ArticleLipids in health and disease2022
Development and application of a novel model to predict the risk of non-alcoholic fatty liver disease among lean pre-diabetics with normal blood lipid levels.
Article in Lipids in health and disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 11 citations in OpenAlex.
- The effect of hepatic steatosis index on prediabetes: A large-scale retrospective cohort study.Scientific reports · 2025Article
- The association of serum phospholipids levels with chronic liver diseases: A systematic review of observational studies.Health promotion perspectives · 2025Review
- Photoreceptor metabolic window unveils eye-body interactions.Nature communications · 2025Article
- Threshold effect and age interaction of TyG index on diabetes incidence in normolipidemic population: a multicenter cohort study.Frontiers in endocrinology · 2025Article
- Nomogram for predicting 5-year metabolic dysfunction-associated steatotic liver disease risk: retrospective cohort study.Endocrine connections · 2024Article
- Deep learning imaging phenotype can classify metabolic syndrome and is predictive of cardiometabolic disorders.Journal of translational medicine · 2024Article
- Nomogram for predicting the risk of nonalcoholic fatty liver disease in older adults in Qingdao, China: A cross-sectional study.Asia Pacific journal of clinical nutrition · 2024Article
- A dynamic machine learning model for prediction of NAFLD in a health checkup population: A longitudinal study.Heliyon · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-alcoholic fatty liver disease (NAFLD) has been associated with type 2 diabetes, but its relationship with pre-diabetes is still unknown. This study aims to determine whether pre-diabetes is associated with NAFLD, followed by establishing a NAFLD predictive nomogram for lean Chinese pre-diabetics with normal blood lipids.
methodsDatasets from 3 previous studies, 1 (2774 pre-diabetics with normal blood lipids for training, 925 for validation), 2 (546 for longitudinal internal validation, post-5-year follow-up), and 3 (501 from another institution for external validation), were used. Kaplan-Meier determined cumulative NAFLD hazard, and least absolute shrinkage and selection operator regression analysis uncovered its risk factors. Multivariate logistic regression analysis constructed the nomogram, followed by validation with receiver operating characteristic curve, calibration plot, and decision curve analyses.
resultsNAFLD incidence increased with diabetes progression, and pre-diabetics had higher cumulative risk versus non-diabetics, even for lean individuals with normal blood lipids. Six risk factors were identified: body mass index, total cholesterol, alanine aminotransferase:aspartate aminotransferase, triglyceride:high density lipoprotein cholesterol, fasting blood glucose and γ-glutamyl-transferase. The nomogram yielded areas under the curve of 0.808, 0.785, 0.796 and 0.832, for respectively, training, validation, longitudinal internal validation, and external validation, which, along with calibration curve values of p = 0.794, 0.875, 0.854 and 0.810 for those 4 datasets and decision curve analyses, validated its clinical utility.
conclusionsLean pre-diabetic Chinese with normal blood lipids have higher NAFLD risk versus non-diabetics. The nomogram is able to predict NAFLD among such individuals, with high discrimination, enabling its use for early detection and intervention.
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.