A novel electrocardiogram-based model for prediction of dementia—The Atherosclerosis Risk in Communities (ARIC) study

IF 1.3 4区 医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
Deling Chen , Yuchen Yao , Ethan D. Moser , Wendy Wang , Elsayed Z. Soliman , Thomas Mosley , Wei Pan
{"title":"A novel electrocardiogram-based model for prediction of dementia—The Atherosclerosis Risk in Communities (ARIC) study","authors":"Deling Chen ,&nbsp;Yuchen Yao ,&nbsp;Ethan D. Moser ,&nbsp;Wendy Wang ,&nbsp;Elsayed Z. Soliman ,&nbsp;Thomas Mosley ,&nbsp;Wei Pan","doi":"10.1016/j.jelectrocard.2024.153832","DOIUrl":null,"url":null,"abstract":"<div><h3>Aim</h3><div>Create an ECG-based model to predict dementia and compare its performance with the existing Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) model.</div></div><div><h3>Methods and Results</h3><div>Participants without prevalent dementia in the Atherosclerosis Risk in Communities study were studied. Visit 4 (V4) (1996–98, mean age, 62 years) and V5 (2011–13, mean age, 75 years) were used as baselines. Incident dementia cases were adjudicated through 2019. We created parsimonious ECG models by using Cox regression with a backward selection method. C-statistic (95 % CI) of the ECG-based model (two or three ECG variables and age) was higher than the CAIDE model (seven variables) at V4 (0.72 [0.71–0.74] vs. 0.67 [0.66–0.68]) and V5 (0.70 [0.68–0.72] vs. 0.64 [0.62–0.66]). The ECG-based model was well calibrated, but the CAIDE model was poorly calibrated at V4 (<em>P</em> &lt; 0.001).</div></div><div><h3>Conclusion</h3><div>For middle-aged and older adults, a novel ECG-based model has good discrimination that is superior to the CAIDE model in predicting dementia. Since ECG variables are readily obtainable, the ECG-based model will be easy to adopt clinically.</div></div>","PeriodicalId":15606,"journal":{"name":"Journal of electrocardiology","volume":"88 ","pages":"Article 153832"},"PeriodicalIF":1.3000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of electrocardiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022073624003029","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

Aim

Create an ECG-based model to predict dementia and compare its performance with the existing Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) model.

Methods and Results

Participants without prevalent dementia in the Atherosclerosis Risk in Communities study were studied. Visit 4 (V4) (1996–98, mean age, 62 years) and V5 (2011–13, mean age, 75 years) were used as baselines. Incident dementia cases were adjudicated through 2019. We created parsimonious ECG models by using Cox regression with a backward selection method. C-statistic (95 % CI) of the ECG-based model (two or three ECG variables and age) was higher than the CAIDE model (seven variables) at V4 (0.72 [0.71–0.74] vs. 0.67 [0.66–0.68]) and V5 (0.70 [0.68–0.72] vs. 0.64 [0.62–0.66]). The ECG-based model was well calibrated, but the CAIDE model was poorly calibrated at V4 (P < 0.001).

Conclusion

For middle-aged and older adults, a novel ECG-based model has good discrimination that is superior to the CAIDE model in predicting dementia. Since ECG variables are readily obtainable, the ECG-based model will be easy to adopt clinically.
一种新的基于心电图的痴呆预测模型——社区动脉粥样硬化风险(ARIC)研究
建立一个基于心电图的模型来预测痴呆,并将其与现有的心血管危险因素、衰老和痴呆(CAIDE)模型进行比较。方法和结果对社区动脉粥样硬化风险研究中无流行痴呆的参与者进行研究。随访4 (V4)(1996-98年,平均年龄62岁)和随访5(2011-13年,平均年龄75岁)作为基线。到2019年为止,对偶发性痴呆案件进行了判决。采用Cox回归和逆向选择方法建立了简洁的心电模型。基于ECG的模型(2个或3个ECG变量和年龄)的c -统计量(95% CI)在V4(0.72[0.71-0.74]比0.67[0.66-0.68])和V5(0.70[0.68-0.72]比0.64[0.62-0.66])高于CAIDE模型(7个变量)。基于心电图的模型校准良好,但CAIDE模型在V4时校准较差(P <;0.001)。结论对于中老年人,基于脑电图的新模型在预测痴呆方面具有较好的辨别力,优于CAIDE模型。由于心电图变量容易获得,因此基于心电图的模型易于临床应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of electrocardiology
Journal of electrocardiology 医学-心血管系统
CiteScore
2.70
自引率
7.70%
发文量
152
审稿时长
38 days
期刊介绍: The Journal of Electrocardiology is devoted exclusively to clinical and experimental studies of the electrical activities of the heart. It seeks to contribute significantly to the accuracy of diagnosis and prognosis and the effective treatment, prevention, or delay of heart disease. Editorial contents include electrocardiography, vectorcardiography, arrhythmias, membrane action potential, cardiac pacing, monitoring defibrillation, instrumentation, drug effects, and computer applications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信