DEVELOPMENT OF A PREDICTION TOOL FOR THE ASSESSMENT OF RISKS ASSOCIATED WITH ACENOCOUMAROL

Abstract

Objective: To develop a statistical predictive model to ensure the safest use of oral anticoagulant (Acenocoumarol) therapy. Methods: It is a retrospective observational single-center study done at PSG Hospitals in Coimbatore, Tamilnadu, India. The data were collected from 2019 to 2020 from Hospital Information System (HIS). The statistical analysis was done using Chi-square and Multinomial logistic regression. Results: The study includes 82 patients who were treated with Acenocoumarol. The results were calculated using a student t-test and the P-value was<0.0001, which is significant as it is less than 0.05, and the prediction tool is developed by using Multinomial Logistic Regression. Conclusion: The Risk Assessment tool was developed. As the sample size increases, the accuracy of predictability also increases. So further validation of the tool is required for more accuracy and the data input should also be increased.