Early-onset sepsis: a predictive model based on maternal risk factors.

TitleEarly-onset sepsis: a predictive model based on maternal risk factors.
Publication TypeJournal Article
Year of Publication2013
AuthorsPuopolo KM, Escobar GJ
JournalCurr Opin Pediatr
Volume25
Issue2
Pagination161-6
Date Published2013 Apr
ISSN1531-698X
KeywordsAge of Onset, Algorithms, Anti-Bacterial Agents, Decision Support Techniques, Female, Humans, Infant, Newborn, Infectious Disease Transmission, Vertical, Pregnancy, Pregnancy Complications, Infectious, Risk Assessment, Risk Factors, Sepsis
Abstract

PURPOSE OF REVIEW: Neonatal early-onset sepsis (EOS) is a very low-incidence, but potentially fatal condition among term and late preterm newborns. EOS algorithms based on risk-factor threshold values result in evaluation and empiric antibiotic treatment of large numbers of uninfected newborns, leading to unnecessary antibiotic exposures and maternal/infant separation. Ideally, risk stratification should be quantitative, employ information conserving strategies, and be readily transferable to modern comprehensive electronic medical records.

RECENT FINDINGS: We performed a case-control study of infants born at or above 34 weeks' gestation with blood culture-proven EOS. We defined the relationship of established predictors to the risk of EOS, then used multivariate analyses and split validation to develop a predictive model using objective data. The model provides an estimation of sepsis risk that can identify the same proportion of EOS cases by evaluating fewer infants, as compared with algorithms based on subjective diagnoses and cut-off values for continuous predictors.

SUMMARY: An alternative approach to EOS risk assessment based only on objective data could decrease the number of infants evaluated and empirically treated for EOS, compared with currently recommended algorithms. Prospective evaluation is needed to determine the accuracy and safety of using the sepsis risk model to guide clinical decision-making.

DOI10.1097/MOP.0b013e32835e1f96
Alternate JournalCurr. Opin. Pediatr.
PubMed ID23407183
Grant ListR01-GM-80180-3 / GM / NIGMS NIH HHS / United States