# Incidence and Risk Factors for Postoperative Delirium in Patients Undergoing Spine Surgery: A Systematic Review and Meta-Analysis

Authors: Xinjie Wu; Wei Sun; Mingsheng Tan
Journal: BioMed Research International
 (2019)

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## Abstract

Background. The present study aims to investigate the incidence and risk factors associated with postoperative delirium in patients undergoing spine surgery. Methods. PubMed, EMBASE, Cochrane Library, and Science Citation Index were searched up to August 2019 for studies examining postoperative delirium following spine surgery. Incidence and risk factors associated with delirium were extracted. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for outcomes. The Newcastle–Ottawa Scale (NOS) was used for the study quality evaluation. Results. The final analysis includes a total of 40 studies. The pooled analysis reveals that incidence of delirium is 8%, and there are significant differences for developing delirium in age (OR 1.07; 95% CI 1.04–1.09), age more than 65 (OR 4.77; 95% CI 4.37–5.16), age more than 70 (OR 15.87; 95% CI 6.03–41.73), and age more than 80 (OR 1.91; 95% CI 1.78–2.03) years, male (OR 0.81; 95% CI 0.76–0.86), a history of alcohol abuse (OR 2.11; 95% CI 1.67–2.56), anxiety (OR 1.74; 95% CI 1.04–2.44), congestive heart failure (OR 1.4; 95% CI 1.21–1.6), depression (OR 2.5; 95% CI 1.52–3.49), hypertension (OR 1.12; 95% CI 1.04–1.2), kidney disease (OR 1.41; 95% CI 1.16–1.66), neurological disorder (OR 4.66; 95% CI 4.22–5.11), opioid use (OR 1.86; 95% CI 1.18–2.54), psychoses (OR 2.77; 95% CI 2.29–3.25), pulmonary disease (OR 1.81; 95% CI 1.27–2.35), higher mini-mental state examination (OR 0.7; 95% CI 0.5–0.89), preoperative pain (OR 1.88; 95% CI 1.11–2.64), and postoperative urinary tract infection (OR 5.68; 95% CI 2.41–13.39). Conclusions. A comprehensive understanding of incidence and risk factors of delirium can improve prevention, diagnosis, and management. Risk of postoperative delirium can be reduced based upon identifiable risk factors.


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## Body

## 1. Introduction

Postoperative delirium is a common complication after surgery in the elderly and causes difficulty in postoperative care [1, 2]. It is defined as an acute change in the cognitive status characterized by fluctuating consciousness, attention, memory, perceptions, and behavior postoperatively [3]. Postoperative delirium often brings out many adverse outcomes, such as functional disability, increased health care costs, and higher morbidity and mortality rates [4]. Thus, a further understanding and prevention of delirium may help reduce these problems and the associated costs. Some previous studies have reported the incidence and risk factors for delirium. However, incidences of postoperative delirium differ greatly, and risk factors of these studies are inconsistent. Therefore, we perform a systematic review and meta-analysis to explore incidence and risk factors for developing postoperative delirium following spine surgery.


## 2. Materials and Methods

### 2.1. Search Strategy

The systematic review and meta-analysis were done according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and AMSTAR (assessing the methodological quality of systematic reviews) Guidelines [5, 6]. PubMed, EMBASE, Cochrane Library, and Science Citation Index were searched exhaustively with inception to August 2019. The language was restricted to English, and only published articles were included. The search terms were combinations of epidemiology, prevalence, incidence, delirium, deliriums, deliria, delirious, confusion, transient mental disorder, spine, spinal cord, vertebrae, surgery, and operation. Papers from the reference lists of included studies and other meta-analyses were also searched.


### 2.2. Selection Criteria

Studies included in this systematic review and meta-analysis met the following criteria: (1) original articles on patients who underwent spine surgery, (2) observational, case series or cohort study design, (3) at least incidence reported or one risk factor identified as being associated with delirium, and (4) full text available. If the inclusion criteria were not met, the study was excluded. If the same study was published in different years or various journals, then the most frequently cited study was included for this meta-analysis. The potentially qualified studies were selected independently by 2 authors according to the inclusion and exclusion criteria. Any discrepancy was resolved by discussion to reach a consensus.


### 2.3. Data Extraction

Data were extracted by two independent authors. By discussion or by involving a third author, disagreements were addressed. The general features cover the first author, publication year, country, study type, sample size, patient characteristics, patients who underwent surgery, delirium diagnosis tool, incidence duration of delirium, and significant factors.


### 2.4. Quality Assessment

Two authors independently evaluated the quality of the studies, and the level of agreement between them was recorded. Any disagreements between the 2 authors were resolved by discussion with a third author. Newcastle–Ottawa Scale (NOS) was utilized to assess the quality of each study [7] since no studies were randomized controlled trials. Studies with 7–9 points could be identified as high quality, 5–6 points as moderate quality, and 0–4 as poor quality.


### 2.5. Statistical Analysis

The meta-analysis of comparable data was performed using Stata/SE version 15.0 software. All adjusted odds ratio (OR) with 95% confidence interval (CI) were collected and pooled to evaluate the relationships between various risk factors and postoperative delirium in patients undergoing spine surgery. In addition, crude ORs with 95% CIs were calculated based on the frequency reported in the original literature. Inconsistency was quantified withI2 statistic, and an I2 of >50% was considered to indicate substantial heterogeneity. The random-effects model or the fixed-effect model was used depending on the heterogeneity of studies included. A random-effects model was used for heterogeneous data. Otherwise, a fixed-effect model was used. Begg’s and Egger’s test were used to estimate publication bias, when 10 or more studies are presented. For any variable presenting with large heterogeneity, sensitive analysis or subgroup analysis was used to investigate the potential origin of heterogeneity.


### 2.6. Search Results

There were 1360 relevant studies included according to the search strategy. After the titles and abstracts were reviewed, 1256 of them were removed. A full-text review was evaluated in the 104 records maintained, and 64 of them were excluded because they did not meet the inclusion criteria. Finally, 40 studies representing 712820 patients were included in the present meta-analysis (Figure1).Figure 1
Flow chart of the literature search and article selection.


### 2.7. Study Characteristics and Quality Assessment

The characteristics of the included studies are summarized in Table1. 22 studies were conducted in Asian countries, 16 studies in North America, and 2 studies in Europe. 31 studies were retrospective, and 9 were prospective in design. The sample size ranged from 35 to 578457 patients. The reported incidence of delirium ranged from 0.49% to 31.43% for patients after spinal surgery. To evaluate the quality of each study, the NOS was utilized. In those studies, all of them were of moderate to high quality (range, 6–8) (Table 1).Table 1
Study characteristics and quality assessment.
Author
Publication year
Country
Study type
Sample size
Age mean (SD, range) years
Sex ratio (M : F)
Patients who underwent surgery
Delirium diagnosis tool
Delirium incidence
Duration of delirium (days)
Significant factors
Study quality
Pan et al. [8]
2019
Korea
Prospective
83
71.4 ± 4.6
27 : 56
Lumbar spine
CAM
12/83 (14.5%)
2.6 (1–5)
Male, parkinsonism, lower baseline MMSE score
8
Oe et al. [9]
2019
Japan
Retrospective
319
>18
85 : 234
Spinal deformity
—
30/319 (9.4%)
—
Age, PNI
7
Elsamadicy et al. [10]
2019
USA
Retrospective
138
≥18
40 : 98
Complex spinal fusion (≥5 levels)
—
15/138 (10.9%)
—
Age, intraoperative ketamine use
7
Takenaka et al. [11]
2019
Japan
Prospective
13188
11–94
7174 : 6014
Lumbar spine
—
65/13188 (0.49%)
—
CVD, dural tear
8
Kin et al. [12]
2019
Japan
Retrospective
67
69.6 ± 12.0
49 : 18
Cervical spine
CAM, DSM-IV
10/67 (14.9%)
<3
Low general health perception
8
Oichi et al. [13]
2019
Japan
Retrospective
88370
≥65
47408 : 40962
Lumbosacral, thoracic, cervical, unspecified
—
4502/88370 (5.1%)
—
Age >80
8
Watanabe et al. [14]
2019
Japan
Retrospective
322
75.7 years (67–89)
69 : 253
Thoracic, lumbar spine
—
26/322 (8.1%)
—
Parkinsonism
7
Morino et al. [15]
2018
Japan
Retrospective
532
64.2 (10–89)
283 : 249
Spine
DSM-IV
59/532 (11.1%)
<5
Blood loss
8
Adogwa et al. [16]
2018
USA
Retrospective
82
≥65
33 : 49
Thoracolumbar deformity
CAM
22/82 (18%)
—
Cognitive impairment
7
Adogwa et al. [17]
2018
USA
Retrospective
293
≥18
105 : 188
Lumbar spine
—
28/293 (9.6%)
—
CKD
7
Susano et al. [18]
2018
Portugal
Retrospective
715
73.6 ± 6.0
351 : 400
Cervical, lumbar spine
—
127/715 (17.8%)
—
Age, ASA physical status ≥3, METs <4, depression, nonelective surgery, invasiveness tier 3 or 4, BIS monitoring, mean pain score postoperative day 1
7
Elsamadicy et al. [19]
2018
USA
Retrospective
204
≥60
204 : 0
Elective complex spinal fusion (≥3 levels)
—
25/204 (12.3%)
—
Preoperative hgb level <13.5 g/dl
7
Oichi et al. [20]
2018
Japan
Retrospective
2712
≥20
1738 : 974
Lumbar spine
—
52/2712 (1.9%)
—
Open laminectomy
7
Kobayashi et al. [21]
2018
Japan
Retrospective
35
91.3 (90–98)
14 : 21
Cervical, thoracic, lumbar spine
—
11/35 (31.43%)
—
—
6
Yoshida et al. [22]
2018
Japan
Retrospective
304
62.9 (18–84)
64 : 240
Spinal deformity
—
34/304 (11.2%)
—
Age, operative time ≥6 hours
8
Kim et al. [23]
2018
Korea
Prospective
104
71.7 ± 4.7
36 : 68
Cervical, thoracic, lumbar spine
CAM
15/104 (14.4%)
—
Hyposmia (CCSIT score <9) and RBD (RBDSQ-K >4)
8
Ramos et al. [24]
2017
USA
Retrospective
11043
67 ± 9
2981 : 8062
Spinal deformity
—
269/11043 (2.4%)
—
Movement disorder, parkinsonism
7
Oichi et al. [25]
2017
Japan
Retrospective
6921
≥20
3324 : 3597
Lumbosacral, thoracic, cervical, unspecified
—
670/6921 (9.7%)
—
Parkinsonism
7
Elsamadicy et al. [26]
2017
USA
Retrospective
453
≥65
211 : 242
Spine
DSM-V
17/453 (3.75%)
—
Superficial surgical site infection, UTI, length of hospital stay
8
Elsamadicy et al. [27]
2017
USA
Retrospective
923
≥18
333 : 590
Spinal deformity
—
66/923 (7.15%)
—
Depression, age, operative time, postoperative UTI
7
Elsamadicy et al. [28]
2017
USA
Retrospective
839
≥18
329 : 510
Elective complex spinal fusion (≥3 levels)
—
67/839 (7.98%)
—
—
6
Radcliff et al. [29]
2017
USA
Retrospective
2792
≥65
1487 : 1305
Cervical spine
—
157/2792 (5.6%)
—
Dementia, TIA/stroke, age≥ 85 in cervical decompression patients
7
Jiang et al. [30]
2017
China
Retrospective
451
65.1 (45–84)
226 : 225
Cervical and lumbar spine
—
42/451 (9.3%)
6.7 (4–10)
Intraoperative hypotension <80 mmHg, intraoperative use of dezocine
7
Soh et al. [31]
2017
Korea
Prospective
109
>70
56 : 53
Cervical, thoracic, lumbar spine
ICDSC; CAM-ICU
9/109 (8.2%)
—
Pulmonary disease
7
Adogwa et al. [32]
2017
USA
Prospective e
125
≥65
50 : 75
Spinal deformity
—
22/125 (17.6)
—
—
7
Adogwa et al. [33]
2017
USA
Retrospective
82
≥65
33 : 49
Spinal deformity
—
13/82 (15.9%)
—
Cognitive impairment
7
Kobayashi et al. [1]
2017
Japan
Retrospective
262
82.7 (80–91)
142 : 140
Cervical, thoracic, and lumbar spine
—
15/262 (5.72)
<3
Cervical lesion surgery, blood loss>300 mL
7
Brown et al. [34]
2016
USA
Prospective
195
74 (72–78)
47 : 42
Cervical, lumbar spine
CAM; CAM-ICU; DRS-98-R
36/195 (18.5%)
—
Lower baseline MMSE score, higher average baseline pain, more intravenous fluid, baseline, antidepressant medication
7
Lee et al. [35]
2016
Korea
Retrospective
129
73.5 (70 to 85)
51 : 78
Lumbar spine
CAM; DSM-IV
18/129 (13.9%)
13.2 (1 to 92)
Cognitive impairment
7
Balabaud et al. [36]
2015
France
Retrospective
121
83.2 ± 2.4
48 : 73
Lumbar spine
—
16/(13%)
—
Instrumentation, blood loss
7
Glennie et al. [37]
2015
Canada
Retrospective
276
42.9 ± 18.8
190 : 86
Thoracic, lumbar spine
—
38/276 (13.8%)
—
Age, male, head injury
7
Dea et al. [38]
2014
Canada
Prospective
101
62 (33–85)
50 : 51
Thoracic, lumbar, sacral spine
—
21/101 (20.8)
—
—
6
Seo et al. [39]
2014
Korea
Prospective
70
70.1 ± 5.8
32 : 38
Cervical, lumbar spine
ICDSC; CAM-ICU
17/70 (24.3%)
—
Preoperative GDS, BIS measured intraoperatively under 40
8
Kelly et al. [40]
2014
Canada
Prospective
92
66.08 ± 10.59
—
Lumbar spine
—
5/92 (5.4%)
—
CCI, dural tear
8
Fineberg et al. [41]
2013
USA
Retrospective
578457
>18
285520 : 292937
Lumbar spine
—
4857/578457 (0.84%)
—
Age ≥65, teaching hospital, alcohol abuse, deficiency anemia, congestive heart failure, coagulopathy, depression, DM with end-organ damage, drug abuse, hypertension, fluid/electrolyte disorders, metastatic neoplasm, neurological disorder, psychoses, pulmonary circulation disorders, renal failure, weight loss
6
Imagama et al. [42]
2011
Japan
Retrospective
918
54 (11–87)
521 : 397
Lumbar spine
—
5/918 (0.54%)
—
—
6
Lee et al. [43]
2010
Korea
Retrospective
87
73.5 (70–85)
27 : 50
Lumbar spine
CAM, DSM-IV
11/81 (13.6%)
13.2 (1 to 92)
Cerebral vascular disease, low hemoglobin and hematocrit levels at 1 day after surgery, bad nutritional status
7
Ushida et al. [44]
2009
Japan
Retrospective
122
52–86
—
Cervical spine
DOS, DSM-IV
26/122 (21.3%)
—
Age >70, high-dose methylprednisolone (>1000 mg), hearing impairment
6
Gao et al. [45]
2008
China
Retrospective
549
48.2 (10–83)
302 : 247
Cervical, thoracic, lumbar, sacral spine
DOS, DSM-IV
18/549 (3.3%)
3.1 (1 to 8)
Central nervous system disorder, surgical history, age> 65, DM, blood transfusion ≥800 ml, hemoglobin <100 g/L
7
Kawaguchi et al. [46]
2006
Japan
Retrospective
341
59.2 (14–88)
186 : 155
Cervical, thoracic, lumbar, sacral spine
CAM, DSM–III–R
13/341 (3.8%)
≤7
Low concentrations of hemoglobin and hematocrit 1 day after surgery, ambulatory status at admission
8
DOS, delirium observation screening scale; DSM, diagnostic and statistical manual of mental disorders; CAM, confusion assessment method; MMSE, mini-mental state examination; CVD, cardiovascular disease; CKD, chronic kidney disease; CAM-ICU, confusion assessment method for the intensive care unit; DRS-98-R, delirium rating scale revised-98; ICDSC, intensive care delirium screening checklist; PNI, Prognostic Nutritional Index; ASA, American Society of Anesthesiologists physical status; BIS, Bispectral Index; METs, metabolic equivalents of task; UTI, urinary tract infection; RBD, rapid eye movement sleep behavior disorder; CCSIT, cross-cultural smell identification test; RBDSQ-K, Korean version of RBD screening questionnaire; TIA, transient ischemic attack; GDS, global deterioration scale; BIS, Bispectral Index; CCI, Charlson Comorbidity Index.


### 2.8. Incidence of Postoperative Delirium after Spine Surgery

The final meta-analysis included 40 studies [1, 8–46] from 7 different countries, and the pooled incidence was 8% (Figure 2). There was high heterogeneity (I-squared > 50%, P<0.001). Interestingly, the heterogeneity remained high with each of the subgroups of study type, countries, or operated levels (Figure 2(a)–2(c)). After sensitive analysis, 3 studies [11, 25, 41] showed great influence on the pooled result (Figure 2(d)). The asymmetry Begg’s funnel plot suggested the presence of publication bias for incidence of postoperative delirium after spine surgery (P<0.001) (Figure 2(e)).Figure 2
Pooled result of incidence of delirium: (a) subgroup analysis based on the factor of country; (b) subgroup analysis based on the factor of study type; (c) subgroup analysis based on the factor of surgical site; (d) result of sensitive analysis; (e) Begg’s funnel plot.
(a)
(b)
(c)
(d)
(e)


### 2.9. Risk Factors for Postoperative Delirium after Spine Surgery

The ORs and 95% CIs of the risk factors are displayed in Table2. Among these, 33 factors were examined in 2 or more studies and 18 factors demonstrated statistical significance.Table 2
Outcomes of meta-analysis for risk factors.
Risk factors
No. of studies
Pooled OR (95% CI)
HeterogeneityI2 (%)
P value
Effects model
Admission to ICU
3
2.51 (0.38–4.64)
0
0.944
Fixed
Age
7
1.07 (1.04–1.09)
16.5
0.304
Fixed
Age >65
3
4.77 (4.37–5.16)
0
0.383
Fixed
Age >70
3
15.87 (6.03–41.73)
48
0.14
Fixed
Age >80
2
1.91 (1.78–2.03)
0
0.844
Fixed
Alcohol abuse
4
2.11 (1.67–2.56)
0
0.397
Fixed
Anxiety
2
1.74 (1.04–2.44)
0
0.773
Fixed
Blood loss
5
1 (0.99–1.01)
83.9
<0.001
Random
Blood transfusion
3
0.62 (0.07–1.17)
74.4
0.02
Random
Cardiovascular comorbidity
10
0.81 (0.34–1.29)
0
0.697
Fixed
CCI
2
1.26 (0.56–1.96)
0
0.355
Fixed
Cervical surgery
6
0.97 (0.45–1.48)
0
0.514
Fixed
Congestive heart failure
3
1.4 (1.21–1.6)
0
0.708
Fixed
Depression
7
2.5 (1.52–3.49)
76
<0.001
Random
DM
13
1.09 (0.6–1.59)
0
0.978
Fixed
Dural tear
2
3.21 (0.07–6.35)
0
0.864
Fixed
Gender (male)
17
0.81 (0.76–0.86)
44.6
0.025
Fixed
History of surgery
6
1.09 (0.55–1.64)
0
0.617
Fixed
Hypertension
13
1.12 (1.04–1.2)
28.3
0.16
Fixed
Kidney disease
6
1.41 (1.16–1.66)
0
0.92
Fixed
MMSE score
3
0.7 (0.5–0.89)
51.7
0.126
Random
Neurological disorder
4
4.66 (4.22–5.11)
0
0.521
Fixed
Operated levels
2
1.02 (0.81–1.22)
0
0.523
Fixed
Operation time
4
1 (0.99–1)
0
0.725
Fixed
Parkinsonism
5
5.37 (0.63–10.1)
88
<0.001
Random
Preoperative VAS
2
1.88 (1.11–2.64)
0
0.816
Fixed
Previous cerebral vascular diseases
7
1.82 (0.7–2.94)
0
0.952
Fixed
Previous mild cognitive impairment
5
2.43 (0.99–3.86)
0
0.967
Fixed
Previous opioid use
3
1.86 (1.18–2.54)
0
0.659
Fixed
Psychoses
5
2.77 (2.29–3.25)
0
0.474
Fixed
Pulmonary disease
6
1.81 (1.27–2.35)
0
0.925
Fixed
Postoperative UTI
2
5.68 (2.41–13.39)
0
0.463
Fixed
Superficial surgical site infection
2
0.28 (-3.25-3.81)
0
0.433
Fixed
CCI, Charlson Comorbidity Index; DM, diabetes mellitus; MMSE, mini-mental state examination; VAS, Visual Analogue Scale; UTI, urinary tract infection.After synthesis of 7 studies, it revealed that patients who developed delirium were significantly older (OR 1.07; 95% CI 1.04–1.09). Meanwhile, age older than 65 (OR 4.77; 95% CI 4.37–5.16), 70 (OR 15.87; 95% CI 6.03–41.73), and 80 (OR 1.91; 95% CI 1.78–2.03) years were significantly associated with the risk of developing delirium. Another demographic factor male was considered to be associated with less delirium risk in the pooled analysis (OR 0.81; 95% CI 0.76–0.86).A history of alcohol abuse (OR 2.11; 95% CI 1.67–2.56), anxiety (OR 1.74; 95% CI 1.04–2.44), congestive heart failure (OR 1.4; 95% CI 1.21–1.6), depression (OR 2.5; 95% CI 1.52–3.49), hypertension (OR 1.12; 95% CI 1.04–1.2), kidney disease (OR 1.41; 95% CI 1.16–1.66), neurological disorder (OR 4.66; 95% CI 4.22–5.11), opioid use (OR 1.86; 95% CI 1.18–2.54), psychoses (OR 2.77; 95% CI 2.29–3.25), and pulmonary disease (OR 1.81; 95% CI 1.27–2.35) were more likely to develop delirium than controls. Assessment of mental state, as measured by mini-mental state examination (MMSE), demonstrated a significantly lower risk to develop delirium in patients with higher scores (OR 0.7; 95% CI 0.5–0.89). In addition, preoperative pain and postoperative urinary tract infection (UTI) were related to the development of delirium (OR 1.88; 95% CI 1.11–2.64 and OR 5.68; 95% CI 2.41–13.39, respectively).


## 2.1. Search Strategy

The systematic review and meta-analysis were done according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and AMSTAR (assessing the methodological quality of systematic reviews) Guidelines [5, 6]. PubMed, EMBASE, Cochrane Library, and Science Citation Index were searched exhaustively with inception to August 2019. The language was restricted to English, and only published articles were included. The search terms were combinations of epidemiology, prevalence, incidence, delirium, deliriums, deliria, delirious, confusion, transient mental disorder, spine, spinal cord, vertebrae, surgery, and operation. Papers from the reference lists of included studies and other meta-analyses were also searched.


## 2.2. Selection Criteria

Studies included in this systematic review and meta-analysis met the following criteria: (1) original articles on patients who underwent spine surgery, (2) observational, case series or cohort study design, (3) at least incidence reported or one risk factor identified as being associated with delirium, and (4) full text available. If the inclusion criteria were not met, the study was excluded. If the same study was published in different years or various journals, then the most frequently cited study was included for this meta-analysis. The potentially qualified studies were selected independently by 2 authors according to the inclusion and exclusion criteria. Any discrepancy was resolved by discussion to reach a consensus.


## 2.3. Data Extraction

Data were extracted by two independent authors. By discussion or by involving a third author, disagreements were addressed. The general features cover the first author, publication year, country, study type, sample size, patient characteristics, patients who underwent surgery, delirium diagnosis tool, incidence duration of delirium, and significant factors.


## 2.4. Quality Assessment

Two authors independently evaluated the quality of the studies, and the level of agreement between them was recorded. Any disagreements between the 2 authors were resolved by discussion with a third author. Newcastle–Ottawa Scale (NOS) was utilized to assess the quality of each study [7] since no studies were randomized controlled trials. Studies with 7–9 points could be identified as high quality, 5–6 points as moderate quality, and 0–4 as poor quality.


## 2.5. Statistical Analysis

The meta-analysis of comparable data was performed using Stata/SE version 15.0 software. All adjusted odds ratio (OR) with 95% confidence interval (CI) were collected and pooled to evaluate the relationships between various risk factors and postoperative delirium in patients undergoing spine surgery. In addition, crude ORs with 95% CIs were calculated based on the frequency reported in the original literature. Inconsistency was quantified withI2 statistic, and an I2 of >50% was considered to indicate substantial heterogeneity. The random-effects model or the fixed-effect model was used depending on the heterogeneity of studies included. A random-effects model was used for heterogeneous data. Otherwise, a fixed-effect model was used. Begg’s and Egger’s test were used to estimate publication bias, when 10 or more studies are presented. For any variable presenting with large heterogeneity, sensitive analysis or subgroup analysis was used to investigate the potential origin of heterogeneity.


## 2.6. Search Results

There were 1360 relevant studies included according to the search strategy. After the titles and abstracts were reviewed, 1256 of them were removed. A full-text review was evaluated in the 104 records maintained, and 64 of them were excluded because they did not meet the inclusion criteria. Finally, 40 studies representing 712820 patients were included in the present meta-analysis (Figure1).Figure 1
Flow chart of the literature search and article selection.


## 2.7. Study Characteristics and Quality Assessment

The characteristics of the included studies are summarized in Table1. 22 studies were conducted in Asian countries, 16 studies in North America, and 2 studies in Europe. 31 studies were retrospective, and 9 were prospective in design. The sample size ranged from 35 to 578457 patients. The reported incidence of delirium ranged from 0.49% to 31.43% for patients after spinal surgery. To evaluate the quality of each study, the NOS was utilized. In those studies, all of them were of moderate to high quality (range, 6–8) (Table 1).Table 1
Study characteristics and quality assessment.
Author
Publication year
Country
Study type
Sample size
Age mean (SD, range) years
Sex ratio (M : F)
Patients who underwent surgery
Delirium diagnosis tool
Delirium incidence
Duration of delirium (days)
Significant factors
Study quality
Pan et al. [8]
2019
Korea
Prospective
83
71.4 ± 4.6
27 : 56
Lumbar spine
CAM
12/83 (14.5%)
2.6 (1–5)
Male, parkinsonism, lower baseline MMSE score
8
Oe et al. [9]
2019
Japan
Retrospective
319
>18
85 : 234
Spinal deformity
—
30/319 (9.4%)
—
Age, PNI
7
Elsamadicy et al. [10]
2019
USA
Retrospective
138
≥18
40 : 98
Complex spinal fusion (≥5 levels)
—
15/138 (10.9%)
—
Age, intraoperative ketamine use
7
Takenaka et al. [11]
2019
Japan
Prospective
13188
11–94
7174 : 6014
Lumbar spine
—
65/13188 (0.49%)
—
CVD, dural tear
8
Kin et al. [12]
2019
Japan
Retrospective
67
69.6 ± 12.0
49 : 18
Cervical spine
CAM, DSM-IV
10/67 (14.9%)
<3
Low general health perception
8
Oichi et al. [13]
2019
Japan
Retrospective
88370
≥65
47408 : 40962
Lumbosacral, thoracic, cervical, unspecified
—
4502/88370 (5.1%)
—
Age >80
8
Watanabe et al. [14]
2019
Japan
Retrospective
322
75.7 years (67–89)
69 : 253
Thoracic, lumbar spine
—
26/322 (8.1%)
—
Parkinsonism
7
Morino et al. [15]
2018
Japan
Retrospective
532
64.2 (10–89)
283 : 249
Spine
DSM-IV
59/532 (11.1%)
<5
Blood loss
8
Adogwa et al. [16]
2018
USA
Retrospective
82
≥65
33 : 49
Thoracolumbar deformity
CAM
22/82 (18%)
—
Cognitive impairment
7
Adogwa et al. [17]
2018
USA
Retrospective
293
≥18
105 : 188
Lumbar spine
—
28/293 (9.6%)
—
CKD
7
Susano et al. [18]
2018
Portugal
Retrospective
715
73.6 ± 6.0
351 : 400
Cervical, lumbar spine
—
127/715 (17.8%)
—
Age, ASA physical status ≥3, METs <4, depression, nonelective surgery, invasiveness tier 3 or 4, BIS monitoring, mean pain score postoperative day 1
7
Elsamadicy et al. [19]
2018
USA
Retrospective
204
≥60
204 : 0
Elective complex spinal fusion (≥3 levels)
—
25/204 (12.3%)
—
Preoperative hgb level <13.5 g/dl
7
Oichi et al. [20]
2018
Japan
Retrospective
2712
≥20
1738 : 974
Lumbar spine
—
52/2712 (1.9%)
—
Open laminectomy
7
Kobayashi et al. [21]
2018
Japan
Retrospective
35
91.3 (90–98)
14 : 21
Cervical, thoracic, lumbar spine
—
11/35 (31.43%)
—
—
6
Yoshida et al. [22]
2018
Japan
Retrospective
304
62.9 (18–84)
64 : 240
Spinal deformity
—
34/304 (11.2%)
—
Age, operative time ≥6 hours
8
Kim et al. [23]
2018
Korea
Prospective
104
71.7 ± 4.7
36 : 68
Cervical, thoracic, lumbar spine
CAM
15/104 (14.4%)
—
Hyposmia (CCSIT score <9) and RBD (RBDSQ-K >4)
8
Ramos et al. [24]
2017
USA
Retrospective
11043
67 ± 9
2981 : 8062
Spinal deformity
—
269/11043 (2.4%)
—
Movement disorder, parkinsonism
7
Oichi et al. [25]
2017
Japan
Retrospective
6921
≥20
3324 : 3597
Lumbosacral, thoracic, cervical, unspecified
—
670/6921 (9.7%)
—
Parkinsonism
7
Elsamadicy et al. [26]
2017
USA
Retrospective
453
≥65
211 : 242
Spine
DSM-V
17/453 (3.75%)
—
Superficial surgical site infection, UTI, length of hospital stay
8
Elsamadicy et al. [27]
2017
USA
Retrospective
923
≥18
333 : 590
Spinal deformity
—
66/923 (7.15%)
—
Depression, age, operative time, postoperative UTI
7
Elsamadicy et al. [28]
2017
USA
Retrospective
839
≥18
329 : 510
Elective complex spinal fusion (≥3 levels)
—
67/839 (7.98%)
—
—
6
Radcliff et al. [29]
2017
USA
Retrospective
2792
≥65
1487 : 1305
Cervical spine
—
157/2792 (5.6%)
—
Dementia, TIA/stroke, age≥ 85 in cervical decompression patients
7
Jiang et al. [30]
2017
China
Retrospective
451
65.1 (45–84)
226 : 225
Cervical and lumbar spine
—
42/451 (9.3%)
6.7 (4–10)
Intraoperative hypotension <80 mmHg, intraoperative use of dezocine
7
Soh et al. [31]
2017
Korea
Prospective
109
>70
56 : 53
Cervical, thoracic, lumbar spine
ICDSC; CAM-ICU
9/109 (8.2%)
—
Pulmonary disease
7
Adogwa et al. [32]
2017
USA
Prospective e
125
≥65
50 : 75
Spinal deformity
—
22/125 (17.6)
—
—
7
Adogwa et al. [33]
2017
USA
Retrospective
82
≥65
33 : 49
Spinal deformity
—
13/82 (15.9%)
—
Cognitive impairment
7
Kobayashi et al. [1]
2017
Japan
Retrospective
262
82.7 (80–91)
142 : 140
Cervical, thoracic, and lumbar spine
—
15/262 (5.72)
<3
Cervical lesion surgery, blood loss>300 mL
7
Brown et al. [34]
2016
USA
Prospective
195
74 (72–78)
47 : 42
Cervical, lumbar spine
CAM; CAM-ICU; DRS-98-R
36/195 (18.5%)
—
Lower baseline MMSE score, higher average baseline pain, more intravenous fluid, baseline, antidepressant medication
7
Lee et al. [35]
2016
Korea
Retrospective
129
73.5 (70 to 85)
51 : 78
Lumbar spine
CAM; DSM-IV
18/129 (13.9%)
13.2 (1 to 92)
Cognitive impairment
7
Balabaud et al. [36]
2015
France
Retrospective
121
83.2 ± 2.4
48 : 73
Lumbar spine
—
16/(13%)
—
Instrumentation, blood loss
7
Glennie et al. [37]
2015
Canada
Retrospective
276
42.9 ± 18.8
190 : 86
Thoracic, lumbar spine
—
38/276 (13.8%)
—
Age, male, head injury
7
Dea et al. [38]
2014
Canada
Prospective
101
62 (33–85)
50 : 51
Thoracic, lumbar, sacral spine
—
21/101 (20.8)
—
—
6
Seo et al. [39]
2014
Korea
Prospective
70
70.1 ± 5.8
32 : 38
Cervical, lumbar spine
ICDSC; CAM-ICU
17/70 (24.3%)
—
Preoperative GDS, BIS measured intraoperatively under 40
8
Kelly et al. [40]
2014
Canada
Prospective
92
66.08 ± 10.59
—
Lumbar spine
—
5/92 (5.4%)
—
CCI, dural tear
8
Fineberg et al. [41]
2013
USA
Retrospective
578457
>18
285520 : 292937
Lumbar spine
—
4857/578457 (0.84%)
—
Age ≥65, teaching hospital, alcohol abuse, deficiency anemia, congestive heart failure, coagulopathy, depression, DM with end-organ damage, drug abuse, hypertension, fluid/electrolyte disorders, metastatic neoplasm, neurological disorder, psychoses, pulmonary circulation disorders, renal failure, weight loss
6
Imagama et al. [42]
2011
Japan
Retrospective
918
54 (11–87)
521 : 397
Lumbar spine
—
5/918 (0.54%)
—
—
6
Lee et al. [43]
2010
Korea
Retrospective
87
73.5 (70–85)
27 : 50
Lumbar spine
CAM, DSM-IV
11/81 (13.6%)
13.2 (1 to 92)
Cerebral vascular disease, low hemoglobin and hematocrit levels at 1 day after surgery, bad nutritional status
7
Ushida et al. [44]
2009
Japan
Retrospective
122
52–86
—
Cervical spine
DOS, DSM-IV
26/122 (21.3%)
—
Age >70, high-dose methylprednisolone (>1000 mg), hearing impairment
6
Gao et al. [45]
2008
China
Retrospective
549
48.2 (10–83)
302 : 247
Cervical, thoracic, lumbar, sacral spine
DOS, DSM-IV
18/549 (3.3%)
3.1 (1 to 8)
Central nervous system disorder, surgical history, age> 65, DM, blood transfusion ≥800 ml, hemoglobin <100 g/L
7
Kawaguchi et al. [46]
2006
Japan
Retrospective
341
59.2 (14–88)
186 : 155
Cervical, thoracic, lumbar, sacral spine
CAM, DSM–III–R
13/341 (3.8%)
≤7
Low concentrations of hemoglobin and hematocrit 1 day after surgery, ambulatory status at admission
8
DOS, delirium observation screening scale; DSM, diagnostic and statistical manual of mental disorders; CAM, confusion assessment method; MMSE, mini-mental state examination; CVD, cardiovascular disease; CKD, chronic kidney disease; CAM-ICU, confusion assessment method for the intensive care unit; DRS-98-R, delirium rating scale revised-98; ICDSC, intensive care delirium screening checklist; PNI, Prognostic Nutritional Index; ASA, American Society of Anesthesiologists physical status; BIS, Bispectral Index; METs, metabolic equivalents of task; UTI, urinary tract infection; RBD, rapid eye movement sleep behavior disorder; CCSIT, cross-cultural smell identification test; RBDSQ-K, Korean version of RBD screening questionnaire; TIA, transient ischemic attack; GDS, global deterioration scale; BIS, Bispectral Index; CCI, Charlson Comorbidity Index.


## 2.8. Incidence of Postoperative Delirium after Spine Surgery

The final meta-analysis included 40 studies [1, 8–46] from 7 different countries, and the pooled incidence was 8% (Figure 2). There was high heterogeneity (I-squared > 50%, P<0.001). Interestingly, the heterogeneity remained high with each of the subgroups of study type, countries, or operated levels (Figure 2(a)–2(c)). After sensitive analysis, 3 studies [11, 25, 41] showed great influence on the pooled result (Figure 2(d)). The asymmetry Begg’s funnel plot suggested the presence of publication bias for incidence of postoperative delirium after spine surgery (P<0.001) (Figure 2(e)).Figure 2
Pooled result of incidence of delirium: (a) subgroup analysis based on the factor of country; (b) subgroup analysis based on the factor of study type; (c) subgroup analysis based on the factor of surgical site; (d) result of sensitive analysis; (e) Begg’s funnel plot.
(a)
(b)
(c)
(d)
(e)


## 2.9. Risk Factors for Postoperative Delirium after Spine Surgery

The ORs and 95% CIs of the risk factors are displayed in Table2. Among these, 33 factors were examined in 2 or more studies and 18 factors demonstrated statistical significance.Table 2
Outcomes of meta-analysis for risk factors.
Risk factors
No. of studies
Pooled OR (95% CI)
HeterogeneityI2 (%)
P value
Effects model
Admission to ICU
3
2.51 (0.38–4.64)
0
0.944
Fixed
Age
7
1.07 (1.04–1.09)
16.5
0.304
Fixed
Age >65
3
4.77 (4.37–5.16)
0
0.383
Fixed
Age >70
3
15.87 (6.03–41.73)
48
0.14
Fixed
Age >80
2
1.91 (1.78–2.03)
0
0.844
Fixed
Alcohol abuse
4
2.11 (1.67–2.56)
0
0.397
Fixed
Anxiety
2
1.74 (1.04–2.44)
0
0.773
Fixed
Blood loss
5
1 (0.99–1.01)
83.9
<0.001
Random
Blood transfusion
3
0.62 (0.07–1.17)
74.4
0.02
Random
Cardiovascular comorbidity
10
0.81 (0.34–1.29)
0
0.697
Fixed
CCI
2
1.26 (0.56–1.96)
0
0.355
Fixed
Cervical surgery
6
0.97 (0.45–1.48)
0
0.514
Fixed
Congestive heart failure
3
1.4 (1.21–1.6)
0
0.708
Fixed
Depression
7
2.5 (1.52–3.49)
76
<0.001
Random
DM
13
1.09 (0.6–1.59)
0
0.978
Fixed
Dural tear
2
3.21 (0.07–6.35)
0
0.864
Fixed
Gender (male)
17
0.81 (0.76–0.86)
44.6
0.025
Fixed
History of surgery
6
1.09 (0.55–1.64)
0
0.617
Fixed
Hypertension
13
1.12 (1.04–1.2)
28.3
0.16
Fixed
Kidney disease
6
1.41 (1.16–1.66)
0
0.92
Fixed
MMSE score
3
0.7 (0.5–0.89)
51.7
0.126
Random
Neurological disorder
4
4.66 (4.22–5.11)
0
0.521
Fixed
Operated levels
2
1.02 (0.81–1.22)
0
0.523
Fixed
Operation time
4
1 (0.99–1)
0
0.725
Fixed
Parkinsonism
5
5.37 (0.63–10.1)
88
<0.001
Random
Preoperative VAS
2
1.88 (1.11–2.64)
0
0.816
Fixed
Previous cerebral vascular diseases
7
1.82 (0.7–2.94)
0
0.952
Fixed
Previous mild cognitive impairment
5
2.43 (0.99–3.86)
0
0.967
Fixed
Previous opioid use
3
1.86 (1.18–2.54)
0
0.659
Fixed
Psychoses
5
2.77 (2.29–3.25)
0
0.474
Fixed
Pulmonary disease
6
1.81 (1.27–2.35)
0
0.925
Fixed
Postoperative UTI
2
5.68 (2.41–13.39)
0
0.463
Fixed
Superficial surgical site infection
2
0.28 (-3.25-3.81)
0
0.433
Fixed
CCI, Charlson Comorbidity Index; DM, diabetes mellitus; MMSE, mini-mental state examination; VAS, Visual Analogue Scale; UTI, urinary tract infection.After synthesis of 7 studies, it revealed that patients who developed delirium were significantly older (OR 1.07; 95% CI 1.04–1.09). Meanwhile, age older than 65 (OR 4.77; 95% CI 4.37–5.16), 70 (OR 15.87; 95% CI 6.03–41.73), and 80 (OR 1.91; 95% CI 1.78–2.03) years were significantly associated with the risk of developing delirium. Another demographic factor male was considered to be associated with less delirium risk in the pooled analysis (OR 0.81; 95% CI 0.76–0.86).A history of alcohol abuse (OR 2.11; 95% CI 1.67–2.56), anxiety (OR 1.74; 95% CI 1.04–2.44), congestive heart failure (OR 1.4; 95% CI 1.21–1.6), depression (OR 2.5; 95% CI 1.52–3.49), hypertension (OR 1.12; 95% CI 1.04–1.2), kidney disease (OR 1.41; 95% CI 1.16–1.66), neurological disorder (OR 4.66; 95% CI 4.22–5.11), opioid use (OR 1.86; 95% CI 1.18–2.54), psychoses (OR 2.77; 95% CI 2.29–3.25), and pulmonary disease (OR 1.81; 95% CI 1.27–2.35) were more likely to develop delirium than controls. Assessment of mental state, as measured by mini-mental state examination (MMSE), demonstrated a significantly lower risk to develop delirium in patients with higher scores (OR 0.7; 95% CI 0.5–0.89). In addition, preoperative pain and postoperative urinary tract infection (UTI) were related to the development of delirium (OR 1.88; 95% CI 1.11–2.64 and OR 5.68; 95% CI 2.41–13.39, respectively).


## 3. Discussion

Delirium is thought to be a less transient disorder than previously believed in several studies [8, 11]. In addition, it has been reported that patients with postoperative delirium have a higher mortality rate than in those without it [4]. Due to the fact that delirium is varying and multifactorial, it will be helpful for prevention of delirium through identifying predictable risk factors.This systematic review and meta-analysis were performed to pool and identify the incidence and risk factors of postoperative delirium after spine surgery. The pooled incidence of delirium in this meta-analysis is 8%. However, the present study showed wide variation and heterogeneity in incidence of delirium. A previous meta-analysis of 6 studies reported incidence of delirium after spine surgery varies from 0.84% to 21.3% [47]. Interestingly, the heterogeneity remained high with each of the subgroups of study type, countries, or operated levels (Figures 2(a)–2(c)). We found that patients with spinal deformity have higher rate of delirium (10%) and lower rate in patients with lumbar spine (1%). Meanwhile, prospective studies have a higher incidence of postoperative delirium than retrospective studies. After sensitive analysis, 3 studies [11, 25, 41] showed great influence on the pooled result (Figure 2(d)). All these 3 studies have relatively a larger sample size (range, 13188 to 578457), low incidence of delirium (range, 0.49 to 5.1%), and retrospective nature of study design, which may contribute to the heterogeneity. The asymmetry Begg’s funnel plot suggested the presence of publication bias for incidence of postoperative delirium after spine surgery, and lower incidence values could be missing (Figure 2(e)).One of the most important risk factors was older age, especially in patients over 65. This may be attributed to the fact that elderly patients are more likely influenced by age-related physical and psychical changes. Aging is also associated with a higher incidence of comorbidity such as hypertension, diabetes mellitus, and pulmonary disease [12, 30]. The highest rate of delirium in our meta-analysis is 31.43% in a multicenter prospective study with patient’s age more than 90 [21]. Another significant demographic factor is male as a protective factor. Through subgroup analysis, we found that study design may contribute to the heterogeneity and prospective studies showing relatively a higher risk of developing delirium in females (Figure 3(a)). For publication bias, Begg’ funnel plot demonstrated no significant bias (Figure 3(b)).Figure 3
Pooled result of male: (a) subgroup analysis based on the factor of study type; (b) Begg’s funnel plot.
(a)
(b)The present study showed that comorbidities significantly increase the risk of postoperative delirium after spine surgery. A history of alcohol abuse, congestive heart failure, hypertension, neurological disorder, opioid use, psychoses, and pulmonary disease are related to develop delirium. However, diabetes mellitus, history of surgery, and cerebral vascular diseases were not found to be related to developing delirium, which was consistent with the previous meta-analysis [47]. For the cardiovascular comorbidity, the pooled result of 10 studies [8, 11, 15, 23, 26, 30, 31, 34, 43, 45] showed no significance (OR 0.81; 95% CI 0.34–1.29) with low heterogeneity (I2 0%) (Figure 4(a)). Only one study found cardiovascular comorbidity as a risk factor for delirium [11]. The symmetry Begg’s funnel plot suggested no presence of publication bias for cardiovascular comorbidity (Figure 4(b)). Interestingly, however, pooled results showed congestive heart failure as a significant factor. This may be due to the severity of heart diseases.Figure 4
Pooled result of cardiovascular comorbidity: (a) forest plot of cardiovascular comorbidity; (b) Begg’s funnel plot.
(a)
(b)Regarding the comorbidity of hypertension, the meta-analysis of 13 studies [1, 8, 12, 23, 26, 30, 31, 34, 39, 41, 43, 45, 46] identified it as a significant factor, and subgroup analysis showed heterogeneity comes from study design (Figure 5(a)). For publication bias, Begg’s funnel plot suggested no significant bias (Figure 5(b)). Previous study showed that hypertension leading to microembolization phenomena and cerebral ischemia may be responsible for the occurrence of delirium [48].Figure 5
Pooled result of hypertension: (a) forest plot of hypertension; (b) Begg’s funnel plot.
(a)
(b)For neurological or mental diseases, neurological disorder, psychoses, anxiety, and depression were found to be associated with developing delirium. The meta-analysis of 5 studies showed that mild cognitive impairment is not related to the occurrence of delirium (OR 2.43; 95% CI 0.99–3.86;I2 0%). Meanwhile, parkinsonism was also not found to be related to postoperative delirium (OR 5.37; 95% CI 0.63–10.1). However, there is still controversy in the role of parkinsonism for postoperative delirium. Kim et al. [23] found that that parkinsonism is not a risk factor for postoperative delirium after multivariable analysis. Interestingly, Pan et al. [8] found an opposite result, which may be attributed to relatively a smaller sample of patients with parkinsonism in their study. Notably, the result should be explained with caution since the heterogeneity is high (I2 88%). After subgroup analysis, there was a high heterogeneity between retrospective studies (Figure 6(a)). Moreover, the result of sensitive analysis showed two studies [24, 25] contributing greatly to the high heterogeneity (Figure 6(b)). Both studies were retrospective design and focus on patients with parkinsonism, which may result in high heterogeneity.Figure 6
Pooled result of parkinsonism: (a) forest plot of parkinsonism; (b) result of sensitive analysis.
(a)
(b)Mental states, as assessed by MMSE, were associated with the development of delirium (OR 0.7; 95% CI 0.5–0.89). Through subgroup analysis, we found that geographical factors may contribute to heterogeneity (Figure7). This measure of the state of mental health appears to have a clearer association with postoperative delirium compared to Charlson Comorbidity Index (CCI) which assesses the number of specific medical comorbidities. These findings are also seen in other studies where CCI appears less clearly associated with the incidence of delirium in older patients [12, 49].Figure 7
Pooled result of MMSE score. Subgroup analysis based on the factor of country.The finding that preoperative pain and opioid use is associated with increased probability of delirium has been previously reported in patients with or without hip fracture or patients with cancer [49, 50]. In addition, elderly patients are more sensitive to opioid-related adverse events [51]. In patients with spine disease, pain may lead to stress reaction and changes of nerve conduction if not effectively controlled [34]. However, the accumulation of active metabolites in patients receiving opioid may contribute to the psychotic features such as delirium [52]. Hence, it is suggested that a less toxic drug, buprenorphine patch other than morphine, should be considered for patients with osteoarthrosis and other types of lumbago when pain continues despite adequate administrations of nonopioid analgesics [53].In our study, intraoperative factors do not appear to influence the prevalence of delirium based on normal clinical practice such as blood loss, blood transfusion, cervical surgery, dural tear, operated levels, and operation time. Notably, for intraoperative blood loss, there was high heterogeneity among studies (Figure8(a)). After sensitive analysis, we found that one study [23] focused on patients with parkinsonism lead to the high heterogeneity. In addition, high heterogeneity was also seen in the meta-analysis of blood transfusion (Figure 9(a)). The sensitive analysis showed that the heterogeneity comes from one study [43], which had more fusion levels (2.27 ± 1.34) and blood loss (1263 ± 903) than other studies (Figure 9(b)). Postoperatively, patients experiencing complications such as UTI had a higher probability to develop delirium.Figure 8
Pooled result of blood loss: (a) forest plot of blood loss; (b) result of sensitive analysis.
(a)
(b)Figure 9
Pooled result of blood transfusion: (a) forest plot of blood transfusion; (b) result of sensitive analysis.
(a)
(b)There are some limitations in our study. First, no randomized controlled trials were included despite our exhausted search from literatures, which may influence the quality of the result. Second, although subgroup analyses were used, the pooled result of incidence was still reported with high heterogeneity, which should be explained with caution.


## 4. Conclusions

In summary, the study reveals that pooled incidence of delirium is 8% and age, gender, history of alcohol abuse, anxiety, congestive heart failure, depression, hypertension, kidney disease, neurological disorder, opioid use, psychoses, pulmonary disease, MMSE, preoperative pain, and postoperative UTI were significant factors for delirium after spine surgery. A comprehensive understanding of incidence and risk factors of delirium can improve prevention, diagnosis, and management.



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*Source: 2139834-2019-11-26.xml*