The objective of this feasibility study is to predict the metabolic condition in women with a history of gestational diabetes mellitus (GDM) from the shape of oral glucose tolerance test (OGTT) data. The rationale for this approach is that the evolution to a metabolic condition could be traceable in the shape of OGTT curves. 3-h OGTT data of 136 women with follow up, for a total of 401 OGTTs were analyzed. Subjects were classified as having normal (NGT) or non-normal glucose tolerance (NON-NGT), according to the American Diabetes Association criteria. The measured glucose, insulin, C-peptide data and combination of them were used to build up NGT and NON-NGT reference curves. Similarity between reference and individual OGTT-based curves was calculated using the Kullback-Leibler divergence. Our findings suggest that the shape of OGTT curves (1) contains information on the evolution to disease and (2) could be a reliable indicator to predict with high sensitivity (75%) and high specificity (69%) the metabolic condition of women with a history of GDM. In the future, the proposed shape-based prediction could be easily translated to the clinical practice, because it does not require the intervention of an operator specifically trained, thus facilitating its application in a clinical setting and ultimately empowering risk estimation, by improving/complementing the information which is currently adopted for risk stratification after pregnancy with GDM.
Predicting the metabolic condition after gestational diabetes mellitus from oral glucose tolerance test curves shape
Pacini G;Tura A
2014
Abstract
The objective of this feasibility study is to predict the metabolic condition in women with a history of gestational diabetes mellitus (GDM) from the shape of oral glucose tolerance test (OGTT) data. The rationale for this approach is that the evolution to a metabolic condition could be traceable in the shape of OGTT curves. 3-h OGTT data of 136 women with follow up, for a total of 401 OGTTs were analyzed. Subjects were classified as having normal (NGT) or non-normal glucose tolerance (NON-NGT), according to the American Diabetes Association criteria. The measured glucose, insulin, C-peptide data and combination of them were used to build up NGT and NON-NGT reference curves. Similarity between reference and individual OGTT-based curves was calculated using the Kullback-Leibler divergence. Our findings suggest that the shape of OGTT curves (1) contains information on the evolution to disease and (2) could be a reliable indicator to predict with high sensitivity (75%) and high specificity (69%) the metabolic condition of women with a history of GDM. In the future, the proposed shape-based prediction could be easily translated to the clinical practice, because it does not require the intervention of an operator specifically trained, thus facilitating its application in a clinical setting and ultimately empowering risk estimation, by improving/complementing the information which is currently adopted for risk stratification after pregnancy with GDM.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
