Early detection of the risk of gestational diabetes
 
 
 
11.912 out of 30.000 euros

11.912 euros raised
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102projects
1.253.314euros

The project
Who is behind

What is our goal?

Gestational diabetes mellitus (GDM) is defined as the presence of high blood glucose levels during pregnancy in previously healthy women, which can lead to significant metabolic complications for the mother and the offspring, both in the short and long term. Its prevalence is increasing since approximately 7-15% of all pregnancies are complicated by GDM.

Particularly, GDM has been associated with substantial adverse health outcomes for both mothers, who have considerably elevated risk for impaired type 2 diabetes mellitus (T2D) in the years following pregnancy, and the offspring, who are more likely to develop macrosomia and prematurity, as well as an increased risk of obesity and insulin resistance in adulthood. Among the risk factors which predispose to gestational diabetes development, those related to lifestyle are especially important, mainly sedentary lifestyle, and poor diet.

One of the main problems is that GDM is usually diagnosed at 24–28 gestational weeks, according to the recommendations of international associations and committees, when the pathology is already established. Therefore, it is necessary an early identification of the risk of gestational diabetes, which allows to modify, as soon as possible, the lifestyle (food, physical activity), to reduce the progression of the disease and minimize the adverse consequences for the mother and fetus.

Our main objective is the development of an early prediction tool for the risk of GDM, based on based on epigenetic biomarkers and lifestyle variables (food, physical activity) using artificial intelligence techniques.

In this study, we aim to develop and validate a tool that allows us to predict the risk of gestational diabetes as soon as possible, for instance, in the first gestational trimester. This tool is based on the analysis of a type of epigenetic biomarkers, called microRNAs, that circulate in blood and are shared by the mother and fetus through the blood-placental barrier. These biomarkers have a great value for early prediction of the risk of GDM, as they are systematically modified in women who subsequently develop GDM even before clinical changes in blood glucose levels can be detected. Since microRNAs are also modified by lifestyle, both sources of information will allow us to optimize the predictive capacity of the tool, which will be develop by artificial intelligence techniques.

Abaout Precipita
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C/Pintor Murillo, 15
28100 Alcobendas (Madrid) - España
T.+(00 34) 91 425 09 09
info@precipita.es
AENOR
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