Objectives: A recent discussion surrounding the extension of antenatal corticosteroid (ACS) use beyond 34 weeks of gestation did not include the subgroup of infants of diabetic mothers (IDM). We aimed to examine the association between ACS exposure and outcomes in neonates born at term and at near-term gestation in a large cohort of IDMs. Methods: We selected 13976 eligible near-term and term infants who were included in the PEARL-Peristat Perinatal Registry Study (PPS). We assessed the association of ACS exposure with neonatal outcomes in a multivariate regression model that controlled for diabetes mellitus (DM) and other perinatal variables. Results: The incidence of DM was 28% (3,895 of 13,976) in the cohort. Caesarean section was performed in one-third of the study population. The incidence of ACS exposure was low (1.8%) and typically occurred>2 weeks before delivery. The incidence rates of respiratory distress syndrome (RDS)/ transient tachypnoea of newborns (TTN), all-cause neonatal intensive care unit (NICU) admissions, NICU admissions for hypoglycaemia, and low 5-min Apgar scores were 3.5, 8.8, 1.3, and 0.1%, respectively. In a multivariate regression model, ACS was associated with a slight increase in NICU admissions (OR: 1.44; 95% CI: 1.04–2.03; p=0.028), but not with RDS/TTN. Conclusions: Although the low exposure rate was a limitation, ACS administration did not reduce respiratory morbidity in near-term or term IDMs. It was independently associated with an increase in NICU admissions. Randomized controlled trials are required to assess the efficacy and safety of ACS administration in diabetic mothers at late gestation.

Multi-omics approaches, which integrate genomics, transcriptomics, proteomics, and metabolomics, have emerged as powerful tools in the diagnosis of rare diseases. We used untargeted metabolomics and whole-genome sequencing (WGS) to gain a more comprehensive understanding of a rare disease with a complex presentation affecting female twins from a consanguineous family. The sisters presented with polymicrogyria, a Dandy–Walker malformation, respiratory distress, and multiorgan dysfunctions. Through WGS, we identified two rare homozygous variants in both subjects, a pathogenic variant in ADGRG1(p.Arg565Trp) and a novel variant in CNTNAP1(p.Glu910Val). These genes have been previously associated with autosomal recessive polymicrogyria and hypomyelinating neuropathy with/without contractures, respectively. The twins exhibited symptoms that overlapped with both of these conditions. The results of the untargeted metabolomics analysis revealed significant metabolic perturbations relating to neurodevelopmental abnormalities, kidney dysfunction, and microbiome. The significant metabolites belong to essential pathways such as lipids and amino acid metabolism. The identification of variants in two genes, combined with the support of metabolic perturbation, demonstrates the rarity and complexity of this phenotype and provides valuable insights into its underlying mechanisms.

Background: Preterm deliveries have many negative health implications on both mother and child. Identifying the population level factors that increase the risk of preterm deliveries is an important step in the direction of mitigating the impact and reducing the frequency of occurrence of preterm deliveries. The purpose of this work is to identify preterm delivery risk factors and their progression throughout the pregnancy from a large collection of Electronic Health Records (EHR).Results: The study cohort includes about 60,000 deliveries in the USA with the complete medical history from EHR for diagnoses, medications and procedures. We propose a temporal analysis of risk factors by estimating and comparing risk ratios and variable importance at different time points prior to the delivery event. We selected the following time points before delivery: 0, 12 and 24 week(s) of gestation. We did so by conducting a retrospective cohort study of patient history for a selected set of mothers who delivered preterm and a control group of mothers that delivered full-term. We analyzed the extracted data using logistic regression and random forests models. The results of our analyses showed that the highest risk ratio and variable importance corresponds to history of previous preterm delivery. Other risk factors were identified, some of which are consistent with those that are reported in the literature, others need further investigation.Conclusions: The comparative analysis of the risk factors at different time points showed that risk factors in the early pregnancy related to patient history and chronic condition, while the risk factors in late pregnancy are specific to the current pregnancy. Our analysis unifies several previously reported studies on preterm risk factors. It also gives important insights on the changes of risk factors in the course of pregnancy. The code used for data analysis will be made available on github.

Climate change is the single greatest existential threat to children worldwide, adversely affecting the health and well-being of children and young people. The Royal College of Paediatrics and Child Health members living outside the UK (respondents) were invited to an online anonymised survey where opting-in participants answered 32 questions covering 6 domains. 139 respondents from 50 countries responded to the survey. Respondents agreed that climate change influences the rising rates of children with heat-related (50%), infectious (64%) and mental health (36%). The climate crisis is a global emergency, and working together is paramount to safeguarding the planet for future generations.