A systematic review on pharmacokinetics, cardiovascular outcomes and safety profiles of statins in cirrhosis
Bibliographic record
Abstract
BACKGROUND/AIMS: There is increased interest in the therapeutic use of statins in cirrhosis, but preferred statin and safety outcomes are still not well known. In this systematic review we aimed to address pharmacokinetics (PK), safety, and effects on cardiovascular (CV) outcomes of statins in cirrhosis. METHODS: Our systematic search in several electronic databases and repositories of two regulatory bodies up to 2020-06-11 yielded 22 articles and 2 drug monographs with relevant data. RESULTS: Rosuvastatin and pitavastatin showed minimal PK changes in Child-Pugh A cirrhosis. Only rosuvastatin was assessed in a repeated dosing PK study. Atorvastatin showed pronounced PK changes in cirrhosis. No PK data was found for simvastatin, the most commonly used statin in cirrhosis trials. There was insufficient data to assess CV effects of statins in cirrhosis. Clinical trials in cirrhosis were limited to simvastatin, atorvastatin, and pravastatin. In patients taking simvastatin 40 mg, pooled frequency of rhabdomyolysis was 2%, an incidence 40-fold higher than that reported in non-cirrhosis patients, while this was no rhabdomyolysis observed in patients on simvastatin 20 mg, atorvastatin 20 mg, or pravastatin 40 mg. Drug-induced liver injury was of difficult interpretation due to co-existence of muscle damage. No overt liver failure was reported. CONCLUSIONS: Simvastatin 40 mg should be avoided in decompensated cirrhosis. Safety data on simvastatin 20 mg or other statins are based on small study sample size. This rarity of evidence combined with lack of data in dose adjustment methods in cirrhosis is a barrier for using statins for CV indications or for investigational use for liver indications.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".