OBJECTIVE:Using primary care data, develop and validate sex-specific prognostic models that estimate the 10-year risk of people with non-diabetic hyperglycaemia developing type 2 diabetes. DESIGN:Retrospective cohort study. SETTING:Primary care. PARTICIPANTS:154 705 adult patients with non-diabetic hyperglycaemia. PRIMARY OUTCOME:Development of type 2 diabetes. METHODS:This study used data routinely collected in UK primary care from general practices contributing to the Clinical Practice Research Datalink. Patients were split into development (n=109 077) and validation datasets (n=45 628). Potential predictor variables, including demographic and lifestyle factors, medical and family history, prescribed medications and clinical measures, wer...
Background The comparative performance of existing models for prediction of type 2 diabetes across p...
Aims/hypothesis: Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engin...
BACKGROUND: The comparative performance of existing models for prediction of type 2 diabetes across ...
Objectives To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 ye...
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...
Aims: To develop and validate sex-specific risk prediction models based on easily obtainable clinica...
OBJECTIVE: To validate risk scores to predict occurrence of type 2 diabetes in the Dutch population....
Type 2 diabetes has increased in prevalence globally in recent years, mainly due to obesity. Many ot...
AimTo identify, predict and validate distinct glycaemic trajectories among patients with newly diagn...
OBJECTIVES: To study the characteristics of UK individuals identified with non-diabetic hyperglycaem...
BACKGROUND: The World Health Organisation estimates that by 2030 there will be approximately 350 mil...
Context: A recent overview of all CVD models applicable to diabetes patients is not available. Objec...
Background: The comparative performance of existing models for prediction of type 2 diabetes across ...
The prevalence and mortality related to diabetes mellitus type 2 (DM2) have increased consistently f...
Background The comparative performance of existing models for prediction of type 2 diabetes across p...
Aims/hypothesis: Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engin...
BACKGROUND: The comparative performance of existing models for prediction of type 2 diabetes across ...
Objectives To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 ye...
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...
Aims: To develop and validate sex-specific risk prediction models based on easily obtainable clinica...
OBJECTIVE: To validate risk scores to predict occurrence of type 2 diabetes in the Dutch population....
Type 2 diabetes has increased in prevalence globally in recent years, mainly due to obesity. Many ot...
AimTo identify, predict and validate distinct glycaemic trajectories among patients with newly diagn...
OBJECTIVES: To study the characteristics of UK individuals identified with non-diabetic hyperglycaem...
BACKGROUND: The World Health Organisation estimates that by 2030 there will be approximately 350 mil...
Context: A recent overview of all CVD models applicable to diabetes patients is not available. Objec...
Background: The comparative performance of existing models for prediction of type 2 diabetes across ...
The prevalence and mortality related to diabetes mellitus type 2 (DM2) have increased consistently f...
Background The comparative performance of existing models for prediction of type 2 diabetes across p...
Aims/hypothesis: Treatment guidelines recommend the UK Prospective Diabetes Study (UKPDS) risk engin...
BACKGROUND: The comparative performance of existing models for prediction of type 2 diabetes across ...