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Objectives: To investigate the clinical characteristics of (UU) infection and colonization in extremely preterm infants and its impact on the incidence of bronchopulmonary dysplasia (BPD).
Methods: A retrospective analysis was conducted on 258 extremely preterm infants who were admitted to the Department of Neonatology, Shenzhen Maternity and Child Healthcare Hospital, from September 2018 to September 2022. According to the results of UU nucleic acid testing and the evaluation criteria for UU infection and colonization, the subjects were divided into three groups: UU-negative group (155 infants), UU infection group (70 infants), and UU colonization group (33 infants). The three groups were compared in terms of general information and primary and secondary clinical outcomes.
Results: Compared with the UU-negative group, the UU infection group had significant increases in the incidence rate of BPD, total oxygen supply time, and the length of hospital stay (<0.05), while there were no significant differences in the incidence rates of BPD and moderate/severe BPD between the UU colonization group and the UU-negative group (>0.05).
Conclusions: The impact of UU on the incidence of BPD in extremely preterm infants is associated with the pathogenic state of UU (i.e., infection or colonization), and there are significant increases in the incidence rate of BPD, total oxygen supply time, and the length of hospital stay in extremely preterm infants with UU infection. UU colonization is not associated with the incidence of BPD and moderate/severe BPD in extremely preterm infants.
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http://dx.doi.org/10.7499/j.issn.1008-8830.2403002 | DOI Listing |
J Perinatol
September 2025
University of Colorado School of Medicine, Department of Pediatrics, Aurora, CO, USA.
Objective: Determine whether acute kidney injury (AKI) is associated with subsequent late-onset infection (LOI) among extremely low gestational age newborns (ELGAN).
Study Design: Secondary analysis of participants in the Preterm Erythropoietin for Neuroprotection Trial. Infants surviving ≥7 days with sufficient serum creatinine data were included.
Neuroimage
September 2025
Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland; Advanced Magnetic Imaging Centre, Aalto University School of Science, Espoo, Finland. Electronic address:
Cognitive functions emerge from dynamic functional interplay of cortical and subcortical areas that form networks. Preterm birth poses a risk for the formation and functionality of brain networks which may lead to severe brain dysfunctions. Infants born extremely preterm have the highest risk of developing neurocognitive impairments.
View Article and Find Full Text PDFInt J Pediatr
August 2025
Department of Neonatology, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.
This study is aimed at evaluating the cumulative effect of postnatal risk factors on the survival of preterm neonates by examining key clinical parameters and complications across various gestational ages. A retrospective cohort study was conducted using data from 1109 neonates admitted to neonatal intensive care units at two tertiary regional hospitals in Kazakhstan between 2021 and 2024. Patients were classified into three groups based on gestational age: extremely preterm (< 28 weeks, = 223), very preterm (28-31 weeks, = 384), and moderate to late preterm (32-36 weeks, = 502).
View Article and Find Full Text PDFFront Public Health
September 2025
Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA, United States.
The frequency and severity of heat waves are expected to worsen with climate change. Exposure to extreme heat, or prolonged unusually high temperatures, are associated with increased morbidity and mortality. The fetus, infant, and young child are more sensitive to higher temperatures than older children and most adults given that they are rapidly developing.
View Article and Find Full Text PDFFront Physiol
August 2025
Department of Ultrasound, Deyang People's Hospital, Deyang, Sichuan, China.
Background: Antiphospholipid syndrome (APS) is a major immune-related disorder that leads to adverse pregnancy outcomes (APO), including recurrent miscarriage, placental abruption, preterm birth, and fetal growth restriction. Antiphospholipid antibodies (aPLs), particularly anticardiolipin antibodies (aCL), anti-β2-glycoprotein I antibodies (aβ2GP1), and lupus anticoagulant (LA), are considered key biomarkers for APS and are closely associated with adverse pregnancy outcomes. This is a prospective observational cohort study to use machine learning model to predict adverse pregnancy outcomes in APS patients using early pregnancy aPL levels and clinical features.
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