Active clinical trials for "Premature Birth"

Several clinical and preclinical studies have focused interest on lipoprotein(a) [Lp(a)], showing a direct and independent relationship of its circulating levels with the progression of atherosclerosis and its clinical manifestations. However, to date, Lp(a) represents an underestimated predictor of CV risk, especially in higher-risk populations, such as patients with strong CV familiarity and recurrent and/or early-onset CV events. The key point of the project will be the evaluation of the role of Lp(a) in the development of atherosclerotic disease and, specifically, acute coronary syndrome.

This is a 24-week, multicenter, open-label, single-arm, observational, post approval commitment study, which is designed to collect effectiveness, safety and other clinical information of intravitreal ranibizumab 0.2 mg for the treatment of Retinopathy of Prematurity (ROP) participants in a real world clinical setting in mainland China.

The aim of this study is to determine the effect of repetitive tactile stimulation compared to selective stimulation on oxygenation of the infant at 5 minutes after birth. Infants born before 32 weeks of gestation will be included in this trial. This is a stepped-wedge cluster randomised controlled trial. The participating centre, rather than the individual infant, will be the unit of randomisation. This design is appropriate to test the effect of an intervention that encompasses a behavioral aspect - in this case the performance of tactile stimulation.

The study will be a 5-year retrospective and prospective case control study, included 650 participants, and participants will be divided into four groups.By this research the investigators will achieve several aims:(1) Through the cross-sectional analysis of this study, the investigators can understand the current prevalence of developmental disorders in Taiwan ,especially ADHD and ASD, and the ratio of male to female in school-age children. (2) Analysis of risk factors in preterm infants during pregnancy and infant, and construct the diagnostic predictive models. (3) By the cohort study of premature infants, to analyze early risk factors of premature children with neurological developmental disorders (such as ADHD), and develop the diagnostic predictive models and early interventional tools. (4) Using artificial intelligence and machine learning analysis to analyze the characteristics of preterm and development of diagnostic prediction model of premature infant or premature children combined ADHD. (5) The application of noninvasive physiological signal capture real-time analysis system in screening and evaluation of "premature infant and neurodevelopmental disorders".

Neonatal intensive care relies on indwelling plastic medical devices fundamental in respiratory support, intravenous catheterization, and nutrition. While being in a critical developmental period, constant exposure to these invasive medical devices puts premature neonates at risk of plasticizers' potential toxicity. Despite novel regulations and development of alternative plasticizers (AP), reference to guide manufacturers and an overview of the prevailing exposure levels to DEHP or alternatives in the neonatal intensive care unit (NICU) are still missing. The three main objectives of this project are: (1) to assess current exposure to plasticizers in the NICU, (2) to identify the sources of exposure and (3) to study the resultant long-term health risk in premature neonates. These objectives are addressed in three work packages (WP). In work package 1, in vivo exposure of premature neonates to phthalates and alternative plasticizers is assessed by determining their metabolites in biological matrices (urine and hair). Work package 2 explores ex vivo leaching characteristics of different plasticizers from medical devices used in the NICU. Finally, Work package 3 studies the long-term neurocognitive and lung development in relation to plasticizer exposure in the NICU.

MagnetoEncephaloGraphy (MEG) is a method of recording brain activity with high temporal resolution and good spatial resolution, compared to current recording techniques such as ElectroEncephaloGraphy (EEG). The main limitation of MEG is its cost due to the sensors used, the Super Quantum Interference Devices (SQUID). These require a complex infrastructure from an instrumentation point of view to operate, requiring liquid helium, most often at a loss, at increasing cost. Optical Pumping Magnetometers (OPM) type sensors represent a promising alternative to SQUIDs sensors, especially since they do not require helium cooling. The purpose of this project is to Identify biomarkers in Magnetoencephalography of normal brain development in healthy adults, premature and term newborns from "a priori" obtained by the classical technique of High Resolution EEG performed.

Aim 1. To examine the latency period according to antibiotic regimens (erythromycin iv for two days followed by orally for 5 days vs. azithromycin iv for 2 days followed by 5 days orally). Aim 2. To examine the latency period according to races stratified by antibiotic regimens. Aim 3: To examine if there is a difference in neonatal morbidity and mortality stratified by antibiotic regimen.

To evaluate the efficacy of less invasive surfactant administration（LISA ）technique in the treatment of neonatal respiratory distress syndrome（NRDS） by comparing with the traditional Intubate-Surfactant-Extubate（INSURE） technique.

Sleep is a key factor for normal brain development of the newborn. However, it is poorly studied and little is known about its characterization, especially in premature infants. Body movements during sleep are easy to evaluate but studies on their relationship to normal sleep states are scarce and limited. This project aims to characterize body movements during sleep, assessed by electroencephalography, in very premature infants. Then, a correlation between body movements, sleep organization and neurodevelopmental outcome will be evaluated at 3 years of age.

Prematurely born children are at higher risk of cognitive impairments and behavioral disorders than full-term children. There is growing evidence of significant volumetric and shape abnormalities in subcortical structures of premature neonates, which may be associated to negative long-term neurodevelopmental outcomes. The general objective is to look directly at the long-term neurodevelopmental implications of these neonatal subcortical structures abnormalities. Investigators propose to develop biomarkers of prematurity by comparing the morphological and diffusion properties of subcortical structures between preterm, with and without associated brain injuries, and full-term neonates using brain MRI. By combining subcortical morphological and diffusion properties, investigators hypothesize to be able to: (1) delineate specific correlative relationships between structures regionally and differentially affected by normal maturation and different patterns of white matter injury, and (2) improve the specificity of neuroimaging to predict neurodevelopmental outcomes earlier. The specific aims and general methodology are: 1) Build a new toolbox for neonatal subcortical structures analyses that combine a group lasso-based analysis of significant regions of shape changes, a structural correlation network analysis, a neonatal tractography, and tensor-based analysis on tracts; 2) Ascertain biomarkers of prematurity in neonates with different patterns of abnormalities using correlational and connectivity analysis within and between structures features; 3) Assess the predictive potential of subcortical imaging on neurodevelopmental outcomes by correlating neonatal imaging results with long-term neurodevelopmental scores at 9 and 18 months, and 6-8 years, follow-up. In each of these aims, investigators will use advanced neuroimaging analysis developed by their group and collaborator, including multivariate tensor-based morphometry and multivariate tract-based analysis. This application will provide the first complete subcortical network analysis in both term and preterm neonates. In the first study of its kind for prematurity, investigators will use sparse and multi-task learning to determine which of the biomarkers of prematurity at birth are the best predictors of long-term outcome. Once implemented, these methods will be available to compare subcortical structures for other pathologies in newborns and children.