Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets

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 and Greving, Jacoba P. (2017) Predicting major bleeding in patients with noncardioembolic stroke on antiplatelets. Neurology, 89 (9). pp. 936-943. ISSN 1526-632X

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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.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/879644
Schools/Departments: University of Nottingham, UK > Faculty of Medicine and Health Sciences > School of Medicine > Division of Clinical Neuroscience
Identification Number: https://doi.org/10.1212/WNL.0000000000004289
Depositing User: Eprints, Support
Date Deposited: 24 Jan 2018 10:42
Last Modified: 04 May 2020 19:02
URI: https://eprints.nottingham.ac.uk/id/eprint/49314

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