History Of High Blood Glucose Research Articles

A Chinese Diabetes Risk Score for Screening of Undiagnosed Diabetes and Abnormal Glucose Tolerance

This study is aimed at developing and evaluating a diabetes risk score (DRS) to predict incident diabetes and screen for undiagnosed diabetes and abnormal glucose tolerance in the Chinese population. Three DRS instruments were respectively developed and validated based on the data collected from a 10-year longitudinal health checkup-based population of 1,851 individuals without diabetes at baseline. The efficiency on glucose abnormality screening was evaluated based on the testing of a cross-sectional sample of 699 individuals without known diabetes. The DRS consisting of age, hypertension, history of high blood glucose, body mass index, fasting plasma glucose, serum triglycerides, and serum high-density lipoprotein-cholesterol had the best prediction properties (area under curve [AUC] = 0.734 [95% confidence interval 0.702-0.766] and 0.759 [0.686-0.831] in exploratory and validation cohorts, respectively). The DRS had a sensitivity of 64.5% and 72.9%, respectively, and a specificity of 71.6% and 63.9%, respectively, with an optimal cutoff of 4. AUCs were 0.828 (0.797-0.860) and 0.909 (0.884-0.933) for detecting abnormal glucose tolerance and diabetes, respectively, through cross-sectional screening. Performance of the oral glucose tolerance test (OGTT) in selected subjects with DRS ≥ 4 led to the identification of 76.2% cases of abnormal glucose tolerance and 100% cases of diabetes, while avoiding an OGTT in 52.8% of the study group. The DRS instrument including age, hypertension, history of high blood glucose, body mass index, fasting plasma glucose, triglycerides, and high-density lipoprotein-cholesterol is practical and effective in predicting incident diabetes and screening glucose abnormality in the Chinese population.

A More Simplified Finnish Diabetes Risk Score for Opportunistic Screening of Undiagnosed Type 2 Diabetes in a German Population with a Family History of the Metabolic Syndrome

The aim of the present study was to evaluate the performance of the Finnish diabetes risk score (FINDRISC) for identifying undiagnosed type 2 diabetes in a German population and to develop a more simplified alternative model. We invited 921 individuals with a family history of the metabolic syndrome in a cross-sectional survey. Of these, 771 subjects completed the FINDRISC questionnaire and underwent an oral glucose tolerance test. The performance of the FINDRISC was assessed using the area under the receiver operating characteristics curve (ROC-AUC). The ROC-AUC of the FINDRISC was 0.81 (0.76-0.87). We detected no difference in diabetes prevalence between individuals with or without a family history of diabetes. Two logistic regression models (continuous- and categorical-model) were developed using the diagnosis of diabetes as the dependent variable, and age, body mass index (BMI), waist circumference, use of blood pressure medication, and history of high blood glucose as independent variables. After stepwise backward elimination of the insignificant variables, the following variables remained: age, BMI, and history of high blood glucose. The ROC-AUCs for the continuous- and categorical-models were 0.88 (0.85-0.92) and 0.86 (0.82-0.90), respectively, and were significantly larger than the ROC-AUC of the FINDRISC. There was no significant difference between the ROC-AUC of fasting plasma glucose and those of the two regression models. The FINDRISC questionnaire can be used to identify undetected diabetes in a German population. The simplified version, the categorical-model, may be a useful alternative for identifying asymptomatic type 2 diabetes.