OBJECTIVES: The purpose of this study was to develop a risk stratification score to predict warfarin-associated hemorrhage. BACKGROUND: Optimal decision making regarding warfarin use for atrial fibrillation requires estimation of hemorrhage risk. METHODS: We followed up 9,186 patients with atrial fibrillation contributing 32,888 person-years of follow-up on warfarin, obtaining data from clinical databases and validating hemorrhage events using medical record review. We used Cox regression models to develop a hemorrhage risk stratification score, selecting candidate variables using bootstrapping approaches. The final model was internally validated by split-sample testing and compared with 6 published hemorrhage risk schemes. RESULTS: We observed 461 first major hemorrhages during follow-up (1.4% annually). Five independent variables were included in the final model and weighted by regression coefficients: anemia (3 points), severe renal disease (e.g., glomerular filtration rate <30 ml/min or dialysis-dependent, 3 points), age ≥75 years (2 points), prior bleeding (1 point), and hypertension (1 point). Major hemorrhage rates ranged from 0.4% (0 points) to 17.3% per year (10 points). Collapsed into a 3-category risk score, major hemorrhage rates were 0.8% for low risk (0 to 3 points), 2.6% for intermediate risk (4 points), and 5.8% for high risk (5 to 10 points). The c-index for the continuous risk score was 0.74 and 0.69 for the 3-category score, higher than in the other risk schemes. There was net reclassification improvement versus all 6 comparators (from 27% to 56%). CONCLUSIONS: A simple 5-variable risk score was effective in quantifying the risk of warfarin-associated hemorrhage in a large community-based cohort of patients with atrial fibrillation.
OBJECTIVES: The purpose of this study was to develop a risk stratification score to predict warfarin-associated hemorrhage. BACKGROUND: Optimal decision making regarding warfarin use for atrial fibrillation requires estimation of hemorrhage risk. METHODS: We followed up 9,186 patients with atrial fibrillation contributing 32,888 person-years of follow-up on warfarin, obtaining data from clinical databases and validating hemorrhage events using medical record review. We used Cox regression models to develop a hemorrhage risk stratification score, selecting candidate variables using bootstrapping approaches. The final model was internally validated by split-sample testing and compared with 6 published hemorrhage risk schemes. RESULTS: We observed 461 first major hemorrhages during follow-up (1.4% annually). Five independent variables were included in the final model and weighted by regression coefficients: anemia (3 points), severe renal disease (e.g., glomerular filtration rate <30 ml/min or dialysis-dependent, 3 points), age ≥75 years (2 points), prior bleeding (1 point), and hypertension (1 point). Major hemorrhage rates ranged from 0.4% (0 points) to 17.3% per year (10 points). Collapsed into a 3-category risk score, major hemorrhage rates were 0.8% for low risk (0 to 3 points), 2.6% for intermediate risk (4 points), and 5.8% for high risk (5 to 10 points). The c-index for the continuous risk score was 0.74 and 0.69 for the 3-category score, higher than in the other risk schemes. There was net reclassification improvement versus all 6 comparators (from 27% to 56%). CONCLUSIONS: A simple 5-variable risk score was effective in quantifying the risk of warfarin-associated hemorrhage in a large community-based cohort of patients with atrial fibrillation.
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