Sex-Consistent Performance of an AI-Enabled ECG for Acute Myocardial Infarction The ROMIAE Study

  • Lee, Hak Seung; 
  • Kang, Sora; 
  • Kwon, Joon-myoung; 
  • Shin, Tae Gun; 
  • Lee, Youngjoo; 
  • ... Choi, Sung Hyuk; 
  • 외 18명
Citations

WEB OF SCIENCE

0
Citations

SCOPUS

0

초록

Background Women with suspected acute myocardial infarction (AMI) are at increased risk of delayed or missed diagnosis. Artificial intelligence-enabled electrocardiogram (AI-ECG) may support earlier AMI detection, but prospective evidence for sex-consistent performance and rule-out safety is limited. Objectives The purpose of this study was to evaluate sex-stratified diagnostic performance, rule-out safety, and phenotype robustness of an AI-ECG for AMI in a prospective, multicenter emergency department cohort. Methods ROMIAE (Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis) was a prospective external validation study at 18 centers in South Korea. Adults with suspected AMI were enrolled. AI-ECG analyzed initial ECGs using prespecified risk thresholds. Diagnostic performance was assessed using the area under the receiver-operating characteristic curve. Rule-out safety was evaluated by sensitivity, negative predictive value, and missed AMI rate at the low-risk cutoff. All analyses were sex-stratified, with prespecified subgroup analyses. Results Among 8,493 patients, 3,186 were women. AI-ECG demonstrated comparable discrimination in women and men (area under the receiver-operating characteristic curve 0.875 [95% CI: 0.853-0.896] vs 0.871 [95% CI: 0.858-0.883]). At the prespecified low-risk cutoff, rule-out sensitivity was 98.8% (95% CI: 97.0-99.5) in women and 99.8% (95% CI: 99.4-100.0) in men, with high negative predictive value (99.2% [95% CI: 97.9-99.7] in women and 99.1% [95% CI: 96.7-99.7] in men) and low missed AMI rates (<1% in both sexes). Performance remained stable across ST-segment elevation and non-ST-segment elevation myocardial infarction, without degradation in women. Conclusions In a prospective, multicenter emergency department cohort, AI-ECG demonstrated sex-consistent diagnostic performance and preserved rule-out safety for AMI. Further validation and implementation studies are warranted. (ROMIAE [Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis] Trial; NCT05435391)

키워드

AI-ECG; artificial intelligence; electrocardiogram; acute myocardial infarction; MACHINE LEARNING ALGORITHM; CHEST-PAIN PATIENTS; VALIDATION; DIAGNOSIS; OUTCOMES; SCORE; RISK
제목
Sex-Consistent Performance of an AI-Enabled ECG for Acute Myocardial Infarction The ROMIAE Study
저자
Lee, Hak Seung; Kang, Sora; Kwon, Joon-myoung; Shin, Tae Gun; Lee, Youngjoo; Kim, Dong Hoon; Choi, Sung Hyuk; Cho, Hanjin; Lee, Mi Jin; Jeong, Ki Young; Kim, Won Young; Min, Young Gi; Han, Chul; Yoon, Jae Chol; Jung, Eujene; Kim, Woo Jeong; Ahn, Chiwon; Seo, Jeong Yeol; Lim, Tae Ho; Kim, Jae Seong; Son, Jeong Min; Kim, Kyung Su; Kim, Kyuseok; Lee, Min Sung
DOI
10.1016/j.jacadv.2026.102813
발행일
2026-06
유형
Article
저널명
JACC: Advances
권
5
호
6