Lessons from a systematic literature review of the effectiveness of recombinant factor VIIa in acquired haemophilia
Bibliographic record
Abstract
To conduct a systematic review of the literature reporting efficacy and safety of recombinant factor VIIa (rFVIIa) for the treatment of bleeding in acquired haemophilia and, if data permitted, undertake a meta-analysis of the current evidence. MEDLINE ® , Embase ® , and the Cochrane Central Register of Controlled Trials (CENTRAL) databases were searched for all studies on rFVIIa treatment in acquired haemophilia. Heterogeneity of included studies was measured using the inconsistency index ( I 2 ). Of the 2353 publications screened, 290 potentially relevant references were identified: 12 studies published in 32 publications met inclusion criteria. In total, 1244 patients and 1714 bleeds were included (671 patients received rFVIIa treatment for 1063 bleeds). In seven of 12 studies, the initial dose of Recombinant FVIIa was 90 ± 10 μg/kg. Recombinant FVIIa was used as first-line therapy in the majority of cases. Median number of doses administered ranged from 10 to 28. Between 68 and 74% of bleeds were spontaneous, whereas 4–50% were traumatic. Thirty-nine to 90% of bleeds were severe. Haemostatic effectiveness was > 90% in 5/6 studies for both patient and bleed level. Recombinant FVIIa had a favourable safety profile with low risk of general adverse events and thromboembolic-associated events. The heterogeneity of the studies and data precluded a meta-analysis. Recombinant FVIIa demonstrated effectiveness for the treatment of bleeds and had a good safety profile. It is apparent from these data that there is a need for more standardised measures of clinical effectiveness in acquired haemophilia to enable comparison and pooling of results in the future.
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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 | 0.106 | 0.318 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".