Evaluation of Moderate to Severe Influenza Disease in Children 6 Months to 8 Years in Colorado
Conditions: Influenza, Otitis Media, Lower Resp Tract Infection, Encephalitic Infection, Myositis Viral, Fever
Sponsor: University of Colorado, Denver

NCT02979626   Unique Protocol ID: 16-1785 
 
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PI: Edwin Asurias, MD/DO 
Protocol Version: January/17 
COMIRB# 16-1785 
w 
COMIRB Protocol 
COLORADO MULTIPLE INSTITUTIONAL REVIEW BOARD 
CAMPUS BOX F-490    TELEPHONE:  303-724-1055  Fax:  
303-724-0990 
 
 
 
Protocol #: 16-1785 
Project Title: Evaluation of Moderate to Severe Influenza Disease in Children 6 
months to 8 years in Colorado 
 
 
 
 
Principal Investigator:  
Edwin Asturias, MD 
Version Date: 7/27/16 
 
 
 
 
 
 
  
 
I. Hypotheses and Specific Aims:   
Children 6 months to 8 years of age with moderate to severe influenza have a higher risk 
of hospitalization, intensive care unit (ICU) admission, antibiotic use and complications 
compared with children with mild influenza illness. 
Specific Aims: 
Aim #1:  To determine the validity of the moderate to severe endpoint for influenza as 
a predictor for hospitalization among children aged 6 months to 8 years evaluated at 
Children’s Hospital Colorado (CHCO) emergency department (ED) and urgent cares 
(UC) during the 2016-2017 influenza season. 
 
Aim #2: To prospectively evaluate the usefulness of the moderate to severe influenza 
endpoint against additional severity measures such as ICU admission, antibiotic and 
antiviral use, parental and child absenteeism and recurrent healthcare visits among 
children aged 6 months to 8 years evaluated at ED and UC centers in Colorado. 
 
Aim # 3: To compare the healthcare costs associated with management of moderate 
to severe versus mild influenza disease. 
Exploratory Objectives: 
1) To compare the moderate to severe influenza definition, and other severity measures 
such as ICU admission, hospitalization, antibiotic, antiviral use, child and caregiver 
absenteeism among patients vaccinated with injectable influenza vaccine (IIV) versus 
unvaccinated individuals.  
2) To evaluate severity measures such as hospitalization, ICU admission, antibiotic, 
antiviral use, caregiver and child absenteeism among children with influenza like 
illness who test negative for influenza.  
3) To determine whether clinical measurements taken at ED/UC presentation such as 
systemic inflammatory response syndrome (SIRS) criteria, adjusted heart rate, oxygen 
saturation and temperature predict hospitalization, ICU admission and having 
polymerase chain reaction (PCR)-confirmed influenza.   We will also consider the 
prediction value of peak temperature and temperature duration. 
II. Background and Significance:  
Influenza is an important cause of morbidity in children, annually causing 1-7 
hospitalizations per 10,000 in US children under the age of 18 years (1-6).  Children are 

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among those at high risk of serious outcomes and hospitalization for influenza and 
influenza-related complications (7, 8).  The social and economic impacts of influenza 
range from significant healthcare costs and decreased productivity due to parental 
absenteeism (9).  Annual influenza vaccination is the most effective strategy to prevent 
influenza illness, and is recommended for all children aged greater than 6 months of age.  
The Center for Disease Control and Prevention (CDC) estimates that for the 2013-2014 
influenza season, influenza vaccination prevented approximately 7.2 million illnesses 
associated with influenza (10).  
 
While the ultimate goal of vaccination is to prevent influenza infection, prevention of 
severe disease would provide the greatest public health impact in terms of benefits to the 
individual and society. Influenza vaccine effectiveness has been traditionally studied 
against lab-confirmed influenza, or medically-attended illness, but influenza vaccination 
has been shown to be effective in reducing hospitalization in children (11-14).   
 
More recently, a multicenter, phase 3, randomized controlled quadrivalent influenza 
vaccination study conducted in Asia, Central America and Europe showed that influenza 
vaccination was highly effective in reducing moderate to severe influenza, defined as 
fever greater than 39⁰C, or presence of otitis media defined by the American Academy of 
Pediatrics (AAP) guideline criteria, lower respiratory tract infection (shortness of breath, 
pulmonary congestion, pneumonia, bronchiolitis, bronchitis, wheezing, croup), or serious 
extrapulmonary manifestations (e.g., myocarditis, encephalitis, seizure) (15). The same 
moderate to severe influenza endpoint has been shown in a Finnish study to be clinically 
meaningful, in terms of illness duration, child and parental absenteeism, and antibiotic use 
(16). However, the relationship between this definition of moderate to severe influenza 
and important clinical and public health outcomes such as ED visits, hospitalization, ICU 
admission, use of antimicrobials and recurrent health care utilization has not been 
evaluated prospectively in US children. 
 
The purpose of the proposed study is to validate that the definition of moderate to severe 
influenza in children predicts greater risk of healthcare endpoints such as hospitalization, 
increased length of stay, use of antimicrobials (including antivirals), absenteeism, 
increased duration of illness, and increased healthcare costs.  
 
Understanding and validating the relationship between moderate to severe influenza and 
these clinically relevant endpoints is critical to establishing relevant surrogate markers of 
clinical and public health outcomes.  If shown to be clinically relevant, this definition of 
moderate to severe influenza can be an important endpoint for assessing influenza 
vaccine effectiveness.  
 
 
III. Preliminary Studies/Progress Report:   
CHCO provides an ideal site for the study of influenza in children.  CHCO is a large 
tertiary institution with a large catchment area of Denver Metro, Aurora and surrounding 
states.  It serves 67% of children in the state of Colorado.  From December 1, 2010 to 
April 30, 2014, there were 409 patients admitted to CHCO with PCR-confirmed influenza; 
62% of these were defined as high-risk (16), and 38% were vaccinated against influenza 
during the same season. Accurate immunization data was available for 83% of patients 
via the Colorado Immunization Information System (CIIS). Clinical presentation and 

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hospital-based outcomes such as length of hospitalization among children admitted with 
influenza are shown in Table 1.  
 
Table 1.  Children Admitted To CHCO with Influenza, 2010-2014 
Children admitted to CHCO with 
influenza N = 395 
< 3 years 
N = 156 
>3 years 
N = 239 
Otitis media  
10 (6) 
6 (3) 
Pneumonia 
7 (5) 
22 (9) 
Hypoxia 
19 (12) 
141 (59) 
Fever  
133 (85) 
207 (87) 
Median duration of fever, days 
(range) 
2 (1-17) 
4 (1-64) 
Tachypnea 
64 (41) 
91 (38) 
Antibiotics  
88 (56) 
157 (66) 
Median duration of antibiotics, days 
(range)  
7 (0-23) 
8 (0-77) 
Pediatric Intensive Care Unit (PICU) 
55 (35) 
81 (34) 
PICU length of stay, days  
2 (1-100) 
3(1-83) 
Death 
1 (1) 
2 (1) 
Median duration of hospitalization, 
days (range) 
3 (1-100) 
3 (1-128) 
Vaccinated during current season 
against influenza 
39 (25) 
87 (36) 
Preliminary data from the 2013-2014 and 2014-2015 influenza seasons demonstrated that 
among 11,997 patients who presented to CHCO ED, UC or outpatient clinics for an acute 
respiratory illness, 1398 (12%) underwent viral testing (either respiratory pathogen panel 
multiplex PCR or influenza PCR).  1375 patients were admitted for a respiratory illness, 
and of these, 994 (72%) underwent viral testing Additional data regarding ED visits during 
these time periods are shown in Table 2. 
Table 2. Children Presenting to CHCO ED or UC with Acute Respiratory Illness, 
2013-2014 and 2014-2015 
CHCO data: 
2013-2014 
2014-2015 
Total 
ED/UC/Clinic visits due to an acute 
respiratory illness  
5900 
6097 
11997 
ED visits due to an acute respiratory 
illness, limited to patients < 8 yrs 
4510 
4595 
9105 
ED visits limited to CHCO, Uptown Urgent 
Care, South Urgent Care with an acute 
respiratory illness, limited to patients < 8 
yrs 
2703 
2809 
5512 
ED visits with above restrictions further 
limited to Jan to March 
1290 
1745 
3035 
Limit visits to < 8 yrs Jan to March, no 
repeat visits  
1244 
1688 
2932 
Admission for acute respiratory illness, 
454 
486 
940 

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Jan -Mar 
 
IV. Research Methods 
The study comprises a prospective analysis of children presenting to CHCO ED, and 
North Campus UC with an influenza-like illness (ILI) during the 2016-2017 influenza 
season. Once enrolled in the study, we will collect respiratory samples (nasopharyngeal 
(NP) specimens), socio demographic, and clinical data including variables of interest 
outlined above, and follow the clinical outcome of these children for 14 days after their 
initial presentation.  A complete list of the variables being collected can be found in 
Appendix A. 
 
A.  Outcome Measure(s):   
Primary outcome measure /Endpoints:  
1) Hospitalization in patients presenting to the CHCO Main ED or North Campus UC with 
influenza  
Secondary outcome measures/Endpoints: 
1) ICU admission in patients presenting to the CHCO Main ED or North Campus UC with 
influenza 
2) Antiviral use in patients presenting to the CHCO Main ED or North Campus UC with 
influenza 
3) Antibiotic use in patients presenting to the CHCO Main ED or North Campus UC with 
influenza 
4) Number of visits to the ED or healthcare provider in patients presenting to the CHCO 
Main ED or North Campus UC with influenza  
5) Number of days of absenteeism from school or daycare in patients presenting to the 
CHCO Main ED or North Campus UC with influenza 
6) Number of days of absenteeism from work in caregivers of children presenting to the 
CHCO Main ED or North Campus UC with influenza 
7) Healthcare costs associated with ED visits or hospitalization in patients presenting to 
the CHCO Main ED or North Campus UC with influenza 
Exploratory Outcome measures/Endpoints: 
1) Vaccination status in subjects testing positive for influenza: 
a. Injectable influenza vaccine (IIV) receipt in patients presenting to the CHCO 
Main ED or North Campus UC with moderate to severe influenza 
b. IIV receipt in patients presenting to the CHCO Main ED or North Campus UC 
who are hospitalized 
c. IIV receipt in patients presenting to the CHCO Main ED or North Campus UC 
who are admitted to the ICU 
d. Number of days of fever in patients who received IIV presenting to the CHCO 
Main ED or North Campus UC 
e. Number of days of caregiver and child absenteeism in patients who received 
IIV presenting to the CHCO Main ED or North Campus UC 

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f. 
IIV receipt in patients presenting to the CHCO Main ED or North Campus UC 
who received antibiotics 
g. IIV receipt in patients presenting to the CHCO Main ED or North Campus UC 
who received antivirals 
2) Influenza-like-illness among subjects testing negative for influenza:  
a. Hospitalization in patients with ILI who test negative for influenza 
b. ICU admission in patients with ILI who test negative for influenza 
c. Duration of fever in patients with ILI who test negative for influenza 
d. Number of days of absenteeism from work in caregivers of patients with ILI 
who test negative for influenza 
e. Number of days of absenteeism from school in patients with ILI who test 
negative for influenza 
f. 
Antibiotic use in patients with ILI who test negative for influenza 
g. Antiviral use in patients with ILI who test negative for influenza 
 
3) Fever, vital sign data and extrapulmonary complications:  
a. Number of days of fever in patients presenting to the CHCO Main ED or North 
Campus UC with influenza 
b. Peak temperature at any time during illness in patients presenting to the CHCO 
Main ED or North Campus UC with influenza 
c. Modified SIRS criteria met in patients presenting to the CHCO Main ED or 
North Campus UC with influenza 
d. Initial and peak adjusted heart rate in patients presenting to the CHCO Main 
ED or North Campus UC with influenza 
e. Oxygen saturation in patients presenting to the CHCO Main ED or North 
Campus UC with influenza 
f. 
Extrapulmonary complications in patients presenting to the CHCO Main ED or 
North Campus UC with ILI 
Definitions:  
Influenza like illness (ILI): child with temperature of ≥ 37.8⁰C and at least one of the 
following: cough, sore throat, runny nose or nasal congestion 
 
Influenza: child with respiratory test that is positive for influenza by PCR 
 
Moderate to severe influenza: child with influenza and one or more of the 
following criteria: 
1. fever > 39⁰C,  
2. presence of otitis media defined by AAP guideline criteria,  
3. lower respiratory tract infection (shortness of breath, pulmonary 
congestion, pneumonia, bronchiolitis, bronchitis, wheezing, croup), or  
4. serious extrapulmonary manifestations (e.g., myocarditis, encephalitis, 
seizure)(15). 
Mild influenza: child with ILI symptoms, but do not have any of the criteria for 
moderate to severe influenza 

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SIRS:  Defined as the presence of two or more of the following, one of which must be 
abnormal temperature or leukocyte count:  
1. core temperature <36 or >38.5°C 
2. tachycardia (or bradycardia in infants),  
3. tachypnea 
 
Modified SIRS criteria (18):  same definition as SIRS criteria excluding neutrophil 
criteria, i.e. the presence of two or more of the following, one of which must be abnormal 
temperature : 
1. core temperature <36 or >38.5°C 
2. tachycardia (or bradycardia in infants),  
3. tachypnea 
 
Tachycardia and tachypnea definitions by age:  
Age group 
Tachycardia 
Bradycardia 
Respiratory rate  
1 month-1 year  
>180 
<90 
>34 
2-5 years 
>140 
NA 
>22 
6-12 years 
>130 
NA 
>18 
 
B. Description of Population to be Enrolled:   
 
Population: 
Children 6 months to 8 years of age seeking evaluation and management of ILI at the 
Main CHCO ED or North Campus UC will be eligible for participation in the study.  The 
study will commence during the influenza season as determined by the department of 
microbiology and epidemiology at CHCO (the influenza season commences when there 
are 3 positive influenza PCR tests within a week).  The study will continue for 5 months 
following the start of the influenza season. 
 
Inclusion criteria: 
1) Age 6 months < 8 years 
2) Presentation to the CHCO Main ED or North Campus UC with signs and 
symptoms of ILI (temperature of >37.8⁰C and at least one of the following: cough, 
sore throat, runny nose or nasal congestion) 
3) Patients seen during the 2016-2017 influenza season 
Exclusion criteria: 
1) Respiratory symptom duration > 14 days 
2) Prior enrollment in study 
3) Nurse only visit 
 
C. Study Design and Research Methods   
 
 This will be a prospective observational cohort study conducted at the CHCO Main ED 
and North Campus UC.   

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Surveillance Methods: 
The study group will review the CHCO Main ED or North Campus UC visits for patients 
meeting study criteria presenting with ILI.  Screening will be conducted by designated 
professional research assistants (PRAs) at each site. The study team has a treatment 
relationship with potential subjects, since one of the co-investigators is an ED physician, 
thus enabling screening of potential patients. The parents/legal guardians of eligible 
patients will be approached for consent to obtain respiratory specimens for PCR testing, 
interviewed to obtain medical information pertaining to the current and future ILI visits, 
asked permission to obtain additional information (vaccination status, influenza 
vaccination type [LAIV] or IIV) and medical comorbidities) from the primary care provider, 
and to bank residual blood and respiratory samples.  A memory aid card will be provided 
to the family member upon discharge from the ED/UC setting as an aide memoire, and 
the medical chart will be reviewed for additional clinical and demographic information.  On 
day 14(+/-3) following the initial visit,  caregivers of all participants who test positive for  
influenza will be contacted by phone to provide additional follow-up information regarding 
child and parental absenteeism, additional healthcare visits, duration of illness.  
Additionally, a random sample of participants whose influenza test is negative in a 1 to 4 
ratio will be contacted for follow-up.  A second chart review will occur at this time for 
details regarding additional visits or admissions.  Data will be managed with REDCap 
(Research Electronic Data Capture) tools hosted at the University of Colorado (19) and 
exported to SAS 9.3 (Cary, NC) for statistical analyses.  
 
A flow diagram summarizing the study methods is shown in Figure 1.  
 

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Figure 1. Flow diagram summarizing methods for proposed surveillance study 
 
 
 
Specimen Testing:  
Nasal (NP) swabs will be obtained for testing by trained nurses/medical staff.  If a 
respiratory sample has already been collected as part of routine clinical care, this will 
replace the study NP swab, and no additional testing will be required.  Influenza testing 
will be conducted at the microbiology lab at CHCO.  Testing is conducted using the 
Cepheid Xpert® influenza real time RT- PCR. This test detects influenza A and influenza 
B and provides the influenza A 2009 H1N1 subtype. It is run daily during the influenza 
season, with most results available in 3 hours on average once specimens have been 
received by the lab. Our lab undergoes annual individualized quality control, with stable 
performance, the details of which can be provided upon request. This test has sensitivity 
of 100% and specificity of 95-100%, (depending on the influenza strain).  Specific data 
regarding the excellent sensitivity and specificity of the test is available at: 
http://www.cepheid.com/administrator/components/com_productcatalog/library-
files/1412ce637a3184a887a44f8e287b67ec-Xpert-Flu-Datasheet-US-0418-02.pdf. 

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Once testing has occurred, family members will be given a number to call (PRA phone 
number) if they would like to have results of the influenza PCR test.  If the flu test is being 
performed for clinical purposes we will use that result.  
 
Biobanking of Samples:  
We will obtain consent from parents/legal guardians regarding banking residual 
respiratory and blood samples obtained during routine clinical care.  All left-over blood 
(whole blood, serum, and plasma) samples collected for clinical purposes will be stored in 
the CHCO CTRC lab (depending on the assay and sample) in case repeat or additional 
testing is requested. These samples can be used for future research after they have been 
discharged from care.   
 
D.   Description, Risks and Justification of Procedures and Data Collection 
Tools: 
 
Description, risks and justification of procedures:  
Respiratory specimens will be collected using a nasopharyngeal (NP) FLOQSwab and 
placed in Universal Transport Media (Copan Diagnostics Inc., Murrieta, CA).  NP swabs 
will be collected for study purposes.  If a respiratory specimen has already been collected 
for clinical purposes during the ED or UC visit, these will be used for testing, and no 
additional testing will be required.   NP swabs, nasal washes or nasopharyngeal samples 
will be permitted for the study. This source is cleared by the FDA for the FA respiratory 
pathogen panel (RPP) and the collection method is standard clinical and research practice 
at our institution.  We have successfully used this system to collect leftover clinical 
specimens for a number of previous and ongoing studies.  Risks of the procedure are 
minimal, and include mild local discomfort at the time of specimen collection.   
 
Data collection tools:  
Study data will be collected and managed using REDCap (Research Electronic Data 
Capture). REDCap is a secure web application designed to support data capture for 
research studies, providing user-friendly web-based case report forms, real-time data 
entry validation (e.g. for data types and range checks), audit trails and a de-identified data 
export mechanism to common statistical packages (SPSS, SAS, Stata, R/S-Plus).  
 
The system was developed by a multi-institutional consortium which includes University of 
Colorado–Denver and was initiated at Vanderbilt University. The database is hosted at the 
University of Colorado–Denver Development and Informatics Service Center (DISC), 
which will be used as a central location for data processing and management. REDCap 
data collection projects rely on a thorough study-specific data dictionary defined in an 
iterative self-documenting process by all members of the research team with planning 
assistance from the DISC. This iterative development and testing process results in a 
well-planned data collection strategy for individual studies. REDCap also includes a 
powerful tool for building and managing online surveys. The research team can create 
and design surveys in a web browser and engage potential respondents using a variety of 
notification methods. REDCap is flexible enough to be used for a variety of types of 
research and provides an intuitive user interface for database and survey design and data 
entry. 
   

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Patients will be assigned a sequential study number for the database that will have no 
relationship to any patient identifying information.  The legend will be maintained until data 
editing is complete, and then the link will be destroyed.  During the study period, the 
legend will be stored in a secure manner in a locked room with limited access, and 
computerized data will be similarly maintained in a secure fashion by the study team at 
CHCO.  Data will only be publicly presented in aggregate form.  This minimizes the risks 
related to invasion of privacy and breach of confidentiality.      
E.   Potential Scientific Problems:   
A potential limitation of the study is potential selection bias due to the inability to test all 
patients who present with ILI to the ED.  This is due to a high volume of patients 
presenting to the ED, as shown in Table 1.  We will select patients based on age, restrict 
the season to once the influenza season has commenced, and will attempt to include all 
patients during this time period, which aims to avoid the skewing of data to more patients 
with co-morbidities or higher severity of illness who will undergo testing during routine 
clinical care. 
 
There is also a possibility for recall bias regarding vaccination status and other medical 
history obtained from the parents/legal guardians.  We will verify this information with the 
electronic medical record, which is linked to the CIIS.  The CIIS is a lifelong immunization 
record tracking system managed by the Colorado Department of Public Health and 
Environment (CDPHE). Approximately 85% of Colorado primary care practices utilize the 
registry. In addition, if vaccination status cannot be determined from the electronic medical 
record, a member of the study team will contact the primary care Physician (PCP) for 
vaccination information. The combination of verification from the PCP as well as the CIIS 
registry will increase the accuracy of influenza vaccination status. 
 
The study may have limited external validity and cannot provide population-based 
estimates of moderate to severe influenza, given its design.  
 
F.   Data Analysis Plan:   
For all study objectives, we will present data descriptively using frequencies for 
categorical variables and measures of central tendency for continuous variables. We will 
explore bivariable associations between moderate to severe versus mild influenza for 
covariates including demographic factors and clinical factors outlined above. Proportions 
will be compared using Chi-square test. Mean values will be compared using student’s t 
test for normally-distributed data, otherwise Wilcoxon-Rank-Sum test will be used.    
 
Aim #1/Primary Endpoint Analysis: We will use logistic regression to estimate odds ratios 
(and 95%CI) for hospitalization, adjusted for significant covariates at the level of P < 0.2 
on bivariable analysis; and other covariates selected a priori that could affect outcomes 
such as hospitalization (age group, high risk medical condition, vaccination status, 
influenza type).  We will verify to ensure statistical assumptions are met for each model.  
The intraclass correlation coefficient will be estimated and a multi-level model will be used 
if we need to account for multiple visits per child. If we use a multi-level model, the optimal 
covariance structure will be determined through the examination of information criteria 
statistics and graphical techniques.    
 
Aim #2/Secondary Endpoint #1-6 Analysis: We will use logistic regression to estimate 
each of our dichotomous secondary outcomes of interest, ICU admission, antibiotic, 

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antiviral use, adjusted for significant covariates at the level of P < 0.2 on bivariable 
analysis; and other covariates selected a priori that could affect outcomes such as 
hospitalization (age group, high risk medical condition, vaccination status, influenza type).  
We will verify to ensure statistical assumptions are met for each model. The intraclass 
correlation coefficient will be estimated and a multi-level model will be used if we need to 
account for multiple visits per child.   If we use a multi-level model, the optimal covariance 
structure will be determined through the examination of information criteria and graphical 
techniques.  We will also explore our secondary outcomes of interest expressed as 
continuous variables (number of recurrent visits to the ED, duration of absenteeism in 
days). We will use a log linear model to compare these variables between the mild versus 
moderate to severe influenza groups and will exponentiate the coefficients to yield 
geometric mean ratios.   
 
Aim #3/Secondary Endpoint #7 Analysis: An economic analysis will be conducted to 
compare the healthcare costs in the mild and moderate to severe influenza groups.  We 
will work with the finance department at CHCO to obtain charge data for each influenza-
related ED visit and hospitalization. Direct costs associated with healthcare utilization will 
be obtained by collecting hospital charge data and applying a cost to charge ratio to 
estimate costs.  Mean costs and standard deviations for each group will be determined 
and compared using t tests for normally distributed data, and presented as median (IQR) 
costs with analysis conducted using non parametric tests for non-normally distributed 
data.  Relative healthcare costs will be modeled on log-transformed data using linear 
regression or a generalized linear model, depending on the data distribution. 
 
Exploratory Objective #1-2/Exploratory Endpoints #1-2: In addition to the primary and 
secondary outcomes outlined above, we will also assess the odds ratios and 95% CI of 
several exploratory dichotomous outcomes –moderate to severe influenza, hospitalization, 
ICU admission, antibiotics and antiviral use among patients with IIV versus unvaccinated 
children using log linear regression in a manner similar to the above specific aims.  For 
continuous variables (duration of fever, number of days of absenteeism), we will use a log 
linear model as described for our prior secondary outcomes.    
We will conduct a similar analysis as outlined above for patients with influenza like illness 
who test negative for influenza using the clinical severity outcome measures outlined.  
 
Exploratory Objective #3/Exploratory Endpoint#3: We will determine the predictive value 
for hospitalization, ICU admission and having PCR-confirmed influenza of duration of 
fever, SIRS criteria, adjusted heart rate, respiratory rate and oxygen saturation using 
logistic regression models with two-way interactions between factors in the model when 
needed.  We will use the Brier score to assess overall model performance and the c 
statistic to assess discriminative ability.  In addition to logistic regression, we will explore 
machine learning methods for the predictive modeling of these three outcomes.  The 
predictive value of peak temperature will also be assessed using a logistic regression 
model.   
 
To compare temperature trajectories between hospitalized and non-hospitalized, we will 
use a linear mixed model.  This will allow us to use all of the longitudinal temperature 
measurements to measure the mean temperature trajectory of patients in one group (e.g. 
hospitalized patients) compared to the other (e.g. non-hospitalized patients).  We will 
accomplish this by including an interaction term between time and hospitalization status, 
which will give us hospitalization status-specific trajectories.  We will do this for each 

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dichotomous outcome: hospitalization, ICU status, influenza diagnosis.  This method is 
preferred over subgroup analysis because it will optimize statistical power. 
 
Two sensitivity analyses will be conducted.  Firstly, analyses will be restricted to patients 
presenting to the main CHCO ED. Secondly, to further evaluate whether temperature > 
39⁰C is a predictor of healthcare utilization or poorer outcomes, an analysis of each of the 
secondary outcome measures will be conducted.  Firstly, we will compare all moderate to 
severe versus mild influenza cases.  If these reach statistical significance with an odds 
ratio >1, we will then repeat the analysis with a definition of moderate to severe influenza 
as solely temperature > 39⁰C.  
 
 
Power and sample size calculations: 
Using historical data from our institution, a sample size of 408 patients (of which we 
assume 30% have mild flu and 70% have moderate/severe flu) will achieve 80% power at 
a 0.05 significance level to detect an odds ratio of approximately 2 for hospitalization 
among the moderate/severe compared to the mild cases, accounting for the inclusion of 
correlated covariables in our multivariable model.  Assuming that 25% of patients tested 
will be influenza positive (19) during the influenza season; we will need to test 
approximately 1632 subjects (Figure 1).  A sample size of 151 patients with the same 
assumptions, power and significance level will detect an odds ratio of 3 for hospitalization 
among the moderate/severe compared with mild cases, so 604 subjects will need to be 
tested.   
 
Using these sample size estimates (using sample size of 408), assuming 50% vaccination 
status, and a ratio of IIV to LAIV receipt among vaccinated individuals of 9:1, we will 
have 80% power at a 0.05 significance level to detect an odds ratio of 3 for hospitalization 
among the mild versus moderate to severe cases, among patients vaccinated with IIV. 
 We won't be adequately powered to detect a statistically significant difference for LAIV 
recipients.  

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Figure 1. Flowchart to produce the analysis sample* 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
G.  Summarize Knowledge to be Gained:   
Influenza is an important public health and clinical challenge, and contributes to a 
significant burden of disease among children.  Understanding and validating the 
relationship between moderate to severe influenza and clinically relevant endpoints such 
as ED visits, hospitalizations and ICU admissions is critical to establishing relevant 
surrogate markers of clinical and public health outcomes.  If shown to be clinically 
relevant, this definition of moderate to severe influenza can be an important endpoint for 
assessing influenza vaccine effectiveness.  
 
 H. References: 
 
1. 
Ampofo K, Gesteland PH, Bender J, Mills M, Daly J, Samore M, et al. 
Epidemiology, complications, and cost of hospitalization in children with laboratory-
confirmed influenza infection. Pediatrics. 2006;118(6):2409-17. 
2. 
Coffin SE, Zaoutis TE, Rosenquist AB, Heydon K, Herrera G, Bridges CB, et al. 
Incidence, complications, and risk factors for prolonged stay in children hospitalized with 
community-acquired influenza. Pediatrics. 2007;119(4):740-8. 
3. 
Dawood FS, Fiore A, Kamimoto L, Bramley A, Reingold A, Gershman K, et al. 
Burden of seasonal influenza hospitalization in children, United States, 2003 to 2008. The 
Journal of pediatrics. 2010;157(5):808-14. 
*N’s are conservative estimates based on data from Children’s Hospital Colorado collected during the 2014-2015 flu season 
**Primary outcome of interest 
Children age 6 months – 8 years presenting to the ED or Urgent Care 
in December 2016 – April 2017 with acute respiratory illness 
N ~ 1600 
Flu + test: N ~400 
Flu - test: N ~ 1200 
Moderate/severe 
influenza: N ~ 280 
Mild influenza: N ~ 
120 
Hospitalized** 
100 
  
Not 
Hospitalized 
180 
Not 
Hospitalized 
120 
Hospitalized** 
20  

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COMIRB# 16-1785 
4. 
Schrag SJ, Shay DK, Gershman K, Thomas A, Craig AS, Schaffner W, et al. 
Multistate surveillance for laboratory-confirmed, influenza-associated hospitalizations in 
children: 2003-2004. The Pediatric infectious disease journal. 2006;25(5):395-400. 
5. 
Izurieta HS, Thompson WW, Kramarz P, Shay DK, Davis RL, DeStefano F, et al. 
Influenza and the rates of hospitalization for respiratory disease among infants and young 
children. The New England journal of medicine. 2000;342(4):232-9. 
6. 
Neuzil KM, Mellen BG, Wright PF, Mitchel EF, Jr., Griffin MR. The effect of 
influenza on hospitalizations, outpatient visits, and courses of antibiotics in children. The 
New England journal of medicine. 2000;342(4):225-31. 
7. 
Wong JY, Kelly H, Cheung CM, Shiu EY, Wu P, Ni MY, et al. Hospitalization 
Fatality Risk of Influenza A(H1N1)pdm09: A Systematic Review and Meta-Analysis. 
American journal of epidemiology. 2015;182(4):294-301. 
8. 
Osterholm MT, Kelley NS, Sommer A, Belongia EA. Efficacy and effectiveness of 
influenza vaccines: a systematic review and meta-analysis. The Lancet Infectious 
diseases. 2012;12(1):36-44. 
9. 
Cowling BJ, Chan KH, Feng S, Chan EL, Lo JY, Peiris JS, et al. The effectiveness 
of influenza vaccination in preventing hospitalizations in children in Hong Kong, 2009-
2013. Vaccine. 2014;32(41):5278-84. 
10. 
Menniti-Ippolito F, Da Cas R, Traversa G, Santuccio C, Felicetti P, Tartaglia L, et 
al. Vaccine effectiveness against severe laboratory-confirmed influenza in children: results 
of two consecutive seasons in Italy. Vaccine. 2014;32(35):4466-70. 
11. 
Ferdinands JM, Olsho LE, Agan AA, Bhat N, Sullivan RM, Hall M, et al. 
Effectiveness of influenza vaccine against life-threatening RT-PCR-confirmed influenza 
illness in US children, 2010-2012. The Journal of infectious diseases. 2014;210(5):674-83. 
12. 
Hadler JL, Baker TN, Papadouka V, France AM, Zimmerman C, Livingston KA, et 
al. Effectiveness of 1 dose of 2009 influenza A (H1N1) vaccine at preventing 
hospitalization with pandemic H1N1 influenza in children aged 7 months-9 years. The 
Journal of infectious diseases. 2012;206(1):49-55. 
13. 
Molinari NA, Ortega-Sanchez IR, Messonnier ML, Thompson WW, Wortley PM, 
Weintraub E, et al. The annual impact of seasonal influenza in the US: measuring disease 
burden and costs. Vaccine. 2007;25(27):5086-96. 
14. 
Ambrose CS, Wu X, Caspard H, Belshe RB. Efficacy of live attenuated influenza 
vaccine against influenza illness in children as a function of illness severity. Vaccine. 
2014;32(43):5546-8. 
15. 
Jain VK, Rivera L, Zaman K, Espos RA, Jr., Sirivichayakul C, Quiambao BP, et al. 
Vaccine for prevention of mild and moderate-to-severe influenza in children. The New 
England journal of medicine. 2013;369(26):2481-91. 
16. 
Thomas RE, Russell ML, Lorenzetti DL. Systematic review of interventions to 
increase influenza vaccination rates of those 60 years and older. Vaccine. 
2010;28(7):1684-701. 
17. 
Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research 
electronic data capture (REDCap)--a metadata-driven methodology and workflow process 
for providing translational research informatics support. Journal of biomedical informatics. 
2009;42(2):377-81. 
18. 
Grohskopf LA, Sokolow LZ, Olsen SJ, Bresee JS, Broder KR, Karron RA. 
Prevention and Control of Influenza with Vaccines: Recommendations of the Advisory 
Committee on Immunization Practices, United States, 2015-16 Influenza Season. MMWR 
Morbidity and mortality weekly report. 2015;64(30):818-25. 
 

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Appendix A data variables to be collected  
 
PHI: 
Study ID:  
 
 
 
MRN:   
 
 
HAR:  
Visit Date:  
 
Child’s last name, first name:  
Primary, secondary, additional Caregiver name, relationship to child, phone number, number of 
days per week working   
  
ZIP 
 
 
 County: 
 
 
 
 State: 
PCP name(s) and number  
 
 
 
 
Date of birth:  
 
Age: 
  
______years _____months _______days 
 
Demographic and clinical information  
Visit type 
Sex 
Race:  Ethnicity:  
Attends daycare/school :  
Height (cm): 
 
 Weight (kg): 
 
BMI: 
Second hand smoke exposure 
Reason for visit  
 
Symptoms 
Symptom onset and type  
Fever onset and number of days of fever   
medical conditions 
influenza vaccination status 
high risk medical comorbidities: 
 
Vital Signs 
Initial Temperature (C):   Initial Heart rate:     Initial Respiratory rate:    Initial oxygen saturation (on 
room air): 
Initial systolic blood pressure:  Initial diastolic blood pressure: 
Highest temperature in ED (C)::    Heart rate during this time:  
Initial PEWS:  
 
Highest PEWS recorded in ED:   
Meets SIRS criteria? Yes no   
Signs: 
Diagnosis 
 
Test results 
Influenza test results 
Bacterial pathogens: source:  date of test:  result: 
Viral pathogens: source: date of test: result: 
Radiology:  CXR CT chest other:   result: 
Other lab results: date: type: CBC with differential, CRP, ESR, PCT result: 
Treatment  
oseltamivir or other antiviral 
antibiotics 
steroids 
other treatments 
 
 
Outcomes 
 Sent home from ED  Observation  Hospitalized death other _____ 
Hospital length of stay, days _________  
Admitted to ICU? yes no  

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ICU length of stay,days ____________  
Reason for ICU admission: 
Oxygen use, duration   
 
Heated high flow use, duration 
BiPAP use, duration (days) 
CPAP use, duration (days) 
Intubation, duration (days) 
ECMO use, duration (days) 
Death 
 
Follow up:  
Child absenteeism and number of days 
Parent/caregiver absenteeism and number of days 
Duration of illness 
Duration of fever 
Antipyretic use