Impact of Systematic Joint Examination (Ultrasound, Functional and Physical) on Treatment Management Decisions in Patients With Haemophilia A in France: Final Data From the Prospective, Observational A‐MOVE Study
Bibliographic record
Abstract
BACKGROUND: Haemophilia management aims to prevent bleeding and preserve joint function. Changes in patients' joint health may influence physicians' decisions to adjust treatment. The Haemophilia Joint Health Score (HJHS) and Haemophilia Early Arthropathy Detection with Ultrasound (HEAD-US) score assess joint health but are not routinely used. AIM: To evaluate whether systematic joint examination with HJHS and/or HEAD-US had an impact on treatment management decisions in France, using final data from the A-MOVE study. METHODS: A-MOVE (NCT04133883) was a 12-month prospective, multicentre study, which enrolled persons with haemophilia A (all severities, aged 6-40 years) treated prophylactically or on demand with standard/extended half-life FVIII replacement. At baseline, 6 and 12 months, HJHS/HEAD-US and changes in patients' management were assessed. RESULTS: Eighty-six patients from 20 sites were included in the final analysis; 68 had HJHS/HEAD-US assessments at 12 months. Over 12 months, 24.4% (n = 21/86) of patients experienced an impact on their haemophilia management due to HJHS/HEAD-US scores; these decisions were impacted by HJHS in about half of the patients (52.4%, n = 11/21) and HEAD-US in almost all patients (95.2%, n = 20/21). Both assessments contributed to a change in management decisions in about half of the patients (47.6%, n = 10/21). Twenty-nine patients (33.7%) had haemophilia management decisions impacted by factors other than HJHS/HEAD-US, including physical examination findings (n = 9) and the occurrence of bleeding episodes (n = 8). CONCLUSIONS: Final data from the A-MOVE study show that systematic joint assessments, through functional/physical examination (HJHS) and ultrasound (HEAD-US), may impact treatment management decisions in persons with haemophilia A.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".