چاپ صفحه |  صفحه نخست سامانه |  چکیده مقاله |  نویسندگان |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| Background and objective: The use and range of indications for anticoagulation therapy are steadily growing. The objective of this study was to develop a scoring model to predict the occurrence of significant bleeding in patients taking warfarin with a supra-therapeutic international normalized ratio. Methods: Data were collected from the medical records of patients taking warfarin with an international normalized ratio > 3.5. The characteristics of bleeding episodes and the need for transfusion of blood products were recorded. Regression models were constructed to predict the occurrence of significant bleeding (requiring a transfusion of more than 2 units of packed red blood cells, intrapericardial or intracranial hemorrhage). The predictive values of previously published scores (ATRIA: anemia, hypertension, severe renal disease, age ≥ 75 years, or prior bleeding history; and ORBIT: old, reduced hemoglobin, bleeding history, kidney insufficiency or antiplatelet treatment) were compared with our New Bleeding Score (NBLDSCOR); the areas under the curve for the receiver-operating characteristic plots were compared using a non-parametric DeLong test. Results: Significant bleeding was reported in 87 out of 389 admitted patients. With an area under the curve of 0.736 ± 0.032, NBLDSCOR was the best predictor of significant bleeding in this population. Neither ATRIA nor ORBIT was a good predictor of significant bleeding, where the area under the curve for the receiver-operating characteristic plot for ATRIA was 0.654 ± 0.034 and for ORBIT was 0.604 ± 0.033. The predictive power of NBLDSCOR was superior to ATRIA and ORBIT (p < 0.001), while there was no meaningful difference in the predictive powers of ATRIA and ORBIT. Conclusion: The NBLDSCOR including age, negative Rhesus factor, low hemoglobin, renal impairment, and concomitant peptic ulcer and disseminated cancer is a good predictor of significant bleeding in this patient population. |
| نویسنده | نفر چندم مقاله |
|---|---|
| لیلی پورافکاری | اول |
| صمد غفاری باویل | دوم |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| pourafkari2019(1).pdf | 1399/08/22 | 701030 | دانلود |
