Objective: As the predominant complication in preterm infants, Bronchopulmonary Dysplasia (BPD) necessitates accurate identification of infants at risk and expedited therapeutic interventions for an improved prognosis. This study evaluates the potential of Monosaccharide Composite (MC) enriched with environmental information from circulating glycans as a diagnostic biomarker for early-onset BPD, and, concurrently, appraises BPD risk in premature neonates.
Materials And Methods: The study incorporated 234 neonates of ≤32 weeks gestational age. Clinical data and serum samples, collected one week post-birth, were meticulously assessed. The quantification of serum-free monosaccharides and their degraded counterparts was accomplished via High-performance Liquid Chromatography (HPLC). Logistic regression analysis facilitated the construction of models for early BPD diagnosis. The diagnostic potential of various monosaccharides for BPD was determined using Receiver Operating Characteristic (ROC) curves, integrating clinical data for enhanced diagnostic precision, and evaluated by the Area Under the Curve (AUC).
Results: Among the 234 neonates deemed eligible, BPD development was noted in 68 (29.06%), with 70.59% mild (48/68) and 29.41% moderate-severe (20/68) cases. Multivariate analysis delineated several significant risk factors for BPD, including gestational age, birth weight, duration of both invasive mechanical and non-invasive ventilation, Patent Ductus Arteriosus (PDA), pregnancy-induced hypertension, and concentrations of two free monosaccharides (Glc-F and Man-F) and five degraded monosaccharides (Fuc-D, GalN-D, Glc-D, and Man-D). Notably, the concentrations of Glc-D and Fuc-D in the moderate-to-severe BPD group were significantly diminished relative to the mild BPD group. A potent predictive capability for BPD development was exhibited by the conjunction of gestational age and Fuc-D, with an AUC of 0.96.
Conclusion: A predictive model harnessing the power of gestational age and Fuc-D demonstrates promising efficacy in foretelling BPD development with high sensitivity (95.0%) and specificity (94.81%), potentially enabling timely intervention and improved neonatal outcomes.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10860215 | PMC |
http://dx.doi.org/10.1186/s12887-024-04556-x | DOI Listing |
Lancet Reg Health Eur
January 2025
Department of Neurology, St. Josef-Hospital - Katholisches Klinikum Bochum, Ruhr University Bochum, Gudrunstr. 56, 44791, Bochum, Germany.
Background: In recent decades, relapsing remitting multiple sclerosis (MS) became more treatable through new disease-modifying therapies (DMTs). Identifying safe treatments with minimal fetal risks for family planning is needed.
Methods: In this prospective cohort from the German MS and Pregnancy Registry (DMSKW), we analyzed pregnancy and neonatal outcomes in MS-patients using descriptive statistics and logistic/linear regression models to compare DMT-exposed pregnancies to DMT-unexposed pregnancies.
Heliyon
January 2025
Department of Endocrinology, Bangabandhu Sheikh Mujib Medical University, Shahbag, Dhaka, Bangladesh.
Background And Aims: Resistin is inflammatory adipocytokine released from adipose and other tissue. It is thought that it is related to insulin resistance and pathogenesis of gestational diabetes mellitus (GDM). This study was aimed to determine the level of serum resistin in mothers with GDM and normal glucose tolerance (NGT) in all trimesters to see whether it differs among different trimesters as well as between GDM and NGT.
View Article and Find Full Text PDFDiabetes Metab Res Rev
January 2025
Division of Research, Kaiser Permanente Northern California, Pleasanton, California, USA.
Aims: Gestational diabetes mellitus (GDM) poses a significant risk for developing type 2 diabetes mellitus (T2D) and exhibits heterogeneity. However, understanding the link between different types of post-GDM individuals without diabetes and their progression to T2D is crucial to advance personalised medicine approaches.
Materials And Methods: We employed a discovery-based unsupervised machine learning clustering method to generate clustering models for analysing metabolomics, clinical, and biochemical datasets.
Arch Public Health
January 2025
Department of Maternity and Neonatal Nursing, School of Nursing, College of Health Sciences, Comprehensive Specialized Hospital, Aksum University, Aksum, Tigray, Ethiopia.
Background: A preterm neonate is defined by the World Health Organization as a child delivered before 37 weeks of gestation. In low- and middle-income countries, including Ethiopia, preterm-related complications are serious health problems due to increases in the mortality and morbidity of newborns and children under 5 years of age. The aim of this study was to assess the time to neonatal mortality and its predictors among preterm neonates admitted to the neonatal intensive care unit in northern Ethiopia, 2023/2024.
View Article and Find Full Text PDFBMC Pediatr
January 2025
Faculty of Medicine, Department of Pediatrics, Division of Neonatology, Izmir Katip Celebi University, Izmir, Turkey.
Background: Overweight and obesity are global issues, especially among women of childbearing age, linked to adverse maternal and neonatal outcomes. These risks vary by age, race, and ethnicity, with increasing rates among immigrant and minority women. This study compares overweight and obesity rates, pregnancy weight gain, and neonatal outcomes in Turkish and Syrian immigrant/refugee women.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!