Evaluation of definitions for oral anticoagulant-associated major bleeding: A population-based cohort study
Bibliographic record
Abstract
INTRODUCTION: Major bleeding is the most serious complication of oral anticoagulants (OACs). While 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. We sought to evaluate the agreement of cases identified by the three definitions and to assess their effect on mortality and OAC resumption. METHODS: We used a dataset of individuals ≥66 years in Ontario, Canada presenting with OAC-related bleeding from 2010 to 2015. For case agreement, we calculated Cohen's κ between the three major bleeding definitions. We used multivariate regression to determine differences in mortality and OAC resumption among ISTH, BARC and TIMI-defined major bleeds. RESULTS: Among 2002 cases of OAC-related bleeding, agreement in case identification between ISTH and BARC was substantial (Cohen's κ = 0.69); however, agreement between TIMI and other definitions were poor. Using 30-day mortality of clinically relevant non-major bleeds as comparator, ISTH-, BARC- and TIMI-defined major bleeds conferred 3.3-, 3.2- and 5.9-fold increased risk. Among survivors, 50% with ISTH- and BARC-defined major bleeds resumed OACs at 180 days, compared to 31% of TIMI-associated cases. CONCLUSION: Major bleeds identified by ISTH and BARC criteria showed good agreement and similar prognostic utility, whereas TIMI criteria identified patients at greater clinical risk. Our results highlight the need to revise major bleeding definitions based on criteria that are independently predictive of clinically relevant morbidity and mortality to more effectively reflect the risk associated with major bleeding and appropriately influence anticoagulant therapy decisions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".