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01 April 2020 : Clinical Research  

A Retrospective Population Study to Develop a Predictive Model of Prediabetes and Incident Type 2 Diabetes Mellitus from a Hospital Database in Japan Between 2004 and 2015

Hai Wang1E, Xin Zheng1A, Zheng-Hai Bai1C, Jun-Hua Lv1C, Jiang-Li Sun1C, Yu Shi1E, Hong-Hong Pei1A*

DOI: 10.12659/MSM.920880

Med Sci Monit 2020; 26:e920880

Abstract

BACKGROUND: Type 2 diabetes mellitus is a global public health problem. Prediabetes may be reversed by weight loss, diet, and lifestyle changes. However, without intervention, between 30–50% of individuals with prediabetes develop type 2 diabetes. This retrospective population study was conducted to develop a predictive model of prediabetes and incident type 2 diabetes mellitus using data from 2004 to 2015 from the DRYAD Japanese hospital database.

MATERIAL AND METHODS: A retrospective longitudinal population study was conducted using the DRYAD database from Murakami Memorial Hospital, Gifu, Japan, to construct a predictive model for prediabetes and incident type 2 diabetes mellitus in the population. Univariate analysis and multivariate analysis were performed to identify the variables that were associated with prediabetes. These variables were used to construct (75% samples) and verify (25% samples) the predictive model.

RESULTS: From 2004 to 2015, a total of 11,113 cases were identified. Multivariate logistic regression analysis included the six variables of age, waist circumference, smoking history, the presence of fatty liver, fasting blood glucose (FBG), and glycated hemoglobin (HbA1c) level. Data were used to construct (75% samples) and verify (25% samples) in a predictive model. The area under the receiver operating characteristic (ROC) curve (AUC) of the predictive model was 0.87 (0.85–0.89) in the training cohort and 0.87 (0.86–0.90) in the validation cohort.

CONCLUSIONS: A prognostic model based on six variables was predictive for incident type 2 diabetes mellitus and prediabetes in a healthy population in Japan.

Keywords: Decision Support Techniques, Diabetes Mellitus, Type 2, Healthy People Programs, Age Factors, Blood Glucose, Body Mass Index, Databases, Factual, Glycated Hemoglobin A, Incidence, Japan, Longitudinal Studies, Middle Aged, nomograms, Prediabetic State, ROC Curve, Retrospective Studies, Risk Factors, waist circumference

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Science Editor, Medical Science Monitor, International Scientific Information, Inc., Melville, NY, USA

DOI: 10.12659/MSM.939580

Med Sci Monit 2023; 29:e939580

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750