The Effect of Platelet-Rich Plasma (PRP) on Improvement in Pain and Symptoms of Shoulder Subacromial Impingement Syndrome
Bibliographic record
Abstract
Abstract Background: Subacromial impingement is one of the most common complaints of shoulder. Treatments include avoiding of painful activities, oral anti-pain drugs, physical therapy modalities, corticosteroid injection and exercise therapy. Some studies have shown that platelet- rich plasma(PRP) is effective on tendinitis and tearing of tendons, ligaments and muscles, but evidence that has proved PRP as a conservative treatment in shoulder pathologies is very limited. This study aims to investigate the effect of PRP injection on relieving pain and improving daily function of patients with shoulder impingement syndrome. Materials and Methods: In this clinical trial study, patients older than 40 with pain more than three months were included. If they had three of four positive diagnostic clinical tests of shoulder impingement that were confirmed by shoulder MRI, could be injected PRP twice. The time between injections was 1 month. Pain was measured by visual analog scale (VAS) and function was measured by two questionnaires named disabilities of the arm, shoulder and hand (DASH) and western Ontario rotator cuff index (WORC). Range of motion (ROM) of shoulder was measured in five directions by goniometry . All of these parameters were evaluated before intervention and in 1, 3, 6 months later. Results: with due attention to a six-month folloe-up, PRR injection was effective in pain reduction and improvement of patient's function (p<0.05). Shoulder Rom increased in all directions except external rotation and the power of shoulder muscles was evidently improved statistically in flexion, abduction and internal toration. Conclusion: PRP injection could effectively reduce pain and improve daily activities in patients with shoulder impingement syndrome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".