世界的预测值落在AGELESS-MELoR队列中的指南算法
Soo Jin Sherry Lee1, Maw Pin Tan2, Sumaiyah Mat3
1Department of Medicine, Faculty of Medicine, University of Malaya 50603 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia.
Archives of gerontology and geriatrics
|June 15, 2024
概括
世界布指南 (WFG) 算法显示高特异性,但对于预测马来西亚老年人落的敏感性较低. 定期重新评估对于在不同人群中有效管理跌倒风险至关重要.
科学领域:
- 老年学是一门学科.
- 公共卫生 公共卫生
- 流行病学 流行病学
背景情况:
- 世界布指南 (WFG) 算法是为布风险分层开发的.
- 它在马来西亚等低收入和中等收入国家的适用性是不确定的,原因是不同的风险因素和资源限制.
研究的目的:
- 评估WFG风险分层算法在预测马来西亚社区居住的老年人中跌倒的有效性.
主要方法:
- 利用了马来西亚长者纵向研究 (MELR) 队列研究 (2013-2022) 的数据.
- 包括来自Klang Valley的55岁以上的参与者.
- 使用基线数据进行风险分层;使用第二,第三和第四波的后续数据评估落预测.
主要成果:
- 在预测跌倒时,WFG算法表现出高的特异性 (从78.4%到81.6%不等),但低的灵敏度 (从第2波的51.3%下降到第4波的26.0%下降).
- 随着时间的推移,在各个风险组 (低,中,高) 的个体中,跌倒的百分比越来越高.
结论:
- 在马来西亚的背景下,WFG算法具有高的特异性,但对于秋季预测的敏感性正在下降.
- 建议定期进行重新评估,以准确识别和管理老年人的跌倒风险,特别是在资源有限的环境中.
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