Aims: To develop and validate sex-specific risk prediction models based on easily obtainable clinical data for predicting 5-year risk of type 2 diabetes (T2D) among individuals with impaired fasting glucose (IFG), and generate practical tools for public use. Methods: The data used for model training and internal validation came from a large prospective cohort (N = 18,384). Two independent cohorts were used for external validation. A two-step approach was applied to screen variables. Coefficient-based models were constructed by multivariate Cox regression analyses, and score-based models were subsequently generated. The predictive power was evaluated by the area under the curve (AUC). Results: During a median follow-up of 7.55 years, 5697 ne...
Aims: To develop and validate a non-invasive score for detecting undiagnosed impaired fasting glucos...
Background: The comparative performance of existing models for prediction of type 2 diabetes across ...
Background The comparative performance of existing models for prediction of type 2 diabetes across p...
Objectives: To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 y...
Objective: To identify existing prediction models for the risk of development of type 2 diabetes and...
OBJECTIVE: To identify existing prediction models for the risk of development of type 2 diabetes and...
A risk score model was developed based in a population of 1,224 individuals from the general popula...
OBJECTIVE: Type 2 diabetes arises from the interaction of physiological and lifestyle risk factors. ...
A risk score model was developed based in a population of 1,224 individuals from the general populat...
Kyungdo Han,1,* Jae-Seung Yun,2,* Yong-Moon Park,3 Yu-Bae Ahn,2 Jae-Hyoung Cho,2 Seon-Ah Cha,2 Seung...
OBJECTIVE-To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis...
OBJECTIVE: To validate risk scores to predict occurrence of type 2 diabetes in the Dutch population....
BACKGROUND: The World Health Organisation estimates that by 2030 there will be approximately 350 mil...
OBJECTIVE:Using primary care data, develop and validate sex-specific prognostic models that estimate...
OBJECTIVE—To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis...
Aims: To develop and validate a non-invasive score for detecting undiagnosed impaired fasting glucos...
Background: The comparative performance of existing models for prediction of type 2 diabetes across ...
Background The comparative performance of existing models for prediction of type 2 diabetes across p...
Objectives: To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 y...
Objective: To identify existing prediction models for the risk of development of type 2 diabetes and...
OBJECTIVE: To identify existing prediction models for the risk of development of type 2 diabetes and...
A risk score model was developed based in a population of 1,224 individuals from the general popula...
OBJECTIVE: Type 2 diabetes arises from the interaction of physiological and lifestyle risk factors. ...
A risk score model was developed based in a population of 1,224 individuals from the general populat...
Kyungdo Han,1,* Jae-Seung Yun,2,* Yong-Moon Park,3 Yu-Bae Ahn,2 Jae-Hyoung Cho,2 Seon-Ah Cha,2 Seung...
OBJECTIVE-To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis...
OBJECTIVE: To validate risk scores to predict occurrence of type 2 diabetes in the Dutch population....
BACKGROUND: The World Health Organisation estimates that by 2030 there will be approximately 350 mil...
OBJECTIVE:Using primary care data, develop and validate sex-specific prognostic models that estimate...
OBJECTIVE—To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis...
Aims: To develop and validate a non-invasive score for detecting undiagnosed impaired fasting glucos...
Background: The comparative performance of existing models for prediction of type 2 diabetes across ...
Background The comparative performance of existing models for prediction of type 2 diabetes across p...