Trends of use and factors that determine the choice of oral anticoagulants in women and men with atrial fibrillation.

The aim was to identify sex-specific factors linked with oral anticoagulant initiation in a cohort of patients with atrial fibrillation using administrative data from Quebec (Canada) between 2014 and 2017. Cohort entry defined as new users, that is, no claims in last 12 months, a cohort of 32 050 patients was stratified in two groups, that is, women and men. Multivariable regression models were used to identify factors of initiations for low- and standard-dose direct oral anticoagulants (DOACs) versus warfarin, and low- versus standard-dose DOACs. In both sexes, warfarin initiation decreased and DOAC initiation increased, with year of initiation as major factors of DOACs use. In 2017, the increase was of 2- to 4-fold and 3- to 8-fold for low- and standard-dose DOACs (vs. warfarin), respectively. The proportion of patients starting on a low-dose DOAC was higher in women than men. Older age for both sexes and CHADS2 score ≥2 (only women) were major factors of low-dose dabigatran and rivaroxaban versus warfarin use. The only significant factor of standard-dose DOAC versus warfarin use was age of 65-79 for women or men treated with apixaban by 1.8- and 1.4-fold, respectively. Factors that made women and men less likely to receive a standard-dose DOAC versus warfarin were higher CHADS2 (for dabigatran and rivaroxaban), HAS-BLED and frailty scores, prior coronary disease, major bleeding, and chronic kidney disease (CKD) status. The choice of a low- versus standard-dose DOAC was mainly driven by age and CKD, and higher CHADS2 score (for dabigatran and apixaban) for both sexes.

Predicting major bleeding among hospitalized patients using oral anticoagulants for atrial fibrillation after discharge.

AIM: Real-world predictors of major bleeding (MB) have been well-studied among warfarin users, but not among all direct oral anticoagulant (DOAC) users diagnosed with atrial fibrillation (AF). Thus, our goal was to build a predictive model of MB for new users of all oral anticoagulants (OAC) with AF. METHODS: We identified patients hospitalized for any cause and discharged alive in the community from 2011 to 2017 with a primary or secondary diagnosis of AF in Quebec's RAMQ and Med-Echo administrative databases. Cohort entry occurred at the first OAC claim. Patients were categorized according to OAC type. Outcomes were incident MB, gastrointestinal bleeding (GIB), non-GI extracranial bleeding (NGIB) and intracranial bleeding within 1 year of follow-up. Covariates included age, sex, co-morbidities (within 3 years before cohort entry) and medication use (within 2 weeks before cohort entry). We used logistic-LASSO and adaptive logistic-LASSO regressions to identify MB predictors among OAC users. Discrimination and calibration were assessed for each model and a global model was selected. Subgroup analyses were performed for MB subtypes and OAC types. RESULTS: Our cohort consisted of 14,741 warfarin, 3,722 dabigatran, 6,722 rivaroxaban and 11,196 apixaban users aged 70-86 years old. The important MB predictors were age, prior MB and liver disease with ORs ranging from 1.37-1.64. The final model had a c-statistic of 0.63 (95% CI 0.60-0.65) with adequate calibration. The GIB and NGIB models had similar c-statistics of 0.65 (95% CI 0.63-0.66) and 0.67 (95% CI 0.64-0.70), respectively. CONCLUSIONS: MB and MB subtype predictors were similar among DOAC and warfarin users. The predictors selected by our models and their discriminative potential are concordant with published data. Thus, these models can be useful tools for future pharmacoepidemiologic studies involving older oral anticoagulant users with AF.