Risk of cardiovascular outcomes with bempedoic acid in high-risk statin intolerant patients: a systematic review and meta analysis
Bibliographic record
Abstract
Aim: Statin intolerance and myopathy is a major issue with prolonged use of statins myopathy. Bempedoic acid can be a good alternative for those intolerant to statins. This systematic review aims to observe incidence of major adverse cardiovascular events (MACE) and other adverse events, in high-risk statin intolerant patients receiving bempedoic acid.Methods: Literature search was conducted via Google Scholar, Science Direct and PubMed, after which screening, selection and data extraction of articles was done. Meta-analysis was performed on RevMan 5.4. Subgroup analysis was also conducted and heterogeneity was evaluated. Risk of bias was performed using ROB2 assessment scale. (CRD42024536827).Results: Only six randomized controlled trials were used in final analysis consisting of 17,844 patients. Treatment with bempedoic acid was associated with a reduced risk of MACE compared with placebo (RR 0.86; 95% CI [0.79, 0.94] p = 0.0005), with myocardial infarction significantly reduced. Incidence of adverse effects was increased with bempedoic acid (RR: 1.02; 95% [1.00, 1.03] p = 0.01) but no significant difference was observed. Incidence of myalgia was reduced in bempedoic group as well.Conclusion: Bempedoic acid is a safe and effective alternative to statins in high-risk patients intolerant to statins, decreasing the risk of MACE.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".