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

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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

acute myocardial infarctionAI-ECGartificial intelligenceelectrocardiogramMACHINE LEARNING ALGORITHMCHEST-PAIN PATIENTSVALIDATIONDIAGNOSISOUTCOMESSCORERISK
제목
Sex-Consistent Performance of an AI-Enabled ECG for Acute Myocardial Infarction: The ROMIAE Study
저자
Lee, Hak SeungKang, SoraKwon, Joon-myoungShin, Tae GunLee, YoungjooKim, Dong HoonChoi, Sung HyukCho, HanjinLee, Mi JinJeong, Ki YoungKim, Won YoungMin, Young GiHan, ChulYoon, Jae CholJung, EujeneKim, Woo JeongAhn, ChiwonSeo, Jeong YeolLim, Tae HoKim, Jae SeongSon, Jeong MinKim, Kyung SuKim, KyuseokLee, Min Sung
DOI
10.1016/j.jacadv.2026.102813
발행일
2026-06
유형
Article
저널명
JACC: Advances
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