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Record W2895996792 · doi:10.2340/16501977-2366

Efficacy of hyaluronic acid after knee arthroscopy: A systematic review and meta-analysis

2018· review· en· W2895996792 on OpenAlexaboutno aff
Dongchao Shen, Min Chen, Kun Chen, Ting Wang, Laijin Lu, Xiaojing Yang

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHyaluronic acidWOMACArthroscopyMeta-analysisRandomized controlled trialOsteoarthritisConfidence intervalPhysical therapyKnee painInternal medicineSurgery

Abstract

fetched live from OpenAlex

Hyaluronic acid might be beneficial for patients after knee arthroscopy.However, the results remain controversial.A systematic review and meta-analysis was conducted to explore the efficacy of hyaluronic acid following knee arthroscopy.Randomized controlled trials assessing the effect of hyaluronic acid in knee arthroscopy were included.Compared with control intervention after knee arthroscopy, hyaluronic acid treatment was found to significantly improve Western Ontario and McMaster Universities Osteoarthritis Index scores and decrease pain on motion, but had no substantial influence on pain scores at 2, 6 and 12 weeks after knee arthroscopy.Objective: To investigate the effect of hyaluronic acid on functional recovery and pain control in patients following knee arthroscopy.Design: A systematic review and meta-analysis was conducted to explore the efficacy of hyaluronic acid following knee arthroscopy.Subjects and methods: Randomized controlled trials (RCTs) assessing the effect of hyaluronic acid in knee arthroscopy were included.A meta-analysis was performed using the random-effect model.Results: Six RCTs involving 310 patients were included in the meta-analysis.Overall, compared with control intervention following knee arthroscopy, hyaluronic acid treatment was found to significantly increase Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores (mean difference 11.43; 95% confidence intervals (95% CI) 1.39-21.47;p = 0.03), but had no impact on pain scores at 2 weeks (mean difference -0.16; 95% CI -0.81-0.49;p = 0.63), pain scores at 6 weeks (mean difference 0.01; 95% CI -0.86-0.89;p = 0.98), pain scores at 12 weeks (mean difference -0.51; 95% CI -1.56-0.53;p = 0.34).In addition, pain on motion was significantly reduced after knee arthroscopy (risk ratio (RR) 0.22; 95% CI 0.06-0.79;p = 0.02).Conclusion: Compared with control intervention after knee arthroscopy, hyaluronic acid treatment was found to significantly improve WOMAC score and decrease pain on motion, but had no substantial influence on pain scores at 2, 6 and 12 weeks after knee arthroscopy.

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)0.012
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: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0200.034
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0030.002
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 head0.042
GPT teacher head0.376
Teacher spread0.334 · 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

Citations17
Published2018
Admission routes1
Has abstractyes

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