Effectiveness of Ultrasound-Guided Corticosteroid Injections, Prolotherapy, and Exercise Therapy on Partial-Thickness Supraspinatus Tears
Bibliographic record
Abstract
CONTEXT: To investigate the effects of steroid injection (STE), prolotherapy (PRO), and exercise therapy in the treatment of partial tears of the supraspinatus. DESIGN: A retrospective cohort study. METHODS: A total of 64 patients with clinically and radiologically diagnosed partial-thickness supraspinatus tear who received either a cortisone injection (STE), dextrose PRO, or physical therapy combined with home-based exercise therapy were included. Main outcome measures were patients' visual analog scale scores, Western Ontario Rotator Cuff (WORC) Index scores, and the Shoulder Pain and Disability Index scores at the baseline, 3 weeks, and 3 months. RESULTS: The effect of group, time, and group-time interaction on visual analog scale, WORC, and Shoulder Pain and Disability Index scores was statistically significant (P < .001). Visual analog scale and Shoulder Pain and Disability Index scores were the lowest in the STE group at week 3, and the lowest in the PRO group at month 3 (P < .001). WORC scores of the STE group were the highest at week 3 (P < .001). At month 3, WORC scores of STE and PRO groups were similar (P = .089), but significantly higher than exercise therapy. CONCLUSIONS: Corticosteroids provide a fast pain-relieving effect and improvement in function in partial-thickness rotator cuff tears, but these effects diminish over time, whereas PRO provides a long-lasting effect.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".