A composite risk assessment model to screen for gestational diabetes mellitus among Mediterranean women.

OBJECTIVE: To determine whether clinical risk assessment for gestational diabetes mellitus (GDM) may preclude the need for universal screening with an oral glucose tolerance test (OGTT) in situations of economic restraint. METHODS: Women with either GDM (n=119) or normal glucose tolerance (n=1249) were recruited from centers among 11 Mediterranean countries between August 1, 2010, and May 31, 2011. Outcome measures included anthropomorphic and biological data, obstetric outcomes, and infant outcomes. RESULTS: Significant risk factors for GDM included maternal age of 30 years or more; elevated body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters); elevated diastolic blood pressure; previous history of macrosomia; and family history of diabetes mellitus. These factors each had high specificity but low sensitivity for predicting GDM; however, when used in combination, sensitivity increased but specificity fell. Fasting blood glucose (FBG) level had high sensitivity (73.9%) and specificity (90.2%) for predicting GDM. Sensitivity was further increased by combining FBG measurement with maternal age and BMI (96.6%). CONCLUSION: Use of a composite model to prescreen women for GDM risk may reduce the need for universal screening with the OGTT among centers facing health-cost pressures.

Hyperglycaemia in pregnancy in Mediterranean women.

New diagnostic criteria have recently been proposed that will result in a higher proportion of individuals being diagnosed as suffering from gestational diabetes mellitus (GDM) than previously. The present circum-Mediterranean study sets out to identify the relevance of the new criteria in this population. The study was a prospective, non-interventional, multicentre study in the Mediterranean region. A convenient sample of 1,368 pregnant women was recruited. All participants underwent a 75 g oGTT subdivided into five different glycaemic categories. The women's anthropomorphic and biological data, together with obstetric and infant outcomes, were collected. There was a threefold increase in diagnosis using the new criteria. Most of the biological characteristics generally associated with GDM showed high specificity and low sensitivity values. The biological characteristics, including maternal age, BMI and FBG, showed a progressive increase as a function of maternal glycaemia with moderate sensitivity and specificity values. Using these latter characteristics in combination ensures that 72.3 % of the GDM population would be correctly identified, while an oGTT would only be required in 18.7 % of the population. The progressive relationship of increasing glycaemia to adverse characteristics suggests that the new IADPSG criteria are reasonable provided that dietary advice is given to all pregnant women. In situations of economic restraints, it appears possible to screen Mediterranean women for GDM risk using a composite model using FBG >5.0 mmol/l combined with the performance of an oGTT in women with a low FBG but who are overweight and aged >30 years.

A hybrid Decision Support System for the risk assessment of retinopathy development as a long term complication of Type 1 Diabetes Mellitus.

The aim of the present study is to design and develop a Decision Support System (DSS) closely coupled with an Electronic Medical Record (EMR), able to predict the risk of a Type 1 Diabetes Mellitus (T1DM) patient to develop retinopathy. The proposed system is able to store a wealth of information regarding the clinical state of the T1DM patient and continuously provide the health experts with predictions regarding the possible future complications that he may present. The DSS is a hybrid infrastructure combining a Feedforward Neural Network (FNN), a Classification and Regression Tree (CART) and a Rule Induction C5.0 classifier, with an improved Hybrid Wavelet Neural Network (iHWNN). A voting mechanism is utilized to merge the results from the four classification models. The proposed DSS has been trained and evaluated using data from 55 T1DM patients, acquired by the Athens Hippokration Hospital in close collaboration with the EURODIAB research team. The DSS has shown an excellent performance resulting in an accuracy of 98%. Care has been taken to design and implement a consistent and continuously evolving Information Technology (IT) system by utilizing technologies such as smart agents periodically triggered to retrain the DSS with new cases added in the data repository.

Dietary fat intake as risk factor for the development of diabetes: multinational, multicenter study of the Mediterranean Group for the Study of Diabetes (MGSD).

OBJECTIVE: To investigate the role of dietary factors in the development of type 2 diabetes. RESEARCH DESIGN AND METHODS: In the context of the Multinational MGSD Nutrition Study, three groups of subjects were studied: 204 subjects with recently diagnosed diabetes (RDM), 42 subjects with undiagnosed diabetes (UDM) (American Diabetes Association criteria-fasting plasma glucose [FPG] > or =126 mg/dl), and 55 subjects with impaired fasting glucose (IFG) (FPG > or =110 and <126 mg/dl). Each group was compared with a control group of nondiabetic subjects, matched one by one for center, sex, age, and BMI. Nutritional habits were evaluated by a dietary history method, validated against the 3-day diet diary. In RDM, the questionnaire referred to the nutritional habits before the diagnosis of diabetes. Demographic data were collected, and anthropometrical and biochemical measurements were taken. RESULTS: Compared with control subjects, RDM more frequently had a family history of diabetes (49.0 vs. 14.2%; P < 0.001), exercised less (exercise index 53.5 vs. 64.4; P < 0.01), and more frequently had sedentary professions (47.5 vs. 27.4%; P < 0.001). Carbohydrates contributed less to their energy intake (53.5 vs. 55.1%; P < 0.05), whereas total fat (30.2 +/- 0.5 vs. 27.8 +/- 0.5%; P < 0.001) and animal fat (12.2 +/- 0.3 vs. 10.8 +/- 0.3%; P < 0.01) contributed more and the plant-to-animal fat ratio was lower (1.5 +/- 0.1 vs. 1.8 +/- 0.1; P < 0.01). UDM more frequently had a family history of diabetes (38.1 vs. 19.0%; P < 0.05) and sedentary professions (58.5 vs. 34.1%; P < 0.05), carbohydrates contributed less to their energy intake (47.6 +/- 1.7 vs. 52.8 +/- 1.4%; P < 0.05), total fat (34.7 +/- 1.5 vs. 30.4 +/- 1.2%; P < 0.05) and animal fat (14.2 +/- 0.9 vs. 10.6 +/- 0.7%; P < 0.05) contributed more, and the plant-to-animal fat ratio was lower (1.6 +/- 0.2 vs. 2.3 +/- 0.4; P < 0.05). IFG differed only in the prevalence of family history of diabetes (32.7 vs. 16.4%; P < 0.05). CONCLUSIONS: Our data support the view that increased animal fat intake is associated with the presence of diabetes.