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Meta-Analysis
. 2024 Apr 10;19(4):e0297941.
doi: 10.1371/journal.pone.0297941. eCollection 2024.

Development of insomnia in patients with stroke: A systematic review and meta-analysis

Junwei Yang  1 , Aitao Lin  2 , Qingjing Tan  1 , Weihua Dou  1 , Jinyu Wu  1 , Yang Zhang  1 , Haohai Lin  1 , Baoping Wei  1 , Jiemin Huang  1 , Juanjuan Xie  1
Affiliations
Meta-Analysis

Development of insomnia in patients with stroke: A systematic review and meta-analysis

Junwei Yang et al. PLoS One. .

Abstract

Background and aim: Stroke is a serious threat to human life and health, and post-stroke insomnia is one of the common complications severely impairing patients' quality of life and delaying recovery. Early understanding of the relationship between stroke and post-stroke insomnia can provide clinical evidence for preventing and treating post-stroke insomnia. This study was to investigate the prevalence of insomnia in patients with stroke.

Methods: The Web of Science, PubMed, Embase, and Cochrane Library databases were used to obtain the eligible studies until June 2023. The quality assessment was performed to extract valid data for meta-analysis. The prevalence rates were used a random-efect. I2 statistics were used to assess the heterogeneity of the studies.

Results: Twenty-six studies met the inclusion criteria for meta-analysis, with 1,193,659 participants, of which 497,124 were patients with stroke.The meta-analysis indicated that 150,181 patients with stroke developed insomnia during follow-up [46.98%, 95% confidence interval (CI): 36.91-57.18] and 1806 patients with ischemic stroke (IS) or transient ischemic attack (TIA) developed insomnia (47.21%, 95% CI: 34.26-60.36). Notably, 41.51% of patients with the prevalence of nonclassified stroke developed insomnia (95% CI: 28.86-54.75). The incidence of insomnia was significantly higher in patients with acute strokes than in patients with nonacute strokes (59.16% vs 44.07%, P < 0.0001).Similarly, the incidence of insomnia was significantly higher in the patients with stroke at a mean age of ≥65 than patients with stroke at a mean age of <65 years (47.18% vs 40.50%, P < 0.05). Fifteen studies reported the follow-up time. The incidence of insomnia was significantly higher in the follow-up for ≥3 years than follow-up for <3 years (58.06% vs 43.83%, P < 0.05). Twenty-one studies used the Insomnia Assessment Diagnostic Tool, and the rate of insomnia in patients with stroke was 49.31% (95% CI: 38.59-60.06). Five studies used self-reporting, that the rate of insomnia in patients with stroke was 37.58% (95% CI: 13.44-65.63).

Conclusions: Stroke may be a predisposing factor for insomnia. Insomnia is more likely to occur in acute-phase stroke, and the prevalence of insomnia increases with patient age and follow-up time. Further, the rate of insomnia is higher in patients with stroke who use the Insomnia Assessment Diagnostic Tool.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Search strategy of PubMed.
Fig 2
Fig 2. Literature screening process and results.
Fig 3
Fig 3. Forest plot of the meta-analysis of prevalence of insomnia among stroke patients.
Fig 4
Fig 4. Forest plot of the meta-analysis of prevalence of insomnia among IS or TIA patients.
Fig 5
Fig 5. Forest plot of the meta-analysis of prevalence of insomnia among nonclassified stroke patients.
Fig 6
Fig 6. Forest plot of the meta-analysis of prevalence of insomnia among acute stroke stroke patients.
Fig 7
Fig 7. Forest plot of the meta-analysis of prevalence of insomnia among non-acute stroke patients.
Fig 8
Fig 8. Forest plot of the meta-analysis of prevalence of insomnia in patients of mean age ≥65 years with stroke patients.
Fig 9
Fig 9. Forest plot of the meta-analysis of prevalence of insomnia in patients of mean age <65 years with stroke patients.
Fig 10
Fig 10. Forest plot of the meta-analysis of prevalence of insomnia among patients with stroke with follow-up for ≥ 3years.
Fig 11
Fig 11. Forest plot of the meta-analysis of prevalence of insomnia among patients with stroke with follow-up for < 3years.
Fig 12
Fig 12. Forest plot of the subgroup analysis with assessment tool.
Fig 13
Fig 13. Forest plot of the subgroup analysis without assessment tool.
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MeSH terms

Grants and funding

This work was supported by Administration of Traditional Chinese medicine in guangxi, self-financing scientific research subject[grant numbers GXZYA20220072]; Natural Science Foundation of Guangxi[grant numbers 2023GXNSFAA026200]; Hospital scientific research project of the First Affiliated Hospital of Guangxi University of Traditional Chinese Medicine[grant numbers 2021QN008]; Guangxi University of Traditional Chinese Medicine research project[grant numbers 2022QN019]. This work was supported by Junwei YANG and Qingjing TAN.
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