Potential Impact of Umbilical-Cord-Blood Procalcitonin-Based Algorithm on Antibiotics Exposure in Neonates With Suspected Early-Onset Sepsis.
Ontology highlight
ABSTRACT: 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.
SUBMITTER: Huetz N
PROVIDER: S-EPMC7181674 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
ACCESS DATA