Predictors of Bleeding Risks and Episodes in Heart Patients

Objective: The aim of this study was to determine predictors of bleeding risks and episodes in heart patients. This study also determined the effect of demographic characteristics and comorbidities on the bleeding episodes in heart patients. Methods: A retrospective and observational study was done on a data collection form to obtain the required data. After adjusting confounders in logistic regression analysis model, (predicting likelihood of reporting bleeding risks and episodes), pure predictors of bleeding risks and episodes were determined. Descriptive and inferential statistics were applied using the Statistical Package for Social Sciences (SPSS) version 24.0. A p-value < 0.05 was considered statistically significant. Results: Overall, 220 patients’ data on data collection forms were collected in the study. Out of the total studied patients, around 56 were on warfarin, 47 on dabigatran, 67 on rivaroxaban and 50 on apixaban. In addition, age and presence of comorbidity were observed as the pure and strong predictors of bleeding risks and episodes among the studied patients. Conclusion: Age and presence of comorbidity were the pure and strong predictors of bleeding risks and episodes.