Andexanet alfa for the reversal of the low-molecular-weight heparin enoxaparin
Bibliographic record
Abstract
Background: Andexanet alfa (andexanet) is the only approved reversal agent for patients with acute major bleeding during apixaban or rivaroxaban treatment. Its mechanism suggests it may also reverse the effects of low-molecular-weight heparin. Aim: To evaluate the effects of andexanet in healthy volunteers and in patients with acute major bleeding on enoxaparin. Methods: In the first study, healthy volunteers received enoxaparin 1 mg/kg twice daily for ≥3 doses and were randomized to receive either andexanet or placebo in high- or low-dose regimens, given 3 hours (high dose) or 8 hours (low dose) after the last dose. In the second study (Andexanet Alfa, a Novel Antidote to the Anticoagulant Effects of FXa Inhibitors 4), dosing depended on timing and amount of last enoxaparin dose: high dose if > 40 mg or <8 hours since last dose (or unknown), low dose if ≤ 40 mg or ≥8 hours. The high dose consisted of an 800 mg bolus followed by 960 mg >2 hours, while low dose consisted of a 400 mg bolus followed by 480 mg >2 hours. The primary outcome was change in anti-Xa activity. Hemostatic efficacy was assessed in patients with confirmed bleeding and baseline anti-Xa ≥ 0.25 IU/mL. Results: In the first study, 24 volunteers received andexanet (12 at a high dose and 12 at a low dose), and 7 received a placebo. Median anti-Xa activity decreased by 83% (0.92-0.17 IU/mL) in the high-dose cohort, and by 73% (0.78-0.22 IU/mL) in the low-dose cohort. In the second study, 22 patients received andexanet; anti-Xa activity decreased by 75% (95% CI, 67%-79%; 0.48-0.14 IU/mL). Good/excellent hemostasis was achieved in 14 of 16 assessable patients (88%). Conclusion: In enoxaparin-treated subjects, andexanet reduced anti-Xa activity and achieved effective hemostasis in 88% of patients. Results align with findings of patients using apixaban, rivaroxaban, or edoxaban.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".