A Time-Insensitive Predictive Instrument for Acute Myocardial Infarction Mortality

This study develops a "time-insensitive" predictive instrument for acute myocardial infarction mortality that would be useful both as a real-time clinical decision aid in the emergency medical setting and also for retrospective assessment and comparison of medical care based on risk-adjusted mortality predictions. This was done using prospectively-collected data on 5,773 patients with chief complaints of chest pain or other symptoms suggesting acute cardiac ischemia who came to six New England hospitals over a 2-year period. In phase one, based upon 4,099 patients, multivariate logistic regression was used to develop the predictive instrument. In phase two, its accuracy and diagnostic performance were tested on an independent sample of 1,387 patients presenting with symptoms compatible with acute cardiac ischemia. Discrimination between patients who lived and those who died was reflected by receiver-operating characteristic (ROC) curve areas of 0.85, 0.80, and 0.76, respectively, for all emergency department study subjects regardless of final diagnosis, subjects who proved to be having acute cardiac ischemia, and subjects who proved to be having acute infarction. Good calibration was shown by the fact that the predicted mortality was found to not vary significantly from actual mortality rates across deciles of predicted probabilities from 0% to 100%. In phase three, based on all 945 study subjects with acute myocardial infarction, each of the six hospitals' actual mortality rates were compared to their rates predicted by the predictive instrument. Actual hospital mortality rates ranged from 9.9% to 19.3%, with one hospital having a significantly higher rate (P = 0.005) and two hospitals both). Predicted mortality rates ranged from 13.4% to 19.4%, with one hospital having a significantly higher predicted rate (P = 0.005) and two hospitals having significantly lower predicted rates (P = 0.04 and P = 0.03). Individual hospitals' differences between actual and predicted mortality ranged from -3.4% to +3.1% (all NS). When grouped by hospital type, the actual mortality rates were 14.9%, 17.3%, and 13.0%, respectively, for urban teaching, smaller city teaching, and rural nonteaching hospitals (all NS). The predicted mortality rates were 16.5%, 17.1%, and 13.6%, respectively, with the rate for rural nonteaching hospitals being significantly lower (P = 0.009). No hospital type had significant differences between their actual and predicted mortality rates (NS). The time-insensitive predictive instrument for acute infarction mortality shows potential for risk-adjusted studies of hospitals mortality for multihospital groups, hospital-to-hospital comparisons, and within-hospital assessment.(ABSTRACT TRUNCATED AT 400 WORDS)