评估10/66痴呆症分类算法用于国际比较分析与美国的痴呆症分类算法
Jorge J Llibre Guerra1, Jordan Weiss2, Jing Li3
1Department of Neurology, Washington University in St. Louis, St. Louis, USA.
American journal of epidemiology
|January 2, 2025
概括
在低收入国家验证的10/66痴呆症分类算法,准确地识别了美国人口中的痴呆症. 这支持全球痴呆症风险因素比较.
科学领域:
- 神经科学是一个神经科学.
- 流行病学 流行病学
- 老年学是指老年学的学科.
背景情况:
- 跨国痴呆症患病率研究至关重要,但由于各种分类方法存在障碍.
- 10/66算法是低收入和中等收入国家 (LMICs) 验证的痴呆症分类工具.
研究的目的:
- 在美国适应和验证10/66算法用于痴呆症分类. 老龄化,人口统计和记忆研究 (ADAMS).
- 评估修改后的10/66算法的性能与美国现有的痴呆症分类方法相比.
主要方法:
- 将可比的10/66算法项目映射到ADAMS数据中.
- 使用ADAMS临床诊断和k倍交叉验证重新训练了10/66算法.
- 将修改后的10/66算法的精度和教育梯度估计与其他四个ADAMS验证的算法进行了比较.
主要成果:
- 经过修改的10/66算法在ADAMS.中显示出高灵敏度 (87%) 和特异性 (93%).
- 它在痴呆症分类准确度方面表现优于四个比较算法.
- 所有算法,包括修改后的10/66,都倾向于高估痴呆症的教育梯度.
结论:
- 修改后的10/66算法是美国痴呆症分类的可靠工具.
- 这种验证有助于更准确地在美国和LMICs之间进行痴呆风险因素的跨国比较.
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