View clinical trials related to Fetal Growth Restriction.
Filter by:Fetal Growth Restriction (FGR) and Small for Gestational Age (SGA) are two conditions that can happen when a baby doesn't grow as much as expected during pregnancy. FGR is caused by things like problems with the mother's nutrition and inflammation, while SGA is usually because of genetic and other factors. It's important to know if a baby has FGR or SGA because FGR babies can have more health problems and are at risk of dying before or shortly after birth. SGA babies are usually healthy, but they might have more health problems later in life. Doctors can use a simple blood test called the HALP score to see if a mother has problems with her nutrition and inflammation. However, it hasn't been studied for FGR and SGA. We want to study if the HALP score can help us tell if a baby has FGR or SGA by looking at the mother's blood test results.
Routine fetal ultrasound scan during the second trimester of the pregnancy is a low-cost, noninvasive screening modality that has been proven to lower fetal mortality by up to 20%. One of the critical elements of this exam is the measurement of fetal biometric parameters, which are the head circumference (HC), biparietal diameter (BPD), abdominal circumference (AC), and femur length (FL) measured on biometry standard planes. Those standard planes are taken according to quality standards first described by Salomon et al. and used as the guidelines of the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG). The biometric parameters extracted from them are essential to diagnose fetal growth restriction (FGR), the world's first cause of perinatal fetal mortality. Such measurements and image quality assessment are time-consuming tasks that are prone to inter and intraobserver variability depending on the level of skill of the sonographer or the physician performing the exam. Amniotic fluid (AF) volume assessment is also an essential step in routine screening scans allowing the diagnosis of oligo or hydramnios, both associated with increased fetal mortality rates. The AF is measured by two main "semi-quantitative" techniques: Amniotic Fluid Index (AFI) and the single deepest pocket (SDP). The latter is more specific as it lowers the overdiagnosis of oligo-amnios without any impact on mortality or morbidity and is easier to perform for the sonographer (only one measurement versus four in the case of the AFI technique). However, AF assessment remains a time-consuming and poorly reproducible task. Attempts to automate such biometric measurements and AF volume assessment have been made using Artificial Intelligence (AI) and deep learning (DL) tools. Studies showed excellent results "in silico," reaching up to 98 %, 95%, 93 % dice score coefficients for HC, AC, and FL measurements and 89 % DSC for AFI measurements. However, they were all conducted retrospectively without validation on prospectively acquired images. Reviews and experts have stressed the need for quality peer-reviewed prospective studies to assess AI tools' performance with real-world data. Their performance is expected to be worse and to reflect better their use in the clinical workflow. This study aims to develop DL models to automate HC, BPD, AC, and FL measurements and AF volume assessment from retrospectively acquired data and test their performances to those of clinicians and experts on prospective real-world fetal US scans.
Normal fetal growth is a critical component for a healthy pregnancy and for ensuring the health and well-being of infants throughout childhood and adolescence. One promising area of research suggests that changes in fetal soft tissue may be the earliest changes that occur in pathologic growth. Three-dimensional volume assessments may be used to detect changes in fetal lean mass, fat mass, and organ size that result from pathologic growth earlier than conventional 2D measures. This knowledge may lead to interventions that could minimize or prevent pregnancy and newborn health problems in the future.
Preterm birth (PTB), preeclampsia (PE), fetal growth restriction (FGR) and intra-uterine fetal death (IUFD) constitutes the main causes of perinatal morbidity and mortality and are called "Great Obstetrical Syndromes". Algorithms to predict those outcomes have been developed by combining maternal characteristics (history, age, BMI, blood pressure), biochemical (sFlt-1, β-hCG, PlGF, AFP) and sonographic (uterine artery Doppler, 3D of placenta, cervical length, nasal bone measurement, nuchal translucency) markers. Another prospective observational study ("PREDICTION study" NCT 02189148) is also ongoing, which aims to validate those algorithms at the first trimester of pregnancy. Recent data suggest that repeating the same measurements later in pregnancy could improve the detection rates, allowing closer monitoring of high-risk patients and potential therapeutics under investigation. The current study (PREDICTION2) is an ancillary study of PREDICTION and aims at validating the use of these markers in a combined iterative manner in the prediction of preeclampsia and other obstetrical outcomes.
The goal of the study is to determine whether labor induction at 37 weeks of pregnancy can improve the baby's health at birth when compared with delivery at a later point in the pregnancy.
Preeclampsia may have several causes leading to different characteristics of the pathology. Differentiation between the "type of preeclampsia" would help to treat patients more accurately. This project aims to identify early markers that are specific to each type of preeclampsia (early or late, with or without growth restriction). Through a case-control study, many data will be collected prospectively (serum markers, ultrasonographic markers, maternal factors) among nulliparous women with no sign of preeclampsia (as soon as the first trimester) and nulliparous women with preeclampsia (at diagnosis).
To evaluate the feasibility of screening for preeclampsia and fetal growth restriction between 11-13+6 weeks' gestation utilizing the combination of uterine artery doppler, maternal blood pressure, maternal characteristics, placental volume, and maternal serum factors, including PAPPA-A, PLGF, AFP and free Beta HCG. This is a non interventional study.
Preeclampsia is a complication of pregnancy related to adverse maternal and neonatal outcomes, including fetal growth restriction and perinatal death. Several measures are used or under investigation (low-dose aspirin, low-molecular weight heparin, calcium, folic acid, among others) for the prevention of preeclampsia. Unfortunately, most high-risk women who could benefit from those preventive measures are not identified until late in pregnancy. Recent evidences suggest that the investigators could identify women at risk of developing preeclampsia using a combination of serum and ultrasound biomarkers in the first-trimester of pregnancy. This screening test needs external validation. A first-trimester screening strategy will strengthen clinical research on preeclampsia and will contribute to the development of strategy combining the prediction and prevention of the disease and its related complications.
In many low-income countries, the use of ultrasound by medical officers and non-physician health care staff (e.g., midwives) for antenatal identification of high risk pregnancies is a new intervention requiring authoritative investigation. The primary hypothesis to be assessed in this study is that antenatal ultrasound screenings performed by medical officers and non-physician health care staff will significantly reduce a composite outcome consisting of maternal mortality and maternal near miss, stillbirth and neonatal mortality in low-resource settings. Underpinning this hypothesis are two assumptions. The first assumption is that antenatal detection of complicated pregnancies will lead to appropriate referral at the right time for complicated pregnancies to comprehensive emergency obstetric and neonatal care (EmONC) facilities. The second assumption is that ultrasound's introduction will increase antenatal attendance leading to greater rates of institutional delivery. To assess these underlying assumptions beyond the composite end point, this study will investigate the health system impact of compact ultrasound. Secondary outcomes include antenatal attendance rates, institutional delivery rates at basic EmONC facilities, referral rates to comprehensive EmONC facilities, cesarean section rates (both planned and emergent) and an assessment of medical officers and non-physician health care provider ultrasound competence and training quality.
The purpose of this study is to use an air filter intervention to evaluate the relationship between particulate matter air pollution exposure during pregnancy and fetal growth. We hypothesize that: 1) portable high efficiency air (HEPA) filters will produce major reductions in home indoor concentrations of particulate matter and 2) pregnant women whose exposures to particulate matter are reduced by this intervention will give birth to children with greater mean body weight for gestational age. In an extended follow-up of this cohort, we aim to evaluate the relationship between use of portable air purifiers during pregnancy and the growth and development of children from birth to age four years. In particular, the follow-up study will focus on children's physical growth, respiratory symptoms, and behavioral, social and neurocognitive development.