Prevalence and Predictive factors of Post-Stroke Depression in Patients with Acute Cerebral Infarction.

Abstract

Objective: Acute cerebral infarction (ACI) has a high mortality and disability, which brings a heavy burden to the medical and health system. This study aims to discover the clinical prevalence of post-stroke depression (PSD) in patients with ACI, explore the predictive factors leading to this complication, and provide more evidence for better identification of PSD in clinic.

Methods: From April 2021 to April 2023, this retrospective study selected 166 ACI patients as the research subjects, collected clinical symptoms and laboratory indicators at baseline, and observed the prevalence of PSD using the Hamilton depression scale 17 and the diagnostic and statistical manual of mental disorders. Multiple logistic regression analysis was adopted to explore the predictive factors of PSD in patients with ACI.

Results: The total incidence of PSD was 35.54% in 166 patients with ACI. The score of National Institute of Health Stroke Scale (NIHSS), the score of daily life ability scale (ADL), and homocysteine (Hcy) level in the PSD group were higher than non-PSD group (P _NIHSS < .001, P _ADL < .001, P _Hcy = .001). Multiple logistic regression analysis showed that high Hcy levels, NIHSS scores, and ADL scores were independent risk factors for PSD (P _Hcy =.038, P _NIHSS =.002, P _ADL <.001). The receiver operating characteristic (ROC) curve showed that areas under curve (AUC) = 0.894, standard error^a = 0.025, progressive significance^b <.001, 95% CI = 0.845-0.943, cut-off value = 0.520, sensitivity = 91.60%, specificity = 74.60%, and Hosmer-Lemeshow goodness-of-fit test P = .246, suggesting that ROC curve has a certain clinical predictive efficacy.

Conclusion: The prevalence of early PSD in patients with ACI is relatively high. Homocysteine levels, NIHSS scores and ADL scores may be independent risk factors for PSD, and targeted clinical intervention should be implemented for the above factors.