Inhibitor development in nonsevere hemophilia: data from the European Haemophilia Safety Surveillance (EUHASS) registry
Bibliographic record
Abstract
Background: Information on inhibitor development in nonsevere hemophilia and its association with clotting factor concentrate type is limited. Objectives: To assess inhibitor development in patients with nonsevere hemophilia A (HA) and hemophilia B (HB) in the European Haemophilia Safety Surveillance system. Methods: Inhibitors and total treated patients are reported annually. Any exposure to concentrate per year was considered a treatment year. Incidence rates per 1000 treatment years and 95% CIs were calculated according to type of concentrate and compared using incidence rate ratios (IRRs). Results: = .002) were significantly reduced. Conclusion: Inhibitors in nonsevere hemophilia occurred at a rate of 4.2 per 1000 treatment years in HA and 0.1 per 1000 treatment years in HB. Compared with standard half-life FVIII, inhibitor development on plasma-derived and extended half-life FVIII were reduced. These data show that inhibitor monitoring is relevant with nonsevere HA in both sexes and should be continued lifelong.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".