Weight Change is Associated With Metabolic Liver Health in a General Population Extending Beyond Weight Loss Targets of International Guidelines
Bibliographic record
Abstract
Background and aims: Weight loss of ≥3%-10% is recommended in metabolic dysfunction-associated steatotic liver disease (MASLD) management, according to current guidelines. We investigated the associations between weight change and impaired metabolic liver health and focused on associations beyond these recommendations. Methods: , excessive alcohol and viral hepatitis. Impaired metabolic liver health included MASLD (controlled attenuation parameter ≥275 dB/m with ≥1 cardiometabolic riskfactor), at-risk metabolic dysfunction-associated steatohepatitis (MASH) (FibroScan aspartate aminotransferase score ≥0.35) and LSM ≥8 kPa. Multivariate logistic regression models were adjusted for demographics and prior weight. Results: We included 6802 individuals (aged 48 years [33-62], 48.9% male). MASLD was present in 42.2%, at-risk MASH in 6.5% and LSM ≥8 kPa in 9.1%. Over 1 year, 29% gained and 28% lost ≥3% weight. Compared to stable weight, weight gain ≥3% was associated with increased MASLD prevalence (adjusted odds ratio (aOR):1.78; 95% confidence interval (CI): 1.48-1.95), at-risk MASH (aOR: 1.78; 95% CI: 1.39-2.29) and LSM ≥8 kPa (aOR:1.48; 95%CI:1.19-1.84); whilst weight loss ≥ 3% was associated with reduced MASLD prevalence (aOR: 0.54; 95% CI: 0.47-0.62), at-risk MASH (aOR: 0.72; 95% CI: 0.55-0.94) and LSM ≥8 kPa (aOR: 0.62; 95% CI: 0.49-0.78). Results were consistent when weight loss was further categorized or when assessed as continuous variable without evidence for nonlinearity. Conclusion: The prevalence of impaired metabolic liver health decreased with weight loss. Greater reported weight loss was associated with lower observed risks. Hence, we should recommend losing weight beyond the currently recommended targets to further reduce the risk of advanced liver disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".