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Record W3176564191 · doi:10.1177/23259671211011948

Adverse Reactions and Clinical Outcomes for Leukocyte-Poor Versus Leukocyte-Rich Platelet-Rich Plasma in Knee Osteoarthritis: A Systematic Review and Meta-analysis

2021· review· en· W3176564191 on OpenAlexaboutno aff
Jun‐Ho Kim, Yong‐Beom Park, Chul‐Won Ha, Young Ju Roh, Jung-Gwan Park

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePlatelet-rich plasmaOsteoarthritisMeta-analysisPlateletAdverse effectIntensive care medicinePhysical therapyImmunologyInternal medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

Background: Platelet-rich plasma (PRP) has gained attention as a therapeutic option for knee osteoarthritis; however, its efficacy varies widely. Leukocytes in PRP raise the concern of aggravating proinflammatory activity. To date, PRP has rarely been investigated with regard to leukocyte concentration. Purpose: To provide clinical evidence of the intra-articular injection of PRPs containing different leukocyte concentrations. Study Design: Systematic review; Level of evidence, 4. Methods: We systematically searched the MEDLINE, Embase, Cochrane Library, CINAHL, and Scopus databases. PRP was classified into leukocyte-poor (LP-PRP) and leukocyte-rich (LR-PRP). Clinical outcomes including Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), visual analog scale (VAS) for pain score, International Knee Documentation Committee (IKDC) subjective score, and adverse reactions were evaluated. The Methodological Index for Non-Randomized Studies criteria were used for quality assessment. Results: Included were 32 studies with an evidence level between 1 and 4. Both LP-PRP and LR-PRP showed improvements above the minimal clinically important difference (MCID) in VAS pain score. No significant intergroup difference was seen at 3, 6, or 12 months of follow-up. Regarding function, both LP-PRP and LR-PRP showed improvements above the MCID in the WOMAC and IKDC scores, with no significant difference between the groups. Adverse reactions for pain were significantly higher in LR-PRP than in LP-PRP (odds ratio, 1.64; 95% confidence interval, 1.29-2.10; P = .01). After intra-articular PRP injection, LR-PRP showed a significantly higher rate of swelling than LP-PRP (odds ratio, 1.56; 95% confidence interval, 1.22-1.99; P = .02). The mean Methodological Index for Non-Randomized Studies score of the included studies was 18.6 (range, 10-24). Conclusion: Intra-articular PRP injection resulted in improvements above the MCID in terms of pain and function in patients with knee osteoarthritis up to 12 months. The risk of local adverse reactions appeared to be increased after LR-PRP compared with LP-PRP injection. The findings of this review can support the potential use of intra-articular PRP injection for the treatment of knee osteoarthritis. In clinical application, clinicians need to consider selecting a specific type of PRP for knee osteoarthritis.

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)0.011
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0210.033
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.097
GPT teacher head0.393
Teacher spread0.296 · 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

Citations94
Published2021
Admission routes1
Has abstractyes

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