aPatients with no diagnosis of diabetes and either fasting glucose bAdjusted for age, gender, statin treatment, glycated haemoglobin, triglycerides, uric acid, urinary albumin creatinine ratio, body m

Figshare2015-12-02 更新30

Multivariate adjusted logistic regression model for the incidence of new-onset diabetes by the combination pattern of obesity and FLI-NAFLD.

糖尿病风险预测

脂肪肝与肥胖关联

Multivariate adjusted logistic regression model for the incidence of new-onset diabetes by the combination pattern of obesity and FLI-NAFLD.

NIAID Data Ecosystem20

Multivariate logistic regression analysis of presence of diabetes for high AIP(>0.24).

糖尿病风险预测

生物标志物分析

Multivariate logistic regression analysis of presence of diabetes for high AIP(>0.24).

NIAID Data Ecosystem40

Baseline Characteristics of Study Participants.

糖尿病风险预测

代谢物生物标志物

Objective This study aims to investigate the prevalence of prediabetes among U.S. adults using NHANES 2017–2023 data, explore the relationship between the weight-adjusted waist circumference index (WW

NIAID Data Ecosystem20

The results on early-stage diabetes risk prediction dataset.

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