Metabolic associated fatty liver disease and adverse maternal and fetal outcomes: a systematic review and meta-analysis
Bibliographic record
Abstract
Aim of the study: Metabolic-associated fatty liver disease (MAFLD) is now the most prevalent chronic liver disease in the world.Its prevalence in women of reproductive age is approximately 10%.Due to its high prevalence in this specific population, it is important to investigate adverse maternal and fetal outcomes caused by MAFLD during pregnancy.We aimed to summarize the association between MAFLD and adverse maternal and fetal outcomes. Material and methods:A search was conducted on PubMed and ProQuest from inception to April 1, 2021, for studies assessing the association between MAFLD and adverse maternal and fetal outcomes.The quality of included studies was assessed using the Newcastle-Ottawa scale (NOS).We analyzed the pooled odds ratios (ORs) with 95% confidence intervals (CIs) using a fixed and random-effects model.Heterogeneity was assessed using I 2 .Results: Six studies comprising 20,535,994 (5,964 MAFLD) pregnant women were included.The quality of studies ranged from 6 to 8 stars.MAFLD was significantly associated with increased risk of dysglycemia (OR = 3.65, 95% CI = 2.47-5.39),pregnancy-associated hypertension (OR = 3.27, 95% CI = 2.75-3.88),cesarean section (OR = 2.78, 95% CI = 1.60-4.83),and preterm birth (OR = 1.70, 95% CI = 1.37-2.10)but not large for gestational age (OR = 1.69, 95% CI = 0.64-4.45). Conclusions:The presence of MAFLD is associated with adverse maternal and fetal outcomes.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 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 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".