Passive digital markers for Alzheimer's disease and other related dementias: A systematic evidence review

IF 4.5 2区 医学 Q1 GERIATRICS & GERONTOLOGY
Britain Taylor MBA, MSE, Cristina Barboi MD, MS, Malaz Boustani MD, MPH
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引用次数: 0

Abstract

Background

The timely detection of Alzheimer's disease and other related dementias (ADRD) is suboptimal. Digital data already stored in electronic health records (EHR) offer opportunities for enhancing the timely detection of ADRD by facilitating the development of passive digital markers (PDMs). We conducted a systematic evidence review to identify studies that describe the development, performance, and validity of EHR-based PDMs for ADRD.

Methods

We searched the literature published from January 2000 to August 2022 and reviewed cross-sectional, retrospective, or prospective observational studies with a patient population of 18 years or older, published in English that collected and interpreted original data, included EHR as a source of digital data, and had the primary purpose of supporting ADRD care. We extracted relevant data from the included studies with guidance from the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist and used the US Preventive Services Task Force criteria to appraise each study.

Results

We included and appraised 19 studies. Four studies were considered to have a fair quality, and none was considered to have a good quality. The functionality of the PDMs varied from detecting mild cognitive impairment, Alzheimer's disease or ADRD, to forecasting stages of ADRD. Only seven studies used a valid reference diagnostic method. Nine PDMs used only structured EHR data, and five studies provided complete information on the race and ethnicity of its population. The number of features included in the PDMs ranges from 10 to 853, and the PMDs used a variety of statistical and machine learning algorithms with various time-at-risk windows. The area under the curve (AUC) for the PDMs varied from 0.67 to 0.97.

Conclusion

Although we noted heterogeneity in the PDMs development and performance, there is evidence that these PDMs have the potential to detect ADRD at earlier stages.

阿尔茨海默病和其他相关痴呆的被动数字标记:系统证据综述
背景及时发现阿尔茨海默病和其他相关痴呆(ADRD)是不理想的。已经存储在电子健康记录(EHR)中的数字数据通过促进被动数字标记(pdm)的发展,为加强及时发现ADRD提供了机会。我们进行了系统的证据回顾,以确定描述基于ehr的pdm治疗ADRD的发展、性能和有效性的研究。方法我们检索了2000年1月至2022年8月发表的文献,回顾了18岁及以上患者群体的横断面、回顾性或前瞻性观察性研究,这些研究以英文发表,收集和解释原始数据,包括电子病历作为数字数据来源,主要目的是支持ADRD护理。我们根据预测模型研究系统评价的关键评价和数据提取清单的指导,从纳入的研究中提取相关数据,并使用美国预防服务工作组标准评估每项研究。结果我们纳入并评价了19项研究。四项研究被认为具有一般质量,没有一项研究被认为具有良好质量。pdm的功能各不相同,从检测轻度认知障碍、阿尔茨海默病或ADRD,到预测ADRD的阶段。仅有7项研究采用了有效的参考诊断方法。9个PDMs仅使用结构化的电子病历数据,5个研究提供了其人口种族和民族的完整信息。pdm中包含的特征数量从10到853不等,pmd使用了各种统计和机器学习算法,具有不同的时间风险窗口。曲线下面积(AUC)在0.67 ~ 0.97之间变化。结论:尽管我们注意到pdm的发展和表现存在异质性,但有证据表明这些pdm有可能在早期发现ADRD。
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来源期刊
CiteScore
10.00
自引率
6.30%
发文量
504
审稿时长
3-6 weeks
期刊介绍: Journal of the American Geriatrics Society (JAGS) is the go-to journal for clinical aging research. We provide a diverse, interprofessional community of healthcare professionals with the latest insights on geriatrics education, clinical practice, and public policy—all supporting the high-quality, person-centered care essential to our well-being as we age. Since the publication of our first edition in 1953, JAGS has remained one of the oldest and most impactful journals dedicated exclusively to gerontology and geriatrics.
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