Clinical presentation and course of bleeding events in patients with venous thromboembolism, treated with apixaban or enoxaparin and warfarin
Bibliographic record
Abstract
Apixaban, a direct acting oral anticoagulant (DOAC), was found to be non-inferior to and safer as enoxaparin followed by warfarin for treatment of venous thromboembolism (VTE) in the AMPLIFY trial. Information is needed on how bleeding events with DOACs present and develop. In this post-hoc analysis, the clinical presentation and course of all major and clinically relevant non major (CRNM) bleeding events in the AMPLIFY trial were blindly classified by three investigators, using pre-designed classification schemes containing four categories. Odds ratios (OR) for classifying as category three or four (representing a more severe clinical presentation and course) were calculated between apixaban and enoxaparin/warfarin. In total, 63 major and 311 CRNM bleeding events were classified. Of the major bleeds, a more severe clinical presentation occurred in 28.5 % of apixaban versus 44.9 % of enoxaparin/warfarin related recipients (OR 0.49, 95 % confidence interval [CI] 0.14-1.78). A severe clinical course was observed in 14.3 % and in 12.2 %, respectively (OR 1.19, 95 %CI 0.21-6.69). Of the CRNM bleeding events, a more severe clinical presentation and extent of clinical care was found in 25 % of apixaban recipients compared to 22.7 % in the enoxaparin/warfarin group (OR 1.13, 95 %CI 0.65-1.97). The clinical presentation and course of major and CRNM bleeds were similar in apixaban and enoxaparin/warfarin treated patients. This finding should reassure physicians and patients that even in the absence of a specific reversal agent, apixaban is a convenient and safe choice for VTE.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".