Predicting the metabolic condition after gestational diabetes mellitus from oral glucose tolerance test curves shape
Academic Article
Publication Date:
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.
Iris type:
01.01 Articolo in rivista
Keywords:
OGTT; Curve shape; Pregnancy; Kullback-Leibler divergence; Prediction of metabolic state
List of contributors: