Thirty‐day mortality with andexanet alfa compared with prothrombin complex concentrate therapy for life‐threatening direct oral anticoagulant‐related bleeding
Bibliographic record
Abstract
Objective: Compare 30-day mortality among patients receiving the specific reversal agent andexanet alfa versus replacement prothrombin complex concentrate (PCC) in the management of direct-acting oral anticoagulant (DOAC)-related bleeds. Methods: Two patient-level datasets were used: ANNEXA-4, a prospective, single-arm trial of patients taking apixaban or rivaroxaban who received andexanet alfa and ORANGE, a prospective, observational study of anticoagulated patients in UK hospitals, some of whom received PCC. Patients were propensity score matched based on demographic and clinical characteristics. Subgroup analyses were performed by bleed type (intracranial hemorrhage [ICH], gastrointestinal [GI], other). Relative risk (RR) of all-cause 30-day mortality was calculated. Results: 322 ANNEXA-4 patients treated with andexanet alfa (mean age = 77.7 years; 64.9% ICH) were matched with 88 ORANGE patients treated with PCC (mean age = 74.9 years, 67.1% ICH). Adjusted 30-day mortality for patients treated with andexanet alfa (14.6%) was lower than patients treated with PCC (34.1%; RR, 0.43; 95% CI, 0.29-0.63). In the ICH subgroup, patients treated with andexanet alfa had lower mortality (15.3%) than patients treated with PCC (48.9%; RR, 0.31; 95% CI, 0.20-0.48). Mortality risk was lowest for patients in the GI subgroup but did not differ significantly by treatment (12.2% for andexanet alfa vs 25.0% for PCC; RR, 0.49; 95% CI, 0.21-1.16). Conclusions: In this propensity score-matched comparison across 2 independent datasets, adjusted 30-day mortality rates were lower for patients treated with andexanet alfa than in matched patients receiving PCC. This indirect comparison was limited in that it could not account for several highly predictive variables including GCS score, hematoma volume, and expected survival. Further research is warranted to confirm the mortality differences between reversal/replacement agents for DOAC-related bleeding.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".