The global prevalence and impact of steatotic liver disease and viral infections: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Steatotic liver disease (SLD) affects ~30% of adults worldwide. The global population is continuously threatened by epidemic and endemic viral diseases. This study aims to thoroughly examine the interaction between SLD and major viral diseases. METHODS: We systematically searched databases from inception to April 2, 2024, for observational studies recording viral-infected adult patients with eligible data on the presence of hepatic steatosis. RESULTS: Six hundred thirty-six eligible studies were included in the analysis of SLD prevalence. Among patients with monoinfections, the highest SLD prevalence was observed in those infected with HCV at 49% (95% CI: 47%-51%), followed by SARS-CoV-2 (39%, 95% CI [34%-44%]), HIV (39%, 95% CI [33%-44%]), and HBV (36%, 95% CI [32%-40%]). Additionally, co-infections, such as HCV-HIV and HBV-HCV, exhibit even higher SLD prevalence. The prevalence of steatohepatitis is particularly high in HIV-infected (24%, 95% CI: 17%-30%) and HCV-infected (18%, 95% CI: 13%-24%) populations. The co-existence of SLD with viral infections was associated not only with the progression of liver disease but also with more severe outcomes of the infections and poorer responses to antiviral treatment. The combination of cardiometabolic risk factors and viral-associated and host factors contributes to the higher risk of SLD in viral-infected populations. CONCLUSIONS: SLD is highly prevalent in viral-infected populations, and the reciprocal interactions between SLD and viral diseases exacerbate both conditions, leading to poorer patient outcomes in general.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".