North American prophylaxis studies for persons with severe haemophilia: background, rationale and design
Bibliographic record
Abstract
Arthropathy is associated with the greatest cost and morbidity to persons with haemophilia. Clinical protocols have been developed empirically to prevent or retard the development of joint disease using routine infusions of replacement factor concentrate. However, randomized clinical trials to determine optimal therapy to prevent joint disease in persons with severe haemophilia are lacking. Two clinical trials are ongoing to answer important clinical questions about the prevention of arthropathy. The first, a US randomized clinical trial, is comparing an aggressive multiple-infusion episode-based protocol to standard alternate-day prophylaxis to determine whether prevention of joint disease requires prevention of the bleeding event, per se, or can be achieved by promoting complete resolution of each bleeding event in the joint. This study included the development and validation of sensitive new physical and imaging scales to detect the earliest signs of joint disease in young children. The second, a single-arm, open-label Canadian study, is asking whether prevention of joint disease in young children can be individualized by escalating the dose and frequency of routine replacement infusions of factor concentrate based upon the clinical course of haemophilia in the affected child. Both of these studies will contribute valuable information regarding optimal therapy and will help establish evidence-based medicine for the management of severe haemophilia.
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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 | 0.026 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".