Evaluating the Minimum Clinically Important Difference and Patient Acceptable Symptom State for the Womac Osteoarthritis Index after Unicompartmental Knee Arthroplasty
Bibliographic record
Abstract
Patient-Reported Outcome Measures (PROMs) are standardized questionnaires that gather information on health-related quality of life directly from patients. Since a significant statistical mean change may not correspond to a clinical improvement, there is a need to calculate a considerable change in scores. This is done by the Minimum Clinically Important Difference (MCID) and Patient Acceptable Symptom State (PASS). The objective of this article is to report the MCID and the PASS values of the WOMAC (Western Ontario and McMaster University) osteoarthritis index for patients undergoing Unicompartmental Knee Arthroplasty (UKA). A total of 37 patients (25 females and 12 males; mean age 68 ± 8.1 years and mean BMI 28.7 ± 4) who underwent UKA were enrolled. All patients were assessed using the WOMAC and the Oxford Knee Score (OKS) questionnaires before and six months following the procedure. To measure the cut-off values for MCID, distribution methods and anchor methods were applied, while the PASS was assessed only via anchor approaches. The MCID related to the WOMAC average global score was 90.7 ± 7.6, the average pain dimension score was 93.2 ± 6.6, the average stiffness dimension score was 92.6 ± 17, and the average physical function dimension score was 89.7 ± 7.6. In terms of PASS, the normalized WOMAC was 82.8, the pain dimension was 87.5, the stiffness dimension was 93.7, and the functional dimension was 83.1. A 34.5 amelioration in the WOMAC score, from initial evaluation to final follow-up, using change in OKS > 5 as anchor, indicates that the patients' health state improved to a clinically significant degree. A value at least of 82.8 in WOMAC score after treatment denotes that the symptom state is deemed acceptable by most of the 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 | 0.004 | 0.014 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".