Comparison of the responsiveness of the WOMAC and the 12-item WHODAS 2.0 in patients with Kashin–Beck disease
Bibliographic record
Abstract
Abstract Background Several questionnaires have been used to assess the health status of patients with Kashin-Beck disease (KBD) in clinical trials, but the evidence regarding the responsiveness of these instruments in KBD patients is limited. Therefore, the aim of this study was to evaluate and compare the responsiveness of the Chinese version of the Western Ontario and McMaster Universities Osteoarthritis index (WOMAC) and 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in KBD patients undergoing intra-articular injection of hyaluronic acid (HA). Methods A sample of 232 KBD patients treated with intra-articular injection of HA completed the WOMAC, 12-item WHODAS 2.0 and joint dysfunction index (JDI) both pre- and post-treatment. Responsiveness was assessed using correlation and receiver operating characteristic (ROC) curve analyses following the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. Results Overall, there were significant improvements in the mean scores on the WOMAC and on the 12-item WHODAS 2.0, except for in the cognition domain. Correlation analysis showed that changes in the WOMAC and 12-item WHODAS 2.0 scores had moderate or weak positive associations with the changes in the JDI. However, acceptable areas under the ROC curve (value > 0.7) were found for all domains and for the total score on the WOMAC, but only for the mobility domain and the total score on the 12-item WHODAS 2.0. Conclusions These results demonstrated that the WOMAC was more responsive than the 12-item WHODAS 2.0 in KBD patients treated with intra-articular injection of HA. Our findings support the continued use of the WOMAC as an outcome measure in assessing disability in KBD 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 | 0.003 | 0.011 |
| 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".