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AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios.
BMC Pregnancy Childbirth
January 2025
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of Utah Health, 30 N. Mario Capecchi Dr., Level 5 South, Salt Lake City, UT, 84132, USA.
Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.
Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
study protocol for a pilot trial of a novel parenting and mental health prevention intervention for migrant mothers with young children at the Mexico-US border.
BMJ Open
January 2025
El Colegio de la Frontera Norte, Tijuana, Mexico.
Introduction: Migrant women in transit face high risk of developing mental health problems such as depression and anxiety, driven by gendered social-structural factors including violence, social isolation, migration uncertainty, limited access to services and gender inequities. Although migrant women who endure such conditions have high need for mental health prevention, few evidence-based interventions are tailored to this population. Moreover, while women and children's mental health are interconnected, few mental health interventions address parenting needs.
View Article and Find Full Text PDFEpidemiological analysis of reported acute glyphosate poisoning in Malaysia: identifying risk factors and high-risk groups (2006-2023).
BMJ Open
January 2025
National Poison Centre, Universiti Sains Malaysia, Georgetown, Penang, Malaysia
Objective: Glyphosate is widely used in Malaysian agriculture but poses a significant under-reported public health concern due to poisoning. This paper aims to study the epidemiology of glyphosate poisoning in Malaysia, assessing severity, identifying risk factors, and high-risk groups.
Setting: All glyphosate-related data of the Malaysia National Poison Centre from 2006 to 2023.
Objective: To assess the effectiveness of an mHealth neonatal intensive care unit (NICU) parent support smartphone application to improve psychosocial well-being, specifically reduced stress and anxiety, increased parenting competence, and improved social support among a diverse group of parents with infants born preterm in three Chicago-area NICUs.
Study Design: A time-lapsed, quasi-experimental design in which control participants were enrolled and then intervention participants enrolled. Data collection occurred at three timepoints: NICU admission (AD), discharge (DC), and 30 days post-discharge (DC+30).
Preterm Neonates Exhibit a "Catch-Up" Pattern in Motor Development During the Neonatal Period: A Diffusion Tensor Imaging Study.
Pediatr Neurol
January 2025
Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China; Shaanxi Engineering Research Center of Computational Imaging and Medical Intelligence, Xi'an, China. Electronic address:
Background: Preterm infants are at high risk for subsequent neurodevelopmental disability. Early developmental characterization of brain and neurobehavioral function is critical for identifying high-risk infants. This study aimed to elucidate the early evolution of sensorimotor function in preterm neonates by exploring postnatal age-related changes in the brain white matter (WM) and neurobehavioral abilities.
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