Context: The incidence of early-onset neonatal infection has greatly decreased, but a new diagnostic approach is needed to avoid overdiagnosis and overtreatment. The aim of this study was to assess the potential impact of an algorithm incorporating umbilical-cord-blood procalcitonin (PCT) level on neonatal antibiotics prescription rate as compared with current practice. Material and methods: We conducted a prospective study in three maternity wards in France. All term and preterm neonates with the usual risk factors for neonatal group B Streptococcus infection were eligible for umbilical-cord-blood PCT testing. We compared the proportion of neonates who were exposed early to antibiotics (before 6 days of life) to that of neonates for whom antibiotics prescription would be indicated according to the PCT-based algorithm. Results: Among the 3,080 neonates included, 1 neonate presented with certain infection and 38 neonates with probable infection. The global antibiotics prescription rate was 4.6% [95% confidence interval (CI), 4.1-5]. With the PCT-based algorithm, the potential decrease in prescription rate would be 1.8% (95% CI, 1.3-2.3), corresponding to a 39% (95% CI, 37.3-40.7) relative reduction in antibiotics exposure (p < 0.05). Conclusion: These results suggest that the umbilical-cord-blood PCT-based algorithm could significantly help the clinicians in their antibiotic prescription decision to decrease neonatal antibiotics exposure as compared with current practice. If validated in a larger interventional randomized study, this approach could help clinicians stratify the risk of early-onset neonatal infection and initiate early antibiotics treatment in newborns at high risk of infection while limiting the deleterious effects of useless prescriptions in non-infected newborns.

Intrauterine Growth Restriction (IUGR) affects 8% of newborns and increases morbidity and mortality for the offspring even during later stages of life. Single omics studies have evidenced epigenetic, genetic, and metabolic alterations in IUGR, but pathogenic mechanisms as a whole are not being fully understood. An in-depth strategy combining methylomics and transcriptomics analyses was performed on 36 placenta samples in a case-control study. Data-mining algorithms were used to combine the analysis of more than 1,200 genes found to be significantly expressed and/or methylated. We used an automated text-mining approach, using the bulk textual gene annotations of the discriminant genes. Machine learning models were then used to explore the phenotypic subgroups (premature birth, birth weight, and head circumference) associated with IUGR. Gene annotation clustering highlighted the alteration of cell signaling and proliferation, cytoskeleton and cellular structures, oxidative stress, protein turnover, muscle development, energy, and lipid metabolism with insulin resistance. Machine learning models showed a high capacity for predicting the sub-phenotypes associated with IUGR, allowing a better description of the IUGR pathophysiology as well as key genes involved.

Background: There are concerns about the efficacy of antenatal corticosteroid treatment (ACT) in the growth-restricted fetus. Objective: To evaluate the effect of ACT on neurodevelopmental outcome at 2 years of corrected age according to the z score of birth head circumference (ZS HC) in a large prospective cohort of preterm infants. Methods: This study was conducted as a population-based, prospective, multicenter study, including 4,965 infants born between 24 and 33 weeks' gestation and whose status regarding ACT and the measurement of head circumference at birth were available. They were evaluated at 2 years of corrected age to assess neurological outcome. Three approaches were considered to estimate the effect of ACT on neurodevelopment: (i) logistic regression with adjustment on propensity score, (ii) weighted logistic regression using the inverse probability of treatment weighting method, and (iii) 1:1 matching of gestational age, ZS HC, and propensity score between treated and nontreated infants. Results: ACT was documented in 60% of infants. Three groups of infants were considered according to their ZS HC: between -3 and -1 standard deviation (SD), -1 and +1 SD, and +1 and +3 SD, respectively. ACT was associated with a significant improvement of neurodevelopmental outcome only for infants with an ZS HC of between +1 and +3 SD (adjusted OR 1.72; 95% CI 1.06-2.79). Moreover, ORs estimated in the -3 to -1 and +1 to +3 categories were significantly different. Conclusion: We found beneficial effects of ACT on neurodevelopmental outcomes at 2 years of corrected age only in preterm infants with a ZS HC >1 SD.