S2820 Comprehensive Evaluation of Effect of Statins on Hepatic Decompensation in the Settings of Liver Cirrhosis—Meta-Analysis
Bibliographic record
Abstract
Introduction: Decompensated cirrhosis is defined as an acute deterioration in liver function in a patient with cirrhosis and is characterized by jaundice, ascites, hepatic encephalopathy, hepatorenal syndrome or variceal hemorrhage. The aim of this study was to perform a meta-analysis in order to evaluate the effect of statins on hepatic decompensation in the settings of liver cirrhosis. Methods: Seven databases were searched to find relevant papers. The quality assessment of observational studies was assessed using the Newcastle–Ottawa scale (NOS) tool. The Comprehensive Meta-Analysis version 3 (Biostat Inc., USA) software was used to conduct the statistical analysis. Pooled hazard ratio (HR) with 95% confidence intervals (CIs) was calculated for hepatic decompensation using random effects. Results: This meta-analysis included 7 studies. Overall, the scores of included studies ranged from 5 to 7 stars. Indeed, 5 were assessed to be of good quality, while 2 articles were of fair quality. The forest plot revealed that statin treatment was associated with a significant reduction in hepatic decompensation (HR: 0,536; 95% CI: 0,365 to 0,785; P = 0,001). Interestingly, a high heterogeneity was detected across studies: Chi2 = 119,08, P = 0,000, I2 = 94%. Conclusion: Our results confirm the beneficial effect of statins in reducing the risk of hepatic decompensation. This result requires validation by conducting further studies with a larger sample size.
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 | 0.022 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.065 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".