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Retrospective Study
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World J Psychiatry. Jun 19, 2026; 16(6): 114616
Published online Jun 19, 2026. doi: 10.5498/wjp.v16.i6.114616
Association between vascular risk factor clustering and post-stroke depression
Song-Wang Qiu, Jia-Long Huang, Kai-Yan Lin, Chang-Wei Yu, Jie-Dong Zhao
Jie-Dong Zhao, Chang-Wei Yu, Jia-Long Huang, Song-Wang Qiu, Department of Neurology, The First Affiliated Hospital of Xiamen University, Xiamen 361000, Fujian Province, China
Kai-Yan Lin, The School of Clinical Medicine, Fujian Medical University, Fuzhou 361000, Fujian Province, China
Co-first authors: Jie-Dong Zhao and Chang-Wei Yu.
Co-corresponding authors: Jia-Long Huang and Song-Wang Qiu.
Author contributions: Zhao JD and Qiu SW contributed to the study conception and design; Zhao JD, Yu CW, Lin KY, and Huang JL contributed to data collection; Zhao JD and Yu CW contributed to data analysis and interpretation. The first draft of the manuscript was written by Zhao JD, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Institutional review board statement: This study was reviewed and approved by the Institutional Review Board of the First Affiliated Hospital of Xiamen University (No. 2025091649). All research procedures complied with the principles of the Declaration of Helsinki.
Informed consent statement: The requirement for signed informed consent was waived by the Ethics Committee of the First Affiliated Hospital of Xiamen University due to the retrospective nature of the study. All patient data were anonymized to protect confidentiality.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.
Corresponding author: Song-Wang Qiu, Department of Neurology, The First Affiliated Hospital of Xiamen University, No. 55 Zhenhai Road, Xiamen 361000, Fujian Province, China. 13599920433@163.com
Received: October 24, 2025
Revised: November 25, 2025
Accepted: February 2, 2026
Published online: June 19, 2026
Processing time: 216 Days and 1.8 Hours
Abstract
BACKGROUND

Among stroke patients, post-stroke depression (PSD) represents a frequent complication that substantially impacts neurological rehabilitation and quality of life. While vascular risk factor clustering might serve as a crucial predictor for PSD development, the specific mechanisms underlying its influence remain incompletely understood.

AIM

To examine how vascular risk factor clustering affects PSD development.

METHODS

This retrospective study investigation enrolled 110 patients with acute cerebral infarction who were admitted to our hospital’s neurology department between January 2022 and December 2024. Based on vascular risk factor clustering severity, participants were categorized into: Low-risk cohort (≤ 2 risk factors, n = 52) and high-risk cohort (≥ 3 risk factors, n = 58). The cutoff threshold of ≥ 3 vascular risk factors was determined through receiver operating characteristic curve analysis, which demonstrated an optimal balance between sensitivity (71.1%) and specificity (73.6%) for predicting PSD (Youden index = 0.447, area-under-curve = 0.753). The evaluated vascular risk factors encompassed hypertension, diabetes mellitus, dyslipidemia, atrial fibrillation, smoking history, alcohol consumption history, and coronary heart disease history. Depression assessment was performed using the Hamilton Depression Rating Scale (HAMD-17) at 3 months post-stroke, with PSD diagnosis established at HAMD-17 scores ≥ 17. The association between vascular risk factor clustering and PSD development was examined through logistic regression analysis.

RESULTS

The study included 110 patients with acute cerebral infarction (average age 67.3 ± 10.2 years, 58.2% males). PSD developed in 38 patients (34.5%) within the 3-month observation period, demonstrating significantly elevated mean HAMD-17 scores vs non-depressed individuals (20.3 ± 3.2 points vs 8.9 ± 2.8 points, P < 0.001). Two independent PSD risk factors were identified through multivariate logistic regression: Vascular risk factor clustering (≥ 3 factors) (odds ratio = 3.42, 95% confidence interval: 1.45-8.06, P = 0.005) and severe neurological impairment (National Institutes of Health Stroke Scale score ≥ 8) (odds ratio = 2.91, 95% confidence interval: 1.38-6.13, P = 0.005). The analysis revealed a clear dose-response association between accumulated vascular risk factors and depression severity (Spearman r = 0.418, P < 0.001), showing PSD incidence escalation from 14.3% among patients with 0-1 risk factors to 66.7% in those with ≥ 5 risk factors (P for trend < 0.001). At the 3-month assessment, the low-risk cohort demonstrated superior functional recovery, achieving favorable outcomes (Modified Rankin Scale: 0-2) in 73.1% compared to 51.7% in the high-risk cohort (P = 0.021). The prediction model exhibited strong discriminatory performance (C-statistic = 0.753), with sensitivity analyses validating the stability of these relationships across various diagnostic thresholds and patient subsets.

CONCLUSION

Multiple vascular risk factor clustering constitutes an independent predictor of PSD development. Individuals presenting with numerous vascular risk factors (≥ 3) demonstrate markedly elevated PSD risk relative to those with limited risk factors (≤ 2).

Keywords: Cerebral infarction; Post-stroke depression; Vascular risk factors; Risk factor clustering; Retrospective study

Core Tip: Post-stroke depression is a common neuropsychiatric complication that seriously affects recovery and quality of life in stroke survivors. This study demonstrates that clustering of multiple vascular risk factors, rather than individual factors, is an independent predictor of post-stroke depression. A clear dose-response relationship was observed, with depression risk rising progressively as the number of vascular risk factors increased. These findings highlight the importance of comprehensive vascular risk factor assessment in routine stroke care to enable early identification and timely intervention for high-risk patients.

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