499 HEMOPHILIA JOINT HEALTH SCORES (HJHS): PERFORMANCE OF THE HJHS IN DIFFERENT POPULATIONS
Bibliographic record
Abstract
Introduction: The Hemophilia Joint Health Score (HJHS) was developed for detection of early joint changes in children and youth with haemophilia with intensive treatment. The HJSH has been reported to be time consuming. The purpose of this study was to determine the performance of the HJHS across different populations and ages and to identify redundant items. Methods: This study was a cross-sectional multicenter secondary analysis on pooled data of published studies using the HJHS (0-124, 0 as optimum score). All patients with haemophilia A (FVIII) and B (FIX) aged 4-30 years were included. To identify redundant items the following aspects were evaluated: inter-item correlations and component loadings with an exploratory factor analysis, internal consistency, item-total correlations and frequency of endorsement. Results: HJHS scores of 499 patients from 7 studies were pooled. Patients from Romania, Pakistan, Lithuania, Brazil and the USA (n=279) had a median age of 13 years (range 4;29), 75% had severe haemophilia and 39% received prophylaxis. Patients from the Netherlands, UK and Canada (n=220) had a median age of 13 years (range 4;30), 93% had severe haemophilia and 91% received prophylaxis. Median (IQR) HJHS total score was significantly higher in the populations with a less intensive treatment: 12 (5-26) vs. 2 (0-7) (p<0.001). Knees were the most affected joints in less intensive treated patients and ankles in the more intensive treated patients. In both groups, the item ‘duration swelling’ was least informative (0 scores: ≥85%) and the item ‘global gait’ was most informative (0 scores: ≤63%). In addition, median (IQR) HJHS total score was significantly higher in adults (n=174) vs. children (n=325): 12 (4-23) vs. 5 (0-12) (p<0.001). In both age groups, the item ‘duration swelling’ was least informative (0 scores: ≥84%) and the item ‘global gait’ was most informative (0 scores: ≤65%). Discussion/Conclusion: This study supports that the HJHS is able to measure joint health in patients across different populations and ages. There might be room for item-reduction based on the non-informative items that have been found in this study. A more compact version of the HJHS is expected to facilitate clinical use in patients with haemophilia. The next step is to combine data from statistical analyses of the pooled data, with expert opinion to explore and consider options for shortening the HJHS without loss of information.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".