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Data Sheet 1_Metabolic syndrome and diabetic kidney disease: a consistent dose–response association validated in an independent clinical cohort.doc

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Metabolic_syndrome_and_diabetic_kidney_disease_a_consistent_dose_response_association_validated_in_an_independent_clinical_cohort_doc/31121488
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BackgroundDiabetic kidney disease (DKD) is a major complication of diabetes. The relative impact of individual metabolic syndrome (MetS) components and cumulative metabolic burden on DKD remains unclear. MethodsWe analyzed 16,236 adults from NHANES 2011–2020. DKD was defined as reduced eGFR or increased urinary albumin-to-creatinine ratio in individuals with diabetes. MetS components included abdominal obesity, high blood pressure, high triglycerides, low high-density lipoprotein (HDL) cholesterol, and elevated glucose. Multivariable logistic regression evaluated associations of single components and MetS component count (MetS score) with prevalent DKD. Discrimination was assessed by receiver operating characteristic curves. External validation was performed in a retrospective cohort of 320 adults from The First Affiliated Hospital of Zhengzhou University. ResultsIn NHANES, 6.1% had DKD. Elevated glucose and low HDL cholesterol were independently associated with higher odds of DKD, whereas other components showed weaker or non-significant associations. DKD prevalence increased progressively with MetS score, and the score showed moderate discrimination (AUC 0.704). In the validation cohort (DKD prevalence 9.1%), elevated glucose, low HDL cholesterol, and high blood pressure were significant predictors of DKD. Each one-point increase in MetS score more than doubled the odds of DKD, with good discriminative performance (AUC 0.869; optimal cutoff ≥3 components). ConclusionElevated glucose and low HDL cholesterol are key MetS components associated with DKD, and a higher MetS component count confers progressively greater DKD risk. The MetS score may serve as a simple tool for DKD risk stratification in clinical practice.
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2026-01-22
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