ArticleJACC. Advances2026
Sex-Consistent Performance of an AI-Enabled ECG for Acute Myocardial Infarction: The ROMIAE Study.
Article in JACC. Advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05435391 (A Prospective, Multicenter, Observational Diagnostic Study to Externally Validate an Artificial Intelligence 12-lead Electrocardiogram Analysis Algorithm to Detect Patients With Acute Myocardial Infarction Who Visit Emergency Medical Center), which is not on this map. Not yet cited in PubMed.
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A Prospective, Multicenter, Observational Diagnostic Study to Externally Validate an Artificial Intelligence 12-lead Electrocardiogram Analysis Algorithm to Detect Patients With Acute Myocardial Infarction Who Visit Emergency Medical Center
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25 authors.
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Abstract
backgroundWomen 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.
objectivesThe 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.
methodsROMIAE (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.
resultsAmong 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.
conclusionsIn 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).
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