Bibliographic record
Abstract
CADTH recommends that Ondexxya should not be reimbursed by public drug plans for adult patients treated with factor Xa (FXa) inhibitors (rivaroxaban or apixaban) when rapid reversal of anticoagulation is needed due to life-threatening or uncontrolled bleeding. Evidence from a clinical trial (ANNEXA-4) demonstrated that Ondexxya treatment could reduce the activity of FXa inhibitors in the blood and improve imaging and laboratory markers of bleeding; however, without a control group, there is uncertainty in how much the observed benefits were due to Ondexxya treatment rather than chance. Clinical outcomes such as neurologic status and mortality were also uncertain. No evidence was submitted at the time of the review that directly compared Ondexxya to usual care for managing bleeding related to an FXa inhibitor. Observational evidence comparing Ondexxya and prothrombin complex concentrate, which is part of the usual care, was uncertain due to limitations of study design and analysis. Based on the evidence reviewed, the CADTH Canadian Plasma Protein Product Expert Committee (CPEC) was not convinced that treatment with Ondexxya would achieve outcomes that are clinically important to patients or meet needs not already addressed by other available treatments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".