ArticleFrontiers in endocrinology2022
Clinical spectrum transition and prediction model of nonalcoholic fatty liver disease in children with obesity.
Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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12 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Global and regional prevalence, burden, and risk factors for MASLD in children and adolescents aged 5 to 24 years: a systematic review, meta-analysis, and modeling study.BMC medicine · 2026Pooled it
- Adipose-inflammatory factor profiles in children with metabolically healthy obesity and their correlation with NAFLD severity.Frontiers in pediatrics · 2026Article
- A nomogram for predicting metabolic-associated fatty liver disease in non-obese newly diagnosed type 2 diabetes patients.Frontiers in endocrinology · 2025Article
- Efficacy of Ultrasound for the Detection of Possible Fatty Liver Disease in Children.Diagnostics (Basel, Switzerland) · 2024Article
- A Gender-, Age-, and Weight Status-Specific Analysis of the High Prevalence of Hyperuricemia Among Chinese Children and Adolescents with Obesity.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Development and validation of machine learning models for MASLD: based on multiple potential screening indicators.Frontiers in endocrinology · 2024Article
- Association between serum uric acid-to-high-density lipoprotein cholesterol ratio and metabolic dysfunction-associated steatotic liver disease among Chinese children with obesity.Frontiers in endocrinology · 2024Article
- Stochastic modeling of obesity status in United States adults using Markov Chains: A nationally representative analysis of population health data from 2017-2020.Obesity science & practice · 2023Article
- Covariate dependent Markov chains constructed with gradient boost modeling can effectively generate long-term predictions of obesity trends.BMC research notes · 2023Article
- Predicting the 5-Year Risk of Nonalcoholic Fatty Liver Disease Using Machine Learning Models: Prospective Cohort Study.Journal of medical Internet research · 2023Article
- Non-Traditional Blood Lipid Indices for Metabolism Dysfunction-Associated Fatty Liver Disease Prediction in Non-Obese Type 2 Diabetes Mellitus.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023Article
- Analysis of risk factors for non-alcoholic fatty liver disease in hospitalized children with obesity before the late puberty stage.Frontiers in endocrinology · 2023Article
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13 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aims to outline the clinical characteristics of pediatric NAFLD, as well as establish and validate a prediction model for the disease. Materials and methods: The retrospective study enrolled 3216 children with obesity from January 2003 to May 2021. They were divided into obese without NAFLD, nonalcoholic fatty liver (NAFL), and nonalcoholic steatohepatitis (NASH) groups. Clinical data were retrieved, and gender and chronologic characteristics were compared between groups. Data from the training set (3036) were assessed using univariate analyses and stepwise multivariate logistic regression, by which a nomogram was developed to estimate the probability of NAFLD. Another 180 cases received additional liver hydrogen proton magnetic resonance spectroscopy (1H-MRS) as a validation set. Results: The prevalence of NAFLD was higher in males than in females and has increased over the last 19 years. In total, 1915 cases were NAFLD, and the peak onset age was 10-12 years old. Hyperuricemia ranked first in childhood NAFLD comorbidities, followed by dyslipidemia, hypertension, metabolic syndrome (MetS), and dysglycemia. The AUROC of the eight-parameter nomogram, including waist-to-height ratio (WHtR), hip circumference (HC), triglyceride glucose-waist circumference (TyG-WC), alanine aminotransferase (ALT), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1(ApoA1), insulin sensitivity index [ISI (composite)], and gender, for predicting NAFLD was 0.913 (sensitivity 80.70%, specificity 90.10%). Calibration curves demonstrated a great calibration ability of the model. Conclusion and relevance: NAFLD is the most common complication in children with obesity. The nomogram based on anthropometric and laboratory indicators performed well in predicting NAFLD. This can be used as a quick screening tool to assess pediatric NAFLD in children with obesity.
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