1582-P: Fasting Insulin as an Independent Predictor of Metabolic Dysfunction–Associated Steatohepatitis (MASH) Severity
Bibliographic record
Abstract
Introduction & Objective: MASH is associated with metabolic syndrome; insulin resistance is a key driver of the disease. Advanced fibrosis (F3/F4) is the strongest predictor of major liver-related outcomes. We aimed to evaluate whether the level of fasting insulin (FI) predicts the histological severity of MASH. Methods: Using the EMMINENCE trial (NCT02784444), we examined patients with liver histology and FI data. 393 patients with available data were divided into 3 groups according to the FI tertiles: lower, ≤ 15.11 mIU/L; middle, 15.16 - 24.23 mIU/L; upper ≥ 24.25 mIU/L. Logistic regressions were performed to predict histological severity. Results: The upper tertile of FI was associated with a higher histological severity (fibrosis and hepatocyte ballooning, table). This was consistent with more severe patient characteristics such as higher liver enzymes, triglycerides, fibrosis biomarkers, HbA1c, and liver stiffness measurement (Table). The upper tertile was predictive of advanced fibrosis and ballooning in univariate analysis (p<0.0001). After adjustment on HbA1c level and diabetes status, the upper tertile remains highly predictive of advanced fibrosis (p=0.001). Conclusions: FI predicts severity of ballooning and fibrosis, independent of HbA1c level and diabetes status. Further research is warranted to assess FI as a noninvasive test to monitor MASH. Disclosure S.A. Harrison: Other Relationship; Akero Therapeutics, Inc. Consultant; 89bio, Inc., Agilos Therapeutics. Other Relationship; Altimmune Inc. Advisory Panel; Arrowhead Pharmaceuticals, Inc. Consultant; Asteroid Therapeutics, Bluejay Therapeutics. Research Support; Bristol-Myers Squibb Company. Consultant; BOEHRINGER INGELHEIM PHARMA, INC, Boxer Capital. Advisory Panel; Chronwell Inc. Consultant; Corcept Therapeutics, ECCOGENE, INC, DEXCOM, INC. Advisory Panel; ECHOSENS NORTH AMERICA, INC. Consultant; Enyo Pharma. Other Relationship; GALECTIN THERAPEUTICS, INC. Consultant; GALECTO, INC, HEPAGENE THERAPEUTICS. Other Relationship; HEPION PHARMACEUTICALS, INC, Gilead Sciences, Inc. Consultant; GlaxoSmithKline plc. Other Relationship; Hepta Bio. Consultant; HISTOINDEX PTE. LTD. Advisory Panel; Humana. Other Relationship; Madrigal Pharmaceuticals, Inc., Intercept Pharmaceuticals, Inc. Advisory Panel; Inventiva Pharma. Other Relationship; Ionis Pharmaceuticals, Medpace. Stock/Shareholder; MGGM THERAPEUTICS LLC. Consultant; NEUROBO PHARMACEUTICALS INC. Other Relationship; NGM BIOPHARMACEUTICALS, INC, NORTHSEA THERAPEUTICS B.V., Novo Nordisk. Research Support; Pfizer Inc. Consultant; PIPER SANDLER & CO. Other Relationship; POXEL. Consultant; Regeneron Pharmaceuticals Inc. Other Relationship; Sagimet Biosciences, Sonic Incytes. Consultant; Takeda Canada. Other Relationship; Terns Pharmaceuticals. Consultant; TRAMONTANE THERAPEUTICS INC (Kriya). Other Relationship; Viking Therapeutics. Consultant; CALIMETRIX, LLC. J. Dubourg: Stock/Shareholder; Poxel SA. S. Jeannin: None. J.R. Colca: Stock/Shareholder; Cirius Therapeutics, Inc. V. Ratziu: None.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".