version 26 was utilized for data
analysis. Continuous variables were assessed fornormality using the Kolmogorov-Smirnov test.
Normally distributed variables were presented asmean ± standard deviation and compared using t-tests
or one-way analysis of variance (ANOVA). Nonparametric variables were presented as median(interquartile range) and compared using the MannWhitney or Kruskal-Wallis test. In cases where
significant differences were observed in ANOVA or
Kruskal-Wallis test, post-hoc Tukey comparison or
Bonferroni correction was employed.

Inclusion Criteriaa)All patients referred to dietitian by medical
officers/nephrologistsb) Aged 18 years and abovec) Available PNI values (albumin andlymphocytes count)d) Complete medical recordse) Patients with follow up at least 1 year

Categorical variables were presented as counts andpercentages and analyzed using Pearson's chisquared test or Fisher's exact test. The strength of therelationship between variables was assessed using
Pearson's bi variate correlation. Kaplan-Meier andCox-regression was used to estimate diseaseprogression. A significance level of p < 0.05 was used
to determine statistical significance.

Exclusion Criteriaa)Patients with a history of cancer, autoimmune
diseases, or chronic infections.
b) Missing datac) Patients with end stage renal disease at baselined) Deaths
Withdrawal Criteria

Risk and benefit to study participants

Not applicable

There were no risk and benefit to the participants as
this was a retrospective study which did not involve
direct contact with any patient.

Sample Size
We used G*Power version 3.1.9.4 to determine therequired sample size for detecting an improvement in
PNI scoring with a medium effect size of 0.3, asignificance level of 5%, and a power of 80%, thisstudy required sample 176 per arm. The two arms
were referring to patients referred to dietitians andpatients not referred to dietitians. Total patients forboth required arms were 352 patients. As no
information on effect size was available for thisparticular factor, we chose to use Cohen's guidelines
for effect size interpretation to determine the target
effect size.

Risk Benefit Assessment
Assessment using PNI should be considered to treat
malnutrition which might lead to significant
improvement in relation to treating and improving
nutritional status of CKD patients. The results of thisstudy may help clinicians identify patients with low
PNI scores and improve their clinical outcome.
Clinicians will be able to accurately identify the
impact of PNI scoring on patient nutritional outcome.
Results from this study will enable Dietitians tofurther strengthen the usage of PNI as a prognostic
tool for treating malnutrition.

Study Duration and Timeline••

Stage 3, presentation and publication - 2 months

Stage 1, proposal development - 1 monthStage 2, data collection and data analysis - 2
months

Ethics of Study

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Asian Journal of Dietetics, 2024
Ethical approval was needed from the Medical
Research and Ethics Committee, Ministry of Health
Malaysia. This research was registered with National
Medical Research Register (NMRR), Malaysia under
the registration identification number of NMRR ID23-03077-3ZW.

Privacy and Confidentiality
Subject’s names were kept on a password-protected
database and were linked only with a study
identification number for this research. The
identification number instead of patient identifiers
was used on subject data sheets. All data were enteredinto a computer that was password protected. On
completion of study, data in the computer was copied
to thumb drives and the data in the computer erased.
Thumb drives and any hard copy data were stored ina locked office of the investigators and maintained fora minimum of three years after the completion of thestudy. The thumb drives and data will be destroyed
after that period of storage. Study will not be sharedwith any third party.

Ethical approval was obtained from other relevant
approvals prior to the start of any study related
activities. The study was performed in compliancewith the principles of the Declaration of Helsinki, in
accordance with the International Conference ofHarmonization Guideline for Good Clinical Practice,and in accordance with applicable regulatory
requirements.
Informed Consent/Assent Process

Termination of Study

Waiver of consent was requested and was granted by
Medical Research and Ethics Committee (MREC) inview of retrospective study and no patient/participant
contacts.

Not applicable

RESULTS
Table 1: Patient characteristics stratified by Dietitian Referred (N=300)
Dietitian Referred
Variable
Yes
No
Total

p-value

GenderEthnicity

FemaleMale

Malay
ChineseIndianOthersDiabetes mellitus
Yes
No
Hypertension
Yes
No
Hypercholesterolemia
Yes
No
Heart DiseaseYes
No
BMI category
Underweight
NormalOverweight
ObeseaChi Square, bExacts

73 (50)77 (50)73 (50)77 (50)146
154>0.999a93 (48.7)
34 (51.5)
21 (51.2)
2 (100)98 (51.3)
32 (48.5)
20 (48.8)
0 (0)

191
66
41
2

0.393b108 (56.5)
42 (38.5)

83 (43.5)
67 (61.5)191
109

0.003a131 (51.6)
19 (41.3)

123 (48.4)
27 (58.7)254
460.200a81 (48.5)
69 (51.9)

86 (51.5)
64 (48.1)

167
133

0.561a25 (52.1)
125 (49.6)

23 (47.9)
127 (50.4)

48252

0.753a7 (70)
41 (53.2)
47 (50.5)
46 (68.7)

3 (30)
36 (46.8)
46 (49.5)
21 (31.3)

10
77
93
67

0.092a34

Nutrition Therapy in Chronic Kidney Patients
Table 2: Parameter changes for overall patients and stratified by dietitian referred.

Table 3: Analysis of PNI towards factor and parameter associated using Generalized Estimating Equation(GEE)
Overall
Referred
Not-Referred
Variableβ (95%CI)
p-valueβ (95%CI)
p-valueβ (95%CI)
p-value
Dietitian0.52 (-0.54,
Referred
0.336
1.58)
Not referred
1
Gender
-1.01 (-2.07,-0.74 (-2.24,-1.28 (-2.77,
Female
0.061
0.334
0.090
0.05)
0.76)
0.20)
Male
1
1
1
Ethnicity
0.53 (-0.70,-0.47 (-2.31,
1.11 (-2.30,
Malay
0.398
0.620
0.523
1.75)
1.38)
4.52)
0.59 (-1.39,
0.10 (-1.93,
Indian
0.561
0.924
2.57)
2.13)
1.78 (0.56,
0.83 (-0.83,
1.58 (0.05,
Others
0.004
0.328
0.043
3.01)
2.50)
3.11)
Chinese1
1
1
Diabetes mellitus-1.00 (-2.07,-1.00 (-2.67,-1.23 (-2.69,
Yes
0.068
0.243
0.099
0.07)
0.68)
0.23)
No
1
1
1
Hypertension-1.49 (-3.12,-2.45 (-5.49,-0.88 (-2.62,
Yes
0.074
0.115
0.322
0.14)
0.59)
0.86)
No
1
1
1
Hypercholesterolemia-0.48 (-1.58,-1.84 (-3.36,
0.95 (-0.62,
Yes
0.398
0.017
0.235
0.63)
-0.32)
2.51)
No
1
1
1
Heart disease0.03 (-1.42,
1.03 (-0.96,-1.07 (-3.05,
Yes
0.973
0.312
0.289
1.47)
3.01)
0.91)
No
1
1
1
Body Mass Index

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Asian Journal of Dietetics, 2024

Variable
Underweight
NormalOverweight
Obese
Age
Body Mass Index
Total Protein
Albumin
Urea
Creatinine
Potassium
Phosphate
Uric Acid
Fasting Blood Sugar
HBA1C
EGFR
Total Cholesterol

Overallβ (95%CI)
p-value
1.19 (-2.40,
0.516
4.77)
0.16 (-1.55,
0.858
1.86)
0.83 (-0.85,
0.333
2.52)
1
0.01 (-0.04,
0.618
0.06)
-0.02 (-0.14,
0.751
0.10)
0.13 (0.06,<0.0010.20)
0.80 (0.69,<0.001
0.90)-0.09 (-0.22,
0.191
0.04)
-0.01 (-0.01,
0.007<-0.001)
0.49 (-0.08,
0.093
1.06)
-1.13 (-2.23, 0.046
0.02)
0.00 (-0.01,
0.214
0.00)
-0.12 (-0.26,
0.119
0.03)
0.19 (-0.61,
0.644
0.98)
0.03 (0.00,
0.025
0.06)
-0.26 (-0.61,
0.155
0.10)

Table 1 showed a total of 300 patients were finally
recruited after considering the inclusion andexclusion criteria. There was equal distribution of
respondents between gender (50%) with Malay
ethnicity being the majority (48.7%). Most
respondents had comorbidities such as diabetes(56.5%), hypertension (51.6%) and high cholesterol(48.5%). Most of the respondents were obese(68.7%).

Referredβ (95%CI)
p-value
0.05 (-4.52,
0.984
4.62)
0.67 (-1.28,
0.502
2.62)
0.92 (-1.07,
0.365
2.92)
1
-0.01 (-0.09,
0.798
0.07)
-0.04 (-0.19,
0.611
0.11)
0.17 (0.06,
0.003
0.27)
0.80 (0.67,<0.001
0.93)-0.09 (-0.25,
0.260
0.07)
-0.01 (-0.02,
0.010<-0.001)
0.24 (-0.58,
0.564
1.06)
-4.67 (-7.25,<0.001-2.08)-0.01 (-0.01,
0.043<-0.001)-0.05 (-0.18,
0.428
0.08)
0.93 (-0.65,
0.247
2.51)
0.05 (0.01,
0.013
0.09)
-0.29 (-0.75,
0.222
0.17)

Not-Referredβ (95%CI)
p-value
3.81 (-0.77,
0.103
8.38)
-0.14 (-3.58,
0.934
3.29)
1.06 (-2.33,
0.540
4.45)
1
0.02 (-0.04,
0.463
0.08)
0 (-0.2, 0.21)
0.11 (0.02,
0.21)
0.79 (0.64,
0.95)-0.16 (-0.30, 0.02)-0.01 (-0.01, <0.001)
0.73 (0.02,
1.43)
0.12 (-0.87,
1.12)
0.00 (0.00,
0.01)-0.36 (-0.82,
0.10)-0.11 (-1.10,
0.89)
0.03 (-0.02,
0.08)-0.22 (-0.76,
0.32)

0.970
0.023
<0.001
0.023
0.044
0.043
0.809
0.640
0.126
0.831
0.241
0.430

DISCUSSION
To the best of our knowledge, this is the first study
that has been done in Malaysia involving MNT and
its effect on improvement of PNI scoring. Besides
improvement of PNI scoring, clinical implications of
our findings is that delivery of MNT by Dietitians
showed improvement in chronic kidney disease andits related parameters such as fasting blood sugar,urea, total cholesterol and albumin.

Results from Table 2 showed significant association(p<0.05) for variables such as PNI, hemoglobin, total
protein, albumin and urea. There was positive
improvement for PNI scoring, hemoglobin, total
protein, albumin. There was also reduction in urea,
potassium, phosphate, uric acid, fasting blood sugar
and total cholesterol among referred patients todietitian.

Improvement of variables such as hemoglobin,
albumin, phosphate and total protein was very much
relayed to the adequate protein that was provided
during dietary counseling (12). A low protein diethelped improved and lower down the urea levels of
respondents (13,14). A plant dominant diet generally
reduces uremic levels in the body (12,13,14). The low
protein diet is beneficial, because they reduce theproduction of protein-derived waste products, theretention of protein-derived toxins and fixed acids,
lower single nephron glomerular hyper filtration andproteinuria, and reduce dietary phosphate load (15).
Since albumin levels had increased significantly, thismight had contributed to the improved scoring of PNI.

Results from Table 3 showed significant associationof PNI with hypercholesterolemia (p=0.017),
albumin (p=0.003), total protein (p=0.003),
creatinine (p=0.01), phosphate (p<0.001), uric acid
(p=0.043) and eGFR (p=0.013) among patientsreferred to dietitian. No significant association wasnoted between BMI and PNI.

36

Nutrition Therapy in Chronic Kidney Patients
Improvement of fasting blood sugar and totalcholesterol in general wad attributed by the adequate
fiber intake (13-14). This plant based diet helps toregulate lipids and achieve better glycemic control
among diabetic nephropathy patients (13-14). The
KDOQI 2020 guidelines also emphasized oninterventions using omega 3 and 6 fats for better lipid
control (12). A reduction of saturated fatty acids(SFA) and trans-fat intake contributes to a reduction
in risk of cardiovascular disease in patient which ispart of the KDOQI 2020 guidelines (12).

study and all the team members for their participationin this study.
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In CKD clinics, medical nutrition therapy (MNT)
should be emphasized and requires the same level ofimportance as pharmacological treatment (16). In thisstudy, we would like to highlight that MNT should bea cornerstone of the management of CKD as well asof other chronic diseases. Provision of MNT for predialysis patients has proven evidence of delaying theneed for dialysis (17,18). All patients regardless ofstages of chronic kidney disease should be referred todietitian for better disease management and patient
outcome.
Limitations of our study was that it has a small
sample size and it was a single center study. A
prospective intervention study with larger sample
size would yield stronger clinical results. The mainstrength of our study was that the results were similarand consistent with other studies that indicates theeffectiveness of MNT in patients’ nutritional status.
Future studies on effectiveness of PNI in
improvement of patient survival should beconsidered. A cohort study specially designed todetermine whether a high PNI scoring can delay theneed for dialysis or delay the progression of kidneydisease among Malaysian CKD patients.
Conclusion
Results of current study suggests that medical
nutrition therapy is an important aspect ofmanagement for chronic kidney patients. Patientswith improved PNI scoring showed better nutritional
status compared to those patients who did not receive
dietary consultations from dietitians. Further study
with large coverage may give a concrete or better
results in future.
Conflict of Interest
The investigators declared they had no conflict ofinterest
Publication Policy
No personal information was disclosed when thefindings of the survey were published. Manuscript
were submitted to National Institutes for Health,
Malaysia for Director General’s approval prior to any
publication and presentation.
ACKNOWLEDGMENT
The authors wish to thank the Director General of
Health Malaysia for his permission to publish this37

Asian Journal of Dietetics, 2024
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2020, 76, S1–S107.

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