Responsiveness of five shoulder outcome measures at follow-ups from 3 to 24 months
Bibliographic record
Abstract
Abstract Background To assess responsiveness of five outcome measures at four different follow-ups in patients with SLAP II lesions of the shoulder. Methods 119 patients with symptoms and signs, MRI arthrography and arthroscopic findings were included. The Western Ontario Shoulder Instability Index (WOSI), Oxford Instability Shoulder Score (OISS), EuroQol (EQ-5D3L), Rowe Score and Constant-Murley Score (CMS) were assessed at baseline, 3, 6, 12 and 24 months. The analysis contains both anchor-based and distribution-based methods, and hypothesis testing. Results Confidence intervals for ROC cut-off values, representing MID, for OISS, CMS and EQ-5D3L crossed zero at 3 months. Cut-off values were stable between 6- and 24-months follow-up. At 24-months ROC cut-off values (95% CI) were: Rowe 18 (13 to 24); WOSI 331 (289 to 442); OISS 9 (5 to 14); CMS 11 (9 to 15) and EQ-5D3L 0.123 (0.035 to 0.222). MID 95%limit estimates were substantially higher than ROC cut-off values and MID MEAN at all follow-ups for all instruments. The reliable change proportion (RCP) values in the improved group were highest for WOSI and the Rowe Score (ranging from 68 to 87%) and significantly lower for CMS. EQ-5D3L had the lowest values (13 to 16%). We found a moderate correlation between mean change scores of the outcome measures and the anchor, except for the EQ-5D3L. Conclusions In patients with SLAP II-lesions the patient reported OISS and WOSI and the clinical Rowe score had best responsiveness. Our results suggest that 3 months follow-up is too early for outcome evaluation.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".