An innovative prognostic model for predicting diabetes risk in the Thai population

Objective: To estimate the prevalence and type 2 diabetes, and to develop a prognostic model for identifying individuals at high risk of undiagnosed type 2 diabetes. Research design and methods: The study was designed as a cross-sectional investigation with 4314 participants of Thai background, aged between 15 and 85. years (mean age: 48). Fasting plasma glucose was initially measured, and repeated if the first measurement was more than 126. mg/dl. Type 2 diabetes was diagnosed using the World Health Organization's criteria. Logistic regression model was used to develop prognostic models for men and women separately. The prognostic performance of the model was assessed by the area under the receiver operating characteristic curve (AUC) and a nomogram was constructed from the logistic regression model. Results: The overall prevalence of type 2 diabetes was 7.4% (n= 125/1693) in men and 3.4% (n= 98/2621) in women. In either gender, the prevalence increased with age and body mass index (BMI). Gender, age, BMI and systolic blood pressure (SBP) were independently associated with type 2 diabetes risk. Based on the estimated parameters of model, a nomogram was constructed for predicting diabetes separated by gender. The AUC for the model with 3 factors was 0.75. Conclusions: These data suggest that the combination of age, BMI and systolic blood pressure could help identify Thai individuals at high risk of undiagnosed diabetes. © 2011

Permanent neonatal diabetes misdiagnosed as type 1 diabetes in a 28-year-old female: a life-changing diagnosis.

Many patients with monogenic diabetes are missed or misclassified. Herein, we report a 28-year-old Indian female who developed diabetes at the age of 3 months. An audit of our type 1 diabetes database led to her genetic testing. A KCNJ11 mutation was identified and she was successfully switched to sulphonylurea