Research Progress on Post-Stroke Depression Driven by Modern Therapies

脑卒中后抑郁(PSD)作为卒中后常见的情感障碍，其发病机制涉及神经递质紊乱、炎症激活及社会心理因素等多维度交互作用。传统治疗手段因疗效局限及副作用显著，故亟需探索现代化疗法的创新应用。本文基于近年研究进展，系统综述现代化疗法在PSD干预中的实际应用、优势以及挑战。研究表明，基于机器学习与神经影像的预测模型可精准识别高危人群，而数字疗法联合动机性访谈可显著改善患者焦虑及功能恢复。然而，现代化疗法仍面临大规模临床数据缺乏、机制解析不深及基层普及不足等挑战。未来需加强多组学研究与跨学科协作，推动PSD干预向精准化、智能化方向发展。Post-stroke depression (PSD) is a common emotional disorder after stroke. Its pathogenesis involves multiple dimensions of interaction such as neurotransmitter imbalance, inflammatory activation, and social psychological factors. Traditional treatment methods have limited efficacy and significant side effects, thus there is an urgent need to explore innovative applications of modern therapies. Based on recent research progress, this article systematically reviews the practical application, advantages, and challenges of modern therapies in the intervention of PSD. Studies have shown that prediction models based on machine learning and neuroimaging can accurately identify high-risk individuals, and digital therapy combined with motivational interviewing can significantly improve patients’ anxiety and functional recovery. However, modern therapies still face challenges such as a lack of large-scale clinical data, insufficient mechanism clarification, and insufficient grassroots dissemination. In the future, it is necessary to strengthen multi-omics research and interdisciplinary collaboration to promote the development of PSD intervention towards precision and intelligence.