ArticleBMJ open2024
Predictive value of anthropometric and biochemical indices in non-alcoholic fatty pancreas disease: a cross-sectional study.
Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Prevalence of fatty pancreas and its associations with pancreatic disease and metabolic disorders: a systematic review and meta-analysis of 124 studies.Frontiers in nutrition · 2026Pooled it
- Pancreatic Steatosis in Patients with Pheochromocytoma and Paraganglioma: A Retrospective Single-Center Study.Journal of clinical medicine · 2026Article
- Development and validation of a clinical prediction model for fatty pancreas disease: from CT-based indicators to an easy-to-use prediction application.Nutrition journal · 2026Article
- High serum uric acid as a marker for fatty pancreas disease in Chinese women with overweight/obesity.BMC endocrine disorders · 2025Article
- Serum uric acid to high‑density lipoprotein cholesterol ratio as a novel predictor of diabetic nephropathy: a cross‑sectional analysis of NHANES 2011-2018.Clinical and experimental medicine · 2025Article
- Relationship of intra-pancreatic fat deposition with low-density lipoprotein subfractions and hepatic lipase.Diabetes, obesity & metabolism · 2025Article
- Retrospective study: analysis of risk factors and construction of prediction model for pancreatic steatosis.BMC gastroenterology · 2025Article
- Triglyceride-glucose index is independently associated with fatty pancreas disease in Chinese elderly.BMC endocrine disorders · 2025Article
- Effect of Freeze Drying and Hot Air Drying on the Composition and Bioactivities of Lipids from Razor ClamFoods (Basel, Switzerland) · 2025Article
- Association between intra-pancreatic fat deposition and diseases of the exocrine pancreas: A narrative review.World journal of gastroenterology · 2025Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTriglyceride (TG), triglyceride-glucose index (TyG), body mass index (BMI), TyG-BMI and triglyceride to high-density lipoprotein ratio (TG/HDL) have been reported to be reliable predictors of non-alcoholic fatty liver disease. However, there are few studies on potential predictors of non-alcoholic fatty pancreas disease (NAFPD). Our aim was to evaluate these and other parameters for predicting NAFPD.
designCross-sectional study design.
settingPhysical examination centre of a tertiary hospital in China.
participantsThis study involved 1774 subjects who underwent physical examinations from January 2016 to September 2016. PRIMARY AND SECONDARY OUTCOME MEASURES: From each subject, data were collected for 13 basic physical examination and blood biochemical parameters: age, weight, height, BMI, TyG, TyG-BMI, high-density lipoprotein (HDL), low-density lipoprotein, total cholesterol, TG, fasting plasma glucose, TG/HDL and uric acid. NAFPD was diagnosed by abdominal ultrasonography. A logistic regression model with a restricted cubic spline was used to evaluate the relationship between each parameter and NAFPD. The receiver operating characteristic (ROC) curve was used to calculate the area under the curve for each parameter.
resultsHDL was negatively correlated with NAFPD, height was almost uncorrelated with NAFPD and the remaining 11 parameters were positively correlated with NAFPD. ROC curve showed that weight-related parameters (weight, BMI and TyG-BMI) and TG-related parameters (TyG, TG and TG/HDL) had high predictive values for the identification of NAFPD. The combinations of multiple parameters had a better prediction effect than a single parameter. All the predictive effects did not differ by sex.
conclusionsWeight-related and TG-related parameters are good predictors of NAFPD in all populations. BMI showed the greatest predictive potential. Multiparameter combinations appear to be a good way to predict NAFPD.
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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 Socratic graph.