ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2025
Predictive Value of the Triglyceride-Glucose Index for Metabolic-Associated Fatty Liver Disease in Individuals with Different Metabolic Obese Phenotypes.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Mechanisms of postpartum metabolic dysfunction-associated steatotic liver disease in women with a history of gestational diabetes mellitus.Endocrine connections · 2026Review
- Ability of triglyceride-glucose indices to predict metabolic dysfunction associated with steatotic liver disease in pediatric obesity.Journal of pediatric gastroenterology and nutrition · 2025Article
- SERUM LncRNA SNHG16: A Biomarker for Diagnosing Childhood Obesity and Predicting Its Progression to Metabolic Syndrome.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To investigate the relationship between triglyceride-glucose (TyG) index and metabolic-associated fatty liver disease (MAFLD), and to evaluate the predictive value of the TyG index for MAFLD in individuals with different metabolic obese phenotypes. The aim is to provide a novel approach for the screening and early diagnosis of MAFLD in the general population. Methods: A total of 2614 subjects were recruited and classified into four categories of metabolic obese phenotypes based on their body mass index (BMI) and metabolic status. Basic data and general blood indices were collected and analyzed. The TyG index was calculated, and an abdominal ultrasound was performed to detect the presence of fatty liver disease. The aforementioned data were then subjected to statistical analysis. Results: The TyG index was significantly higher in the MAFLD group than in the non-MAFLD group (P < 0.001). Furthermore, the TyG index in the metabolically unhealthy and obese (MUO) group and the metabolically unhealthy normal weight (MUNW) group was significantly higher than that in the metabolically healthy and obese (MHO) group and the metabolically healthy normal weight (MHNW) group (P < 0.001). The area under the curve (AUC) of the TyG index for predicting MAFLD in the MHNW, MUNW, MHO, and MUO groups was 0.765, 0.766, 0.659, and 0.650, respectively. The critical values were 8.575, 9.075, 8.795, and 9.165, respectively. Conclusion: The TyG index is a reliable predictor of MAFLD risk, exhibiting a higher predictive ability for the risk of developing MAFLD in individuals with normal BMI compared to those with abnormal BMI. The findings of this study lend support for the use of the TyG index as a screening tool and for guiding subsequent management of patients with MAFLD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.