The Hemophilia Joint Health Score version 2.1 Validation in Adult Patients Study: A multicenter international study
Bibliographic record
Abstract
Background The Hemophilia Joint Health Score (HJHS) was developed and validated to detect arthropathy in children. Additional evidence is required to show validity in adults. We studied the convergent and discriminant construct validity of the HJHS version 2.1(HJHSv2.1) in adults with hemophilia. A secondary aim was to define age-related normative adult HJHSv2.1 reference values. Methods We studied 192 adults with hemophilia, and 120 healthy adults in four age-matched groups—18 to 29, 30 to 40, 41 to 50, and >50 years—at nine centers. Trained physiotherapists scored the HJHS and World Federation of Hemophilia (WFH) joint score. Health history, the Functional Independence Scale of Hemophilia (FISH), Hemophilia Activities List (HAL), and Short-Form McGill Pain Questionnaire (SF-MPQ) were also collected. Results The median age was 35.0 years. Of participants with hemophilia, 68% had severe, 14% moderate, and 18% mild disease. The HJHS correlated strongly with WFH score (Spearman’s rho [rs] = .95, P < .001). Moderate correlations were seen between the FISH (rs = .50, P < .001) and SF-MPQ Present Pain Intensity (rs = .50, P < .001), while a modest correlation was found with the HAL (rs = −.37, P < .001). The HJHS significantly differentiated between age groups (Kruskal-Wallis T = 35.02, P < .001) and disease severity in participants with hemophilia. The HJHS had high internal reliability (Cronbach’s α = .88). We identified duration of swelling as a redundant item in the HJHS. Conclusions The HJHS shows evidence of strong convergent and discriminant construct validity to detect arthropathy in adults with hemophilia and is well suited for use in this population.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 | 0.001 |
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".