Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study.

Journal: Diabetes/metabolism research and reviews
PMID: 39031573

Abstract

INTRODUCTION: Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post-challenge hyperglycemia (IPH), that is., patients with normal fasting plasma glucose (<7.0 mmoL/L) and abnormal 2-h postprandial blood glucose (≥11.1 mmoL/L). We aimed to develop a model to differentiate individuals with IPH from the normal population.

Authors

  • Rui Hou
    Guangzhou KangRui Biological Pharmaceutical Technology Company, 510005 Guangzhou, China.
  • Jingtao Dou
    Department of Endocrinology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Lijuan Wu
    Big Data Decision Institute, Jinan University, Guangzhou, China.
  • Xiaoyu Zhang
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.
  • Changwei Li
    Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education, College of Chemistry, Xiangtan University, Xiangtan 411105, China.
  • Weiqing Wang
    National Clinical Research Center for Metabolic Diseases, State Key Laboratory of Medical Genomics, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Shanghai Institute for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
  • Zhengnan Gao
    Dalian Central Hospital, Dalian, Liaoning, China.
  • Xulei Tang
    First Hospital of Lanzhou University, Lanzhou, Gansu, China.
  • Li Yan
    Wenzhou Public Utilities Investment Group Co. Ltd., Wenzhou 325000, China. Electronic address: Vangji@126.com.
  • Qin Wan
    Ocular and Stem Cell Translational Research Section, National Eye Institute, NIH, Bethesda, Maryland, USA.
  • Zuojie Luo
    First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Guijun Qin
    First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
  • Lulu Chen
  • Jianguang Ji
    Center for Primary Health Care Research, Lund University/Region Skåne, Malmö, Sweden.
  • Yan He
    School of Biology & Engineering, Guizhou Medical University, Guiyang, Guizhou Province, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Yiming Mu
    Department of Endocrinology, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Deqiang Zheng
    Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China.

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