Yifan Li,1,* Wei Qin,1,* Yitong Chen,2 Dongli Zhang,1 Yongchen Zhao1 

1Department of Integrative Traditional Chinese and Western Medicine, Affiliated Hospital of Hebei University, Baoding, Hebei, People’s Republic of China; 2Clinical Specialty of Integrated Chinese and Western Medicine, Hebei University, Baoding, Hebei, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Dongli Zhang; Yongchen Zhao, Department of Integrative Traditional Chinese and Western Medicine, Affiliated Hospital of Hebei University, No. 212 Yuhua East Road, Baoding City, Hebei Province, 071000, People’s Republic of China, Tel +86 0312 5981919, Email zhang_dongli@yeah.net; zhaoyongchen69@outlook.com

Objective: To investigate the prevalence and severity of depression in patients with ischaemic stroke and identify its associated factors using a cross-sectional design over a 6-month period.
Methods: This cross-sectional study included 499 patients with ischaemic stroke who met the diagnostic and inclusion criteria. Depression levels were assessed using the Hamilton Depression Rating Scale (HAMD). Data collection included demographic variables, clinical data and self-reported measures. Neurological deficits were assessed using the National Institutes of Health Stroke Scale (NIHSS), whereas activities of daily living (ADL) were evaluated using the ADL scale. Chi-squared tests and t-tests were used to compare the mild and moderate depression groups. Multiple logistic regression identified independent predictors of depression. The predictive effectiveness of risk factors was evaluated using receiver operating characteristic (ROC) curves.
Results: Of the 499 patients, 305 (61.1%) had mild depression and 194 (38.9%) had moderate depression, with a mean HAMD score of 15.27 ± 6.43. Significant differences were observed between groups in hypertension (p < 0.001), diabetes mellitus (p < 0.001), education level (p < 0.001), stroke (p = 0.037), ADL score (p < 0.001) and NIHSS score (p < 0.001). Logistic regression identified hypertension (odds ratio [OR] = 1.963), diabetes mellitus (OR = 4.126), lower education level (OR = 1.460), left-sided stroke (OR = 1.690), lower ADL scores (OR = 0.718) and higher NIHSS scores (OR = 1.213) as independent predictors of depression. The ROC analysis showed that NIHSS (area under the curve [AUC] = 0.797) and ADL (AUC = 0.741) scores were the most effective predictors.
Conclusion: Depression is common among patients with ischaemic stroke and is substantially influenced by vascular risk factors, education level, stroke , daily living abilities and neurological deficits. The NIHSS and ADL scores demonstrated strong predictive value in identifying patients at risk of depression.

Keywords: stroke, depression, multiple logistic regression