The factor subdimensions of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) help to specify hip and knee osteoarthritis. a prospective evaluation and validation study.
Bibliographic record
Abstract
OBJECTIVE: To determine whether it is possible to specify different score patterns for hip and knee osteoarthritis (OA), and to identify the degree of responsiveness and the validity of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) factors, which are alternative health dimensions obtained by factor analysis of the WOMAC items. METHODS: WOMAC scales and WOMAC factors were compared in a prospective setting examining patients with hip and knee OA before and after rehabilitative inpatient intervention (n = 317). In a partial sample (n = 103), the validity of the WOMAC factors was determined by a global rating of their activities. RESULTS: The WOMAC factor "ascending/descending" was significantly different for hip and knee OA in the health state before therapy (score in hip 5.09, in knee 6.59; p < 0.001); this was also true of the effect size after therapy (hip 0.39, knee 0.65; p = 0.012). The WOMAC scales did not differ for the 2 conditions. The WOMAC factor "ascending/descending" was the most responsive dimension in knee OA (effect size 0.65), but in hip OA the WOMAC pain scale was most responsive (effect size 0.55). Most of the WOMAC factors correlated moderately (r = 0.52-0.69) with the patient's self-rating on the validation questionnaire. CONCLUSION: The WOMAC factors are valid measures. Analyzing the WOMAC by the WOMAC factors facilitates and improves the differential relevance and accuracy of the WOMAC for specific conditions such as hip and knee OA.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.003 | 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".