Clinical Research Directory

Lifestyle Intervention in Preparation for Pregnancy (LIPP)

Studies evaluating lifestyle intervention in obese women during pregnancy have reported limited success in decreasing excessive gestational weight gain, and have failed to achieve the key outcome of breaking the obesity cycle and reducing neonatal adiposity or birth weight. Although some investigators advocate weight loss during pregnancy in obese women, these recommendations were based on extrapolation of retrospective epidemiological data. Of concern, we reported increased small for gestational age babies and decreased lean body mass in neonates of obese women with weight loss or inadequate gestational weight gain. Based on our research, optimal outcomes from lifestyle interventions are likely to be temporal and therefore must be initiated prior to conception to first improve maternal metabolic function, and subsequently, placental/fetal growth. Several large retrospective cohort studies support our hypothesis. For example, women who lost weight between pregnancies had fewer large for gestational age babies in contrast to women who increased interpregnancy weight. In addition, prospective randomized controlled trials have shown that postpartum weight loss is achievable without adverse maternal or neonatal outcomes, these studies include women who breastfed. Based on these observations, we propose a randomized control trial to determine the effect of lifestyle intervention initiated prior to a planned pregnancy on improving neonatal metabolism and adiposity. Our overarching hypothesis is that the maternal pre-pregnancy metabolic condition determines the obesogenic in-utero environment, which affects programming of placental mitochondrial function and metabolic pathways, promoting lipid accumulation and neonatal adiposity. Our rationale is based on the need to establish the most effective time to introduce an intervention that will break the obesity cycle in mothers and their children. Understanding how pregravid metabolic conditioning improves maternal physiology, and cellular and molecular function in pregnancy will provide the empirical data to support the intervention. We have a highly successful record of recruiting women who are planning a pregnancy, obtaining compliance in longitudinal studies, and in long-term follow-up of mothers and their offspring. Lifestyle intervention will be initiated prior to conception to decrease maternal body fat, inflammation, insulin resistance, and ?-cell dysfunction. Our transdisciplinary team has the required expertise in lifestyle interventions management of obesity, and in human physiology that is needed to determine the effects of these interventions on maternal metabolism and fetalplacental growth and function. We will recruit 200 women to pursue the following specific aims: Specific Aim 1: To investigate the physiological significance of lifestyle intervention in preparation for pregnancy (LIPP) on maternal and neonatal metabolism and adiposity. Specific Aim 2: To determine the molecular effects whereby lifestyle intervention initiated before pregnancy can improve placental mitochondrial lipid oxidation and accumulation.

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.

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.

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.