{"title":"Accuracy of the 0/1-Hour Algorithm for Diagnosing Myocardial Infarction in Patients With Atrial Fibrillation.","authors":"Yuhei Kojima, Kenji Inoue, Masayuki Shiozaki, Shun Sasaki, Chien-Chang Lee, Shuo-Ju Chiang, Satoru Suwa, Tohru Minamino","doi":"10.1253/circj.CJ-24-0811","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Patients with atrial fibrillation (AF) often present with symptoms similar to acute coronary syndrome (ACS), including chest pain and elevated levels of high-sensitivity cardiac troponin (hs-cTn). The 0/1-hour algorithm using hs-cTn is a rapid diagnostic tool endorsed by the European Society of Cardiology to rule out myocardial infarction (MI). However, because its effectiveness in patients with AF remains unclear, in this study we assessed the diagnostic accuracy of the 0/1-hour algorithm in patients with and without AF presenting with chest pain in the emergency department.</p><p><strong>Methods and results: </strong>We conducted a secondary analysis of the DROP-ACS cohort, including 1,333 patients from Japan and Taiwan, with AF in 10.3% of cases. We examined the algorithm's negative predictive value (NPV), sensitivity, positive predictive value (PPV), and specificity for ruling MI in or out. Patients with AF were more frequently placed in the observe group (54% vs. 34.9%, P<0.05) and less often in the rule-out group (24.1% vs. 44.6%, P<0.05). The NPV and sensitivity for ruling out MI were 100%, while the PPV and specificity were lower in patients with AF (60% and 89.7%, respectively).</p><p><strong>Conclusions: </strong>The 0/1-hour algorithm effectively ruled out MI in patients with AF, with high safety and accuracy. However, patients with AF are more likely to be stratified into the observe group, requiring further examination for final diagnosis.</p>","PeriodicalId":50691,"journal":{"name":"Circulation Journal","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Circulation Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1253/circj.CJ-24-0811","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Patients with atrial fibrillation (AF) often present with symptoms similar to acute coronary syndrome (ACS), including chest pain and elevated levels of high-sensitivity cardiac troponin (hs-cTn). The 0/1-hour algorithm using hs-cTn is a rapid diagnostic tool endorsed by the European Society of Cardiology to rule out myocardial infarction (MI). However, because its effectiveness in patients with AF remains unclear, in this study we assessed the diagnostic accuracy of the 0/1-hour algorithm in patients with and without AF presenting with chest pain in the emergency department.
Methods and results: We conducted a secondary analysis of the DROP-ACS cohort, including 1,333 patients from Japan and Taiwan, with AF in 10.3% of cases. We examined the algorithm's negative predictive value (NPV), sensitivity, positive predictive value (PPV), and specificity for ruling MI in or out. Patients with AF were more frequently placed in the observe group (54% vs. 34.9%, P<0.05) and less often in the rule-out group (24.1% vs. 44.6%, P<0.05). The NPV and sensitivity for ruling out MI were 100%, while the PPV and specificity were lower in patients with AF (60% and 89.7%, respectively).
Conclusions: The 0/1-hour algorithm effectively ruled out MI in patients with AF, with high safety and accuracy. However, patients with AF are more likely to be stratified into the observe group, requiring further examination for final diagnosis.
背景:房颤(AF)患者通常表现出与急性冠脉综合征(ACS)相似的症状,包括胸痛和高敏感性心肌肌钙蛋白(hs-cTn)水平升高。使用hs-cTn的0/1小时算法是欧洲心脏病学会认可的一种用于排除心肌梗死(MI)的快速诊断工具。然而,由于其在房颤患者中的有效性尚不清楚,在本研究中,我们评估了0/1小时算法在急诊科出现胸痛的房颤和非房颤患者中的诊断准确性。方法和结果:我们对DROP-ACS队列进行了二次分析,包括来自日本和台湾的1333例患者,房颤发生率为10.3%。我们检查了该算法的阴性预测值(NPV)、敏感性、阳性预测值(PPV)和排除MI的特异性。观察组房颤患者被放置的频率更高(54% vs. 34.9%)。结论:0/1小时算法有效地排除了房颤患者的心肌梗死,具有较高的安全性和准确性。然而,房颤患者更有可能被划分为观察组,需要进一步检查才能最终诊断。
期刊介绍:
Circulation publishes original research manuscripts, review articles, and other content related to cardiovascular health and disease, including observational studies, clinical trials, epidemiology, health services and outcomes studies, and advances in basic and translational research.