Clinical efficacy of probiotic supplementation in the treatment of knee osteoarthritis: a meta-analysis
Bibliographic record
Abstract
Background: We aimed to systematically evaluate and analyze the clinical efficacy of oral probiotics in the treatment of knee osteoarthritis (KOA) based on the theory of "gut-joint axis." Methods: We searched PubMed, The Cochrane Library, Embase, China Knowledge Network (CNKI), Wanfang Database, and Wipro Database (CQVIP) databases for clinical randomized controlled trials of oral probiotics for the treatment of KOA. The literature was organized by Note express software, and the quality of the included literature was evaluated according to the Cochrane systematic evaluation method, and meta-analysis was performed using RevMan 5.4 software. Results: Five randomized controlled trials with 694 participants were included in this study, and the results of the meta-analysis showed that the observation group experienced significant reductions in the Western Ontario and McMaster Universities Osteoarthritis Index total score, visual analog score, and high-sensitivity C-reactive protein level compared to the control group, but did not show significant differences in improvement of stiffness and regulation of body weight. Conclusion: Oral probiotics had an ameliorative effect on function, pain, and inflammatory response in patients with KOA, but our results need to be validated in future large-scale studies. Systematic review registration: The website is 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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.033 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".