Responsiveness and Minimal Important Changes of the Western Ontario and McMaster Universities Osteoarthritis Index in Subjects Undergoing Rehabilitation Following Hip Fracture
Bibliographic record
Abstract
OBJECTIVE: To evaluate the responsiveness and minimal important changes (MICs) for the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) and its subscales in subjects with hip fractures. DESIGN: At the beginning and end of a 2-month rehabilitation program, 106 patients completed the WOMAC. After the program, the global perceived effect (GPE) was analyzed to produce a dichotomous outcome (improved vs. stable). Responsiveness for the WOMAC and its subscales were calculated by distribution (effect size; standardized response mean) and anchor-based methods (receiver operating characteristic curves; correlations between change scores of the WOMAC and its subscales and GPE). Receiver operating characteristic curves were also used in order to compute the best cutoff levels between improved and stable subjects (MICs). RESULTS: The effect size ranged from 0.64 to 11.10 and the standardized response mean from 0.79 to 2.65. The receiver operating characteristic analyses revealed an MIC value (area under the curve, sensitivity, specificity) for the WOMAC of 29 (0.817, 92, 78); values of 35 (0.820, 77, 76) 44 (0.625, 25, 95), and 24 (0.707, 100, 76) were found for pain, stiffness, and physical function subscales, respectively. Correlations between change scores of the WOMAC and its subscales and GPE were low (0.240, for stiffness subscale) to moderate (0.438-0.570 for the other subscales and the WOMAC). CONCLUSIONS: The WOMAC and its subscales (all but stiffness) were sensitive in detecting clinical changes in subjects with hip fracture undergoing rehabilitation. We recommend taking the MICs provided into account when assessing patients' improvement or planning studies in this clinical context.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".