1472-P: Clinical Profile of Nonalcoholic Fatty Liver Disease in Adults with Type 2 Diabetes Mellitus
Notice bibliographique
Résumé
Nonalcoholic fatty liver disease (NAFLD), including its severe form known as steatohepatitis or NASH, are increasingly common in patients with type 2 diabetes mellitus (T2DM) and can progress to cirrhosis. However, there is limited information on their comorbid medical conditions in “real world” practice. Thus, the disease characteristics of patients with NASH or NASH-cirrhosis (cirrhosis), with or without T2DM, was evaluated in TARGET-NASH, an ongoing longitudinal observational study of patients with NAFLD, who are managed according to local standards at 60 community and academic hepatology and endocrinology practices in the United States. Among 3085 patients enrolled with NASH or cirrhosis, 1645 had NASH (47% T2DM) and 1440 had cirrhosis (72% T2DM). Patients with T2DM were older (median 61 vs. 56 years) and had a higher median BMI (34.0 vs. 32.0 kg/m2, p<0.001) than participants without T2DM. The prevalence of hypertension (88 vs. 62%), dyslipidemia (78 vs. 56%), cardiovascular diseases (CVD) or event (27 vs. 15%) and any cancer (21 vs. 16%) was higher in patients with vs. without T2DM (all p<0.001). Median alanine aminotransferase in patients with T2DM was lower than in those without diabetes (35 vs. 39 IU/L, p<0.001). Among those with a liver biopsy, having T2DM was associated with a higher prevalence of advanced fibrosis (57% vs. 34%), including cirrhosis (36% vs. 19% in NonT2DM; all p<0.001). Using a logistic regression model, presence of T2DM, hypertension, age, sex, cancer, CVD or event, hyperlipidemia and race were all predictors of developing cirrhosis (all p<0.05). In conclusion, patients with type 2 diabetes and NASH or cirrhosis had more advanced liver disease compared to those without type 2 diabetes. Patients with type 2 diabetes had more than twice the risk of cirrhosis compared to those without type 2 diabetes. These results support a strong link of type 2 diabetes and metabolic risk factors with advanced NASH. Disclosure K. Cusi: Consultant; Self; Allergan plc., AstraZeneca, Bristol-Myers Squibb, Genentech, Inc., Gilead Sciences, Inc., Merck & Co., Inc. Research Support; Self; Cirius Therapeutics, Echosens, Eli Lilly and Company, Inventiva Pharma, Janssen Pharmaceuticals, Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Poxel SA, Zydus Pharmaceuticals, Inc. M. Roden: Advisory Panel; Self; Servier. Board Member; Self; Poxel SA. Consultant; Self; Eli Lilly and Company, Gilead Sciences, Inc., ProSciento, TARGET PharmaSolutions. Research Support; Self; Boehringer Ingelheim International GmbH, Novartis Pharma K.K., Sanofi US. Speaker’s Bureau; Self; Novo Nordisk A/S. A.S. Barritt: Consultant; Self; GENFIT, Intercept Pharmaceuticals, Inc., TARGET PharmaSolutions. R.J. Firpi: None. V. Clark: Research Support; Self; GENFIT, Intercept Pharmaceuticals, Inc., Novo Nordisk Inc. S. Klein: Advisory Panel; Self; Danone Nutricia, Merck & Co., Inc. Research Support; Self; Johnson & Johnson, Pfizer Inc. Stock/Shareholder; Self; Aspire Bariatrics. A. Lok: None. P. Newsome: Research Support; Self; Novo Nordisk A/S. K. Corbin: None. M.B. Vos: Advisory Panel; Self; TARGET PharmaSolutions. Consultant; Self; Boehringer Ingelheim (Canada) Ltd., Immuron, Intercept Pharmaceuticals, Inc., Mallinckrodt Pharmaceuticals, Novo Nordisk A/S. Research Support; Self; Bristol Myers Squibb. R. Reddy: Advisory Panel; Self; Ambys, Epigenomics AG, Mallinckrodt Pharmaceuticals, Merck & Co., Inc. Research Support; Self; Conatus Pharmaceuticals, Exact Sciences, Gilead Sciences, Inc., Intercept Pharmaceuticals, Inc., Mallinckrodt Pharmaceuticals, Merck & Co., Inc. C. Schoen: None. A.R. Mospan: Employee; Self; TARGET PharmaSolutions. J.L. Taunk: None. K. Wyne: Advisory Panel; Self; Novo Nordisk Inc. Research Support; Self; Sanofi. B. Neuschwander-Tetri: Advisory Panel; Self; 89Bio, Allysta, ARTham, Blade, Bristol-Myers Squibb, Gelesis, GENFIT, Histoindex, Madrigal Pharmaceuticals, Inc., Medpace, Merck & Co., Inc., Sagimet, Siemens Corporation. Consultant; Self; Arrowhead Pharmaceuticals, Inc., Axcella, DURECT Corporation, Enanta Pharmaceuticals, Inc., Fortress, Indalo, Innovo, Lipocine, Mundipharma International, pH-Pharma, TARGET PharmaSolutions. A. Sanyal: Consultant; Self; Intercept Pharmaceuticals, Inc., Lilly Diabetes, Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk A/S, Pfizer Inc. Stock/Shareholder; Self; DURECT Corporation, GENFIT, HemoShear, Sanyal Bio, Tiziana Life Sciences plc. Funding TARGET-NASH
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».