Simple risk-score model for in-hospital major bleeding based on multiple blood variables in patients with acute myocardial infarction

Abstract

BackgroundIn-hospital bleeding is associated with poor prognosis in patients with acute myocardial infarction (AMI). We sought to investigate whether a combination of pre-procedural blood tests could predict the incidence of in-hospital major bleeding in patients with AMI. Methods and resultsA total of 1684 consecutive AMI patients who underwent primary percutaneous coronary intervention (PCI) were recruited and randomly divided into derivation (n = 1010) and validation (n = 674) cohorts. A risk-score model was created based on a combination of parameters assessed on routine blood tests on admission. In the derivation cohort, multivariate analysis revealed that the following 5 variables were significantly associated with in-hospital major bleeding: hemoglobin level < 12 g/dL (odds ratio [OR], 3.32), white blood cell count >10,000/μL (OR, 2.58), platelet count <150,000/μL (OR, 2.51), albumin level < 3.8 mg/dL (OR, 2.51), and estimated glomerular filtration rate < 60 mL/min/1.73 m2 (OR, 2.31). Zero to five points were given according to the number of these factors each patient had. Incremental risk scores were significantly associated with a higher incidence of in-hospital major bleeding in both cohorts (P < 0.001). Receiver operating characteristic curve analysis of risk models showed adequate discrimination between patients with and without in-hospital major bleeding (derivation cohort: area under the curve [AUC], 0.807; 95% confidence interval [CI], 0.759–0.848; validation cohort: AUC, 0.793; 95% CI, 0.725–0.847). ConclusionsOur novel laboratory-based bleeding risk model could be useful for simple and objective prediction of in-hospital major bleeding events in patients with AMI.