Clinical Research Directory

New Markers of Glycation to Predict Gestational Diabetes Mellitus and Macrosomia.

Gestational diabetes mellitus (GDM) increases the risk of macrosomia and other adverse pregnancy outcomes. Screening strategies are debated: universal vs. selective, and macrosomia may begin before the time of screening, suggesting that glycation markers may have an interest. The objective of this trail is to compare novel markers: skin autofluorescence and glycated albumin, to HbA1c (reference) as predictors of GDM, macrosomia and other adverse outcomes, in pregnant women.

Artificial Intelligence and Gestacional Diabetes

Artificial intelligence (AI) technology can assist medical teams in remote monitoring and continuing education of women with gestational diabetes (GDM), potentially improving adherence to interventions and impacting outcomes. An AI remote monitoring model called "monitoring model for women with GDM using pharmacological therapy," created by the ChamouDr technical team, will be analyzed focusing on disease education, glycemic control monitoring, and therapeutic interventions. Women diagnosed with GDM are invited to participate in the study and sign a free and informed consent form. The AI tool is installed on the pregnant woman's cell phone, who receives instructions to collect capillary blood glucose 6 times a day according to the protocol, at home, and report the results via WhatsApp to the study tool. Algorithm generated by the AI model based on self monitoring of blood glucose (SMBG) informs about diabetes control in the last week. The dashboard is accessible via a web browser, and signals: in green and red for patients with satisfactory and unsatisfactory control, respectively. Thus, the AI model optimizes the team's time in analyzing and treating patients appropriately in a simple, cost-effective, and accessible way.

Fetal Clavicular Measurement to Predict Fetal Macrosomia

Macrosomia is associated with increased risks for both the mother and the baby, including complications during delivery, injuries, and even death. The accurate diagnosis of macrosomia is often difficult before birth. There are a number of factors that can increase the risk of macrosomia, such as maternal obesity, diabetes, and excessive weight gain during pregnancy. There are also a number of different techniques that can be used to try to predict macrosomia, but none of them are perfect. The aim of this study is to evaluate sensitivity of measuring fetal clavicle length in third trimester compared with biacromial diameter and Hadlock formula IV for prediction of fetal macrosomia.