5069Reversal of apixaban and rivaroxaban anticoagulation by andexanet alfa in ANNEXA-A&R as assessed by non-tissue factor (TF)-initiated thrombin generation independent of TF pathway inhibitor (TFPI)
Bibliographic record
Abstract
Background: Andexanet alfa is a modified factor Xa designed to bind and sequester factor Xa (FXa) inhibitors and thus reverse anticoagulation. Andexanet has been previously shown to reverse anticoagulation effects of FXa inhibitors, apixaban or rivaroxaban, in Phase 3 randomized studies (ANNEXA-A&R) in older healthy volunteers. When administered as a bolus or a bolus plus a 2-hour infusion in anticoagulated subjects, andexanet significantly reversed apixaban or rivaroxaban anti-FXa activity, reduced unbound (pharmacologically active) concentrations of both FXa inhibitors, and restored TF-initiated thrombin generation (TF-TG) when compared with placebo. Purpose: Since andexanet, as a modified FXa, can also bind TFPI, this study compared the effect of andexanet-TFPI interaction on restoration of TG via the TF (extrinsic) and non-TF (intrinsic) pathways in the ANNEXA-A&R. Methods: Retained plasma samples from ANNEXA-A&R subjects who received andexanet bolus plus a 2-hour infusion were analyzed using a validated non-TF-TG assay similar to the TF-TG assay, using an aPTT reagent (Actin FS, Siemens) as an activator. Restoration of TG was assessed by endogenous thrombin potential (ETP) and other TG parameters.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".