Haemophilia specialist nurses’ perceptions of haemophilia B
Bibliographic record
Abstract
Abstract Introduction Some clinicians believe that haemophilia B is associated with less bleeding than haemophilia A, yet there appears to be little difference in health-related outcomes. Current clinical practice reduces the risk of bleeds, making differences difficult to measure. We surveyed specialist haemophilia nurses to discern their opinions about the impact of haemophilia B compared to haemophilia A. Methods Between July and September 2020, European and Canadian nurses were invited to complete an online survey (25 questions) about perceptions of management and treatment of haemophilia B. Results Fifty-nine nurses (46 European, 13 Canadian) completed the survey. Bleeding was reported as different in haemophilia B by 37% of respondents, and treatment as different by over half. Opinions and experience around using extended half-life (EHL) products varied. Self-reported confidence in using EHL products was rated at a mean of 7.1 (range 3–10) with 47% believing these would remain the optimal treatment in 2025. Conclusion Some nurses believe haemophilia A and B are managed differently. Variations in experience and levels of confidence in the use of EHL products, combined with a belief that these products will remain an optimal treatment for haemophilia B for the next five years, indicates a need for education to promote confidence and competence.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".