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CC BY 4.0 · TH Open 2024; 08(01): e121-e131
DOI: 10.1055/a-2259-1134
Original Article

Bleeding Risk Prediction in Patients Treated with Antithrombotic Drugs According to the Anatomic Site of Bleeding, Indication for Treatment, and Time Since Treatment Initiation

Vinai Bhagirath
1   Population Health Research Institute, Hamilton, Ontario, Canada
2   McMaster University, Hamilton, Ontario, Canada
,
Tanya Kovalova
1   Population Health Research Institute, Hamilton, Ontario, Canada
,
Jia Wang
1   Population Health Research Institute, Hamilton, Ontario, Canada
,
Lizhen Xu
1   Population Health Research Institute, Hamilton, Ontario, Canada
,
Shrikant I. Bangdiwala
1   Population Health Research Institute, Hamilton, Ontario, Canada
2   McMaster University, Hamilton, Ontario, Canada
,
Martin O'Donnell
1   Population Health Research Institute, Hamilton, Ontario, Canada
3   University of Galway, Galway, Galway, Ireland
,
Ashkan Shoamanesh
1   Population Health Research Institute, Hamilton, Ontario, Canada
2   McMaster University, Hamilton, Ontario, Canada
,
Jackie Bosch
2   McMaster University, Hamilton, Ontario, Canada
,
Rosa Coppolecchia
4   Bayer US LLC, Whippany, New Jersey, United States
,
Tatsiana Vaitsiakhovich
5   Bayer AG, Berlin, Germany
,
Frank Kleinjung
5   Bayer AG, Berlin, Germany
,
Hardi Mundl
6   Bayer AG, Wuppertal, Germany
,
John Eikelboom
1   Population Health Research Institute, Hamilton, Ontario, Canada
2   McMaster University, Hamilton, Ontario, Canada
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Corrigendum: Bleeding Risk Prediction in Patients Treated with Antithrombotic Drugs According to the Anatomic Site of Bleeding, Indication for Treatment, and Time Since Treatment InitiationTH Open 2024; 08(01): e1-e1
DOI: 10.1055/s-0044-1788303

Abstract

Background Reasons for the relatively poor performance of bleeding prediction models are not well understood but may relate to differences in predictors for various anatomical sites of bleeding.

Methods We pooled individual participant data from four randomized controlled trials of antithrombotic therapy in patients with coronary and peripheral artery diseases, embolic stroke of undetermined source (ESUS), or atrial fibrillation. We examined discrimination and calibration of models for any major bleeding, major gastrointestinal (GI) bleeding, and intracranial hemorrhage (ICH), according to the time since initiation of antithrombotic therapy, and indication for antithrombotic therapy.

Results Of 57,813 patients included, 1,948 (3.37%) experienced major bleeding, including 717 (1.24%) major GI bleeding and 274 (0.47%) ICH. The model derived to predict major bleeding at 1 year from any site (c-index, 0.69, 95% confidence interval [CI], 0.68–0.71) performed similarly when applied to predict major GI bleeding (0.71, 0.69–0.74), but less well to predict ICH (0.64, 0.61–0.69). Models derived to predict GI bleeding (0.75, 0.74–0.78) and ICH (0.72, 0.70–0.79) performed better than the general major bleeding model. Discrimination declined over time since the initiation of antithrombotic treatment, stabilizing at approximately 2 years for any major bleeding and major GI bleeding and 1 year for ICH. Discrimination was best for the model predicting ICH in the ESUS population (0.82, 0.78–0.92) and worst for the model predicting any major bleeding in the coronary and peripheral artery disease population (0.66, 0.65–0.69).

Conclusion Performance of risk prediction models for major bleeding is affected by site of bleeding, time since initiation of antithrombotic therapy, and indication for antithrombotic therapy.

Keywords

bleeding - risk prediction - antithrombotic - atrial fibrillation - ESUS, CAD, PAD

Contributions

All authors contributed to the design, analysis, and interpretation of data; drafting of the manuscript; and final approval of the version to be published.


Disclosures

V.B. has received honoraria from Bayer. T.K., J.W., L.X., S.B., and M.O.'D. have no conflicts of interest to disclose. A.S. has received consulting fees for Alexion, Octapharma, Bayer, Daiichi Sankyo, Bristol Myers Squibb, and Servier Canada. J.B. has received funding from Bayer AG for event adjudication activities. R.C., T.V., F.K., and H.M. are employees of Bayer. J.E. has received honoraria, research or in-kind support from Astra-Zeneca, Bayer, Boehringer-Ingelheim, Bristol-Myer-Squibb, Glaxo-Smith-Kline, Pfizer, Janssen, Sanofi-Aventis and honoraria from Astra-Zeneca, Bayer, Boehringer-Ingelheim, Bristol-Myer-Squibb, Daiichi-Sankyo, Eli-Lilly, Glaxo-Smith-Kline, Merck, Pfizer, Janssen, Sanofi-Aventis, and Servier.


Supplementary Material



Publication History

Received: 29 November 2023

Accepted: 28 January 2024

Accepted Manuscript online:
01 February 2024

Article published online:
18 March 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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