Title

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

Year of Publication

2013

Number of Pages

161-6

Date Published

2013 Apr

ISSN Number

1531-698X

Abstract

<p><strong>PURPOSE OF REVIEW: </strong>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.</p>

<p><strong>RECENT FINDINGS: </strong>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.</p>

<p><strong>SUMMARY: </strong>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.</p>

DOI

10.1097/MOP.0b013e32835e1f96

Alternate Title

Curr. Opin. Pediatr.

PMID

23407183

WATCH THIS PAGE

Subscription is not available for this page.