Copyright 2017 American Medical Association. All rights reserved.
A Quantitative, Risk-Based Approach to the Management
of Neonatal Early-Onset Sepsis
Michael W. Kuzniewicz, MD, MPH; Karen M. Puopolo, MD, PhD; Allen Fischer, MD; Eileen M. Walsh, RN, MPH;
Sherian Li, MS; Thomas B. Newman, MD, MPH; Patricia Kipnis, PhD; Gabriel J. Escobar, MD
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.
JAMA Pediatr. 2017;171(4):365-371. doi:10.1001/jamapediatrics.2016.4678
Published online February 20, 2017.
Supplemental content
Author Affiliations: Perinatal
Research Unit, Division of Research,
Kaiser Permanente Northern
California, Oakland (Kuzniewicz,
Walsh, Li, Escobar); Department of
Pediatrics, University of California,
San Francisco (Kuzniewicz,
Newman); The Permanente Medical
Group, Oakland, California
(Kuzniewicz, Fischer, Escobar);
Newborn Care at Pennsylvania
Hospital, The Children’s Hospital of
Philadelphia, Philadelphia,
Pennsylvania (Puopolo); Perelman
School of Medicine, University of
Pennsylvania, Philadelphia (Puopolo);
Systems Research Initiative, Division
of Research, Kaiser Permanente
Northern California, Oakland (Kipnis,
Escobar).
Corresponding Author: Michael W.
Kuzniewicz, MD, MPH, Perinatal
Research Unit, Division of Research,
Kaiser Permanente Northern
California, 2000 Broadway Ave,
Oakland, CA 94612 (michael.w
.kuzniewicz@kp.org).
Research
JAMA Pediatrics | Original Investigation
(Reprinted) 365
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N
eonatal early-onset sepsis (EOS) is defined as inva-
sive bacterial infection of the blood and/or cerebro-
spinal fluid (CSF) that occurs in the first week after
birth. The pathogenesis is primarily ascending colonization of
the maternal genital tract and uterine compartment with nor-
mal maternal gastrointestinal and genitourinary tract bacte-
rial flora, resulting in subsequent colonization and infection
of the fetus or newborn. Often EOS presents with nonspecific
signs (eg, tachypnea) that are also associated with normal tran-
sition to extrauterine life. In addition, EOS may result in se-
vere systemic illness and even death in 3% to 4% of infected
infants.
1,2
The Centers for Disease Control and Prevention (CDC),
3
the
American Congress of Obstetricians and Gynecologists,
4,5
and
the American Academy of Pediatrics
6
provide guidelines for
the prevention of neonatal group B Streptococcus (GBS), in-
cluding recommendations for intrapartum antibiotic prophy-
laxis and algorithms for evaluation and treatment of at-risk in-
fants. These guidelines are based on epidemiologic data
obtained before the widespread obstetric use of intrapartum
antibiotic prophylaxis (when EOS incidence was 5- to 10-fold
higher than currently observed).
7-11
These guidelines result in
a large percentage (15%-20%) of term and late preterm in-
fants being evaluated for sepsis, with 5% to 8% receiving em-
pirical antibiotics.
12,13
Persistent high rates of evaluation and
treatment contrast with the decreasing incidence of EOS
(0.3-0.8 cases per 1000 births).
12-14
Using a Bayesian approach and a base population of 608 014
newborns, we developed 2 linked prediction models for EOS.
The first model establishes a newborn’s prior probability of EOS
based on gestational age, highest maternal antepartum tem-
perature, GBS carriage status, duration of rupture of mem-
branes, and the nature and timing of intrapartum antibiotic
administration.
15
The second model quantifies how the base-
line risk is modified by the infant’s clinical examination.
16
We instantiated these models with an online calculator
(kp.org\eoscalc).
13
The key elements of the calculator are sum-
marized in eFigure 1 in the Supplement. We made this calcu-
lator available to physicians at Kaiser Permanente Northern Cali-
fornia (KPNC), an integrated health care system in Oakland,
California, and instructed clinicians on its use. In this report,
we describe the effect of this calculator on the rate of blood cul-
tures in neonates, antibiotic use, and adverse outcomes.
Methods
Study Population and Setting
The study cohort included 204 485 infants born at 35 weeks’
gestation or later at a KPNC hospital from January 1, 2010,
through December 31, 2015. Although we developed predic-
tion models using populations that included infants born at
34 weeks’ gestation, we excluded those infants because they
are routinely admitted to the neonatal intensive care unit and
experience a higher level of monitoring. At the KPNC, all in-
patient and outpatient care is tracked through a common medi-
cal record number. If care outside the KPNC was required for
extracorporeal membrane oxygenation (ECMO), we captured
data on repatriation to the KPNC or death. Births occur at 14
hospitals. Infants born at a KPNC hospital are covered under
the mother's insurance for a minimum of 30 days, regardless
of the infant’s insurance status. The KPNC Institutional Re-
view Board approved this study and waived informed con-
sent because this was a data-only study.
Intervention and Study Periods
The baseline period was defined as January 1, 2010, through
November31, 2012, when clinical care was informed by the CDC
GBS guidelines.
3-5
During the learning period (December 1,
2012, through June 30, 2014), the EOS calculator based only
on maternal data was made available for clinical use, but no
guidance was given with respect to incorporation of the new-
born clinical presentation or intervention thresholds, permit-
ting staff to familiarize themselves with the calculator and
probability of EOS at birth. In the EOS calculator period (July
1, 2014, through December 31, 2015), the newborn’s clinical pre-
sentation (well, equivocal, and clinically ill) was incorpo-
rated into the risk prediction, and recommendations based on
the probability of EOS were included in the calculator output.
The categories of clinical presentation are defined at http://kp
.org/eoscalc and in eFigure 1 in the Supplement. Blood cul-
tures were recommended if the EOS risk was 1 or more per 1000
live births and empirical antibiotics if the EOS risk was 3 or more
per 1000 live births.
13
Outcomes
Our primary outcome was antibiotic administration in the first
24 hours. Secondary outcomes included blood culture use in
the first 24 hours, antibiotic administration between 24 and
72 hours, and number of days of antibiotic use (antibiotic days)
per 100 live births. We obtained data on antibiotics from the
electronic medication administration record and ascertained
blood and CSF cultures from the KPNC laboratory database.
Antibiotic days were tabulated as the number of calendar days
the infant received at least 1 dose of intravenous antibiotics.
To evaluate safety, we assessed readmissions for EOS and clini-
cal outcomes in our EOS cases. We defined EOS as blood or CSF
culture–confirmed infection with a pathogenic bacterial spe-
cies that occurred from birth through 7 days of age. We re-
viewed the medical records of all EOS cases to determine the
Key Points
Question Can the use of a predictive model to estimate risk of
early-onset sepsis safely decrease the proportion of newborns
evaluated by blood culture and empirically treated with
antibiotics?
Findings We compared evaluations by blood culture, antibiotic
administration, and readmissions for early-onset sepsis before and
after clinical implementation of a predictive model for early-onset
sepsis. Evaluations by blood culture and empirical antibiotic
administration decreased significantly without any significant
increase in the rate of readmissions for early-onset sepsis.
Meaning Clinical care based on a predictive model reduces the
proportion of newborns evaluated and empirically treated for
early-onset sepsis without apparent adverse effects.
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infant’s clinical presentation, severity of illness, and out-
comes until hospital discharge. We assessed severity of ill-
ness in terms of need for mechanical ventilation or inotrope
medications, the presence of meningitis defined by CSF cul-
ture and/or cell count, or death due to sepsis.
Statistical Analysis
We compared infant and maternal characteristics across the
periods using the χ
2
, Fisher exact, and analysis of variance tests,
as appropriate. We displayed monthly rates of testing and treat-
ment using statistical process control charts. The baseline pe-
riod was used to calculate the control limits, ±3 SDs of the mean.
We estimated the effect of the intervention using an inter-
rupted time series design
17,18
with segmented regression mod-
els controlling for preintervention levels, trends, and other con-
founders (ie, other events that occurred around the same time
as the intervention and that potentially influenced the out-
come). We measured time in months (from 1 to 72). Seg-
mented regression models fit a least squares regression line to
separate segments of time when certain events took place and
assume a linear association between time and the outcome in
each segment.
19
This method is an appropriate means of analy-
sis for this study because we have a clear differentiation of the
baseline, learning, and intervention periods; we have short-
term outcomes that were expected to change relatively quickly
after an intervention is implemented; and sequential mea-
sures of the outcomes are available before and after the inter-
vention. For each outcome, we tested for a possible change in
the intercept and slope in the learning period and EOS calcu-
lator period while controlling for confounding covariates. The
models we fit are described in eFigure 2 in the Supplement.
We explored the effects on time-varying confounders, such as
seasonality and population characteristics, including monthly
percentage of male infants, cesarean delivery, rupture of mem-
branes time of 18 hours or longer, preterm infants, intrapar-
tum antibiotics, GBS positivity, small for gestational age in-
fants, and African American infants. We retained covariates
in the final model if they were significant at a 2-sided P < .05.
Finally, we assessed for autocorrelation in each of the time
series by examining the plot of residuals and the partial
autocorrelation function. We used autoregressive integrated
moving average models to adjust for autocorrelation when it
was present.
20
We compared readmissions for culture-
positive sepsis or meningitis, differences in EOS organism,
symptoms, and infant outcomes by using the χ
2
or Fisher
exact test, as appropriate.
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%]). Characteristics of the infants
born in these 3 periods were similar (Table 1), with small but
statistically significant demographic differences among the pe-
riods. The incidence of culture-confirmed EOS was not statis-
tically different across periods.
Figure 1 and Figure 2 show the monthly rates of infants
undergoing a sepsis evaluation with a blood culture and re-
Table 1. Infant and Maternal Characteristics by Study Period
a
Characteristic
Study Period
P Value
b
Baseline
(n = 95 543)
Learning Period
(n = 52 881)
EOS Calculator
(n = 56 261)
Birth weight, mean (SD), g 3394 (498) 3393 (496) 3385 (497) .006
Gestational age, mean (SD), wk 39.4 (1.3) 39.3 (1.3) 39.4 (1.3) <.001
Male 46 651 (51.0) 27 067 (51.2) 28 575 (50.8) .40
SGA infants (<10th percentile) 4773 (5.0) 2539 (4.8) 3065 (5.5) <.001
GA<38 wk 1280 (13.4) 7393 (14.0) 7523 (13.4) .004
Race/ethnicity
White, non-Hispanic 37 007 (38.8) 20 175 (38.2) 20 494 (36.4) <.001
Asian 21 320 (22.4) 12 140 (23.0) 12 907 (23.0)
African American 6893 (7.2) 3405 (6.4) 3701 (6.6)
Hispanic 21 928 (23.0) 11 112 (21.0) 12 244 (21.8)
Other or unknown 8195 (8.6) 6049 (11.4) 6915 (12.3)
Cesarean delivery 24 835 (26.1) 13 872 (26.2) 14 504 (25.8) .20
GBS status
Positive 21 475 (22.5) 12 369 (23.4) 12 363 (22.0) <.001
Unknown 6015 (6.3) 2018 (3.8) 2276 (4.1)
Maternal temperature ≥38°C 4282 (4.5) 2325 (4.4) 2442 (4.3) .40
ROM≥18 h 15 048 (15.8) 8666 (16.4) 9609 (17.1) <.001
Maternal antibiotic use 20 695 (21.7) 11 690 (22.1) 12 147 (21.6) .09
EOS 24 (0.03) 15 (0.03) 12 (0.02) .80
Abbreviations: EOS, early-onset
sepsis; GA, gestational age;
GBS, group B Streptococcus;
ROM, rupture of membranes;
SGA, small for gestational age.
a
Data are presented as number
(percentage) of infants unless
otherwise indicated.
b
Analysis of variance or χ
2
test.
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ceiving intravenous antibiotics in the first 24 hours after birth.
In a comparison of the baseline period and the EOS calculator
period, blood culture use decreased from 14.5% to 4.9%; the
adjusted difference (change in level from the interrupted time
series analysis) was −7.7% (95% CI, −13.1% to −2.4%) (Table 2).
Empirical antibiotic administration in the first 24 hours de-
creased from 5.0% to 2.6% (adjusted difference, −1.8%; 95%
CI, −2.4% to −1.3%). There was no evidence of an increase in
antibiotic use between 24 and 72 hours after birth because use
decreased from 0.5% to 0.4% (adjusted difference, 0.05%; 95%
CI, −0.12% to 0.22%). Antibiotic days per 100 births also de-
creased from 16.0 to 8.5 days (adjusted difference, −3.3 days;
95% CI, −6.1 to −0.5 days). The learning period was not statis-
tically different from the baseline period in the segmented re-
gression models. The time trend (slope) during the EOS pe-
riod and learning period did not significantly differ from the
baseline period in any of the final models.
We addressed 2 potential adverse effects of decreasing rates
of newborn sepsis evaluation and empirical antibiotics: de-
layed treatment of infants with EOS presenting with more se-
vere clinical illness and increases in hospital readmissions for
EOS after hospital discharge. We reviewed all cases of EOS dur-
ing the study. No statistically significant differences existed
among the study periods in the proportion of cases caused by
GBS and Escherichia coli, the timing of case identification, or
the presence of symptoms (Table 3).
Sepsis-associated severity of illness, as assessed by use of
mechanical ventilation, inotrope medications, meningitis, or
death, did not differ among the study periods. The infant who
died during the learning period had pulmonary hypertension
and respiratory failure and underwent immediate treatment
with antibiotics, mechanical ventilation, and ECMO. The in-
fant who died during the EOS calculator period was born with
severe hypoxic-ischemic encephalopathy and underwent im-
mediate treatment with antibiotics, mechanical ventilation,
inotropic agents, therapeutic hypothermia, and ECMO.
Of the 12 infants with EOS born during the EOS calculator
period, 6 were symptomatic at birth and empirically treated
with antibiotics. Five infants were well-appearing at birth; each
developed symptoms during the birth hospitalization that
prompted evaluation and antibiotic therapy. Only 1 infant
would have met the criteria for sepsis evaluation under the CDC
guidelines. The infant was born to a mother who was GBS posi-
tive with fever (temperature to 38.0°C) who did not receive an-
tibiotics. The infant was well at birth with an EOS risk of 0.15
per 1000 births but developed tachypnea, prompting a blood
culture at approximately 36 hours of life. The infant’s respi-
ratory rate normalized, and the infant was discharged home.
The blood culture eventually yielded E coli, prompting read-
mission. Blood and CSF culture samples obtained before an-
tibiotic therapy were sterile. One infant never developed symp-
toms but would have been empirically administered antibiotics
under the CDC guidelines. The infant was born to a GBS-
positive mother with fever (temperature to 39.1°C) who re-
ceived antibiotics after delivery. This infant had an estimated
EOS risk of 2.3 per 1000 births, and per the calculator recom-
mendations, a blood sample was obtained for culture at birth.
Antibiotic treatment was started when the culture yielded GBS.
Figure 2. Monthly Antibiotic Treatment Rate
0
7
6
5
2
3
4
1
2010 2011 2013 2014 2015
2016
Live Births, %
Year
2012
Upper control limit
Lower control limit
Mean
Baseline period Learning period EOS calculator
Monthly percentage of infants born at 35 weeks’ gestation or later receiving
intravenous antibiotic therapy in the first 24 hours of life. EOS indicates
early-onset sepsis.
Table 2. Comparison of Sepsis Evaluation and Antibiotic Use in the Baseline and EOS Calculator Periods
a
Variable
Study Period Absolute Difference, % (95% CI)
Baseline
(n = 95 543)
EOS Calculator
(n = 56 261) Unadjusted Adjusted
Blood culture in first 24 h 13 797 (14.5) 2741 (4.9) −9.6 (−9.3 to −9.9) −7.7 (−13.1 to −2.4)
Antibiotic use in first 24 h 4741 (5.0) 1482 (2.6) −2.3 (−2.1 to −2.5) −1.8 (−2.4 to −1.3)
Antibiotic use at >24 to 72 h 485 (0.5) 216 (0.4) −0.1 (−0.05 to 0.2) 0.05 (−0.1 to 0.2)
Antibiotic use days per 100 infants 16.0 8.5 −7.6 (−6.7 to −8.5) −3.3 (−6.1 to −0.5)
Abbreviations: EOS, early-onset
sepsis; GBS, group B Streptococcus.
a
Data are presented as number
(percentage) of infants and absolute
difference (95% CI) except for
antibiotic days per 100 infants,
which is days of antibiotic use.
Figure 1. Monthly Early-Onset Sepsis (EOS) Evaluation Rate
2010 2011 2013 2014 2015
2016
Live Births, %
Year
0
20
15
10
5
2012
Upper control limit
Lower control limit
Mean
Baseline period
Learning period EOS calculator
Monthly percentage of infants born at 35 weeks’ gestation or later
undergoing EOS evaluation with a blood culture performed in the first 24 hours
of life.
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Additional blood and CSF culture samples obtained before an-
tibiotic treatmentwere sterile. Giventhe lack of significant symp-
toms and clearingofbloodcultures beforeantibiotic therapy, both
cases may have represented transient bacteremia rather than true
sepsis. The manner in which all EOS cases presented, timing of
blood cultures and antibiotic treatment, and EOS risk after birth
are provided in the eTable in the Supplement.
Readmissions in the first 7 days after birth with a positive
blood culture or CSF culture result were rare in all periods. Dur-
ing the baseline period, 5 infants (5.2 per 100 000 births) were
readmitted; during the learning period, 1 infant was readmit-
ted (1.9 per 100 000 births); and during the EOS calculator pe-
riod, 3 infants were readmitted (5.3 per 100 000 births) (P =.70
for difference in proportions across periods). The infants re-
admitted during the EOS calculator period were all term,
asymptomatic during their initial hospitalization, and born to
afebrile mothers with rupture of membranes time ranging from
3 to 14 hours. All presented to the emergency department with
fever. To capture cases of culture-negative sepsis, we also as-
certained infants readmitted within 7 days of birth who re-
ceived 5 days or more of antibiotic therapy despite sterile blood
and/or CSF cultures. The only such case occurred during the
baseline period.
Discussion
Although the use of predictive analytics is garnering in-
creased attention in the scientific literature,
21,22
use of patient-
specific, multivariable sepsis risk estimates to guide the care
of newborns represents a significant shift from current rec-
ommended practice in neonatology. Our work provides
prospective validation of the efficiency and safety of this
approach.
The CDC EOS recommendations were based on epidemio-
logic findings that preceded widespread implementation of in-
trapartum antibiotic prophylaxis. These recommendations
have been highly effective in reducing the burden of EOS.
3,23
The guidelines suggest empirical administration of antibiot-
ics for all newborns with a maternal diagnosis of chorioam-
nionitis, regardless of the infant’s clinical condition. Chorio-
amnionitis technically describes inflammation of the chorionic
and amniotic fetal membranes but has been widely applied to
any intrapartum temperature of 38.0°C or higher. In our ap-
proach, we use the highest maternal temperature, modeled as
a log-linear relationship with EOS. A recent National Insti-
tutes of Health–sponsored conference of experts in obstetric
and neonatal care highlighted the shortcomings of current ap-
proaches based on a clinical diagnosis of chorioamnionitis and
urged the use of alternate approaches, including our EOS
calculator.
24
Our results indicate that EOS risk can be accu-
rately and safely assessed without using a clinical diagnosis
of chorioamnionitis.
A multicenter analysis examined whether infant clinical ap-
pearance alone could be used to rule out EOS among infants born
to mothers with a clinical diagnosis of chorioamnionitis.
25
That
analysis found that EOS can occur among infants with initially
reassuring clinical status. Our study found that only 50% of in-
fants with EOS were symptomatic at birth. These findings un-
derscore the importance of our approach, incorporating mul-
tiple risk factors and the evolving clinical status in the first day
of life. The CDC recommends sepsis evaluations for newborns
who are clinically ill (a term that is not defined).
3
Our approach
adds clarity by categorizing physiologic disturbances by dura-
tion and severity.
The goal of all existing approaches to neonatal sepsis risk
assessment is newborn safety. In this study, we assessed safety
by measuring the incidence of EOS, use of antibiotics at 24 to
72 hours of age, proportion of infants with EOS who experi-
enced critical illness or death, and incidence of EOS readmis-
sions across the 3 study periods. We were concerned that if
antibiotic administration immediately after birth prevents low-
level bacteremia from progressing to clinical illness and/or de-
tectable bacteremia, a decrease in early antibiotic use could
result in higher rates of EOS. We did not find any difference in
the overall rate of EOS across the study periods. Another con-
cern was that if the EOS calculator failed to appropriately iden-
tify asymptomatic infants destined to later develop sympto-
matic EOS, infants would become ill later in the birth
hospitalization, have more severe illness, or present with illness
Table 3. Clinical Characteristics and Outcomes of Infants With EOS by Study Period
Variable
No. (%) of Infants by Study Period
a
Baseline
(n = 24)
Learning Period
(n = 15)
EOS Calculator
(n = 12)
Organism
GBS 11 (45.8) 6 (40.0) 3 (25.0)
Escherichia coli 5 (20.8) 6 (40.0) 5 (41.7)
Other 8 (33.3) 3 (20.0) 4 (33.3)
Symptomatic at birth 12 (50.0) 8 (53.3) 6 (50.0)
Developed symptoms before discharge 4 (16.7) 4 (26.7) 5 (41.7)
Never symptomatic 8 (33.3) 3 (20.0) 1 (8.3)
Mechanical ventilation 0 2 (13.3) 1 (8.3)
b
Inotropic agents 2 (8.3) 1 (6.7)
c
1 (8.3)
b
CSF culture positive 0 0 0
Elevated CSF WBC count 1 (4.2) 2 (13.3) 2 (16.7)
d
Death 0 1 (6.7)
c
1 (8.3)
b
Abbreviations: CSF, cerebrospinal
fluid; EOS, early-onset sepsis;
GBS, group B Streptococcus;
WBC, white blood cell.
a
P > .05 for all comparisons between
the baseline and EOS calculator
periods.
b
Severe hypoxic-ischemic
encephalopathy at birth, blood
culture positive for GBS, and
transferred for cooling and
extracorporeal membrane
oxygenation.
c
Persistent pulmonary hypertension
of the newborn and respiratory
failure at birth, blood culture
positive for E coli, and transferred
for extracorporeal membrane
oxygenation.
d
Antibiotic treatment started at birth
and blood culture positive for E coli.
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