Simple Risk-Score Model for In-Hospital Major Bleeding Based on Multiple Blood Variables in Patients with Acute Myocardial Infarction

2021 
Background: In-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 Results:  A 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 10000/μL (OR, 2.58), platelet count < 150000/μL (OR, 2.51), albumin level < 3.8 mg/dL (OR, 2.51), and estimated glomerular filtration rate < 60 mL/min/1.73 m 2 (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).  Conclusions: Our novel laboratory-based bleeding risk model could be useful for simple and objective prediction of in-hospital major bleeding events in patients with AMI
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