Adam, Luise; Feller, Martin; Syrogiannouli, Lamprini; Del Giovane, Cinzia; Donzé, Jacques; Baumgartner, Christine; Segna, Daniel; Floriani, Carmen; Roten, Laurent; Fischer, Urs; Aeschbacher, Stefanie; Moschovitis, Giorgio; Schläpfer, Jürg; Shah, Dipen; Amman, Peter; Kobza, Richard; Schwenkglenks, Matthias; Kühne, Michael; Bonati, Leo; Beer, Jürg; ... (2021). Novel Bleeding Risk Score for Patients with Atrial Fibrillation on Oral Anticoagulants, including Direct Oral Anticoagulants. Journal of thrombosis and haemostasis, 19(4), pp. 931-940. Blackwell 10.1111/jth.15251
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OBJECTIVE
Balancing bleeding risk and stroke risk in patients with atrial fibrillation (AF) is a common challenge. Though several bleeding risk scores exist, most have not included patients on direct oral anticoagulants (DOAC). We aimed at developing a novel bleeding risk score for patients with AF on oral anticoagulants (OAC) including both, vitamin K antagonists (VKA) and DOACs.
METHODS
We included patients with AF on OAC from a prospective multicentre cohort study in Switzerland (SWISS-AF). The outcome was time to first bleeding. Bleeding events were defined as major or clinically relevant non-major bleeding. We used backward elimination to identify bleeding risk variables. We derived the score using a point score system based on the beta coefficients from the multivariable model. We used the Brier score for model calibration (<0.25 indicating good calibration), and Harrel's c-statistics for model discrimination. .
RESULTS
We included 2,147 patients with AF on OAC (72.5% male, mean age 73.4 ± 8.2 years), of whom 1209 (56.3%) took DOAC. After a follow-up of totally 4.4. years, a total of 255 (11.9%) bleeding events occurred. After backward elimination, age>75 years, history of cancer, prior major haemorrhage and arterial hypertension remained in the final prediction model. The Brier score was 0.23 (95% CI 0.19- 0.27), the c-statistics at 12 months was 0.71 (95%CI 0.63 - 0.80).
CONCLUSION
In this prospective cohort study of AF patients and predominantly DOAC users, we successfully derived a bleeding risk prediction model with good calibration and discrimination.