Relationship of sleep disturbance and postoperative delirium: a systematic review and meta-analysis

Introduction

Postoperative delirium (PD) is an acute but typically reversible syndrome that manifests as sudden and fluctuating changes in consciousness, attention, and cognition, affecting ranging from 11% to 51% of patients after major surgery (1,2). Increasing evidence has demonstrated both short-term and long-term poor prognoses in surgical patients who develop PD (3). PD is associated with longer hospital stays, increased mortality, and the long-term postoperative cognitive dysfunction, increasing economic burden on the healthcare systems (2,4). In practice, many patients with PD are not identified by doctors in time, which leads to delayed treatment measures and directly affects the patients’ quality of life (5). Thereby, identifying modifiable risk factors and implementing risk reduction strategies may reduce the incidence of PD.

PD is the result of a combination of many factors, including advanced age, low education level, preoperative cognitive impairment, alcoholism, smoking, cardiac or vascular surgery, major non-cardiac surgery, perioperative use of sedative and analgesic drugs, postoperative incomplete analgesia, etc. (6,7). Sleep is currently a hot topic in clinical research due to its potential effects on cognitive function (8). Sleep is a regular physiological process of the human body, and the quality and quantity of sleep can affect the individual’s health status and quality of life (9). Good sleep quality can help quickly eliminate fatigue, strengthen the immune effect, and maintain both physical strength and a healthy mental state (10). However, sleep disturbances are extremely common, becoming a global health concern (11). The disturbances include obstructive sleep apnea (OSA) and insomnia (12), which are associated with mental disorders (13,14). Several studies have shown that sleep disturbance may independently cause PD (15-17). However, the relationship between sleep disturbances and PD remains controversial. Previous studies by Roggenbach et al. and Wang et al. found that OSA was closely associated with PD (18,19). Nevertheless, there is a study obtaining no association between OSA and PD in the context of usual care in the intensive care unit (ICU) (20). Studies by de Rooij et al. (21) and Nguyen et al. (22) demonstrated insomnia was related to PD. Whereas, Wang et al. noticed that perioperative sleep disturbances were not potential risk factors for PD in randomized controlled trials (8). Systematic review and meta-analysis are the most commonly used research methods in evidence-based medicine. Meta-analysis is a statistical method that synthesizes a quantitative index from similar study groups with different results from multiple systematic reviews. The systematic review is a comprehensive summary of all relevant studies worldwide, with a strict evaluation of all included studies one by one, comprehensive analysis and evaluation of all research results, and meta-analysis if necessary (23). Combined with the results of all published studies, this study systematically evaluated the influence of sleep disturbance on PD, providing a basis for guiding the further discussion of PD. Subgroup analysis was performed for a more comprehensive assessment of sleep disturbance on PD in the meta-analysis. We present the following article in accordance with the MOOSE reporting checklist (available at https://gs.amegroups.com/article/view/10.21037/gs-22-312/rc).

Methods

Search strategy

A systematic search of PubMed, Embase, Cochrane Library and Web of Science databases for relevant articles was performed from database inception to April 28, 2021. The search terms were: “Confusion” OR “delirium” OR “delirious” AND “Sleep” OR “Sleep Disorder” OR “Sleep Wake Disorders” OR “dyssomn” OR “parasomn” OR “narcolep” OR “somnolen” OR “hypersomn” OR “insomnolen” OR “hyposomn” OR “hypnogenic paroxysmal” OR “somnamb”.

Inclusion and exclusion criteria

Inclusion criteria were: (I) populations: patients undergoing surgical treatments; (II) observation: patients with PD after surgical treatments assigned to the case group; (III) control: patients without PD after surgical treatments assigned to the control group; (IV) outcomes: the relationship between sleep disturbance and PD; and the relationship between sleep disturbance and PD in different study types, age, sample size, operation type, type of sleep disturbance, occurrence time of sleep disturbance, and delirium assessment tools; (V) study design: cohort or case-control studies; (VI) English literature.

Exclusion criteria were: (I) animal experiments; (II) incomplete data or unable to be extracted; (III) abstracts, letters, editorials, protocols, case reports, reviews, and meta-analyses.

Methodological quality appraisal and data extraction

The modified Newcastle-Ottawa Scale (NOS) (24) was used to evaluate the literature quality, which comprises ten points that determine the selection, comparability, and exposure or outcome. There were four stars in the selection domain, two stars in the comparability domain, and three stars in the exposure or outcome domain. This scale has a total score of 10, with NOS scores >7 being considered high quality, and >5 being considered moderate quality.

Two researchers (Ertao He and Ying Dong) reviewed the identified literature and extracted study data according to the inclusion and exclusion criteria. Discrepancies were resolved through consultation with a third author (Haitao Jia). The following data were extracted from all included studies: name of the first author, year of publication, country of the study, study design, type of surgery, number of participants, mean age (years), sex, number of patients with PD after surgical treatment, type of sleep disturbance, timing of sleep disturbance, sleep quality assessment tool, delirium assessment tool, quality assessment.

Statistical analysis

All studies were statistically analyzed using Stata15.1 software (Stata Corporation, College Station, TX, USA). Odds ratio (OR) was used as the effect indicator, and the 95% confidence interval (CI) was applied to express the effect size. Heterogeneity was tested; for the heterogeneity statistic I²≥50%, random-effect model analysis was performed, otherwise, fixed-effect model analysis was applied. To investigate the high degree of heterogeneity, subgroup analyses were based on study type, age, sample size, type of surgery, type of sleep disturbance, the timing of sleep disturbance, and delirium assessment tool. In addition, meta-regression was used to explore the source of heterogeneity. Sensitivity analysis was performed for all models, and Begg’s test was used to test potential publication bias. P<0.05 was considered statistically significant. All reported P values are two-sided.

Results

Study selection and characteristics of included studies

After the English databases were searched according to the retrieval strategy, a total of 6,827 articles were identified. After duplicates were removed, 3,865 studies remained, and of them, 38 studies were screened for titles and abstracts. Finally, 18 articles (16-18,25-39) including 2,714 patients were enrolled, comparing 16 articles in the quantitative analysis, and 2 in the qualitative analysis. A summary of the search and selection process is depicted in Figure 1. Most of the included studies were of moderate to high quality (Table S1): 5 studies retrospective studies, and 11 prospective studies. Patients in 7 studies were undergoing cardiac surgery, in 5 studies they were undergoing orthopedic surgery, and in 4 studies it was other procedures. The sample size of 5 articles was <100, and that of 11 studies was ≥100. According to the type of sleep disturbance, patients were divided into 5 cases of OSA, 2 cases of insomnia, and 9 cases that did not indicate the specific type. There were 11 cases of sleep disturbance before surgery and 5 cases after surgery. The characteristics of included studies are listed in Tables 1,2.

Figure 1 Summary of the search and selection process.

Pooled analysis of effect of sleep disturbance on PD

Yildizeli et al. (26) reported that among the risk factors associated with PD after thoracic surgery, the factors influencing PD by univariate analysis included sleep disturbance (P=0.008). Jeong et al. (32) studied the risk factors for delirium in 247 prostate surgery patients and found that sleep disturbance was not significantly associated with the occurrence of PD (OR: 0.88; 95% CI: 0.3 to 2.6; P=0.811).

A total of 16 studies were included in the meta-analysis for quantitative analysis, and the heterogeneity test showed I²=60.7%, so a random-effect model was used. The result suggested that sleep disturbance was associated with an increased risk of PD (OR: 3.73; 95% CI: 2.34 to 5.96; P<0.001) (Table 3, Figure 2).

Figure 2 Forest plot of pooled analysis. OR, odds ratio; CI, confidence interval.

Subgroup analysis of effect of sleep disturbance on PD

Study design

The result for study design demonstrated that sleep disturbance increased the risk of PD in both retrospective (OR: 5.74; 95% CI: 3.04 to 10.84; P<0.001) and prospective studies (OR: 3.21; 95% CI: 1.77 to 5.81; P<0.001) (Table 3, Figure 3A).

Figure 3 Forest plots of subgroup analyses: (A) study design; (B) age; (C) sample size; (D) type of surgery; (E) type of sleep disturbance; (F) timing of sleep disturbance; (G) delirium assessment tool. OR, odds ratio; CI, confidence interval.

Age

Based on the mean age of the patients enrolled in the analysis, they were divided into <65 (6 articles) and ≥65 years (9 articles). The result showed sleep disturbance was associated with PD with OR: 6.07 (95% CI: 3.05 to 12.07; P<0.001) in patients <65 years, and OR= 2.90, (95% CI: 1.49 to 5.67, P=0.002) in patients ≥65 years (Table 3, Figure 3B).

Sample size

Results from the sample size analysis showed that no matter the sample size [<100 (OR: 3.93; 95% CI: 1.16 to 13.28; P=0.028); ≥100 (OR: 3.72; 95% CI: 2.21 to 6.26; P<0.001)], there was a high risk of PD in patients with sleep disturbance (Table 3, Figure 3C).

Type of surgery

In this study sleep disturbance was a potential risk factor for PD in patients undergoing cardiac (OR: 3.39; 95% CI: 1.36 to 8.45; P=0.009), orthopedic (OR: 3.94; 95% CI: 2.22 to 7.01; P<0.001), or other surgeries (OR: 4.96; 95% CI: 2.16 to 11.42; P<0.001) (Table 3, Figure 3D).

Type of sleep disturbance

Our analysis showed that OSA (OR: 2.01; 95% CI: 0.75 to 5.35; P=0.164) and insomnia (OR: 4.01; 95% CI: 0.64 to 25.20; P=0.139) were not risk factors for PD (Table 3, Figure 3E).

Timing of sleep disturbance

The result of our analysis indicated that both preoperative (OR: 2.80; 95% CI: 1.52 to 5.18; P=0.001) and postoperative (OR: 6.30; 95% CI: 3.79 to 10.47; P<0.001) sleep disturbances was associated with the risk of PD (Table 3, Figure 3F).

Delirium assessment tool

According to the delirium assessment tool used in the research, the Confusion Assessment Method (CAM) was used in 11 articles, the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) was used in 2 articles, and other tools were using in the remaining 3 articles. Sleep disturbance was a risk factor for PD no matter which delirium assessment tool was used: CAM (OR: 3.72; 95% CI: 2.00 to 6.92; P<0.001), DSM-IV (OR: 5.40; 95% CI: 1.60 to 18.25; P=0.007), and other tools (OR: 3.02; 95% CI: 1.22 to 7.48; P=0.017) (Table 3, Figure 3G).

Meta-regression analysis

To explore the source of heterogeneity, meta-regression was performed by study type, age, sample size, type of surgery, type of sleep disturbance, time of occurrence of sleep disturbance, and delirium assessment tool. The results showed that none of these factors was related to inter-study heterogeneity (P>0.05) (Table 4).

Sensitivity analysis and publication bias

Sensitivity results demonstrated that our study was robust and reliable. Publication bias was assessed using Begg’s test, which showed no publication bias in this pooled analysis (Z=0.14; P=0.893) (Table 3).

Discussion

PD can occur in any surgical patient and its occurrence has adverse effects on the prognosis of postoperative patients (40). Thus, it may be useful to identify potential influential factors. Our analyses demonstrated that in different age groups, and for various types of surgery, both preoperative and postoperative sleep disturbance increased the risk of PD. However, further subgroup analysis suggested that these findings were not conserved for OSA and insomnia as types of sleep disturbance.

A study by Evans et al. found that sleep disturbance on the first night after surgery was a predictor of subsequent delirium (41). Sleep polysomnographic measurements were taken the night before surgery in elderly hospitalized patients scheduled for elective major cardiac surgery and cardiopulmonary bypass suggest an association between longer sleep duration and PD (42). A study that recruited referrals with aortic stenosis undergoing first lifetime surgical aortic valve replacement reported that type II home sleep studies were a predictor of PD (15). Wang et al. found hospitalized sleep disturbances increased the incidence of PD (43). Another study demonstrated that reducing sleep disturbances in an ICU significantly reduced delirium in medical and surgical intensive care patients (44). Lu et al. found that strategies targeted at sleep promotion might help prevent PD (2), and Cho et al. found sleep disturbance strongly related to the development of PD in proximal femoral fracture patients aged 60 years or older (38). The exact mechanism connecting sleep disturbance and PD is still not well understood. Activated neuroinflammation and oxidative stress, impaired function of the blood-brain barrier and glymphatic pathway, decreased hippocampal brain-derived neurotrophic factor, adult neurogenesis, and sirtuin1 expression, as well as accumulated amyloid-beta proteins may be associated with PD in individuals with perioperative sleep disturbance (43). Because of the relationship between sleep quality and PD, the use of sleep deprivation prevention programs in hospital clinical nursing instruction may be critical.

Sleep-disordered breathing is rarely considered a potential risk factor for PD (18). Consistent with our finding, Wang et al. found no association between preoperative OSA, which is the most prevalent form of sleep-disordered breathing, and delirium prevalence (19). King et al. found that, after risk adjustment, there was no significant association between OSA and PD (20). However, a case report by Lombardi et al. independently published reports found that treatment for OSA was successful in alleviating delirium (45). It is important to note that case reports cannot exclude other predisposing factors; therefore, it is difficult to draw definitive conclusions about the relationship between OSA and delirium. Furthermore, OSA could be a less important risk factor for PD than previously believed. The literature draws a somewhat tenuous connection between OSA and postoperative adverse outcomes, with some studies finding (unadjusted) negative associations (20,46). The association between OSA and PD should be further studied with adjustment for confounding factors.

In a large-sample study, Martin et al. showed that individuals who developed PD after cardiac surgery had a greater future risk for stroke and death (47). Therefore, delirium should be approached as a disorder and given full attention. Given our finding of the relationship between sleep disturbance and the risk of PD, clinicians should advise patients and their families to actively cooperate with any sleep intervention before and after surgery. If they understand the positive effect of adequate sleep on disease treatment and rehabilitation, patients will be encouraged to establish good sleep habits.

There were some important limitations to this study. First, we did not control for environmental determinants of sleep such as noise or light, and anesthetic use due to limitations in the included studies. Second, the literature search has language bias since no non-English language databases were searched. Third, most of the included studies used “cases that did not indicate the specific type” to describe the sleep disturbance, making the clinical implications of the significant association between PD and sleep disturbance difficult. Large-scale investigations including more patients should be performed to further verify the effect of sleep disturbance on PD. Despite the limitations of this study, the results encourage future research aimed at addressing the above limitations and confirming or refuting the effects of sleep disturbance on PD.

Conclusions

Our results demonstrated that sleep disturbance may increase the risk of PD. The quality of sleep in patients undergoing surgery should be given attention. More research is needed to confirm the effect of sleep disturbance on PD.

Acknowledgments

Funding: None.

Footnote

Reporting Checklist: The authors have completed the MOOSE reporting checklist. Available at https://gs.amegroups.com/article/view/10.21037/gs-22-312/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-22-312/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: K. Brown)