Evidence map›Paper›PMID 39101191›Full record

ArticleDiabetology international2024

Uric acid is associated with type 2 diabetes: data mining approaches.

Amin Mansoori, Davoud Tanbakuchi, Zahra Fallahi, Fatemeh Asgharian Rezae, Reihaneh Vahabzadeh, Sara Saffar Soflaei, Reza Sahebi, Fatemeh Hashemzadeh, Susan Nikravesh, Fatemeh Rajabalizadeh and 3 more

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Article in Diabetology international, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Amin Mansoori *Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
Davoud Tanbakuchi *Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
Zahra FallahiSchool of Nursing and Midwifery, Mashhad University of Medical Sciences, Mashhad, Iran.
Fatemeh Asgharian RezaeStudent Research Committee, Faculty of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran.
Reihaneh VahabzadehStudent Research Committee, Paramedicine Faculty, Mashhad University of Medical Sciences, Mashhad, Iran.
Sara Saffar SoflaeiInternational UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766 Iran.
Reza SahebiInternational UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766 Iran.
Fatemeh HashemzadehDepartment of Biology, Faculty of Sciences, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
Susan NikraveshDepartment of Nutrition Sciences, Varastegan Institute for Medical Sciences, Mashhad, Iran.
Fatemeh RajabalizadehDepartment of Nutrition Sciences, Varastegan Institute for Medical Sciences, Mashhad, Iran.
Gordon FernsDivision of Medical Education, Brighton and Sussex Medical School, Brighton, UK.
Habibollah EsmailyDepartment of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
Majid Ghayour-MobarhanInternational UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766 Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Several blood biomarkers have been related to the risk of type 2 diabetes mellitus (T2D); however, their predictive value has seldom been assessed using data mining algorithms. Methods: This cohort study was conducted on 9704 participants recruited from the Mashhad Stroke and Heart Atherosclerotic disorders (MASHAD) study from 2010 to 2020. Individuals who were not between the ages of 35 and 65 were excluded. Serum levels of biochemical factors such as creatinine (Cr), high-sensitivity C reactive protein (hs-CRP), Uric acid, alanine aminotransferase (ALT), aspartate aminotransferase (AST), direct and total bilirubin (BIL.D, BIL.T), lipid profile, besides body mass index (BMI), waist circumference (WC), blood pressure, and age were evaluated through Logistic Regression (LR) and Decision Tree (DT) methods to develop a predicting model for T2D. Results: The comparison between diabetic and non-diabetic participants represented higher levels of triglyceride (TG), LDL, cholesterol, ALT, BIL.D, and Uric acid in diabetic cases ( Conclusion: There was a significant association between hypertension and dyslipidemia history, TG, Uric acid, and hs-CRP with T2D development, along with age, WC, and blood pressure through the LR and DT methods. Graphical abstract:

Indexed as

Biochemical factorsData miningDecision treeTyG indexType 2 diabetesUric acid

Identifiers

PMID39101191
PMCPMC11291799

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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 OpenQuestion graph.