Dysglycaemia prediction using readily available clinical, anthropometric, and biochemical measurements

Abstract

Background & aimsA 2-hour postprandial glucose (2-h PG) concentration greater than 140 mg/dL is associated with a greater risk of type-2 diabetes (TD2) and cardiovascular disease. An oral glucose tolerance test (OGTT) is the method most used for detecting either prediabetes or T2D; however, its use in clinical practice is limited due to the 2-h testing period. Therefore, the aim of the study was to assess dysglycaemia, through a prognostic assessment of body composition, biochemical and clinical parameters as predictors of an abnormal 2-h PG. MethodsParticipants underwent a physical examination in which their anthropometric measurements were obtained, and a blood sample was taken for biochemical and hormonal analysis. All patients underwent a 75-g OGTT after 8 h of fasting, and the levels of glucose and insulin were measured. The results were compared statistically by dividing the participants’ 2-h postprandial glucose (2-h PG) into the following groups: normoglycaemia (NGT), < 140 mg/dL; prediabetes, 140 to 199 md/dL; and T2D, ≥ 200 mg/dL. ResultsAmong 381 participants 220 belonged to the NGT group, 131 to the prediabetes group, and 30 to the diabetes group. As expected, fasting glucose, 1-h PG, 2-h PG, haemoglobin glycosylated (A1c) and QUICKI index were significantly higher as the stages of glycaemic dysregulation progressed. Interestingly, 53.4% of the NGT group had a monophasic type of curve in the OGTT and a QUICKI index of 0.32. Subsequently, associative models of 2-h PG were performed, and 4 models were obtained. The best model had a coefficient of determination of 0.747 (p = 0.001) and included the variables A1c, C-reactive protein (CRP), body fat mass, and total cholesterol. ConclusionsThe use of A1c, CRP, body fat mass, and total cholesterol in a model might associate with 2-h PG without the need for a 2-h OGTT.