Anthropometric Indices and Metabolic Dysfunction–Associated Fatty Liver Disease in Males and Females Living With Severe Obesity
Bibliographic record
Abstract
Introduction: Metabolic dysfunction–associated fatty liver disease (MAFLD) is highly prevalent among people living with severe obesity (body mass index [BMI] ≥ 35 kg/m 2 ). However, it remains unknown how sex and adipose tissue distribution are related to MAFLD onset and progression into metabolic dysfunction–associated steatohepatitis (MASH) or advanced stages of fibrosis. Methodology: We retrospectively studied patients with severe obesity who were eligible for bariatric surgery. Demographic characteristics, biomarkers, and cardiometabolic comorbidities were reported. Anthropometric indices such as BMI, waist circumference (WC), waist‐to‐hip ratio (WHR), waist‐to‐height ratio (WHtR), neck circumference (NC), lipid accumulation product (LAP), visceral adiposity index (VAI), body adiposity index (BAI), abdominal volume index (AVI), and body roundness index (BRI) were measured or calculated. MAFLD, MASH, and stages of fibrosis (F1‐F4) were established from perioperative liver biopsies. Standardized univariate and multivariate logistic regression analyses were used to examine the association between demographic variables, anthropometric indices, cardiometabolic conditions, and the risk of MASH or severe fibrosis (F2‐F4). Results: A total of 2091 participants with severe obesity were included in the analyses; BMI 47.9 ± 7.3 kg/m 2 , age 46.2 ± 11.2 years, and 68.4% females. Overall, MAFLD prevalence was 79.5%, with 44.5% having MASH and 24.4% having severe fibrosis (Stage 2 or higher). No anthropometric indices of adiposity were associated with MASH or fibrosis severity. In this population, female sex was a risk factor for severe fibrosis (OR: 1.27, 95% CI 1.01–1.59, p < 0.05). Conclusions: MAFLD and MASH are highly prevalent in individuals living with severe obesity, but no anthropometric indices or laboratory tests are good predictors of MAFLD or MASH in this population. When MAFLD is diagnosed, our results suggest that females with severe obesity might be at higher risk of advanced stages of fibrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".