What is better for rotator cuff tendinopathy: dextrose prolotherapy, platelet-rich plasma, or corticosteroid injections? A randomized controlled study
Bibliographic record
Abstract
Abstract Background Rotator cuff tendinopathy (RCT) is a leading cause of shoulder pain and disability. Management is mainly conservative, but the limited ability of tendons to regenerate is the main cause of unsatisfactory results. So, we conducted our study to compare the efficacy of deep prolotherapy (glucose 25%), platelet-rich plasma (PRP), and betamethasone corticosteroid for treatment of RCT to find the most effective one based on clinical, functional, and radiological assessment. Results Regarding visual analog scale (VAS), it was significantly ( p < 0.001) improved after injection among group 1 (prolotherapy group) and group 3 (steroid group) patients, while no significant improvement was noted among group 2 (PRP group) ( p = 0.212) patients. The Western Ontario Rotator Cuff (WORC) Index significantly improved among the studied groups ( p < 0.001, p = 0.049, and p < 0.001, respectively) after injection. Regarding the range of motion (ROM), a significant improvement ( p = 0.029) was achieved in group 1 after injection but no significant improvements were noted among group 2 and 3 patients ( p = 0.529 and 0.121, respectively). There was a significant improvement among group 1 and 2 patients ( p < 0.001 and p = 0.020, respectively) regarding the grade of tendon lesions but no improvement occurred among group 3 patients ( p = 0.470). Conclusion Prolotherapy injections improve shoulder ROM, VAS, WORC index, and rotator cuff tendon healing while PRP injections improve WORC index and tendon healing but steroid injection has no effect on healing. Trial registration PACTR202005610509496 . Retrospective registration on May 25, 2020, Pan African Clinical Trial Registry.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".