The Role of Platelet‐Rich Plasma in Arthroscopic Rotator Cuff Repair: A Systematic Review With Quantitative Synthesis
Bibliographic record
Abstract
PURPOSE: Despite the theoretic basis and interest in using platelet-rich plasma (PRP) to improve the potential for rotator cuff healing, there remains ongoing controversy regarding its clinical efficacy. The objective of this systematic review was to identify and summarize the available evidence to compare the efficacy of arthroscopic rotator cuff repair in patients with full-thickness rotator cuff tears who were concomitantly treated with PRP. METHODS: We searched the Cochrane Central Register of Controlled Trials, Medline, Embase, and PubMed for eligible studies. Two reviewers selected studies for inclusion, assessed methodologic quality, and extracted data. Pooled analyses were performed using a random effects model to arrive at summary estimates of treatment effect with associated 95% confidence intervals. RESULTS: Five studies (2 randomized and 3 nonrandomized with comparative control groups) met the inclusion criteria, with a total of 261 patients. Methodologic quality was uniformly sound as assessed by the Detsky scale and Newcastle-Ottawa Scale. Quantitative synthesis of all 5 studies showed that there was no statistically significant difference in the overall rate of rotator cuff retear between patients treated with PRP and those treated without PRP (risk ratio, 0.77; 95% confidence interval, 0.48 to 1.23). There were also no differences in the pooled Constant score; Simple Shoulder Test score; American Shoulder and Elbow Surgeons score; University of California, Los Angeles shoulder score; or Single Assessment Numeric Evaluation score. CONCLUSIONS: PRP does not have an effect on overall retear rates or shoulder-specific outcomes after arthroscopic rotator cuff repair. Additional well-designed randomized trials are needed to corroborate these findings. LEVEL OF EVIDENCE: Level III, systematic review of Level I, II, and III studies.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".