Background: Several electrocardiogram (ECG) criteria have been proposed to predict the location of the culprit occlusion in specific subsets of patients presenting with ST-segment elevation myocardial infarction (STEMI). The aim of this study was to develop, through an independent validation of currently available criteria, a comprehensive and easy-to-use ECG algorithm, and to test its diagnostic performance in real-world clinical practice. Methods: We analyzed ECG and angiographic data from 419 consecutive STEMI patients submitted to primary percutaneous coronary intervention over a one-year period, dividing the overall population into derivation (314 patients) and validation (105 patients) cohorts. In the derivation cohort, we tested >60 previously published ECG criteria, using the decision-tree analysis to develop the algorithm that would best predict the infarct-related artery (IRA) and its occlusion level. We further assessed the new algorithm diagnostic performance in the validation cohort. Results: In the derivation cohort, the algorithm correctly predicted the IRA in 88% of cases and both the IRA and its occlusion level (proximal vs mid-distal) in 71% of cases. When applied to the validation cohort, the algorithm resulted in 88% and 67% diagnostic accuracies, respectively. In a real-world comparative test, the algorithm performed significantly better than expert physicians in identifying the site of the culprit occlusion (P = .026 vs best cardiologist and P < .001 vs best emergency medicine doctor). Conclusions: Derived from an extensive literature review, this comprehensive and easy-to-use ECG algorithm can accurately predict the IRA and its occlusion level in all-comers STEMI patients.
A comprehensive and easy-to-use ECG algorithm to predict the coronary occlusion site in ST-segment elevation myocardial infarction
Fasolino, Alessandro;Savastano, Simone;Leonardi, Sergio;
2023-01-01
Abstract
Background: Several electrocardiogram (ECG) criteria have been proposed to predict the location of the culprit occlusion in specific subsets of patients presenting with ST-segment elevation myocardial infarction (STEMI). The aim of this study was to develop, through an independent validation of currently available criteria, a comprehensive and easy-to-use ECG algorithm, and to test its diagnostic performance in real-world clinical practice. Methods: We analyzed ECG and angiographic data from 419 consecutive STEMI patients submitted to primary percutaneous coronary intervention over a one-year period, dividing the overall population into derivation (314 patients) and validation (105 patients) cohorts. In the derivation cohort, we tested >60 previously published ECG criteria, using the decision-tree analysis to develop the algorithm that would best predict the infarct-related artery (IRA) and its occlusion level. We further assessed the new algorithm diagnostic performance in the validation cohort. Results: In the derivation cohort, the algorithm correctly predicted the IRA in 88% of cases and both the IRA and its occlusion level (proximal vs mid-distal) in 71% of cases. When applied to the validation cohort, the algorithm resulted in 88% and 67% diagnostic accuracies, respectively. In a real-world comparative test, the algorithm performed significantly better than expert physicians in identifying the site of the culprit occlusion (P = .026 vs best cardiologist and P < .001 vs best emergency medicine doctor). Conclusions: Derived from an extensive literature review, this comprehensive and easy-to-use ECG algorithm can accurately predict the IRA and its occlusion level in all-comers STEMI patients.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
