基于机器学习的风险评分与退伍军人转变为痴呆症有关。

IF 3.1 3区 医学 Q2 NEUROSCIENCES
Karl Brown, Andrew Shutes-David, Katie Wilson, Yijun Shao, Mark Logue, Qing T Zeng, Debby W Tsuang
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引用次数: 0

摘要

我们之前通过将自然语言处理和机器学习(ML)应用于退伍军人健康管理局的电子健康记录,开发了美国黑人和白人退伍军人(BA和WA)未确诊的阿尔茨海默病和相关痴呆(ADRD)的血统特异性风险评分。使用盲法手工图表回顾,我们确定了在评分产生时,ADRD风险评分与可能的ADRD诊断之间的关联。然而,尚不清楚这些评分是否与未来的ADRD诊断和死亡率有关。目的评价无ADRD诊断的BA和WA退伍军人的ADRD风险评分是否与随后的ADRD发病率和全因死亡率相关。方法进行生存分析,评估基线ADRD风险评分与ADRD诊断或死亡时间之间的关系。病因特异性Cox比例风险模型,将死亡视为竞争风险,用于估计风险比(hr)和95%置信区间(ci)。对BA和WA退伍军人按种族分层并分别进行分析。结果较高的ADRD风险评分与发生ADRD诊断的风险增加(HR = 1.98, 95% CI: 1.72-2.27; HR = 2.13, 95% CI: 1.79-2.54)和死亡率(HR = 1.52, 95% CI: 1.40-1.65; HR = 1.55, 95% CI: 1.42-1.69)显著相关。结论除了识别未确诊病例外,ml衍生的ADRD风险评分与未来发生ADRD的风险增加和死亡率相关,这支持了其在早期发现和预后方面的潜在效用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning-based risk scores are associated with conversion to dementia in Veterans.

BackgroundWe previously developed ancestry-specific risk scores for undiagnosed Alzheimer's disease and related dementias (ADRD) in Black and White American (BA and WA) Veterans by applying natural language processing and machine learning (ML) to Veterans Health Administration electronic health records. Using blinded manual chart reviews, we identified an association between ADRD risk scores and probable ADRD diagnosis at the time the scores were generated. However, it was unclear whether these scores were associated with future ADRD diagnoses and mortality.ObjectiveTo evaluate whether ADRD risk scores are associated with subsequent ADRD incidence and all-cause mortality among BA and WA Veterans without a prior ADRD diagnosis.MethodsWe conducted survival analyses to assess the association between baseline ADRD risk scores and time to either ADRD diagnosis or death. Cause-specific Cox proportional hazards models, treating death as a competing risk, were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Analyses were stratified by race and conducted separately for BA and WA Veterans.ResultsHigher ADRD risk scores were significantly associated with increased risk of developing an ADRD diagnosis (HR = 1.98, 95% CI: 1.72-2.27 for BAs; HR = 2.13, 95% CI: 1.79-2.54 for WAs) and mortality (HR = 1.52, 95% CI: 1.40-1.65 for BAs; HR = 1.55, 95% CI: 1.42-1.69 for WAs).ConclusionsIn addition to identifying undiagnosed cases, ML-derived ADRD risk scores are associated with increased risks of developing future ADRD and mortality, which supports their potential utility for both early detection and prognosis.

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来源期刊
Journal of Alzheimer's Disease
Journal of Alzheimer's Disease 医学-神经科学
CiteScore
6.40
自引率
7.50%
发文量
1327
审稿时长
2 months
期刊介绍: The Journal of Alzheimer''s Disease (JAD) is an international multidisciplinary journal to facilitate progress in understanding the etiology, pathogenesis, epidemiology, genetics, behavior, treatment and psychology of Alzheimer''s disease. The journal publishes research reports, reviews, short communications, hypotheses, ethics reviews, book reviews, and letters-to-the-editor. The journal is dedicated to providing an open forum for original research that will expedite our fundamental understanding of Alzheimer''s disease.
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