Bleed treatment with eptacog beta (rFVIIa) results in a low incidence of rebleeding in adult and adolescent patients with haemophilia A or B with inhibitors
Bibliographic record
Abstract
INTRODUCTION: Eptacog beta is a novel human recombinant FVIIa approved for use in the United States, European Union, United Kingdom and Mexico for the treatment and control of bleeding in patients with haemophilia A or B with inhibitors (≥12 years). It is also indicated for perioperative care in the same patient population in Europe and the United Kingdom. AIM: To assess the incidence of rebleeding and review treatment outcomes in subjects with haemophilia with inhibitors enrolled in the phase 3 PERSEPT 1 clinical trial. METHODS: To treat mild/moderate bleeding episodes (BEs), subjects administered an initial 75 or 225µg/kg dose of eptacog beta, followed (if necessary) by additional 75µg/kg doses at predefined intervals until bleed control. This analysis used subject-reported rebleeding to determine a rebleeding incidence for the first 24 h. Rebleeding through later timepoints was an exploratory, intention-to-treat analysis of bleed treatment data. RESULTS: Four hundred and sixty-five BEs were analysed. Through 24 h, the proportion of rebleeds was 0% (initial 75µg/kg dose) and 0.5% (initial 225µg/kg dose). Through 48 h, the proportion of rebleeds was 3.2% (75µg/kg initial dose) and 5.6% (225µg/kg initial dose); the difference between initial dose strategies was not statistically significant. The majority of rebleeds were controlled with a single dose of eptacog beta and no subject who treated a rebleed required hospitalization. CONCLUSION: Subjects with haemophilia with inhibitors who used eptacog beta to treat mild/moderate BEs experienced a low incidence of rebleeding. Rebleeds that did occur were effectively controlled with eptacog beta (median, one dose) without the need for hospitalization.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".