New Electrocardiographic Algorithm for the Diagnosis of Acute Myocardial Infarction in Patients With Left Bundle Branch Block

Autor: Andrea Di Marco, Marcos Rodriguez, Juan Cinca, Antoni Bayes‐Genis, Jose T. Ortiz‐Perez, Albert Ariza‐Solé, Jose Carlos Sanchez‐Salado, Alessandro Sionis, Jany Rodriguez, Beatriz Toledano, Pau Codina, Eduard Solé‐González, Monica Masotti, Joan Antoni Gómez‐Hospital, Ángel Cequier, Ignasi Anguera
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 9, Iss 14 (2020)
Druh dokumentu: article
ISSN: 2047-9980
DOI: 10.1161/JAHA.119.015573
Popis: Background Current electrocardiographic algorithms lack sensitivity to diagnose acute myocardial infarction (AMI) in the presence of left bundle branch block. Methods and Results A multicenter retrospective cohort study including consecutive patients with suspected AMI and left bundle branch block, referred for primary percutaneous coronary intervention between 2009 and 2018. Pre‐2015 patients formed the derivation cohort (n=163, 61 with AMI); patients between 2015 and 2018 formed the validation cohort (n=107, 40 with AMI). A control group of patients without suspected AMI was also studied (n=214). Different electrocardiographic criteria were tested. A total of 484 patients were studied. A new electrocardiographic algorithm (BARCELONA algorithm) was derived and validated. The algorithm is positive in the presence of ST deviation ≥1 mm (0.1 mV) concordant with QRS polarity, in any lead, or ST deviation ≥1 mm (0.1 mV) discordant with the QRS, in leads with max (R|S) voltage (the voltage of the largest deflection of the QRS, ie, R or S wave) ≤6 mm (0.6 mV). In both the derivation and the validation cohort, the BARCELONA algorithm achieved the highest sensitivity (93%–95%), negative predictive value (96%–97%), efficiency (91%–94%) and area under the receiver operating characteristic curve (0.92–0.93), significantly higher than previous electrocardiographic rules (P
Databáze: Directory of Open Access Journals