Prognosis in Soft Tissue Disorders of the Shoulder: Predicting Both Change in Disability and Level of Disability After Treatment
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Clinicians often are faced with questions about prognosis and outcome of shoulder disorders. The purpose of this study was to identify predictors of both change in disability and level of disability following physical therapy treatment. SUBJECTS: The subjects were consecutive patients (n=361) who were receiving physical therapy for soft tissue shoulder disorders. METHODS: Clinical response to physical therapy, which was measured using the Disabilities of the Arm, Shoulder, and Hand (DASH) measure, was assessed over 12 weeks. The 28 independent baseline predictors included demographics, disorder-related and disability measures, medication use, clinical findings, and expectations for recovery. Multiple linear regression techniques were used. RESULTS: Predictors of greater disability at discharge were: higher initial disability, therapist prediction of restricted activities at discharge, workers' compensation claim, older age, and being female. Predictors of greater improvement in disability were: shoulder surgery, higher pain intensity, shorter duration of symptoms, younger age, and poorer general physical health (measured using the 36-Item Short-Form Health Survey [SF-36]). DISCUSSION AND CONCLUSIONS: Prognostic factors differ depending on the format of the outcome. Only age was significant in both models.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".