[Platelet-rich plasma vs corticosteroid for treatment of rotator cuff tendinopathy:a Meta-analysis].
Bibliographic record
Abstract
OBJECTIVE: To explore clinical effects regrarding functional recovery, pain relief, and range of motion of shoulder of platelet-rich plasma (PRP) injection and corticosteroid(CS) injection in treating rotator cuff tendinopathy. METHODS: Randomized controlled trials (RCT) of PRP injection and CS injection in Cochrane Library, EMBASE(Excerpta Medica Database), PebMed, China knowledge Network(CNKI) and Wanfang database were searched from building database to April 20, 2022. According to inclusion and exclusion criteria, literature screening, data extraction and quality evaluation were carried out between two independent researchers, and extracted data were statistically analyzed by Review Manager 5.4.1 software. Short-term (3-6 weeks), medium-term (8-12 weeks) and long-term (≥24 weeks) visual analogue score (VAS), American Shoulder and Elbow Surgeons (ASES) score, Xi'an Western Ontario Rotator Cuff Index (WORC) and shoulder range of motion (ROM) were compared between two groups. RESULTS: >0.05). CONCLUSION: For patients with shoulder cuff tendon disease, there are no significant difference in pain relief and functional recovery during short and medium-term follow-up period. However, RPR injection showed advantages over corticosteroid injection in terms of functional recovery and pain relief during long-term follow-up. There is no significant difference in shoulder range of motion between two groups during the whole follow-up period.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".