Evaluation of Definitions for Oral Anticoagulant–Associated Major Bleeding: A Population-Based Cohort Study
Bibliographic record
Abstract
Abstract Background: Major bleeding is the most serious complication of oral anticoagulation. Consensus criteria to define major bleeding have been established by the International Society for Thrombosis and Haemostasis (ISTH), Bleeding Academic Research Consortium (BARC) and Thrombolysis in Myocardial Infarction (TIMI). Significant variability exists across these definitions, and their agreement for identifying oral anticoagulant (OAC) related major bleeding is unknown. Furthermore, the association between each definition and mortality in cases of OAC bleeding has not been evaluated. We therefore, sought to evaluate the agreement of cases identified as major bleeding by the ISTH, BARC and TIMI definitions, and to assess associated in-hospital (emergency department or inpatient) and 30-day mortality of cases identified by these criteria. Methods: We used an existing dataset of individuals ≥66 years in Ontario, Canada, who presented to one of five tertiary care institutions with OAC related bleeding across three cities from 2010-2015. Detailed clinical data on consecutive episodes of OAC-associated bleeding were linked to population-based databases held at the Institute for Clinical Evaluative Sciences. We calculated Cohen's κ for agreement between the three major bleeding definitions, and used Pearson's χ2 to determine any differences in in-hospital and 30-day mortality for cases defined as major bleeding by ISTH, BARC and TIMI criteria. Results: We included 2,002 cases of OAC related bleeding in the analysis (460 on direct oral anticoagulants, 1,542 on warfarin). ISTH, BARC and TIMI major bleeding definitions were met in 75%, 77% and 29% of cases, respectively. 18% of cases did not meet criteria for major bleeding by any definition. Age, sex, CHA2DS2-VASc and HAS-BLED score, as well as proportion of chronic kidney disease were similar across ISTH-, BARC- and TIMI-defined cases. Over 9 in 10 cases of TIMI-defined major bleeding events involved an intracranial hemorrhage (94.4%), compared to 37% and 36% of cases identified by ISTH or BARC definitions respectively (p<0.001 across three groups). Agreement in case identification between ISTH and BARC was substantial (agreement 89%; Cohen's κ=0.69). On the other hand, agreement between TIMI and both ISTH (agreement 54%; Cohen's κ =0.24) and BARC (agreement 52%; Cohen's κ=0.21) were poor. The association between in-hospital mortality and TIMI-defined major bleeding was higher (29%) than that for ISTH and BARC (17% for both; p<0.001 for TIMI vs. ISTH and TIMI vs. BARC). The association with 30-day mortality showed a similar trend (30%, 18% and 18% for TIMI-, ISTH- and BARC- defined major bleeding events respectively; p<0.001 for TIMI vs. ISTH and TIMI vs. BARC). 6% of cases that were not categorized as major bleeding by ISTH or BARC definitions died within 30 days of hospital presentation, and this was 10% for cases not meeting criteria for TIMI major bleeding (10%, p=0.036 by Pearson's χ2). Conclusions: Among patients with OAC-associated bleeding, major bleeding events identified by ISTH and BARC criteria showed good agreement and similar prognostic utility. Meanwhile, TIMI criteria identified patients with higher clinical risk and subsequent mortality. Patients presenting with OAC-associated bleeding who did not fulfill ISTH or BARC major bleeding criteria had considerable risk of 30-day mortality and was even higher among those not meeting the TIMI criteria. Our findings suggest the need to refine current major bleeding definitions to identify additional patients at risk of death. Disclosures Wells: Bayer: Honoraria; BMS: Honoraria, Research Funding; Sanofi: Honoraria; Janssen: Honoraria. Sholzberg:Amgen: Research Funding; CSL Behring: Research Funding; Octapharma: Research Funding; Shire: Research Funding.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".