Identifying performance‐based outcome measures of physical function in people with haemophilia (IPOP)
Bibliographic record
Abstract
INTRODUCTION: Recent recommendations of core outcome sets for haemophilia highlight the need for including measures of performance-based physical health and physical function sustainability. To date, there is no consensus on what outcomes might be of value to clinicians and patients. AIM: To identify instruments of performance-based physical function to monitor musculoskeletal health in people with haemophilia that are practical in the clinical setting. METHODS: Utilising components from the Activities and Participation Category of the WHO International Classification of Functioning (WHO-ICF), a consensus-based, decision analysis approach was used to: identify activities people with haemophilia have most difficulty performing; identify quantitative performance-based measures of identified activities via a scoping review; and obtain views on acceptability of the tests utilising a DELPHI approach. RESULTS: Eleven activities were identified: maintaining a standing position, walking long distances, walking up and down stairs, walking on different surfaces, running, hopping, jumping, squatting, kneeling, undertaking a complex lower limb task, undertaking a complex upper limb task. Following a 2-round DELPHI survey of international physiotherapists, the 6-min walk test, timed up and down stairs, 30-s sit to stand, single leg stance, tandem stance, single hop for distance (children only) and timed up and go (adults only) reached consensus. CONCLUSION: This study is the first step in defining a core set of performance-based instruments to monitor physical health and sustainability of physical function outcomes in people with haemophilia. Establishing the psychometric properties of the instruments and whether they are meaningful to people with haemophilia is essential.
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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 | 0.043 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".