Responsiveness of four patient-reported outcome measures to assess physical function in patients with knee osteoarthritis
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to evaluate the responsiveness of four patient-reported outcome measures (PROMs) to measure change in physical function simultaneously in patients with knee osteoarthritis (OA) following currently recommended COSMIN (COnsensus-based Standards for the selection of health status Measurement INstruments) standards. METHOD: Patients with knee OA receiving conservative treatment following a stepped care approach were invited to complete a set of questionnaires at baseline and 3 months. Questionnaires included four widely used measures of physical function: the Knee Injury and Osteoarthritis Outcome Score Physical Function Short Form (KOOS-PS), the Lequesne algofunctional index (LAI), the Lower Extremity Functional Scale (LEFS), and the Western Ontario and McMaster University Osteoarthritis Index Physical Function subscale (WOMAC-PF). Responsiveness of physical function was investigated according to the COSMIN standards by testing 15 a priori defined hypotheses. Responsiveness was considered positive if > 75% of the hypotheses could be confirmed. RESULTS: ]. Baseline values of the four PROMs were, mean (sd): KOOS-PS 53.6 (16.8), LAI 11.0 (4.0), LEFS 40.6 (14.1), and WOMAC-PF 51.8 (19.4). We could confirm 12 out of 15 predefined hypotheses (80%) about expected correlations for the WOMAC-PF whereas for the KOOS-PS, LAI, and LEFS < 75% hypotheses could be confirmed (73, 67, and 73%. respectively). CONCLUSIONS: Our results suggest that the WOMAC-PF is able to detect changes over time in physical function and therefore should be the measure of first choice in clinical trials evaluating the effectiveness of an intervention on physical function in knee OA patients.
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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 | 0.017 | 0.071 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".