P1551D-dimer concentration is associated with increased risk for VTE and greater absolute benefit of extended prophylaxis with betrixaban in acutely Ill medical patients: insights from the APEX trial
Bibliographic record
Abstract
Background: In hospitalized patients elevated D-dimer concentration is associated with an increased risk of occurrence for VTE and mortality. D-dimer concentration may be used to identify medical patients at an elevated VTE risk, who might benefit from extended thromboprophylaxis following hospitalization for an acute illness. Methods: This is a post hoc sub-study of the Acute Medically Ill VTE Prevention with Extended Duration Betrixaban (APEX) trial. The aim was to evaluate the modulation of the treatment effect of betrixaban versus standard duration enoxaparin as a function of D-dimer concentrations, both as a discrete and continuous measurement. Results: There was no interaction between positive D-dimer levels and betrixaban efficacy (Pint=0.54). In D-dimer positive subjects (≥2x ULN), as determined by the central laboratory, extended duration betrixaban versus standard enoxaparin significantly reduced the risk of all VTE (OR=0.71; 95% CI: 0.55–0.90; p=0.005) and asymptomatic DVT (OR=0.68; 95% CI: 0.52–0.89; p=0.004). These results are consistent with previously published findings from the Magellan trial (Risk for VTE among D-dimer positive subjects, as measured by central lab: RR=0.71; 95% CI: 0.54–0.92; p<0.001). For every 0.25 μg/mL increase in D-dimer concentration, there was a 2% relative increase in the odds of experiencing a VTE (DVT, nonfatal PE, or VTE-related death) in both the betrixaban (p<0.001) and enoxaparin (p<0.001) treatment arms (Figure), resulting in greater absolute reductions with extended betrixaban.
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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 | 0.004 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".