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Record W4408240410 · doi:10.3389/fnut.2025.1556133

Efficacy of dietary supplements for treating knee osteoarthritis: a systematic review and network meta-analysis

2025· review· en· W4408240410 on OpenAlexaboutno aff
Peng Du, Asha Ajia, Zhi Xiang, Chenming Hu, Pingxi Wang

Bibliographic record

VenueFrontiers in Nutrition · 2025
Typereview
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisOsteoarthritisMedicineSystematic reviewPhysical therapyAlternative medicinePhysical medicine and rehabilitationMEDLINEInternal medicineBiologyPathology

Abstract

fetched live from OpenAlex

Background: Knee osteoarthritis (KOA) stands as a prevalent clinical condition that frequently affects individuals. A growing body of research has highlighted the potential advantages of dietary supplements, including glucosamine and chondroitin, in the management of KOA. Purpose: This study aims to ascertain the most efficacious dietary supplement for KOA, with a specific focus on reducing pain, alleviating stiffness, and enhancing joint function. Methods: We conducted an exhaustive search of multiple databases, including PubMed, Web of Science, Embase, and the Cochrane Library, from inception to May 2023. We specifically focused on randomized controlled trials (RCTs) comparing various dietary supplements with the placebo group within the context of KOA. Assessment of outcomes among these groups relied on the Western Ontario and McMaster University Osteoarthritis Index (WOMAC), with weighted mean differences (WMDs) and associated 95% confidence intervals (CIs) computed. Network meta-analyses were employed to compare outcomes across different supplement groups in comparison with the placebo. The surface under the cumulative ranking curve (SUCRA) was utilized to rank these supplements. Results: Our comprehensive analysis included 22 studies with 2,777 participants in total. The outcomes from our network meta-analysis yielded the following key findings: To reduce the total WOMAC score, the top three interventions were E-OA-7, LParActin, and LcS. For reducing the WOMAC score of pain, the most effective interventions were Aflapin, NEM, and PFP. In addressing the reduction of the WOMAC score of stiffness, NEM, Aflapin, and MSM emerged as the optimal interventions. Finally, for diminishing the WOMAC score of physical function, the most effective interventions were E-OA-7, LParActin, and LcS. Conclusion: In comparison to the placebo, NEM (for stiffness), Aflapin (for pain), and E-OA-07 (for knee function and WOMAC total score) were discerned as the most effective interventions for the treatment of KOA. Clinical trial registration: https://www.crd.york.ac.uk/prospero/.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.535
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0110.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.331
Teacher spread0.287 · 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 teacher head, not a consensus.

Study designSystematic review
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

Citations2
Published2025
Admission routes1
Has abstractyes

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