Nonlinear dose-response effects of exercise interventions on post-stroke depression: a systematic review and meta-analysis.

To systematically evaluate the effects of exercise interventions on post-stroke depression (PSD) and to clarify the dose-response relationship between physical activity dosage and depressive symptoms in individuals with PSD.

A structured and comprehensive search was conducted in PubMed, Web of Science, Embase, Scopus, and the Cochrane Library. Restricted cubic spline models were applied to examine the dose-response association between physical activity dosage and depressive symptoms in PSD.

A total of 27 publications comprising 31 randomized controlled trials were included, involving 2,247 participants. The meta-analysis indicated that exercise intervention was associated with a modest improvement in depressive symptoms among patients with PSD [SMD = -0.15, 95% CI (-0.23, -0.07), p < 0.01], with moderate heterogeneity (I 2 = 41.9%). Dose-response analysis revealed a non-linear association between exercise dosage and symptom improvement, with the greatest apparent benefit observed at approximately 801 MET-min/week. Subgroup analyses suggested that more favorable improvements were more commonly observed in interventions characterized by resistance training [SMD = -0.55, 95% CI (-0.85, -0.25)], a frequency of 1-2 sessions per week [SMD = -0.41, 95% CI (-0.67, -0.15)], a session duration of ≤30 min [SMD = -0.44, 95% CI (-0.70, -0.19)], and an intervention duration of 9-12 weeks [SMD = -0.16, 95% CI (-0.27, -0.05)].

Moderate-dose exercise intervention, approximately 801 MET-min/week, was associated with a modest improvement in post-stroke depressive symptoms. These findings provide a reference for optimizing exercise dosage and informing individualized prescription strategies for patients with PSD.

https://www.crd.york.ac.uk/PROSPERO/view/CRD420251167322, identifier (CRD420251167322).
Cardiovascular diseases
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Care/Management
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Authors

Liu Liu, Gao Gao, Wang Wang, Yang Yang, Liu Liu, Wu Wu, Liang Liang, Shao Shao, Zhang Zhang, Kang Kang, Liu Liu
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