Thiazolidinediones and type 2 diabetes: new drugs for an old disease

Thiazolidinediones are a new class of drugs for the treatment of type 2 diabetes, and act by improving insulin sensitivity in adipose tissue, liver and skeletal muscle. Rosiglitazone and pioglitazone are registered for use in monotherapy, and in combination with sulfonylureas and metformin. Pioglitazone is also licensed for use in combination with insulin. There is level II evidence that in patients with inadequate glycaemic control both drugs reduce the level of HbA(1c) and fasting plasma glucose (FPG) when used as monotherapy and in combination with sulfonylurea or metformin or insulin; and both drugs increase levels of HDL and LDL and lower free fatty acid levels, but only pioglitazone significantly lowers triglyceride levels. Both drugs lower fasting insulin and C-peptide levels. In monotherapy, they may be slightly less potent at reducing the level of HbA(1c) than sulfonylureas or metformin. The maximal effect of these agents may not be seen for 6-14 weeks after commencement. Both drugs are well tolerated but liver function must be checked at baseline every second month for the first year, and periodically thereafter. The drugs are currently contraindicated in patients with moderate to severe liver dysfunction and alanine aminotransferase levels more than 2.5 times normal, New York Heart Association III-IV cardiac status, pregnancy, lactation and in children. The main side effects include weight gain, oedema, and mild dilutional anaemia.

Beneficial associations of physical activity with 2-h but not fasting blood glucose in Australian adults

OBJECTIVE - We examined the associations of physical activity with fasting plasma glucose (FPG) and with 2-h postload plasma glucose (2-h PG) in men and women with low, moderate, and high waist circumference. RESEARCH DESIGN AND METHODS - The Australian Diabetes, Obesity and Lifestyle (AusDiab) study provided data on a population-based cross-sectional sample of 4,108 men and 5,106 women aged >= 25 years without known diabetes or health conditions that could affect physical activity. FPG and 2-h PG were obtained from an oral glucose tolerance test. Self-reported physical activity level was defined according to the current public health guidelines as active (>= 150 min/week across five or more sessions) or inactive (< 150 min/week and/or less than five sessions). Sex-specific quintiles of physical activity time were used to ascertain dose response. RESULTS - Being physically active and total physical activity time were independently and negatively associated with 2-h PG. When physical activity level was considered within each waist circumference category, 2-h PG was significantly lower in active high-waist circumference women (beta-0.30 [95% CI -0.59 to -0.01], P = 0.044) and active low-waist circumference men(beta-0.25 [-0.49 to -0.02],P = 0.036) compared with their inactive counterparts. Considered across physical activity and waist circumference categories, 2-h PG levels were not significantly different between active moderate-waist circumference participants and active low-waist circumference participants. Associations between physical activity and FPG were nonsignificant. CONCLUSIONS - There are important differences between 2-h PG and FPG related to physical activity. It appears that 2-h PG is more sensitive to the beneficial effects of physical activity, and these benefits occur across the waist circumference spectrum.

Diagnosis of diabetes mellitus: case of different cutoff values: A data mining approach

Objective: An estimation of cut-off points for the diagnosis of diabetes mellitus (DM) based on individual risk factors. Methods: A subset of the 1991 Oman National Diabetes Survey is used, including all patients with a 2h post glucose load >= 200 mg/dl (278 subjects) and a control group of 286 subjects. All subjects previously diagnosed as diabetic and all subjects with missing data values were excluded. The data set was analyzed by use of the SPSS Clementine data mining system. Decision Tree Learners (C5 and CART) and a method for mining association rules (the GRI algorithm) are used. The fasting plasma glucose (FPG), age, sex, family history of diabetes and body mass index (BMI) are input risk factors (independent variables), while diabetes onset (the 2h post glucose load >= 200 mg/dl) is the output (dependent variable). All three techniques used were tested by use of crossvalidation (89.8%). Results: Rules produced for diabetes diagnosis are: A- GRI algorithm (1) FPG>=108.9 mg/dl, (2) FPG>=107.1 and age>39.5 years. B- CART decision trees: FPG >=110.7 mg/dl. C- The C5 decision tree learner: (1) FPG>=95.5 and 54, (2) FPG>=106 and 25.2 kg/m2. (3) FPG>=106 and =133 mg/dl. The three techniques produced rules which cover a significant number of cases (82%), with confidence between 74 and 100%. Conclusion: Our approach supports the suggestion that the present cut-off value of fasting plasma glucose (126 mg/dl) for the diagnosis of diabetes mellitus needs revision, and the individual risk factors such as age and BMI should be considered in defining the new cut-off value.