Direct Oral Anticoagulant- or Warfarin-Related Major Bleeding
Bibliographic record
Abstract
BACKGROUND: Direct oral anticoagulants (DOACs) have expanded the armamentarium for antithrombotic therapy. Although DOAC-related major bleeding was associated with favorable outcomes compared with warfarin in clinical trials, warfarin effects were reversed in < 40% of cases, raising concerns about the generalizability of this finding. METHODS: Consecutive patients ≥ 66 years presented to five tertiary care hospitals across three cities in Ontario, Canada from October 2010 to March 2015 with diagnoses that included hemorrhage. Charts were screened for association with DOAC or warfarin use; eligible cases were abstracted and linked to administrative databases. RESULTS: Among 19,061 records screened, 2,002 (460 receiving DOAC, 1,542 receiving warfarin) were eligible. Reversal agents (72.9% vitamin K, 40.7% prothrombin complex concentrates) were frequently used in warfarin bleeding events. Red blood cell transfusions occurred more often in DOAC bleeding events than in warfarin events (52.0% vs 39.5%; adjusted relative risk [aRR], 1.32; 95% CI, 1.19-2.47). However, units of blood products transfused were not different between the two groups. Thirty-four DOAC cases (7.4%) received activated prothrombin complex concentrates or recombinant factor VIIa. In-hospital mortality was lower following DOAC bleeding events (9.8% vs 15.2%; aRR, 0.66; 95% CI, 0.49-0.89), although differences in 30-day mortality did not reach statistical significance (12.6% vs 16.3%; aRR, 0.79; 95% CI, 0.61-1.03). CONCLUSIONS: In this unselected cohort of patients with oral anticoagulant-related hemorrhage with high rates of warfarin reversal, in-hospital mortality was lower among DOAC-associated bleeding events. These findings support the safety of DOACs in routine care and present useful baseline measures for evaluations of DOAC-specific reversal agents.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".