Abstract

BACKGROUND: An unmet need exists to reliably predict the risk of intracranial hemorrhage (ICH) in patients with atrial fibrillation (AF) treated with oral anticoagulants (OACs). HYPOTHESIS: An externally validated model improves ICH risk stratification. METHODS: Independent factors associated with ICH were identified by Cox proportional hazard modeling, using pooled data from the GARFIELD-AF (Global Anticoagulant Registry in the FIELD-Atrial Fibrillation) and ORBIT-AF (Outcomes Registry for Better Informed Treatment of Atrial Fibrillation) registries. A predictive model was developed and validated by bootstrap sampling and by independent data from the Danish National Patient Register. RESULTS: In the combined training data set, 284 of 53 878 anticoagulated patients had ICH over a 2-year period (0.31 per 100 person-years; 95% confidence interval [CI]: 0.28-0.35). Independent predictors of ICH included: older age, prior stroke or transient ischemic attack, concomitant antiplatelet (AP) use, and moderate-to-severe chronic kidney disease (CKD). Vitamin K antagonists (VKAs) were associated with a significantly higher risk of ICH compared with non-VKA oral anticoagulants (NOACs) (adjusted hazard ratio: 1.61; 95% CI: 1.25-2.08; p = .0002). The ability of the model to discriminate individuals in the training set with and without ICH was fair (optimism-corrected C-statistic: 0.68; 95% CI: 0.65-0.71) and outperformed three previously published methods. Calibration between predicted and observed ICH probabilities was good in both training and validation data sets. CONCLUSIONS: Age, prior ischemic events, concomitant AP therapy, and CKD were important risk factors for ICH in anticoagulated AF patients. Moreover, ICH was more frequent in patients receiving VKA compared to NOAC. The new validated model is a step toward mitigating this potentially lethal complication.