抑郁症的动态模式及其与中风的关联:来自CHARLS,ELSA和HRS的见解
Zongren Zhao1, Siyuan Cheng2, Shun Li3
1Department of Neurology, Ulm university, Ulm, Germany.
International journal of surgery (London, England)
|November 10, 2025
概括
在老年人中,持续高或增加的抑郁症状显著增加中风风险. 对这些抑郁轨迹的监测和干预可以预防中风.
科学领域:
- 老年学是一门学科.
- 神经学 神经学
- 精神病学是一个精神病学.
背景情况:
- 抑郁症是老年人中风的重要危险因素.
- 以前的研究经常使用单个抑郁症测量方法,限制了对动态症状变化的理解.
- 研究一直局限于单一队列,影响了概括性.
研究的目的:
- 分析了三个大型的国际老年群体的抑郁症状轨迹.
- 调查不同抑郁轨迹与随后的中风风险之间的关联.
主要方法:
- 利用了来自健康与退休研究 (HRS),英国老龄化纵向研究 (ELSA) 和中国健康与退休纵向研究 (CHARLS) 的数据.
- 每两年使用流行病学研究中心抑郁症量表 (CES-D) 评估抑郁症症状.
- 采用基于规则的轨迹建模来识别四种模式:没有,减少,增加和持续高症状. 通过自我报告或医疗记录确定中风事件. 后勤回归模型估计了因混因素而调整的中风风险 (率).
主要成果:
- 与"没有"症状组相比",持续高"抑郁症状轨迹在所有队列中显示出明显增加的中风风险 (例如,CHARLS的OR2.56,ELSA的OR2.96,HRS的OR1.56).
- "下降"的轨迹与中风风险没有显著关联.
- "增加"的轨迹与ELSA和HRS队列中中风风险的适度增加有关.
结论:
- 在老年人中,持续高或增加的抑郁症状与中风风险大幅增加有关.
- 通过持续监测和早期干预来准这些高风险的抑郁轨迹可能是一个新的初级中风预防策略.
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