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DOI 10.1016/j.jacc.2019.06.025

Медицинская библиотека · Journal of the American College of Cardiology · 2019

Predicting Major Adverse Events in Patients With Acute Myocardial Infarction.

Nestelberger Thomas, Boeddinghaus Jasper, Wussler Desiree, Twerenbold Raphael, Badertscher Patrick, Wildi Karin, Miró Òscar, López Beatriz, Martin-Sanchez F Javier, Muzyk Piotr, Koechlin Luca, Baumgartner Benjamin, Meier Mario, Troester Valentina, Rubini Giménez Maria, Puelacher Christian, du Fay de Lavallaz Jeanne, Walter Joan, Kozhuharov Nikola, Zimmermann Tobias, Gualandro Danielle M, Michou Eleni, Potlukova Eliska, Geigy Nicolas, Keller Dagmar I, Reichlin Tobias, Mueller Christian, APACE Investigators

СтатьяМногоцентровое исследованиеПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

BACKGROUND

Early and accurate detection of short-term major adverse cardiac events (MACE) in patients with suspected acute myocardial infarction (AMI) is an unmet clinical need.

OBJECTIVES

The goal of this study was to test the hypothesis that adding clinical judgment and electrocardiogram findings to the European Society of Cardiology (ESC) high-sensitivity cardiac troponin (hs-cTn) measurement at presentation and after 1 h (ESC hs-cTn 0/1 h algorithm) would further improve its performance to predict MACE.

METHODS

Patients presenting to an emergency department with suspected AMI were enrolled in a prospective, multicenter diagnostic study. The primary endpoint was MACE, including all-cause death, cardiac arrest, AMI, cardiogenic shock, sustained ventricular arrhythmia, and high-grade atrioventricular block within 30 days including index events. The secondary endpoint was MACE + unstable angina (UA) receiving early (≤24 h) revascularization.

RESULTS

Among 3,123 patients, the ESC hs-cTnT 0/1 h algorithm triaged significantly more patients toward rule-out compared with the extended algorithm (60%; 95% CI: 59% to 62% vs. 45%; 95% CI: 43% to 46%; p < 0.001), while maintaining similar 30-day MACE rates (0.6%; 95% CI: 0.3% to 1.1% vs. 0.4%; 95% CI: 0.1% to 0.9%; p = 0.429), resulting in a similar negative predictive value (99.4%; 95% CI: 98.9% to 99.6% vs. 99.6%; 95% CI: 99.2% to 99.8%; p = 0.097). The ESC hs-cTnT 0/1 h algorithm ruled-in fewer patients (16%; 95% CI: 14.9% to 17.5% vs. 26%; 95% CI: 24.2% to 27.2%; p < 0.001) compared with the extended algorithm, albeit with a higher positive predictive value (76.6%; 95% CI: 72.8% to 80.1% vs. 59%; 95% CI: 55.5% to 62.3%; p < 0.001). For 30-day MACE + UA, the ESC hs-cTnT 0/1 h algorithm had a higher positive predictive value for rule-in, whereas the extended algorithm had a higher negative predictive value for the rule-out. Similar findings emerged when using hs-cTnI.

CONCLUSIONS

The ESC hs-cTn 0/1 h algorithm better balanced efficacy and safety in the prediction of MACE, whereas the extended algorithm is the preferred option for the rule-out of 30-day MACE + UA. (Advantageous Predictors of Acute Coronary Syndromes Evaluation [APACE]; NCT00470587).

Для цитирования: Nestelberger Thomas, Boeddinghaus Jasper, Wussler Desiree, Twerenbold Raphael, Badertscher Patrick, Wildi Karin, Miró Òscar, López Beatriz, Martin-Sanchez F Javier, Muzyk Piotr, Koechlin Luca, Baumgartner Benjamin, Meier Mario, Troester Valentina, Rubini Giménez Maria, Puelacher Christian, du Fay de Lavallaz Jeanne, Walter Joan, Kozhuharov Nikola, Zimmermann Tobias, Gualandro Danielle M, Michou Eleni, Potlukova Eliska, Geigy Nicolas, Keller Dagmar I, Reichlin Tobias, Mueller Christian, APACE Investigators. Predicting Major Adverse Events in Patients With Acute Myocardial Infarction.. Journal of the American College of Cardiology. 2019. DOI: 10.1016/j.jacc.2019.06.025.

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