Abstract 4137169: Artificial Intelligence-Enabled Electrocardiography For The Prediction of Future Type 2 Diabetes Mellitus

医学 心电图 糖尿病 心脏病学 内科学 2型糖尿病 内分泌学
作者
Libor Pastika,Konstantinos Patlatzoglou,Ewa Sieliwończyk,Joseph Barker,Boroumand Zeidaabadi,Kathryn A. McGurk,Sadia Khan,Danilo P. Mandic,James S. Ware,Nicholas S. Peters,Daniel B. Kramer,Jonathan W. Waks,Arunashis Sau,Fu Siong Ng
出处
期刊:Circulation [Lippincott Williams & Wilkins]
卷期号:150 (Suppl_1)
标识
DOI:10.1161/circ.150.suppl_1.4137169
摘要

Background: Undiagnosed diabetes and prediabetes present a significant global health challenge. Artificial Intelligence-enabled electrocardiography (AI-ECG) has shown promise in identifying subtle ECG changes in a wide range of subclinical diseases. Opportunistic ECG screening could identify prediabetic patients, enabling early interventions to prevent T2DM and adverse cardiovascular events. Aims: To develop the AI-ECG Risk Estimator to diagnose prevalent T2DM and predict future T2DM (AIRE-DM) Methods: AIRE-DM was trained on a real-world secondary care cohort from Beth Israel Deaconess Medical Center (BIDMC) of 1,163,401 ECGs and externally validated in the UK Biobank (UKB, N = 65,606). AIRE-DM employs a residual neural network architecture with a discrete-time survival loss function. Results: AIRE-DM accurately identifies prevalent T2DM (AUROC: BIDMC – 0.712 (0.705-0.719), UKB - 0.731 (0.725 - 0.741) and predicts future T2DM (C-index: BIDMC - 0.666 (0.658-0.675), UKB 0.689 (0.663-0.715). In subjects without T2DM, the high-risk quartile shows a markedly increased risk of future T2DM (HR: BIDMC - 4.67 (4.01-5.45), UKB - 10.10 (5.87-17.40), adjusted for age and sex. Adding AIRE-DM to clinical risk factors in BIDMC and to the American Diabetes Association (ADA) score in the UKB significantly enhanced predictive accuracy for future T2DM (C-index improvement: BIDMC - 0.0359 (0.0354-0.0363), UKB: 0.0337 (0.0324-0.0350), continuous net reclassification index: BIDMC - 0.407 (0.360-0.445), UKB - 0.391 (0.259-0.503)). Using phenome- and genome-wide association studies, we identified biologically plausible associations for AIRE-DM, including glucose regulation, cardiac morphology, diastolic dysfunction, arterial stiffness and lipid metabolism. We identified variants adjacent to CASQ2 , TBX3 , NOS1AP , TKT , VGLL2 and PRDM6 , which are known regulators of cardiac morphology, arterial stiffness and glucose metabolism. Conclusion: AIRE-DM can predict future T2DM in non-diabetics and enhances T2DM risk prediction when integrated with clinical risk scores. Its application holds promise for early identification of individuals at high risk of T2DM, enabling early lifestyle and pharmacological interventions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
平凡完成签到,获得积分10
3秒前
4秒前
哈利波特完成签到,获得积分10
7秒前
菓小柒完成签到 ,获得积分10
7秒前
basil完成签到,获得积分10
8秒前
大橙子发布了新的文献求助10
8秒前
mammer应助超帅无色采纳,获得10
9秒前
helloworld完成签到,获得积分10
10秒前
海洋完成签到,获得积分10
10秒前
Hina完成签到,获得积分10
11秒前
ZH完成签到,获得积分10
14秒前
yyds完成签到,获得积分10
15秒前
量子星尘发布了新的文献求助10
17秒前
18秒前
唯梦完成签到 ,获得积分10
18秒前
詹姆斯哈登完成签到,获得积分10
21秒前
李健应助名字不好起采纳,获得10
23秒前
万历完成签到,获得积分10
23秒前
23秒前
林卷卷完成签到,获得积分10
24秒前
大葱鸭发布了新的文献求助10
26秒前
27秒前
李健应助南山无梅落采纳,获得10
27秒前
31秒前
赘婿应助大橙子采纳,获得10
33秒前
40秒前
我是大学霸完成签到,获得积分10
41秒前
随风完成签到,获得积分0
41秒前
yi完成签到 ,获得积分10
42秒前
lin完成签到,获得积分10
43秒前
huahua完成签到 ,获得积分10
43秒前
大橙子发布了新的文献求助10
46秒前
小黑完成签到,获得积分10
49秒前
ZY完成签到 ,获得积分10
52秒前
阿士大夫完成签到,获得积分0
52秒前
chai完成签到,获得积分10
52秒前
GUO完成签到,获得积分10
53秒前
111完成签到 ,获得积分10
54秒前
Llllll发布了新的文献求助200
55秒前
天下无马完成签到 ,获得积分10
56秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
徐淮辽南地区新元古代叠层石及生物地层 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
Handbook of Industrial Diamonds.Vol2 1100
Global Eyelash Assessment scale (GEA) 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 550
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4038157
求助须知:如何正确求助?哪些是违规求助? 3575869
关于积分的说明 11373842
捐赠科研通 3305650
什么是DOI,文献DOI怎么找? 1819255
邀请新用户注册赠送积分活动 892655
科研通“疑难数据库(出版商)”最低求助积分说明 815022