Estimating the Minimal Clinically Important Difference on the Visual Analogue Scale for Carpometacarpal Thumb Joint Osteoarthritis
Bibliographic record
Abstract
BACKGROUND: The minimal clinically important difference (MCID) is the smallest perceived treatment effect that patients deem clinically significant. There is currently no agreement on an appropriate MCID for the pain visual analogue scale (VAS) in the context of thumb osteoarthritis (OA). METHODS: We approximated MCIDs using a distribution-based approach that pooled standard deviations (SDs) associated with baseline mean values of the pain VAS (0-100 mm). We extracted the data from randomized controlled trials (RCTs) included in a systematic review of adults with long-term OA of the thumb. We excluded RCTs that did not report baseline SD values. The MCIDs were derived at 0.4 and 0.5 SDs of the pooled SD and compared with previously published MCIDs for the pain VAS in OA. RESULTS: A total of 403 patients were pooled from 7 RCTs for the analysis. The mean baseline VAS pain score was 5.6 cm. We derived an MCID of 0.72 cm at 0.4 SDs and 0.91 cm at 0.5 SDs using baseline SDs. We found that MCIDs derived from a distribution-based approach approximated published MCIDs for the VAS for pain for OA in the knee and hip. CONCLUSION: The authors propose that a change of 0.7 to 0.9 cm on the VAS is clinically meaningful in the context of long-term OA of the thumb.
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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 | 0.025 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".