Predictive value of the combination of age, creatinine, and ejection fraction score and diabetes in patients with ST-segment elevation myocardial infarction undergoing percutaneous coronary intervention

Background: This study investigated whether the age, creatinine, and ejection fraction (ACEF) score [age (years) /ejection fraction (%) +1 (if creatinine>176 mu mol/L)] could predict 1-year outcomes following ST-segment elevation myocardial infarction after percutaneous coronary intervention, and whether accuracy could be improved by establishing novel ACEF-derived risk models. Methods: A total of 1146 patients were included. The study endpoint was 1-year major adverse cardio-cerebrovascular events, including all-cause death, nonfatal myocardial infarction, unplanned revascularization, and nonfatal stroke. Accuracy was defined with area under the curve by receiver-operating characteristic curve analysis. Results: The incidence of 1-year major adverse cardio-cerebrovascular event increased with the rising age, creatinine, and ejection fraction score tertiles (4.8%, 8.4%, and 15.2%, P < 0.001 for all). Higher ACEF score was significantly associated with an increased risk of the endpoint in overall (odds ratio = 3.75, 95% confidence interval, 2.44-5.77, P < 0.001) and in subgroups (all P < 0.05). The accuracy of the ACEF score was equivalent to the other complex risk scores. The combination of ACEF, and diabetes (ACEF-diabetes score) yielded a superior discriminatory ability than the original ACEF score (increase in C-statistic from 0.67 to 0.71, P = 0.048; continuous net reclassification improvement = 51.9%, 95% confidence interval, 33.4-70.5%, P < 0.001; integrated discrimination improvement = 0.020, 95% confidence interval, 0.011-0.030, P < 0.001). Conclusions: The simplified ACEF score performed well in predicting 1-year outcomes in ST-segment elevation myocardial infarction patients undergoing percutaneous coronary intervention. The novel ACEF-diabetes score provided a better predictive value and thus may help stratify high-risk patients and potentially facilitate decision making.