Risk of cardiovascular events in patients with non-alcoholic fatty liver disease: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent disease and has been repeatedly associated with an increased risk of cardiovascular disease. However, the extent of such association is unclear. We conducted a systematic review and meta-analysis of the literature to evaluate the risk of myocardial infarction (MI), ischaemic stroke (IS), atrial fibrillation (AF), and heart failure (HF) in NAFLD patients. METHODS AND RESULTS: According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched PubMed and EMBASE, from inception to 6 March 2021, and included all studies reporting the incidence of MI, IS, AF, and HF in patients with and without NAFLD. Random-effect fmodels were used to estimate pooled odds ratio (OR), 95% confidence intervals (CI), and 95% prediction intervals (PI); subgroup analyses, meta-regressions, and sensitivity analyses were additionally performed. Among 3254 records retrieved from literature, 20 studies were included. Non-alcoholic fatty liver disease was associated with an increased risk of MI (OR: 1.66, 95% CI: 1.39-1.99, 95% PI: 0.84-3.30), IS (OR: 1.41, 95% CI: 1.29-1.55, 95% PI 1.03-1.93), AF (OR: 1.27, 95% CI: 1.18-1.37, 95% PI: 1.07-1.52), and HF (OR: 1.62, 95% CI: 1.43-1.84, 95% CI: 1.04-2.51). We identified significant subgroup differences according to geographical location, study design, NAFLD definition, and risk of bias; meta-regressions identified mean age, male sex, and study-level characteristics as potential moderators of the risk of MI and IS. CONCLUSIONS: Non-alcoholic fatty liver disease was associated with increased risk of MI, IS, AF, and HF. Age, sex, and study characteristics may moderate the strength of this association. Further studies are required to evaluate specific cardiovascular prevention strategies in patients with NAFLD.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.006 | 0.007 |
| 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) | 0.003 | 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".