Diabetes, Metabolic Syndrome and Obesity (Nov 2021)

A Predictive Model of Metabolic Syndrome by Medical Examination: Evidence from an 8-Year Chinese Cohort

  • Guo H,
  • Jiang W,
  • Zhao B,
  • Xiong Y,
  • Lu Z

Journal volume & issue
Vol. Volume 14
pp. 4459 – 4467

Abstract

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Huanyu Guo,1,* Wenwei Jiang,2,* Bo Zhao,1 Yanhua Xiong,3 Zhenya Lu1 1Department of FSTC Clinic of The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, People’s Republic of China; 2Department of Internal Medicine of Traditional Chinese Medicine, Huzhou Central Hospital, Huzhou, 310003, People’s Republic of China; 3Department of Internal Medicine of Traditional Chinese Medicine, Zhejiang Hospital, Hangzhou, 310007, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhenya LuDepartment of FSTC Clinic of The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310009, People’s Republic of ChinaTel +86 13575458480Email [email protected]: To develop a predictive model for the risk of metabolic syndrome (MetS).Patients and Methods: Totally, 1556 residents without MetS were finally included in 2006 and they were observed for 8 years to check who developed MetS. Univariate and multivariate logistic regression analyses was adopted to explore the risk factors of MetS and develop the predictive model that used the medical examination information of MetS risk after 8 years. The receiver operating characteristic (ROC) curve was drawn to assess the predictive capacity of the model.Results: The risk of MetS in overweight, prehypertension, hypertension subjects were 4.610 [95% confidence interval (CI): 2.415 to 8.800], 2.759 (95% CI: 1.519 to 5.011) and 3.589 (95% CI: 1.672 to 7.706) times higher than that in controls, respectively. The risk of MetS in people with high-density lipoprotein (HDL) < 1.10 mmol/L was 3.716-fold in comparison with HDL ≥ 1.55 mmol/L [odds risk (OR) = 3.716, 95% CI: 1.483 to 9.313]. Individuals with fatty liver had a higher risk of MetS (OR = 2.577, 95% CI: 1.472 to 4.512). The AUC of the predictive model was 0.831 (95% CI: 0.798 to 0.865), with the sensitivity of 0.898 (95% CI: 0.831 to 0.941) and the specificity of 0.676 (95% CI: 0.651 to 0.700).Conclusion: The model performed well predictive power for the risk of MetS, which may provide a reference for clinicians to identify high-risk groups early.Keywords: metabolic syndrome, predictive model, 8-year, Chinese cohort

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