Risk factors for liver fibrosis progression from early stage to late stage in nonalcoholic fatty liver disease: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: The risk factors of fibrosis progression from an early stage to a late stage in non-alcoholic fatty liver disease were systematically analyzed, providing evidence for clinical workers to identify, intervene and block the progression of liver fibrosis in patients at an early stage.METHODS: The author independently used PubMed for a literature search on November 21, 2022. Two researchers independently screened the literature and cross-checked it. Any disputes were resolved by consulting the third researcher. The quality of the literature was evaluated using the Newcastle Ottawa Sca, and Then perform statistical analysis through Review Manager 5.4.RESULTS: Nine kinds of literature were included in this study. A meta-analysis of 11 factors associated with advanced fibrosis in patients with early-stage of nonalcoholic fatty liver disease showed that 5 factors were statistically significant, namely diabetes mellitus (OR=4.04, 95%CI 1.51-10.82, P=0.006). High body mass index (MD=1.89, 95%CI 0.78-3.00, P=0.0009); Low platelet count (MD=-45.05, 95%CI -66.49-(-23.26), P=0.0001); High levels of aspartate aminotransferase (MD=14.92, 95%CI 8.53-21.31, P=0.00001); Low serum albumin (MD=-0.37, 95%CI-0.62-(-0.12), P=0.004). CONCLUSIONS: This study found that diabetes mellitus, high body mass index, low platelet count, high aspartate aminotransferase levels, and low serum albumin may be major risk factors for early fibrosis progression in 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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.040 |
| 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".