Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets

Author:

Hilkens Nina A.,Algra Ale,Diener Hans-Christoph,Reitsma Johannes B.,Bath Philip M.,Csiba Laszlo,Hacke Werner,Kappelle L. Jaap,Koudstaal Peter J.,Leys Didier,Mas Jean-Louis,Sacco Ralph L.,Amarenco Pierre,Sissani Leila,Greving Jacoba P.,

Abstract

Objective:To develop and externally validate a prediction model for major bleeding in patients with a TIA or ischemic stroke on antiplatelet agents.Methods:We combined individual patient data from 6 randomized clinical trials (CAPRIE, ESPS-2, MATCH, CHARISMA, ESPRIT, and PRoFESS) investigating antiplatelet therapy after TIA or ischemic stroke. Cox regression analyses stratified by trial were performed to study the association between predictors and major bleeding. A risk prediction model was derived and validated in the PERFORM trial. Performance was assessed with the c statistic and calibration plots.Results:Major bleeding occurred in 1,530 of the 43,112 patients during 94,833 person-years of follow-up. The observed 3-year risk of major bleeding was 4.6% (95% confidence interval [CI] 4.4%–4.9%). Predictors were male sex, smoking, type of antiplatelet agents (aspirin-clopidogrel), outcome on modified Rankin Scale ≥3, prior stroke, high blood pressure, lower body mass index, elderly, Asian ethnicity, and diabetes (S2TOP-BLEED). The S2TOP-BLEED score had a c statistic of 0.63 (95% CI 0.60–0.64) and showed good calibration in the development data. Major bleeding risk ranged from 2% in patients aged 45–54 years without additional risk factors to more than 10% in patients aged 75–84 years with multiple risk factors. In external validation, the model had a c statistic of 0.61 (95% CI 0.59–0.63) and slightly underestimated major bleeding risk.Conclusions:The S2TOP-BLEED score can be used to estimate 3-year major bleeding risk in patients with a TIA or ischemic stroke who use antiplatelet agents, based on readily available characteristics. The discriminatory performance may be improved by identifying stronger predictors of major bleeding.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Neurology (clinical)

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