Characterization of Major and Clinically Relevant Non-Major Bleeds in the APEX Trial
Bibliographic record
Abstract
Background Among medically ill patients treated with thromboprophylaxis, betrixaban was not associated with an increase in major bleeding compared with enoxaparin, but an increase in clinically relevant non-major (CRNM) bleeding was observed. The aim of this analysis is to describe the severity and clinical consequences of major and CRNM bleeding in the APEX trial. Methods The APEX trial randomized 7,513 hospitalized acutely ill medical patients to receive either enoxaparin for 6 to 14 days or betrixaban for 35 to 42 days. Subjects receiving a concomitant strong p-glycoprotein inhibitor or with creatinine clearance <30 mL/min were administered a reduced dose of study drug. Results A total of 25 (0.7%) and 21 (0.6%) major bleeds occurred in the betrixaban and enoxaparin arms, respectively (p = NS) and a total of 91 (2.5%) and 38 (1.0%) CRNM bleeds occurred in the betrixaban and enoxaparin arm (p < 0.001), respectively. Most major bleeds were considered moderate or severe and most CRNM bleeds were considered mild and moderate (p = NS). One fatal major bleed occurred in each treatment arm. Rates of major or CRNM bleeds resulting in new or prolonged hospitalization (major: 44.0 vs. 28.6%; CRNM: 12.1 vs. 21.1%) or study treatment interruption or cessation (major: 72.0 vs. 71.4%; CRNM: 71.3 vs. 68.4%) were similar between treatment arms (p = NS). Conclusions In the APEX trial, CRNM bleeds were mild or moderate in nature and had less of a clinical impact than major bleeds. The severity and clinical sequela of bleeds in the betrixaban arm were comparable to those in the enoxaparin arm. Clinical Trial Registration URL: http://www.clinicaltrials.gov.; Unique identifier: NCT01583218.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".