Efficacy and safety of andexanet alfa for factor Xa inhibitor-associated intracranial haemorrhage
Bibliographic record
Abstract
BACKGROUND: Current international guidelines suggest andexanet alfa (AA) for the management of factor Xa inhibitor-associated intracranial haemorrhage (ICH). However, those recommendations are based on low-quality evidence and there is uncertainty regarding the net clinical benefit of AA. METHODS: We conducted a systematic review and meta-analysis including available randomised controlled clinical trials (RCTs) and observational studies that investigated efficacy and safety of AA compared with usual care for the treatment of factor Xa inhibitor-associated ICH. Good haemostatic efficacy, defined as haematoma expansion of ≤35% or ≤6 mL, was the primary outcome. Secondary efficacy outcomes were excellent haemostatic efficacy (≤20% haematoma expansion) and good functional outcome (modified Rankin Scale scores 0-3) at follow-up, while safety outcomes were mortality and thrombotic events at follow-up. RESULTS: Eighteen studies (1 RCT) were included comprising a total of 1567 patients treated with AA versus 1969 patients receiving usual care. AA was associated with a higher likelihood of good haemostatic efficacy (RR=1.16; 95% CI=1.06 to 1.26) compared with usual care, while excellent haemostatic efficacy (RR=1.04; 95% CI=0.85 to 1.26) and good functional outcome (RR=0.92; 95% CI=0.53 to 1.62) were similar between the two groups. Regarding safety outcomes, similar rates of mortality (RR=0.77; 95% CI=0.56 to 1.04) and thrombotic events (RR=1.20; 95% CI=0.81 to 1.78) were documented. CONCLUSIONS: The present meta-analysis suggests AA is associated with improved haemostatic efficacy compared with usual care, with no significant differences observed in functional and safety outcomes. These findings indicate that AA may have a role in the management of factor Xa inhibitor-associated ICH, although further high-quality studies are needed to better define its net clinical benefit.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.016 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".