Prognostic Score for Acute Coronary Syndrome in a Private Terciary Hospital

BACKGROUND: Available predictive models for acute coronary syndromes (ACS) have limitations as they have been elaborated some years ago or limitations with applicability. OBJECTIVES: To develop scores for predicting adverse events in 30 days and 6 months in ST-segment elevation and non-ST-segment elevation ACS patients admitted to private tertiary hospital. METHODS: Prospective cohort of ACS patients admitted between August, 2009 and June, 2012. Our primary composite outcome for both the 30-day and 6-month models was death from any cause, myocardial infarction or re-infarction, cerebrovascular accident (CVA), cardiac arrest and major bleeding. Predicting variables were selected for clinical, laboratory, electrocardiographic and therapeutic data. The final model was obtained with multiple logistic regression and submitted to internal validation with bootstrap analysis. RESULTS: We considered 760 patients for the development sample, of which 132 had ST-segment elevation ACS and 628 non-ST-segment elevation ACS. The mean age was 63.2 ± 11.7 years, and 583 were men (76.7%). The final model to predict 30-day events is comprised by five independent variables: age ≥ 70 years, history of cancer, left ventricular ejection fraction (LVEF) < 40%, troponin I > 12.4 ng /ml and chemical thrombolysis. In the internal validation, the model showed good discrimination with C-statistic of 0.71. The predictors in the 6-month event final model are: history of cancer, LVEF < 40%, chemical thrombolysis, troponin I >14.3 ng/ml, serum creatinine>1.2 mg/dl, history of chronic obstructive pulmonary disease and hemoglobin < 13.5 g/dl. In the internal validation, the model had good performance with C-statistic of 0.69. CONCLUSION: We have developed easy to apply scores for predicting 30-day and 6-month adverse events in patients with ST-elevation and non-ST-elevation ACS.