Minimal important differences for the WOMAC osteoarthritis index and the Forgotten Joint Score-12 in total knee arthroplasty patients
Bibliographic record
Abstract
BACKGROUND: Total knee arthroplasty (TKA) is an effective treatment for end-stage osteoarthritis. Patient reported-outcome measures (PROMs) capture the patients' perception of the success of an intervention. The minimal important difference (MID) is an important characteristic of the PROM, which helps to interpret results. The aim of this study was to identify the MID for the Forgotten Joint Score-12 (FJS-12) and Western Ontario and McMaster Universities (WOMAC) osteoarthritis index. METHODS: Data were collected in a prospective cohort study. Patients were asked to complete the FJS-12, WOMAC osteoarthritis index and transition items evaluating change over time to determine the MID. We employed an anchor-based methodology relating score change to the response categories of the transition items using both binary logistic regression and receiver operating characteristic (ROC) analysis. RESULTS: Data from 199 patients were analysed. Mean age was 72.3 years, 58% were women. Employing binary logistic regression the MID for the FJS-12 was 10.8 points, for the WOMAC pain score 7.5 points and for the WOMAC function score 7.2 points. ROC analyses found a MID of 13.0 points for the FJS-12, 12.5 points for WOMAC pain and 14.7 points for WOMAC function. CONCLUSION: We report MIDs for the FJS-12 and the WOMAC Pain and Function scales in a TKA patient cohort, which can be used to interpret meaningful differences in score. In line with previous research, we found more advanced statistical methods to result in smaller MID estimates for both scores. TRIAL REGISTRATION: Written consent for this study was obtained from all participants and ethical approval was granted by the local ethics committee (Ethikkommission St. Gallen; EKSG 14/973; Registered 03 July 2014; http://www.sg.ch/home/gesundheit/ethikkommission.html).
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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 | 0.020 |
| 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 | 0.001 | 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".