An algorithm for the differentiation of the infarct territory in difficult to discern electrocardiograms

Autor: Bozbeyoğlu, E., Aslanger, E., Yıldırımtürk, Ö., Şimşek, B., Karabay, C.Y., Türer, A., Değertekin, M.
Přispěvatelé: Bozbeyoğlu, E., Aslanger, E., Yıldırımtürk, Ö., Şimşek, B., Karabay, C.Y., Türer, A., Değertekin, M., Yeditepe Üniversitesi
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Popis: Background: In a minority of the patients presenting with ST-segment elevation (STE) myocardial infarction (MI), electrocardiogram (ECG) may show a balanced STE in both anterior and inferior lead groups and may cause diagnostic confusion about involved myocardial territory. In this study, we sought ECG clues which may facilitate discriminating (1) MI location and then (2) culprit artery in patients with difficult-to-discern ECGs. Material and methods: Consecutive patients with the diagnosis of STEMI were scanned and patients with ECGs displaying both anterior and inferior STE were enrolled. ECGs with obvious ST elevation in either lead group and reciprocal ST-segment depression were excluded. Predictive power of several ECG variables has been analyzed and an algorithm has been constructed. Results: A total of 959 STEMI cases were scanned, the final study population was consisted of 114 patients. Our algorithm for locating MI territory had a sensitivity, specificity, positive and negative predictive value of 72.1%, 92.5%, 91.7% and 74.2% for inferior versus anterior location, respectively (P < 0.001, ? = 0.652). As anterior MI was strictly reserved for left anterior descending (LAD) artery occlusion, these diagnostic values were also valid for discriminating circumflex artery [Cx]/right coronary artery [RCA] versus LAD as the culprit artery. In patients classified as having inferior MI, an STE in lead III greater than STE in lead II favored RCA over Cx as the culprit artery with a sensitivity, specificity, positive and negative predictive value of 97%, 46.6%, 80% and 87.5%, respectively (P < 0.001; ? = 0.544). Conclusion: Our algorithm can be used in difficult-to-discern ECGs for defining involved myocardial territory and culprit artery. © 2018 Elsevier Inc.
Databáze: OpenAIRE