Minimal Clinically Important Difference of Shoulder Outcome Measures and Diagnoses
Bibliographic record
Abstract
OBJECTIVE: Patient-reported outcome scales determine response to treatment. The minimal clinically important difference of these scales is a measure of responsiveness: the smallest change in a score associated with a clinically important change to the patient. This study sought to summarize the literature on minimal clinically important difference for the most commonly reported shoulder outcome scales. DESIGN: A literature search of PubMed and EMBASE databases identified 193 citations, 27 of which met the inclusion/exclusion criteria. RESULTS: For rotator cuff tears, a minimal clinically important difference range of 9-26.9 was reported for American Shoulder and Elbow Surgeons, 8 or 10 for Constant, and 282.6-588.7 for the Western Ontario Rotator Cuff Index. For patients who underwent arthroplasty, a minimal clinically important difference range of 6.3-20.9 was reported for American Shoulder and Elbow Surgeons, 5.7-9.4 for Constant, and 14.1-20.6 for the Shoulder Pain and Disability Index. For proximal humeral fractures, a minimal clinically important difference range of 5.4-11.6 was reported for Constant and 8.1-13.0 for Disability of the Arm, Shoulder, and Hand. CONCLUSIONS: A wide range of minimal clinically important difference values was reported for each patient population and instrument. In the future, a uniform outcome instrument and minimal clinically important difference will be useful to measure clinically meaningful change across practices and the spectrum of shoulder diagnoses.
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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 | 0.031 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".