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Record W1981688423 · doi:10.1177/0363546515580787

Effect of Leukocyte Concentration on the Efficacy of Platelet-Rich Plasma in the Treatment of Knee Osteoarthritis

2015· article· en· W1981688423 on OpenAlexaboutno aff
Jonathan C. Riboh, Bryan M. Saltzman, Adam B. Yanke, Lisa A. Fortier, Brian J. Cole

Bibliographic record

VenueThe American Journal of Sports Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisMeta-analysisPlatelet-rich plasmaInternal medicinePlaceboAdverse effectCochrane LibraryRandomized controlled trialMean differencePlateletConfidence intervalPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Leukocyte-poor platelet-rich plasma (LP-PRP) is hypothesized to be more suitable for intra-articular injection than leukocyte-rich PRP (LR-PRP) in the treatment of knee osteoarthritis. PURPOSE: To compare clinical outcomes and rates of adverse reactions between LP-PRP and LR-PRP for this application. STUDY DESIGN: Meta-analysis. METHODS: The MEDLINE, EMBASE, and Cochrane databases were reviewed. The primary outcome was the incidence of local adverse reactions. Secondary outcomes were the changes in International Knee Documentation Committee (IKDC) subjective score and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score between baseline and final follow-up measurements. A Bayesian network meta-analysis was performed, with a post hoc meta-regression to correct for baseline differences in WOMAC scores. Treatment rankings were based on surface under the cumulative ranking (SUCRA) probabilities. RESULTS: Included in the analysis were 6 randomized controlled trials (evidence level 1) and 3 prospective comparative studies (evidence level 2) with a total of 1055 patients. Injection of LP-PRP resulted in significantly better WOMAC scores than did injection of hyaluronic acid (mean difference, -21.14; 95% CI, -39.63 to -2.65) or placebo (mean difference, -17.84; 95% CI, -34.95 to -0.73). No such difference was observed with LR-PRP (mean difference, -14.28; 95% CI, -44.80 to 16.25). All treatment groups resulted in equivalent IKDC subjective scores. The SUCRA analysis showed that LP-PRP was the highest ranked treatment for both measures of clinical efficacy (WOMAC and IKDC). Finally, PRP injections resulted in a higher incidence of adverse reactions than hyaluronic acid (odds ratio, 5.63; 95% CI, 1.38-22.90), but there was no difference between LR-PRP and LP-PRP (odds ratio, 0.78; 95% CI, 0.05-11.93). These reactions were nearly always local swelling and pain, with a single study reporting medical side effects including syncope, dizziness, headache, gastritis, and tachycardia (17/1055 total patients). CONCLUSION: LP-PRP results in improved functional outcome scores compared with hyaluronic acid and placebo when used for treatment of knee osteoarthritis. LP-PRP and LR-PRP have similar safety profiles, although both induce more transient reactions than does hyaluronic acid. Adverse reactions to PRP may not be directly related to leukocyte concentration.

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)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.015
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.291
Teacher spread0.273 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations406
Published2015
Admission routes1
Has abstractyes

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