ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2021
A Predictive Model of Metabolic Syndrome by Medical Examination: Evidence from an 8-Year Chinese Cohort.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Cardiometabolic Burden of Irritable Bowel Syndrome: A Case-Control Analysis of Metabolic Syndrome Clustering.Journal of epidemiology and global health · 2026Article
- Machine learning ensemble meets clinical practice: developing a real-world risk prediction model for metabolic syndrome using super learner and scorecard approaches.Journal of advanced research · 2026Article
- Association of simple renal cysts with metabolic syndrome in adults.Frontiers in public health · 2022Article
- Association of Serum Amylase Activity and the Copy Number Variation ofDiabetes, metabolic syndrome and obesity : targets and therapy · 2021Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo develop a predictive model for the risk of metabolic syndrome (MetS). PATIENTS AND
methodsTotally, 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.
resultsThe 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).
conclusionThe model performed well predictive power for the risk of MetS, which may provide a reference for clinicians to identify high-risk groups early.
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