Circulating irisin levels in patients with MAFLD: an updated systematic review and meta-analysis
Bibliographic record
Abstract
Objective: Current research suggests that irisin is closely linked to the pathogenesis and progression of metabolic dysfunction-associated fatty liver disease (MAFLD). This systematic review and meta-analysis updates our previous meta-analysis and further explores the relevance between circulating irisin levels and MAFLD. Methods: August, 2024. The standardized mean difference (SMD) and 95% confidence interval (CI) represent pooled effect size. We used the Newcastle-Ottawa Scale to evaluate the quality of articles and the certainty of evidence assessed by GRADE system. All statistical analyses were performed using RevMan 5.3 and Stata 12(Stata Corporation, yi TX). Results: Fifteen case-control studies were included. Circulating irisin levels in the MAFLD group were markedly lower than those in the healthy group (SMD=-1.04 [-1.93, -0.14]). Subgroup analyses by race, age, severity and T2DM revealed that circulating irisin levels were lower in the MAFLD group compared to those in the healthy controls in the Asian population (SMD=-1.38 [-2.44, -0.31], P<0.05) and in those above 50 years old (SMD=-2.23 [-3.64, -0.81], P<0.05) and higher in the mild MAFLD groups than those in moderate to severe MAFLD groups (SMD = 11.68 [9.05, 14.31], P<0.05). And the circulating irisin levels in MAFLD patients with T2DM were significantly lower than those in healthy group (SMD = -2.90 [-4.49, -1.30]). ELISA kits from different companies also presented different relationships. Conclusions: There were significantly lower circulating irisin levels in the MAFLD group than in the healthy control group. Although these results differed from our previous results, there is no denying that circulating irisin levels are closely associated with the advancement of MAFLD.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.007 | 0.008 |
| 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".