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The Pediatric Infectious Disease Journal • Volume XX, Number XX, XXX 2024 www.pidj.com | 1
ISSN: 0891-3668/24/XXXX-0000
DOI: 10.1097/INF.0000000000004550
O S
The Prognosis in Children With Pneumonia of Respiratory
Syncytial Virus Co-detection With Airway Dominant Flora
Lu Li, MS,* Ximing Xu, PhD,† Enmei Liu , MD,* and Yu Deng, MD*
Background: Airway bacterial microbiota influences the prognosis in chil-
dren with respiratory syncytial virus infection. The study aimed to inves-
tigate the eect of the airway-dominant bacterial microbiota on disease
severity in children with pneumonia of respiratory syncytial virus infection.
Methods: A retrospective study was conducted in the Children’s Hospital
of Chongqing Medical University, which involved a cohort of patients with
respiratory syncytial virus (RSV)-infected pneumonia from January 2012
to December 2021. Patients were assigned to a normal flora group or to a
dominant flora group (with the top 5 individual bacteria) based on the naso-
pharyngeal aspirates culture and matched using propensity-score matching.
Univariate analysis and multivariate analysis were performed to estimate
the risk factors of poor prognosis in dominant flora.
Results: Five thousand five hundred and twelve patients in the normal
flora and 4556 in the dominant flora were included (Escherichia coli 514,
Streptococcus pneumoniae 1516, Staphylococcus aureus 506, Moraxella
catarrhalis 509 and Haemophilus influenzae 1516, respectively). The
dominant flora had more patients developing severe pneumonia, needing
mechanical ventilation/tracheal intubation (up to 15.8% in the S. aureus)
and admission to the intensive care unit (up to 4.5% in the E. coli) than in
the normal flora (28.5% vs. 25.9%; P = 0.001; 9.8% vs. 5.4%; P < 0.001;
2.0% vs. 1.2%; P <0.001). And the hospitalization was longer in the domi-
nant flora than in the normal flora [8 (6–9) vs. 8 (7–9) days; P < 0.001], the
E. coli and S. aureus had the longest hospitalization [8 (7–10) days]. Several
factors were associated with critical illness in Dominant flora according to
multivariate analysis (P < 0.001), including age (OR: 0.965; CI: 0.954–
0.976; P < 0.001), anhelation (OR: 0.530; CI: 0.446–0.631; P < 0.001),
disorders of consciousness (OR: 0.055; CI: 0.016–0.185; P < 0.001) as well
as assisted respiration (OR: 0.115; CI: 0.097–0.138; P < 0.001), C-reactive
protein >10 mg/L (OR: 0.686; CI: 0.560–0.839; P < 0.001), SpO2 <90%
(OR: 0.366; CI: 0.214–0.628; P < 0.001), pulmonary consolidation (OR:
0.511; CI: 0.364–0.717; P < 0.001) and pulmonary atelectasis (OR: 0.362;
CI: 0.236–0.555; P < 0.001).
Conclusions: The airway-dominant bacterial microbiota influenced disease
severity and comorbidities in children with RSV-infected pneumonia. Clini-
cians should pay attention to the nasopharyngeal aspirate culture, especially
after detecting S. aureus and E. coli in RSV-infected children with pneu-
monia, closely observe the disease progression and take timely measures to
avoid adverse outcomes.
Key Words: airway bacterial microbiota, children, pneumonia, prognosis,
respiratory syncytial virus
(Pediatr Infect Dis J 2024;XX:00–00)
Respiratory syncytial virus (RSV) is the leading viral cause of
lower respiratory tract infections in infants and young chil-
dren,1 with annual winter outbreaks placing an enormous bur-
den on health systems globally. In 2019, an estimated 33 million
RSV-associated acute lower respiratory tract infections occurred in
children 0–60 months of age, resulting in 3.6 million hospitaliza-
tions and 101,400 deaths worldwide.2 Approximately half of these
deaths occurred in infants under 6 months of age, with the majority
occurring in developing countries.3 Nearly all children experience
at least one RSV infection before the age of 2 years.4 Despite the
emergence of several vaccines in recent years, their clinical appli-
cation remains limited, and no specific medications are currently
available for the widespread treatment or prevention of RSV infec-
tion in children. For example, the humanized monoclonal antibody
palivizumab is only recommended for infants at high risk of severe
RSV disease,5 and pregnancy-induced RSV immunity based on the
fusion F protein is still in the clinical research stage.6
Compared to other viruses, RSV is associated with increased
disease severity in infants and young children.7 Major risk factors
for severe RSV infection include prematurity, chronic lung disease,
congenital heart disease and immunodeficiency.8 However, most
infants hospitalized with RSV infection possess no predisposing
risk factors for severe disease.9,10 Furthermore, while viral factors,
dysregulated host immune responses, and genetic predisposition
contribute to the severity of RSV infection,11,12 none fully account
for the variability in clinical presentation and outcome. Recent
findings suggest that nasopharyngeal microbiota composition
aects the overall risk of respiratory infections13 and the severity
of acute respiratory symptoms.14 Certain bacteria in the respiratory
and nasopharyngeal microbiota, such as Streptococcus pneumoniae
Accepted for publication July 5, 2024
From the *Department of Respiratory Medicine Children’s Hospital of Chongq-
ing Medical University, National Clinical Research Center for Child Health
and Disorders, Ministry of Education Key Laboratory of Child Development
and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infec-
tion and Immunity, Chongqing, China; and †Department of Data Research
Center Children’s Hospital of Chongqing Medical University, National Clin-
ical Research Center for Child Health and Disorders, Ministry of Education
Key Laboratory of Child Development and Disorders, Chongqing Key Labo-
ratory of Child Rare Diseases in Infection and Immunity, Chongqing, China.
This study was supported by National Key Research and Development Pro-
gram of China (2022YFC2704900); CQMU Program for Youth Innova-
tion in Future Medicine; Natural Science Foundation of Chongqing, China
(cstc2019jcyj-msxmX0858).
The funding source had no role in the design and conduct of the study.
The authors have no conflicts of interest to disclose.
Contributors’ Statement Page
L.L. conceptualized and designed the study, constructed the data collection
instrument, collected data, conducted the initial analyses, interpreted the
statistical analyses, drafted the initial manuscript, and reviewed and revised
the manuscript. X.X. contributed considerably to the conceptualization
and design of the study, during data analysis and in the writing process,
and thoroughly reviewed and revised the manuscript. E.L. conceptualized
and designed the study, participated in data collection instrument develop-
ment, supervised data collection, and critically reviewed and revised the
manuscript. Y.D. conceptualized and designed the study, contributed to the
analysis plan, cleaned the data, participated in data analyses and statistical
interpretation, and reviewed and revised the manuscript for important intel-
lectual content. All authors approved the final manuscript as submitted, and
agreed to be accountable for all aspects of the work.
Supplemental digital content is available for this article. Direct URL citations
appear in the printed text and are provided in the HTML and PDF versions of
this article on the journal’s website (www.pidj.com).
Address for correspondence: Yu Deng, MD, Respiratory Department of Chil-
dren’s Hospital of Chongqing Medical University, 2 Jinyu Avenue, Yubei
District, Chongqing, China. E-mail: dengysure186@aliyun.com.
Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.
This is an open-access article distributed under the terms of the Creative
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NC-ND), where it is permissible to download and share the work provided it
is properly cited. The work cannot be changed in any way or used commer-
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Li et al
and Haemophilus influenzae, may influence the host response to
RSV, modulating inflammation and potentially increasing disease
severity.15,16 However, while these studies primarily utilized 16S
rRNA sequencing methods to analyze the nasopharyngeal micro-
biota, clinical practice still relies on culture-based methods to
identify bacterial species. Therefore, this study was designed to
retrospectively analyze the clinical records and auxiliary examina-
tions of children under 5 with RSV-positive pneumonia over the
past decade. We investigated the relationship between dierent
bacteria identified by respiratory cultures and disease severity and
identified risk factors for poor prognosis in children with domi-
nant flora co-detection. This study should facilitate early prognostic
assessment and timely interventions for clinicians.
MATERIALS AND METHODS
Subjects and Study Design
This retrospective cohort study was conducted at the Chil-
dren’s Hospital of Chongqing Medical University, a tertiary care
and regional teaching hospital located in Southwest China. Hospi-
talized patients with laboratory-confirmed RSV infection from 1
January 2012 to 31 December 2021 were analyzed. The admission
criteria for children with pneumonia included meeting the diag-
nostic criteria for severe pneumonia (detailed below) and high-risk
factors for severe pneumonia (underlying disease, age younger than
3 months, disease duration of more than 1 week without improve-
ment and family ineligible for home observation and monitoring).17
The inclusion criteria included: (1) diagnosis of community-
acquired pneumonia (CAP)17 and age <5 years old (no neonates);
(2) nasopharyngeal aspirates (NPAs) were collected immediately
following hospital admission and sent to the laboratory for stand-
ardized processing and bacterial culture and (3) in cases where more
than 1 RSV-positive sample was obtained from a patient during the
study period, only the first RSV-positive sample was included. The
exclusion criteria included: (1) bacterial infections,18,19 determined
by a positive bacterial culture with any of the following: C-reactive
protein (CRP) >80 mg/L, white blood cell count >15 × 109/L, or
procalcitonin >0.5 g/L; (2) infections with adenovirus, influ-
enza A/B virus, parainfluenza virus or other viral pneumonias; (3)
Mycoplasma or Chlamydia infections, whooping cough or fungal
pneumonia; (4) NPA cultures containing fungus or unknown bac-
teria and (5) incomplete medical records. Patients were grouped
according to their initial NPA culture results upon hospital admis-
sion: those with normal bacteria were classified as the normal flora
group, while those containing the top 5 detected bacteria were clas-
sified as the dominant flora group, which was subsequently catego-
rized into severe or nonsevere based on illness severity.
Microbiologic Analysis
The clinical microbiology laboratory at the Children’s Hos-
pital of Chongqing Medical University provided data on viral and
bacterial identifications, including only RSV-positive NPA speci-
mens. RSV was detected using quantitative real-time fluorescent
polymerase chain reaction (qRT-PCR). NPA samples were cultured
and analyzed using the automated VITEK 2 bacterial identification
system (bioMérieux, Lyon, France), and interpreted according to
the Bacterial and Fungal Smear Microscopy and Culture Expert
Consensus on Standardization of Results Reporting20: (1) “Normal
microbiota” refers to normal bacterial sites isolating normal bacte-
rial flora; (2) “XX bacterial growth” refers to normal bacterial sites
isolating 1 or 2 species of pathogenic bacteria, termed dominant
flora. The study included patients who were RSV-positive and had
NPA cultures showing normal bacterial flora or one of the top 5
dominant bacteria.
Data collection
By reviewing medical and microbiological records from the
children’s initial data after hospital admission, we gathered the fol-
lowing information: sex, age (<1 month, <6 months, <2 years, <5
years), gestational age (<37 weeks is preterm), delivery mode, feeding
method, history of eczema and/or food protein allergy, medical his-
tory (including neonatal hospitalization, previous lower respiratory
tract infection and wheezing), underlying diseases (eg, congenital
heart disease, chronic lung disease, congenital airway developmen-
tal abnormalities and immunodeficiencies) and antibiotic use before
the current visit. Admission data included temperature, respiratory
rate, transcutaneous oxygen saturation, mental status, cyanosis, signs
of assisted respiration (such as triple concave signs, nasal flaring or
nodding), pulmonary rales on admission and hospitalization days.
Auxiliary examination data included routine blood tests (total leuko-
cytes, lymphocytes, platelets, erythrocytes and hemoglobin), inflam-
matory markers (CRP), biochemical indices (gamma-glutamyl
transferase, gamma glutaminase, urea, creatinine and lactate dehy-
drogenase) and chest imaging (chest radiograph and/or chest CT).
Treatment data included oxygen use, mechanical ventilation/intuba-
tion, and admission to the intensive care unit (ICU). Consciousness
disorders included somnolence, coma and convulsions. Hypoxemia
was defined as oxygen saturation by pulse oximeter (SpO2) <92% in
children 1–60 months.1 Shortness of breath referred to respiratory
rate ≥60 bpm in children less than 2 months, ≥50 bpm in children
from 2 months to 1 year old, and ≥40 bpm in children from 1 to 5
years old.17 Inflammatory markers, such as procalcitonin (PCT) and
CRP, were used to assess disease severity, with CRP >10 mg/L con-
sidered abnormal.21 Routine blood22 and biochemical indices23 were
analyzed with reference to the corresponding literature. Diagnostic
criteria of severe pneumonia were based on the Diagnostic and Treat-
ment Guidelines for Community-Acquired Pneumonia in Children
(2019 Edition).17 Severe pneumonia was classified as a child expe-
riencing severe impairment of ventilation and gas exchange (poor
general condition, impaired consciousness, hypoxemia, ultra-high
or persistent high fever for more than 5 days, signs of dehydration/
refusal to eat) or with intrapulmonary and extrapulmonary compli-
cations. SpO2 was measured at admission for all patients. Oxygen
therapy was administered if the SpO2 level was less than 92% and
the child exhibited clinical signs of hypoxia.24 Patients requiring oxy-
gen therapy were considered as critical illness. Critical illness/poor
prognosis also included severe pneumonia requiring admission to the
ICU or requiring invasive mechanical ventilation or death. This com-
posite endpoint was chosen because these serious outcomes of pneu-
monia have been adopted in previous studies to assess the severity of
other significant infectious diseases.17,25
Statistical Analysis
All data were analyzed using SPSS v27.0 (SPSS, Inc., Chi-
cago, IL). Propensity-score matching (PSM) was used to balance
the baseline characteristics between the dominant and normal flora
groups. This was achieved through greedy matching, with a caliper
width of 0.02 standard deviations (±SD) of the logit of the pro-
pensity score. The propensity score was estimated using a nonpar-
simonious multivariable logistic regression model, with dominant
flora as the dependent variable and all baseline characteristics as
covariates (Table 1). To analyze risk factors for poor prognosis
in the dominant flora, univariate logistic regression analysis was
performed to identify potential risk factors. Normally distributed
continuous data were expressed as mean ± SD and compared using
the Student t test, while skewed data were expressed as medians
(with interquartile range) and compared using the Kruskal–Wallis
rank-sum test or Mann–Whitney U test. Categorical data were sum-
marized using absolute values (percentage) and compared using the
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Airway Dominant Flora
χ2 test, Kruskal–Wallis rank-sum test, or Mann–Whitney U test. To
identify independent risk factors, variables with P < 0.001 in the
univariate analysis were included in a multivariate logistic regres-
sion model and analyzed using backward stepwise regression. Odds
ratios (OR) and 95% confidence intervals (CI) were also calculated.
All tests were 2-tailed, and P < 0.05 was considered statistically
significant.
RESULTS
In total, 10,068 patients met the study inclusion criteria,
including 5512 patients in the normal flora (control) group and
4556 patients in the dominant flora (case) group. The top 5 path-
ogenic bacteria were S. pneumoniae, H. influenzae, Escherichia
coli, Moraxella catarrhalis, and Staphylococcus aureus (Figure,
Supplemental Digital Content 1, http://links.lww.com/INF/F718).
After PSM, 9062 participants were included in the final analysis.
The baseline characteristics of the overall and matched cohorts
are listed in Table 1. Before PSM, significant age dierences were
observed between the 2 groups, with the normal flora group being
younger. Additionally, dierences were noted in the rates of vaginal
delivery, breastfeeding, history of food protein allergy and respira-
tory infections, all of which were lower in the normal flora group
compared to the dominant flora group. Conversely, the normal
flora group had higher rates of congenital heart disease and prior
antibiotic use than the dominant flora group (Table 1). After PSM,
most baseline characteristics were similar between the 2 groups,
although dierences remained in age, vaginal delivery, breastfeed-
ing, food protein allergy, congenital heart disease and antibiotic
use (Table 1). As shown in Table 2, after PSM, the dominant flora
group had a higher incidence of severe pneumonia and more fre-
quently required mechanical ventilation, tracheal intubation and
ICU admission compared to the normal flora group.
Univariate analysis was conducted to identify risk fac-
tors associated with critical illness in the dominant flora group
(Table 3). Compared to patients without critical illness, those with
critical illness were younger (4.0 months vs. 8.0 months; P < 0.05)
and had higher rates of premature birth and neonatal hospitalization
(16.5% vs. 9.8% and 24.2% vs. 16.8%, respectively; P < 0.001).
Moreover, these patients had higher incidences of chronic pul-
monary disease, congenital heart disease and immune deficiency
(4.4% vs. 0.7%; 24.2% vs. 13.1% and 0.8% vs 0.1%, respectively;
P < 0.001). Symptoms and signs were analyzed as potential risk
factors (Table 3), revealing that patients with critical illness more
frequently manifested with dyspnea, consciousness disorders,
TABLE 1. Demographic and Clinical Characteristics Before and After PSM
Variable
Full Cohort (N = 10068) Propensity Score−matched Cohort (N = 9062)
Normal Flora
n = 5512 Dominant Flora
n = 4556 PNormal Flora
n = 4531 Dominant Flora
n = 4531 P
Male, n (%) 62.4 (3440) 63.5 (2895) 0.241 63.2 (2862) 63.6 (2881) 0.692
Age (mo, IQR), n (%) 5.0 (2.0–11.0) 6.0 (2.0–14.0) <0.001 5.0 (2.0–11.0) 6.0 (2.0–13.0) <0.001
<6 mo 52.3 (2884) 44.7 (2037) <0.001 52.8 (2386) 45.0 (2037) <0.001
<12 mo 22.8 (1258) 24.5 (1116) 22.6 (1024) 24.6 (1116)
<24 mo 15.9 (877) 18.5 (845) 15.3 (695) 18.6 (843)
<60 mo 8.9 (493) 12.2 (558) 9.5 (430) 11.8 (535)
Vaginal delivery, n (%) 42.2 (2327) 45.1 (2054) 0.004 42.1 ( 1906) 44.9 (2035) 0.005
Breast feeding, n (%) 40.9 (2256) 44.8 (2039) <0.001 39.7 (1797) 44.5 (2018) <0.001
Anamnesis, n (%)
Premature 13.0 (719) 12.1 (551) 0.153 12.6 (572) 12.2 (551) 0.517
Food protein allergy 3.3 (182) 4.2 (193) 0.014 3.0 (137) 4.1 (187) 0.005
Eczema 15.7 (868) 16.4 (746) 0.396 16.1 (728) 16.4 (744) 0.667
Neonate hospitalization 20.8 (1146) 19.4 (884) 0.084 19.1 (901) 19.6 (880) 0.594
Lower respiratory infections 21.2 (1171) 23 (1047) 0.036 21.1 (958) 22.9 (1036) 0.049
Wheeze 14.0 (773) 15 (683) 0.17 14.9 (673) 15.0 (678) 0.906
Underling diseases, n (%)
Congenital airway malformations 7.1 (394) 7.2 (326) 0.989 7.2 (325) 7.2 (324) 1
Chronic pulmonary disease 1.9 (107) 2 (90) 0.902 1.6 (72) 2.0 (90) 0.173
Congenital heart disease 19.4 (1069) 17 (773) 0.002 20.0 (904) 17.0 (772) <0.001
Immune deficiency disease 0.4 (24) 0.37 (17) 0.625 0.5 (24) 0.4 (17) 0.349
History of antibiotic, n (%) 81.9 (4514) 78.1 (3559) <0.001 82.0 (3715) 78.3 (3546) <0.001
IQR indicates interquartile range; mo, month; PSM, propensity-score matching.
TABLE 2. The Outcome Before and After PSM
Variable
Full Cohort (N = 10068) Propensity Score−matched Cohort (N=9062)
Normal Flora
n = 5512 Dominant Flora
n = 4556 PNormal flora
n = 4531 Dominant flora
n = 4531 P
Prognosis, n (%)
Severe pneumonia 28.3 (1560/5512) 28.4 (1294/4556) 0.912 25.9 (1175/4531) 28.5 (1293/4531) 0.006
Oxygen inhalation 15.0 (826/5512) 14.4 (621/4304) 0.44 13.8 (627/4531) 14.5 (620/4280) 0.4
Mechanical ventilation 7.5 (412/5512) 9.8 (419/4296) <0.001 5.4 (246/4531) 9.8 (418/4272) <0.001
Tracheal intubation
Intensive care unit 1.2 (66/5512) 2.0 (92/4556) <0.001 1.2 (56/4531) 2.0 (92/4531) 0.004
Death 0.05 (3/5512) 0.04 (2/4556) 0.813 0.1 (3/4541) 0.0 (2/4531) 1
Hospitalization (day, IQR) 8 (6–9) 8 (7–9) <0.001 8 (6–9) 8 (7–9) <0.001
IQR indicates interquartile range.
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Li et al
cyanosis, assisted respiration, and wheezing rales (65.8% vs.
30.8%; 2.4% vs. 0.1%; 82.4% vs. 59.2%; 74.8% vs. 16.6% and
65.8% vs. 50.3%, respectively; P < 0.001). Routine blood tests also
indicated that the critical illness group had higher neutrophil counts
and lower lymphocyte counts, red blood cell counts and hemoglo-
bin levels compared to those without critical illness (26.4% vs.
13.3%; 13.9% vs. 6.5%; 17.4% vs. 8.7% and 20.6% vs. 11.8%,
respectively; P < 0.001). Furthermore, CRP levels were higher in
the critical illness group (27.2% vs. 19.1%; P < 0.001). Comor-
bidities were also analyzed as potential risk factors. Compared to
patients without critical illness, the critical illness group contained
more patients with SpO2 <90%, urea increase, pulmonary consol-
idation and pulmonary atelectasis (6.1% vs. 1.2%; 2.3% vs. 0.8%;
11.2% vs. 3.8% and 8.5% vs. 1.9%; P < 0.001).
Multivariate analysis on variables that were significant in the
univariate analysis (P < 0.001) was conducted (Table 4). Results
showed that the independent risk factors associated with critical
illness in the dominant flora group included age (OR: 0.965; CI:
0.954–0.976; P < 0.001), dyspnea (OR: 0.530; CI: 0.446–0.631;
P < 0.001), consciousness disorders (OR: 0.055; CI: 0.016–0.185;
P < 0.001), assisted respiration (OR: 0.115; CI: 0.097–0.138; P <
0.001), CRP > 10 mg/L (OR: 0.686; CI: 0.560–0.839; P < 0.001),
SpO2 <90% (OR: 0.366; CI: 0.214–0.628; P < 0.001), pulmo-
nary consolidation (OR: 0.511; CI: 0.364–0.717; P < 0.001), and
pulmonary atelectasis (OR: 0.362; CI: 0.236–0.555; P < 0.001).
Additionally, patients with underlying conditions, such as chronic
pulmonary disease, congenital heart disease and immune defi-
ciency disease, and those with elevated neutrophil counts and
reduced RBC counts were more likely to develop critical illness.
To examine the relationship between individual dominant
bacteria and disease severity in children with RSV-induced pneu-
monia, subgroup analysis of the dominant flora before PSM was
performed (Figure, Supplemental Digital Content 1, http://links.
lww.com/INF/F718). This analysis included 514 patients with E.
coli, 1516 with S. pneumoniae, 506 with S. aureus, 609 with M.
catarrhalis and 1411 with H. influenzae. The median age was 2
months for the E. coli and S. aureus groups, 7 months in the M.
catarrhalis and H. influenzae groups and 11 months in the S. pneu-
moniae group, with significant dierences among the groups (P <
0.001). Baseline characteristics such as breastfeeding, medical his-
tory, underlying diseases, and antibiotic use before hospitalization
varied among the groups (Table, Supplemental Digital Content 2,
http://links.lww.com/INF/F719). Significant dierences in clinical
characteristics, including clinical symptoms/signs, routine blood
tests and inflammatory markers, were observed among the groups
(Table, Supplemental Digital Content 3, http://links.lww.com/
TABLE 3. Univariate Analysis of Risk Factors
Associated With Critical illness in Dominant flora after
PSM
Variable
Critical Illness
PYes = 1619 No = 2912
Male 63.5 (1028/1619) 63.6 (1853/2912) 0.927
Age (mo, IQR), n (%) 4.0 (2.0–9.0) 8.0 (3.0–16.0) <0.001
<6 mo 58.6 (949/1619) 37.4 (1088/2912) <0.001
<12 mo 21.2 (343/1619) 26.5 (773/2912)
<24 mo 13.3 (215/1619) 21.6 (628/2912)
<60 mo 6.9 (112/1619) 14.5 (423/2912)
Vaginal delivery, n (%) 46.3 (749/1619) 44.2 (1826/2912) 0.173
Breast feeding, n (%) 44.4 (719/1619) 44.6 (1299/2912) 0.478
Anamnesis, n (%)
Premature 16.5 (267/1619) 9.8 (284/2912) <0.001
Food protein allergy 4.1 (67/1619) 4.1 (120/2912) 0.977
Eczema 16.1 (260/1619) 16.6 (484/2912) 0.625
Neonate hospitali-
zation 24.2 (392/1619) 16.8 (488/2912) <0.001
Lower respiratory
infections 20.8 (337/1619) 24.0 (699/2912) 0.014
Wheeze 13.0 (210/1619) 16.1 (468/2912) 0.005
Underling diseases,
n (%)
Congenital airway
malformations 7.8 (126/1619) 6.8 (198/2912) 0.218
Chronic pulmonary
disease 4.4 (71/1619) 0.7 (19/2912) <0.001
Congenital heart
disease 24.2 (349/1619) 13.1 (381/2912) <0.001
Immune deficiency
disease 0.8 (13/1619) 0.1 (4/2912) <0.001
History of antibiotic,
n (%) 74.9 (1213/1619) 80.1 (2333/2912) <0.001
Symptom/signs, n (%)
Fever 20.2 (324/1606) 17.7 (514/2903) 0.041
Anhelation 65.8 (1056/1605) 30.8 (895/2905) <0.001
Disorders of con-
sciousness 2.4 (38/1614) 0.1 (4/2905) <0.001
Cyanosis 82.4 (1332/1617) 59.2 (1721/2909) <0.001
Assisted respiration 74.8 (1208/1616) 16.6 (483/2906) <0.001
Wheezing rale 65.8 (1062/1614) 50.3 (1461/2905) <0.001
Blood routine, n (%)
WBC ↑4.5 (70/1572) 7.3 (199/2735) <0.001
Neut ↑26.4 (415/1574) 13.2 (391/2736) <0.001
Lymph ↓13.9 (219/1574) 6.5 (179/2735) <0.001
RBC ↓17.4 (274/1573) 8.7 (238/2737) <0.001
Hb ↓20.6 (324/1574) 11.8 (322/2737) <0.001
PLT ↑10.9 (171/1571) 12.7 (348/2737) 0.076
CRP＞10mg/L, n (%) 27.2 (441/1619) 19.1 (556/2912) <0.001
Comorbidity, n (%)
SpO2<90% 6.1 (98/1618) 1.2 (35/2911) <0.001
AST ↑10.3 (165/1601) 13.1 (375/2859) 0.006
ALT ↑7.3 (117/1600) 6.7 (193/2861) 0.475
LDH ↑8.7 (139/1601) 14.4 (411/2860) <0.001
Urea ↑2.3 (36/1593) 0.8 (24/2853) <0.001
Cr ↑2.4 (38/1598) 1.4 (41/2854) 0.022
Pulmonary consoli-
dation 11.2 (182/1619) 3.8 (110/2912) <0.001
Pulmonary atelec-
tasis 8.5 (138/1619) 1.9 (55/2912) <0.001
↑ indicates increase; ↓, decrease, ALT, alanine amiotransferase; AST, aspartate ami-
notransferase; Cr, creatinine; CRP, C-reactive protein; Hb, hemoglobin; Lymph, lympho-
cyte; LDH, lactate dehydrogenase; Neut, Neutrophil; PLT, Platelet; RBC, red blood cell;
WBC, white blood cell.
TABLE 4. Multivariate Analysis of Risk Factors
Associated With Critical Illness in Dominant Flora
Variable OR (95% CI) P
Age 0.965 (0.954–0.976) <0.001
Premature 0.960 (0.739–1.248) 0.761
Neonate hospitalization 0.845 (0.680–1.050) 0.130
Chronic pulmonary disease 0.351 (0.182–0.679) 0.002
Congenital heart disease 0.758 (0.612–0.940) 0.011
Immune deficiency disease 0.153 (0.033–0.708) 0.016
Anhelation 0.530 (0.446–0.631) <0.001
Disorders of consciousness 0.055 (0.016–0.185) <0.001
Cyanosis 0.855 (0.702–1.041) 0.119
Assisted respiration 0.115 (0.097–0.138) <0.001
Wheezing rale 0.807 (0.680–0.958) 0.014
Neut↑0.617 (0.465–0.818) 0.001
Lymph↓0.757 (0.523–1.095) 0.139
RBC↓0.621 (0.473–0.814) 0.001
Hb↓0.875 (0.681–1.123) 0.294
CRP >10 mg/L 0.686 (0.560–0.839) <0.001
SpO2 <90% 0.366 (0.214–0.628) <0.001
Urea↑1.100 (0.530–2.282) 0.799
Pulmonary consolidation 0.511 (0.364–0.717) <0.001
Pulmonary atelectasis 0.362 (0.236–0.555) <0.001
↑ indicates increase; ↓, decrease; CI, confidence interval; Cr, creatinine; CRP, C-reactive
protein; Hb, hemoglobin; Lymph, lymphocyte; Neut, Neutrophil; OR, odds ratio; RBC,
red blood cell.
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Airway Dominant Flora
INF/F720). Prognosis data (Table, Supplemental Digital Content
4, http://links.lww.com/INF/F721) indicated that the E. coli group
had a higher incidence of atelectasis compared to the other groups,
although this was not significant (P > 0.05). The E. coli group also
had the highest ICU admission rate (4.5%, P < 0.001). The rate
of mechanical ventilation/tracheal intubation was highest in the S.
aureus group (15.8%; P < 0.001). There was 1 child death in both
the E. coli and S. aureus groups. In addition, hospitalization dura-
tion was longer in the E. coli and S. aureus groups (7–10 days)
compared to the other groups (P < 0.001). Overall, these findings
suggest that children with RSV-induced pneumonia co-detected
with S. aureus and E. coli exhibited poorer prognosis than those in
the other 3 groups.
DISCUSSION
The airway bacterial microbiota significantly influences
prognosis in children with RSV infection. Clarifying the relation-
ship between nasopharyngeal bacteria and disease in RSV-infected
children can assist clinicians in assessing disease severity and pre-
dicting outcomes. In the present study, the top 5 co-detected bacte-
ria in children with RSV-induced pneumonia were S. pneumoniae,
H. influenzae, E. coli, M. catarrhalis and S. aureus. Patients with
a dominant flora were more likely to develop severe pneumonia,
require mechanical ventilation/tracheal intubation, and need admis-
sion to the ICU compared to those with a normal flora. In addi-
tion, younger age, marked dyspnea, need for assisted respiration,
consciousness disorders, elevated CRP levels, hypoxemia, pulmo-
nary consolidation and pulmonary atelectasis were more frequently
associated with critical illness in the dominant flora group. Notably,
children with RSV-infected pneumonia co-detected with E. coli and
S. aureus had a poorer prognosis.
Consistent with earlier studies,15,26,27 the most frequently
detected airway bacteria in RSV-infected children were S. pneu-
moniae, H. influenzae, E. coli, M. catarrhalis and S. aureus. Acute
respiratory infections can alter the composition of nasopharyngeal
microbiota.26 Previous 16S rRNA microbiota profiling of infants in
their first year revealed that Staphylococcus species were prevalent
and similar between RSV-infected and healthy infants, significantly
decreased during illness, and remained stable 1-month postillness.
Conversely, moraxella increased significantly before, during, and after
RSV infection, while haemophilus was low before and after illness but
increased significantly during illness in the infected group.27 A pro-
spective observational study of 106 children aged 2 years or younger
experiencing their first RSV infection, compared with 26 healthy con-
trols, identified 3 groups (mild RSV infection, severe RSV requiring
hospitalization and healthy controls) and 4 nasopharyngeal microbiota
clusters enriched with H. influenzae, Streptococcus, Moraxella or S.
aureus.15 Metagenomic sequencing in infants under 1 year of age hos-
pitalized with bronchiolitis showed that H. influenzae, M. catarrhalis
and S. pneumoniae dominated the nasopharyngeal airway.28 In sum-
mary, Streptococcus, Haemophilus and Moraxella are the predominant
respiratory bacterial microbiota found in children with RSV infection.
The interplay between these bacterial populations and RSV can influ-
ence susceptibility to RSV infection, severity of the disease and risk
of bacterial superinfection and may contribute to subsequent recurrent
wheezing and asthma in later childhood.29
Our findings also indicated that RSV-infected patients co-
detected with dominant flora were more likely to progress as severe
pneumonia and require mechanical ventilation/tracheal intubation
and ICU admission than those with normal flora. In the multicenter
MARC-35 (the 35th Multicenter Airway Research Collaboration)
study of 1005 infants hospitalized for bronchiolitis, those with RSV
infection and haemophilus-dominant profiles, also characterized by
older age and prehospitalization antibiotic use, had higher odds
of pediatric ICU (PICU) admission than those with moraxella-
dominant profiles.30 Additionally, a higher relative abundance
of S. pneumoniae was correlated with increased risk of positive
pressure ventilation (PPV) support, with sphingolipid metabolism
significantly enriched in infants using PPV and positively corre-
lated with S. pneumoniae abundance.28 Conversely, higher Morax-
ella abundance was associated with lower PICU admission rates
and shorter hospital stays, indicating a potential protective eect
on RSV bronchiolitis.14,16 Interestingly, patients co-detected with
S. aureus exhibited poorer prognoses than other dominant bacte-
rial groups, contradicting findings by Grier et al,27 who reported
reduced Staphylococcus in respiratory microbiota and a negative
correlation with disease severity in RSV-infected infants. Similarly,
de Steenhuijsen Piters et al15 identified S. aureus as a characteris-
tic respiratory microbiota in RSV-infected children under 2 years
old but found it negatively associated with hospitalization. These
discrepancies may be due to dierences in subject selection crite-
ria. Notably, our study included younger patients (under 3 months)
with underlying conditions such as congenital heart disease,31 while
most subjects were previously healthy in other studies.15,27 We also
found that RSV-infected patients co-detected with E. coli exhibited
poorer prognoses, a finding not reported in previous studies, which
did not consider E. coli a dominant airway bacterium in RSV-
infected children.26,27,32 This poorer prognosis could be attributed to
the younger age (median age of 2 months) and higher incidence of
prematurity in these patients33 (Table, Supplemental Digital Con-
tent 4, http://links.lww.com/INF/F721).
Another significant finding of this study was that younger
patients and those with marked dyspnea requiring assisted respi-
ration, consciousness disorders, elevated CRP levels, hypoxemia,
pulmonary consolidation and pulmonary atelectasis were more
likely to develop critical illness in the dominant flora group. RSV
infection and hospitalization were positively associated with H.
influenzae and Streptococcus. Nasopharyngeal microbiota clus-
ters enriched with H. influenzae and Streptococcus during RSV
infection are associated with more severe clinical disease and an
exaggerated inflammatory response, characterized by overexpres-
sion of genes related to toll-like receptor (TLR) signaling and
neutrophil recruitment and activation, including overexpression of
IFN-related genes, enhanced TLR signaling, and increased expres-
sion of neutrophil- and macrophage-related transcripts.15 In a sep-
arate study of 74 children under 6 months hospitalized for severe
RSV bronchiolitis, Haemophilus species were a major component
of the airway microbiota and associated with elevated CXCL-8,
a neutrophil chemotactic factor, in the nasopharyngeal cavity.34
Another cohort study of 54 infants under 6 months hospitalized
with RSV infection also found overexpression of Haemophilus in
NPA, linked to increased IL-6 and CXCL-8 responses, cytokines
associated with more severe RSV disease.35 These findings sug-
gest that specific nasopharyngeal microbiota clusters, particularly
those dominated by H. influenzae and S. pneumoniae, can modu-
late the host immune response to RSV, potentially impacting dis-
ease severity.
The nasopharyngeal flora in children is established within
the first few months of life, typically colonizing asymptomatically
and only causing disease when immunity decreases or other fac-
tors intervene.36,37 The local host immune response plays a crucial
regulatory role in the carriage of upper respiratory pathogens.38
During viral infections, pathogenic bacteria can more easily attach
to virally infected epithelial cells in the nasopharynx, leading to an
increased bacterial load and potential invasion of the lower respira-
tory tract, resulting in pneumonia.39 For example, RSV infection
can facilitate pneumococcal diseases via several mechanisms: (1)
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Li et al
RSV can damage respiratory epithelial cells, reduce ciliary activ-
ity and impair respiratory epithelial cell clearance, thereby pro-
moting bacterial infection.40,41 (2) The glycoprotein G expressed by
RSV in infected host cells can act as a receptor for S. pneumoniae,
promoting its binding and adhesion to epithelial cells and increas-
ing its invasiveness.42,43 (3) RSV infection can alter the intrinsic
immune response, promoting S. pneumoniae proliferation.43 (4)
RSV infection can induce the expression of virulence genes in S.
pneumoniae, thereby increasing the inflammatory response.40 In
summary, viral infections create favorable conditions for patho-
genic bacteria to develop invasive infections, thus exacerbating
illness in children.
Most cases of community-acquired pneumonia in children
are caused by virus infection and therefore do not require antibiotic
treatment. However, early use of etiology testing in hospitalized
children with community-acquired pneumonia is recommended
in certain cases. For children with typical bacterial pneumonia,
early bacterial culture and antimicrobial susceptibility tests can
guide the selection of more eective antibiotics.44 When viral
pneumonia progresses, early etiology testing can identify whether
clinical symptoms and radiological findings suggest a secondary
bacterial infection, supporting rational antibiotic use.45 In severe
cases, where airway inflammation alters the bacterial flora, such
testing is also essential for detecting secondary bacterial infec-
tions and selecting appropriate antibiotics. Overall, the insights
gained from these findings could lead to changes in clinical prac-
tice for more eective management of community-acquired pneu-
monia. However, our study has several limitations. First, selection
bias may exist as the study was conducted in a single tertiary-care
teaching hospital, suggesting caution when extrapolating our
findings across dierent hospitals and regions. Second, despite the
relatively large sample size, the retrospective nature of the study
and several missing parameters may limit the statistical power for
some critical factors. Finally, although we used PSM to mitigate
biases inherent in observational studies, achieving a perfect 1:1
match is challenging due to inherent population dierences. Pro-
spective, multicenter clinical trials are needed to address these
uncertainties.
CONCLUSIONS
This retrospective study highlighted the significant
impact of airway flora on disease severity in children with RSV-
infected pneumonia, especially those co-detected with dominant
flora. Our findings suggest that clinicians should closely monitor
NPA cultures, alongside clinical symptoms, routine blood tests,
and chest imaging, to accurately assess disease severity and ensure
timely intervention. Particular attention should be paid to RSV-
infected children co-detected with S. aureus and E. coli to pre-
vent adverse outcomes. However, further research is necessary
to explore the relationship between RSV infection and airway-
dominant flora more comprehensively.
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