ArticleItalian journal of pediatrics2025
Development and validation of an online nomogram for screening metabolic-associated fatty liver disease in obese children.
Article in Italian journal of pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMetabolic-associated fatty liver disease (MAFLD) has emerged as a critical pediatric health concern, particularly among children with obesity. However, its diagnosis poses substantial challenges, especially in the use of non-invasive methods. Our goal was to construct an online nomogram for screening MAFLD in obese children.
methodsWe designed a retrospective cross-sectional study involving 2,512 obese children. Detailed anthropometric data and laboratory parameters were collected. The study dataset was randomly allocated into training (n = 1758) and validation (n = 754) sets at a 7:3 ratio. To identify MAFLD risk factors, we conducted logistic regression analyses, from which a web-based predictive nomogram was constructed. Using receiver operating characteristic (ROC) curves and area under the curve (AUC), the nomogram's performance was assessed and contrasted with the triglyceride glucose (TyG) index, Zhejiang University (ZJU) index, and Korean NAFLD (K-NAFLD) score. The goodness-of-fit of the nomogram was evaluated using calibration plots, and the nomogram's clinical value was assessed using decision curve analysis (DCA).
resultsA total of 1,344 participants (53.50%) were diagnosed with MAFLD by ultrasound. Age, gender, BMI Z-score, waist circumference (WC), homeostatic model assessment of insulin resistance (HOMA-IR), and alanine aminotransferase (ALT) were identified as independent factors influencing MAFLD in obese children. These six variables were selected for the construction of the nomogram. ROC analysis revealed that the nomogram had superior diagnostic performance for MAFLD detection compared to the other three models, with AUC values of 0.874 (95% confidence interval [CI]: 0.858-0.890) in the training set and 0.870 (95% CI: 0.845-0.895) in the validation set. Calibration plots indicated a good fit of the nomogram in both datasets. Furthermore, DCA demonstrated its strong clinical applicability.
conclusionsThis study developed an online nomogram that demonstrates robust diagnostic accuracy and clinical utility for assessing obese children's MAFLD risk.
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.