Prediction of in-hospital ventricular fibrillation from admission data in acute myocardial infarction

We studied retrospectively 26 readily obtainable clinical and electrocardiographic variables in 22 consecutive patients who experienced primary ventricular fibrillation in association with an episode of acute myocardial infarction. Twenty-eight consecutive patients who had an uncomplicated course after acute myocardial infarction served as controls. The clinical profile of the two groups was similar except that patients who had primary ventricular fibrillation smoked more and had a higher peak creatinine phosphokinase level at the time of infarction. The data was evaluated using univariate and stepwise logistic regression analysis. This analysis demonstrated that patients who developed primary ventricular fibrillation had, on admission (1) more evidence of congestive heart failure (Killip classification), (2) a lower diastolic blood pressure, (3) greater ST-segment elevation, (4) a longer QTc interval, and (5) a less distinguishable J point on the electrocardiogram. This method of logistic analysis that utilizes easily obtainable hospital admission data serves as a preliminary model for prediction of the relative risk of primary ventricular fibrillation in a patient with acute myocardial infarction. The ability to identify patients at risk has important therapeutic implications.