OBJECTIVE: To define a quantitative stratification algorithm for the risk of early-onset sepsis (EOS) in newborns ≥ 34 weeks' gestation.

METHODS: We conducted a retrospective nested case-control study that used split validation. Data collected on each infant included sepsis risk at birth based on objective maternal factors, demographics, specific clinical milestones, and vital signs during the first 24 hours after birth. Using a combination of recursive partitioning and logistic regression, we developed a risk classification scheme for EOS on the derivation dataset. This scheme was then applied to the validation dataset.

RESULTS: Using a base population of 608,014 live births ≥ 34 weeks' gestation at 14 hospitals between 1993 and 2007, we identified all 350 EOS cases <72 hours of age and frequency matched them by hospital and year of birth to 1063 controls. Using maternal and neonatal data, we defined a risk stratification scheme that divided the neonatal population into 3 groups: treat empirically (4.1% of all live births, 60.8% of all EOS cases, sepsis incidence of 8.4/1000 live births), observe and evaluate (11.1% of births, 23.4% of cases, 1.2/1000), and continued observation (84.8% of births, 15.7% of cases, incidence 0.11/1000).

CONCLUSIONS: It is possible to combine objective maternal data with evolving objective neonatal clinical findings to define more efficient strategies for the evaluation and treatment of EOS in term and late preterm infants. Judicious application of our scheme could result in decreased antibiotic treatment in 80,000 to 240,000 US newborns each year.

<p><strong>Importance: </strong>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.</p>

<p><strong>Objectives: </strong>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.</p>

<p><strong>Design, Setting, and Participants: </strong>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]).</p>

<p><strong>Main Outcomes and Measures: </strong>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.</p>

<p><strong>Results: </strong>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 (0.3% in the baseline period, 0.3% in the learning period, and 0.2% 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.</p>

<p><strong>Conclusions and Relevance: </strong>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.</p>

<p><strong>OBJECTIVE: </strong>To develop a quantitative model to estimate the probability of neonatal early-onset bacterial infection on the basis of maternal intrapartum risk factors.</p>

<p><strong>METHODS: </strong>This was a nested case-control study of infants born at ≥34 weeks' gestation at 14 California and Massachusetts hospitals from 1993 to 2007. Case-subjects had culture-confirmed bacterial infection at &lt;72 hours; controls were randomly selected, frequency-matched 3:1 according to year and birth hospital. We performed multivariate analyses and split validation to define a predictive model based only on information available in the immediate perinatal period.</p>

<p><strong>RESULTS: </strong>We identified 350 case-subjects from a cohort of 608,014 live births. Highest intrapartum maternal temperature revealed a linear relationship with risk of infection below 100.5°F, above which the risk rose rapidly. Duration of rupture of membranes revealed a steadily increasing relationship with infection risk. Increased risk was associated with both late-preterm and postterm delivery. Risk associated with maternal group B Streptococcus colonization is diminished in the era of group B Streptococcus prophylaxis. Any form of intrapartum antibiotic given &gt;4 hours before delivery was associated with decreased risk. Our model showed good discrimination and calibration (c statistic = 0.800 and Hosmer-Lemeshow P = .142 in the entire data set).</p>

<p><strong>CONCLUSIONS: </strong>A predictive model based on information available in the immediate perinatal period performs better than algorithms based on risk-factor threshold values. This model establishes a prior probability for newborn sepsis, which could be combined with neonatal physical examination and laboratory values to establish a posterior probability to guide treatment decisions.</p>

<p><strong>BACKGROUND: </strong>The absolute neutrophil count and the immature/total neutrophil ratio (I/T) provide information about the risk of early onset sepsis in newborns. However, it is not clear how to combine their potentially overlapping information into a single likelihood ratio.</p>

<p><strong>METHODS: </strong>We obtained electronic records of blood cultures and of complete blood counts with manual differentials drawn &lt;1 hour apart on 66,846 infants ≥ 34 weeks gestation and &lt;72 hours of age born at Kaiser Permanente Northern California and Brigham and Women's Hospitals. We hypothesized that dividing the immature neutrophil count (I) by the total neutrophil count (T) squared (I/T) would provide a useful summary of the risk of infection. We evaluated the ability of the I/T to discriminate newborns with pathogenic bacteremia from other newborns tested using the area under the receiver operating characteristic curve (c).</p>

<p><strong>RESULTS: </strong>Discrimination of the I/T (c = 0.79; 95% confidence interval: 0.76-0.82) was similar to that of logistic models with indicator variables for each of 24 combinations of the absolute neutrophil count and the proportion of immature neutrophils (c = 0.80, 95% confidence interval: 0.77-0.83). Discrimination of the I/T improved with age, from 0.70 at &lt;1 hour to 0.87 at ≥ 4 hours. However, 60% of I/T had likelihood ratios of 0.44-1.3, thus only minimally altering the pretest odds of disease.</p>

<p><strong>CONCLUSIONS: </strong>Calculating the I/T could enhance prediction of early onset sepsis, but the complete blood counts will remain helpful mainly when done at &gt;4 hours of age and when the pretest probability of infection is close to the treatment threshold.</p>

<p><strong>BACKGROUND: </strong>A complete blood count (CBC) with white blood cell differential is commonly ordered to evaluate newborns at risk for sepsis.</p>

<p><strong>OBJECTIVES: </strong>To quantify how well components of the CBC predict sepsis in the first 72 hours after birth.</p>

<p><strong>METHODS: </strong>For this retrospective cross-sectional study we identified 67 623 term and late-preterm (≥ 34 weeks gestation) newborns from 12 northern California Kaiser hospitals and 1 Boston, Massachusetts hospital who had a CBC and blood culture within 1 hour of each other at &lt;72 hours of age. We compared CBC results among newborns whose blood cultures were and were not positive and quantified discrimination by using receiver operating characteristic curves and likelihood ratios.</p>

<p><strong>RESULTS: </strong>Blood cultures of 245 infants (3.6 of 1000 tested newborns) were positive. Mean white blood cell (WBC) counts and mean absolute neutrophil counts (ANCs) were lower, and mean proportions of immature neutrophils were higher in newborns with infection; platelet counts did not differ. Discrimination improved with age in the first few hours, especially for WBC counts and ANCs (eg, the area under the receiver operating characteristic curve for WBC counts was 0.52 at &lt;1 hour and 0.87 at ≥ 4 hours). Both WBC counts and ANCs were most informative when very low (eg, the likelihood ratio for ANC &lt; 1000 was 115 at ≥ 4 hours). No test was very sensitive; the lowest likelihood ratio (for WBC count ≥ 20 000 at ≥ 4 hours) was 0.16.</p>

<p><strong>CONCLUSION: </strong>Optimal interpretation of the CBC requires using interval likelihood ratios for the newborn's age in hours.</p>