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与社区老年人跌倒风险相关的因素:决策树分析
Kenneth N K Fong1, Raymond C K Chung1, Patrick P C Sze2
1Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong SAR.
Digital health
|June 16, 2023
概括
决策树分析确定了老年人意外跌倒的关键因素,包括移动性测试,慢性疾病和药物使用. 这有助于为社区居住的老年人开发有效的摔倒查工具.
科学领域:
- 老年学是指老年学的学科.
- 公共卫生 公共卫生
- 生物统计学 生物统计学
背景情况:
- 意外跌倒对居住在社区的老年人构成重大风险,影响他们的健康和独立性.
- 有效的摔倒查工具对于早期干预和预防策略至关重要.
研究的目的:
- 确定香港社区老年人意外跌倒的预测属性.
- 应用决策树分析来开发秋季查模型.
主要方法:
- 一项涉及香港1151名老年人 (平均年龄74.8岁) 的横截面研究.
- 数据被分为训练 (70%) 和测试 (30%) 组,用于决策树分析.
- 对于失败者,室内失败者和室外失败者,生成了三个决策树模型.
主要成果:
- 观察到20%的1年患病率下降.
- 在性别,行走辅助器的使用,慢性疾病 (骨质疏松症,抑郁症) 和功能测试 (定时启动和启动,功能范围) 中发现了显著差异.
- 发现的关键预测因素包括定时启动和启动,功能范围,BMI,高血压,骨质疏松症和药物数量,模型准确度从77.40%到89.44%.
结论:
- 决策树分析为老年人查中临床算法提供了有价值的框架.
- 这种方法促进了基于实用程序的决策,用于使用监督机器学习检测下降风险.
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