Estimating the probability of neonatal early-onset infection on the basis of maternal risk factors

Abstract

Objective: To develop a quantitative model to estimate the probability of neonatal early-onset bacterial infection on the basis of maternal intrapartum risk factors.

Methods: 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 <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.

Results: 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 >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).

Conclusions: 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.

Figures

FIGURE 1

Rate of sepsis according to gestational age. For Figs 1 through 3, a data set was created by including all 350 cases and bootstrapping the 1063 controls in the total (derivation plus validation) data set up to 607 664 simulated controls, for a total of 608 014 simulated births. Shown here are the empirical sepsis rates in the bootstrap data set broken down according to weeks of gestational age. The dotted line represents the overall sepsis frequency in the base population (0.58 per 1000). The red line represents a local regression (Lowess) smooth of the relationship of gestational age to sepsis rate. See the Supplemental Appendix for full details of the statistical methods.

FIGURE 2

Rate of sepsis according to highest maternal intrapartum temperature. Temperature was measured to the nearest 0.1°F, including values from 97°F to 104.2°F. Values above 102.5°F were infrequent. Empirical sepsis relative frequencies were computed in the bootstrapped data set. The dotted line represents the overall sepsis frequency in the base population. The red line represents a local regression (Lowess) smooth of the relationship of temperature to sepsis rate. See the Supplemental Appendix for full details of the statistical methods.

FIGURE 3

Rate of sepsis according to duration of ROM. ROM was measured to the nearest 0.1 hour and took on values from 0 to 226.4 (inclusive); ROM times of >50 hours were rare, and times between 30 and 50 hours were sparse. Empirical sepsis relative frequencies were computed in the bootstrapped data set. The dotted line represents the overall sepsis frequency in the base population. The red line represents a local regression (Lowess) smooth of the relationship of duration of ROM to sepsis rate. See the Supplemental Appendix for full details of the statistical methods.