1443Safety of red yeast rice supplementation: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
Abstract Background Recently, concerns regarding the safety of red yeast rice (RYR) have been raised after the publication of some case reports claiming toxicity. Purpose Since the previous meta-analyses on the effects of RYR were mainly focused on its efficacy to improve the lipid profile and other cardiovascular parameters, we carried out a meta-analysis on safety data derived from the available randomized controlled clinical trials (RCTs). Methods Primary outcomes were musculoskeletal disorders (MuD). Secondary outcomes were non-musculoskeletal adverse events (Non-MuD) and serious adverse events (SAE). Subgroups analyses were carried out considering the intervention (RYR alone or in association with other nutraceutical compounds), monacolin K administered daily dose (≤3, <3–5 and >5 mg/day), follow-up (>12 or ≤12 weeks), with statin therapy or statin-intolerance and type of control treatment (placebo or statin treatment). Results Data were pooled from 52 RCTs comprising 110 treatment arms, which included 8503 subjects, with 4421 in the RYR arm and 4287 in the control one. Monacolin K administration was not associated with increased risk of MuD (odds ratio [OR]=0.94, 95% confidence interval [CI] 0.53,1.65). (Figure below presents the forest plot comparing the RYR associated risk of MuD in the entire population). Moreover, we found a reduced risk of Non-MuD (OR=0.59, 95% CI 0.50, 0.69) and SAE (OR=0.54, 95% CI 0.46, 0.64) vs. control. Subgroups analyses confirmed the high tolerability profile of RYR. Furthermore, increasing daily doses of monacolin K were negatively associated with increasing risk of Non-MuD (slope: −0.10; 95% CI: −0.17, −0.03; two-tailed p<0.01). Forest plot on RYR link with MuD risk. Conclusions Based on our data, RYR use as lipid-lowering dietary supplement seems to be overall tolerable and safe in a large population of moderately hypercholesterolaemic subjects. Acknowledgement/Funding None
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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 | 0.020 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".