A Quantitative, Risk-Based Approach to the Management of Neonatal Early-Onset Sepsis

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Abstract

Importance

Current algorithms for management of neonatal early-onset sepsis (EOS) result in medical intervention for large numbers of uninfected infants. We developed multivariable prediction models for estimating the risk of EOS among late preterm and term infants based on objective data available at birth and the newborn’s clinical status.

Objectives

To examine the effect of neonatal EOS risk prediction models on sepsis evaluations and antibiotic use and assess their safety in a large integrated health care system.

Design, Setting, and Participants

The study cohort includes 204 485 infants born at 35 weeks’ gestation or later at a Kaiser Permanente Northern California hospital from January 1, 2010, through December 31, 2015. The study compared 3 periods when EOS management was based on (1) national recommended guidelines (baseline period [January 1, 2010, through November 31, 2012]), (2) multivariable estimates of sepsis risk at birth (learning period [December 1, 2012, through June 30, 2014]), and (3) the multivariable risk estimate combined with the infant’s clinical condition in the first 24 hours after birth (EOS calculator period [July 1, 2014, through December 31, 2015]).

Main Outcomes and Measures

The primary outcome was antibiotic administration in the first 24 hours. Secondary outcomes included blood culture use, antibiotic administration between 24 and 72 hours, clinical outcomes, and readmissions for EOS.

Results

The study cohort included 204 485 infants born at 35 weeks’ gestation or later: 95 343 in the baseline period (mean [SD] age, 39.4 [1.3] weeks; 46 651 male [51.0%]; 37 007 white, non-Hispanic [38.8%]), 52 881 in the learning period (mean [SD] age, 39.3 [1.3] weeks; 27 067 male [51.2%]; 20 175 white, non-Hispanic [38.2%]), and 56 261 in the EOS calculator period (mean [SD] age, 39.4 [1.3] weeks; 28 575 male [50.8%]; 20 484 white, non-Hispanic [36.4%]). In a comparison of the baseline period with the EOS calculator period, blood culture use decreased from 14.5% to 4.9% (adjusted difference, −7.7%; 95% CI, −13.1% to −2.4%). Empirical antibiotic administration in the first 24 hours decreased from 5.0% to 2.6% (adjusted difference, −1.8; 95% CI, −2.4% to −1.3%). No increase in antibiotic use occurred between 24 and 72 hours after birth; use decreased from 0.5% to 0.4% (adjusted difference, 0.0%; 95% CI, −0.1% to 0.2%). The incidence of culture-confirmed EOS was similar during the 3 periods (0.03% in the baseline period, 0.03% in the learning period, and 0.02% in the EOS calculator period). Readmissions for EOS (within 7 days of birth) were rare in all periods (5.2 per 100 000 births in the baseline period, 1.9 per 100 000 births in the learning period, and 5.3 per 100 000 births in the EOS calculator period) and did not differ statistically (P = .70). Incidence of adverse clinical outcomes, including need for inotropes, mechanical ventilation, meningitis, and death, was unchanged after introduction of the EOS calculator.

Conclusions and Relevance

Clinical care algorithms based on individual infant estimates of EOS risk derived from a multivariable risk prediction model reduced the proportion of newborns undergoing laboratory testing and receiving empirical antibiotic treatment without apparent adverse effects.

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