Apolipoproteins Levels in Fatty Liver Disease: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Fatty liver disease (FLD) is a prevalent condition linked to metabolic disorders and can progress to severe liver diseases. Alterations in apolipoprotein (Apo) levels may provide valuable insights for diagnosing and managing FLD. This systematic review and meta-analysis evaluates these changes across different FLD phenotypes to evaluate their potential as diagnostic biomarkers. METHODS: We evaluated studies from PubMed, EMBASE, and Scopus using a predefined search string. Predefined inclusion and exclusion criteria were applied, and the risk of bias was assessed using the Newcastle-Ottawa Scale (NOS). The main summary outcome was the mean difference (MD) in Apo levels. RESULTS: Out of 773 initial articles, 55 studies involving 432,328 individuals were included. In NAFLD patients vs. controls, ApoA levels showed a MD of -0.029 (95% CI: -0.133, 0.075), ApoA-I had a MD of -0.064 (95%CI: -0.107, -0.021), and ApoB levels had a MD of 0.098 (95%CI: 0.076, 0.120), while ApoB100 had an MD of 0.042 (95% CI: 0.008, 0.076). For NASH vs. controls, ApoA-I levels had a MD of -0.108 (95% CI: -0.125, -0.091) and ApoB levels had a MD of 0.123 (95% CI: 0.054, 0.193), while ApoB100 had a MD of 0.042 (95% CI: -0.051,0.136). In MAFLD vs. controls, ApoA-I levels had a MD of -0.068 (95% CI: -0.124, -0.012) and ApoB a MD of 0.099 (95% CI: 0.091, 0.107). For diabetic NAFLD vs. T2DM (type 2 diabetes mellitus) without NAFLD, ApoA levels had an MD of 0.028 (95% CI: -0.147, 0.204) and ApoB levels an MD of 0.081 (95% CI: 0.040, 0.122). CONCLUSIONS: In NAFLD patients, ApoA-I levels were lower and ApoB and ApoB100 levels were higher compared to controls, with similar patterns seen in NASH patients, who also had higher ApoB levels than those with simple steatosis. MAFLD patients had elevated ApoB and ApoE levels, while overweight/obese NAFLD patients had higher ApoB levels than controls.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".