Prediction of type 2 diabetes mellitus using hematological factors based on machine learning approaches: a cohort study analysis.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
12 01 2023
Historique:
received: 18 10 2022
accepted: 30 12 2022
entrez: 12 1 2023
pubmed: 13 1 2023
medline: 17 1 2023
Statut: epublish

Résumé

Type 2 Diabetes Mellitus (T2DM) is a significant public health problem globally. The diagnosis and management of diabetes are critical to reduce the diabetes complications including cardiovascular disease and cancer. This study was designed to assess the potential association between T2DM and routinely measured hematological parameters. This study was a subsample of 9000 adults aged 35-65 years recruited as part of Mashhad stroke and heart atherosclerotic disorder (MASHAD) cohort study. Machine learning techniques including logistic regression (LR), decision tree (DT) and bootstrap forest (BF) algorithms were applied to analyze data. All data analyses were performed using SPSS version 22 and SAS JMP Pro version 13 at a significant level of 0.05. Based on the performance indices, the BF model gave high accuracy, precision, specificity, and AUC. Previous studies suggested the positive relationship of triglyceride-glucose (TyG) index with T2DM, so we considered the association of TyG index with hematological factors. We found this association was aligned with their results regarding T2DM, except MCHC. The most effective factors in the BF model were age and WBC (white blood cell). The BF model represented a better performance to predict T2DM. Our model provides valuable information to predict T2DM like age and WBC.

Identifiants

pubmed: 36635303
doi: 10.1038/s41598-022-27340-2
pii: 10.1038/s41598-022-27340-2
pmc: PMC9837189
doi:

Substances chimiques

Glucose IY9XDZ35W2
Triglycerides 0
Blood Glucose 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

663

Informations de copyright

© 2023. The Author(s).

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Auteurs

Amin Mansoori (A)

International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran.
Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran.
Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.

Toktam Sahranavard (T)

International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran.

Zeinab Sadat Hosseini (ZS)

Faculty of Medicine, Islamic Azad University of Mashhad, Mashhad, Iran.

Sara Saffar Soflaei (SS)

International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran.

Negar Emrani (N)

Student Research Committee, School of Medicine, Mashhad University of Medical Science, Mashhad, Iran.

Eisa Nazar (E)

International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran.
Student Research Committee, Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.

Melika Gharizadeh (M)

Student Research Committee, School of Paramedical Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.

Zahra Khorasanchi (Z)

Student Research Committee, School of Medicine, Mashhad University of Medical Science, Mashhad, Iran.
Department of Nutrition, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.

Sohrab Effati (S)

Department of Applied Mathematics, Ferdowsi University of Mashhad, Mashhad, Iran.

Mark Ghamsary (M)

School of Public Health, Loma Linda University, Loma Linda, CA, USA.

Gordon Ferns (G)

Division of Medical Education, Brighton and Sussex Medical School, Brighton, UK.

Habibollah Esmaily (H)

Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran. esmailyh@mums.ac.ir.
Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran. esmailyh@mums.ac.ir.

Majid Ghayour Mobarhan (MG)

International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences, Mashhad, 99199-91766, Iran. ghayourm@mums.ac.ir.

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Classifications MeSH