The association between statin use and osteoarthritis-related outcomes: An updated systematic review and meta-analysis
Bibliographic record
Abstract
Objective: Findings among studies evaluating the effect of statin use and OA development in a 2020 meta-analysis of data from 11 observational studies of statin use and osteoarthritis (OA) revealed controversial results. We aimed to determine the associations between statin use and OA-related outcomes in an updated meta-analysis. Methods: The protocol was registered with PROSPERO (CRD42020163983). A systematic literature retrieval was performed in the online databases, including PubMed, Cochrane Library, Embase, Web of Science, and Scopus, from inception to 1 June 2022, for clinical studies that compared the effects of statin users vs. nonusers on OA-related outcomes risks. Systematic reviews and meta-analyses were performed to estimate the correlations between statin use and OA-related outcomes. Tendency analysis was also used to estimate dose-response effects. The risk of bias was evaluated with the Newcastle–Ottawa scale. Results: We included 23 studies involving more than 6,000,000 participants. Statin use was associated with increased OA risk (OR 1.099 [95%CI 1.002–1.206, p = 0.045]). Higher statin doses had higher OA risk (simvastatin equivalent daily of >40 mg). OA and related surgery risks were significantly reduced in statin users using antihypertensive drugs (AHDs). No significant differences were seen in other outcomes. Conclusion: This meta-analysis inferred that statin use might be associated with increased OA development, especially at higher doses. The present study highlights the importance of recognizing potential OA risk in the population with long-term and/or high-dose statin use, especially in older populations. In addition, AHDs are associated with lower OA risk and fewer surgeries in hypertensive statin users. Due to limitations of heterogeneity and confounders, more rigorous studies are needed to define the correlations between statin use and OA-related outcomes.
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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 | 0.021 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.044 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".