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Record W4303684300 · doi:10.1186/s13018-022-03293-0

Platelet-rich plasma use in meniscus repair treatment: a systematic review and meta-analysis of clinical studies

2022· review· en· W4303684300 on OpenAlexaboutno aff
Ziquan Li, Xisheng Weng

Bibliographic record

VenueJournal of Orthopaedic Surgery and Research · 2022
Typereview
Languageen
FieldMedicine
TopicKnee injuries and reconstruction techniques
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsMedicinePlatelet-rich plasmaOrthopedic surgeryMeta-analysisMeniscusSurgeryPlateletInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is conflicting clinical evidence whether platelet-rich plasma (PRP) therapies could translate to an increased meniscus healing rate and improved functional outcomes. The objective of this systematic review and meta-analysis was to compare the failure rate and patient-reported functional outcomes in meniscus repair augmented with and without PRP. METHODS: We comprehensively searched the PubMed, Web of Science, Medline, Embase, and Cochrane Library databases to identify studies that compared the clinical efficacy of meniscus repair performed with PRP versus without PRP. The primary outcome was the meniscus repair failure rate, while the secondary outcomes were knee-specific patient-reported outcomes, including the International Knee Documentation Committee (IKDC) score, Lysholm knee scale, visual analog scale, Tegner activity level score, Western Ontario and McMaster Universities Osteoarthritis Index score, Single Assessment Numeric Evaluation score, and Knee injury and Osteoarthritis Outcome Score. Furthermore, subgroup analyses were performed by stratifying the studies according to the PRP preparation technique to investigate the potential sources of heterogeneity among studies. RESULTS: Our meta-analysis included nine studies (two RCTs and seven non-RCTs) with 1164 participants. The failure rate in the PRP group was significantly lower than that in the non-PRP group [odds ratio: 0.64, 95% confidence interval (CI) (0.42, 0.96), P = 0.03]. Furthermore, the PRP group was associated with a statistically significant improvement in the visual analog scale for pain [Mean difference (MD): - 0.76, 95% CI (- 1.32, - 0.21), P = 0.007] and Knee injury and Osteoarthritis Outcome Score-symptom [MD: 8.02, 95% CI (2.99, 13.05), P = 0.002] compared with the non-PRP group. However, neither the IKDC score nor the Lysholm knee scale showed any differences between the two groups. In addition, the results of subgroup analyses favored PRP over platelet-rich fibrin matrix (PRFM) regarding the IKDC score. CONCLUSIONS: Although meniscus repairs augmented with PRP led to significantly lower failure rates and better postoperative pain control compared with those of the non-PRP group, there is insufficient RCT evidence to support PRP augmentation of meniscus repair improving functional outcomes. Moreover, PRP could be recommended in meniscus repair augmentation compared with PRFM. PRFM was shown to have no benefit in improving functional outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.032
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.036
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.545
GPT teacher head0.539
Teacher spread0.006 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations49
Published2022
Admission routes1
Has abstractyes

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