Measurement of joint health in persons with haemophilia: A systematic review of the measurement properties of haemophilia‐specific instruments
Bibliographic record
Abstract
INTRODUCTION: Accurate assessment of joint health in persons with haemophilia is crucial. Several haemophilia-specific measurement tools are available, but an overview of the measurement properties is lacking. AIM: To provide an overview of the measurement properties of haemophilia-specific measurement tools to assess clinical joint health. METHODS: MEDLINE and EMBASE were searched for reports on reliability, validity or responsiveness of the World Federation of Haemophilia Orthopedic Joint Score (WFH), Colorado Physical Examination Score (CPE), joint examination score by Petrini (PJS) and Hemophilia Joint Health Score (HJHS). Methodological quality of the studies was assessed using an adapted COSMIN checklist. RESULTS: The search yielded 2905 unique hits, and 98 papers were included. The methodological quality of the included studies was limited. The HJHS was studied most extensively, which yielded limited evidence for good internal consistency and structural validity, moderate evidence for hypothesis testing in adults and conflicting evidence for hypothesis testing in children. Reliability, measurement error and responsiveness were rated unknown due to low COSMIN scores. For the CPE and PJS, we found limited to moderate evidence for good responsiveness and conflicting evidence for hypothesis testing. CONCLUSION: Only patchy evidence is available on the quality of measurement properties of all haemophilia-specific joint health scores. Although significant gaps in the evidence for all instruments remain, measurement properties of the HJHS were most extensively studied and show no drawbacks for use in clinical practice. This review forms the basis for further research aimed at the assessment of measurement properties of measurement tools to assess joint health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".