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痴呆症风险预测模型有什么新鲜事? 一个更新的系统审查

Jacob Brain^1,2, Aysegul Humeyra Kafadar¹, Linda Errington³

¹Institute of Mental Health, School of Medicine, University of Nottingham, Innovation Park, Jubilee Campus, Nottingham, UK.

Dementia and geriatric cognitive disorders extra

|July 17, 2024

概括

新的痴呆风险预测模型正在迅速出现,自2014年以来已经开发了50多种. 虽然机器学习越来越多地被使用,但普遍适合和验证的模型对于广泛的临床使用仍然难以捉摸.

科学领域:

神经科学是一个神经科学.
流行病学流行病学
生物统计学生物统计学

背景情况:

识别患有痴呆症高风险的人对于临床护理,预防和临床试验资格至关重要.
自2010-2015年以来,痴呆症风险预测建模的使用大幅增加.

研究的目的:

更新先前关于痴呆风险建模的系统审查.
批判性地审查自2014年以来痴呆风险预测模型的新发展.

主要方法:

在 MEDLINE,Embase,Scopus 和 Web of Science 的系统文献搜索 (2014 年 3 月 - 2022 年 6 月).
包括基于人口的队列,电子健康记录和预测晚年痴呆症的模型.
专注于模型的歧视,校准和外部验证.

主要成果:

74项研究符合纳入标准,揭示了自2014年以来发表的50多个新的痴呆风险模型.
增加了机器学习的使用,并测试了450多个独特的预测变量.
在26%的研究中进行了外部验证,结果不一;在低收入和中等收入国家 (LMICs) 和少数群体中开发和验证的模型出现了.

结论:

痴呆症风险预测建模正在迅速发展,有新的分析技术和LMICs中的测试.
在推单一模型用于常规临床使用方面仍然存在挑战.
对于预防痴呆症而言,迫切需要一个强大,经过验证和广泛实施的风险预测模型.

关键词:

阿尔茨海默氏症是阿尔茨海默氏症的疾病痴呆症是一种痴呆症.事件发生率事件发生率风险预测风险预测统计模型统计模型

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