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![Page 1: Community Validation of Influenza-like Illness as a Predictor of Influenza Jonathan L. Temte, MD/PhD & Alexis Eastman, MS-2 University of Wisconsin School.](https://reader035.fdocuments.net/reader035/viewer/2022062722/56649f305503460f94c4b01c/html5/thumbnails/1.jpg)
Community Validation of
Influenza-like Illness as a Predictor of
InfluenzaJonathan L. Temte, MD/PhD & Alexis Eastman, MS-2
University of Wisconsin School of Medicine and Public Health
Peter A. Shult, PhD, Carol J. Kirk & Mary Wedig
Wisconsin State Laboratory of Hygiene
Madison, Wisconsin
![Page 2: Community Validation of Influenza-like Illness as a Predictor of Influenza Jonathan L. Temte, MD/PhD & Alexis Eastman, MS-2 University of Wisconsin School.](https://reader035.fdocuments.net/reader035/viewer/2022062722/56649f305503460f94c4b01c/html5/thumbnails/2.jpg)
Influenza-like Illness
Definition Fever of 100oF (37.8oC) or higher Cough and/or Sore Throat Not due to any other illness
Utility Simple and elegant Clinically relevant Easily ascertained
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ILI uses
Clinical identification of influenza infection High PPV from research protocols
Adults Children
Age 65+
Age 25-64
Age 5-24
Age 0-4
ILI in WisconsinOct. 2007 thtough Sept. 2008
Community surveillance of influenza
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Factors Affecting Symptoms
AgeAge
ImmuneImmuneStatusStatus
UnderlyingUnderlyingDiseaseDisease
Viral StrainViral Strain
Viral SubtypeViral Subtype
Host Factors Viral Factors
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Purpose of Study
Review the contents of a large database Surveillance data emerging from a
partnership between a public health laboratory and primary care clinicians
Symptoms and virus identification
Validate ILI for influenza infection Community—not research—perspective
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The Surveillance Database
Partnership of WSLH and UW-DFM since 1994 Major modification of symptom check off in 1997
Opportunistic sampling with “fee-exempt” virus culture physicians obtain specimens, record demographic and symptom
data, sample is transported to WSLH by courier. Standard culture methods with isolation rate = 45% Limited, de-identified data used
1997-2007 IRB approved
3,796 episodes of acute respiratory illness care available
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Preferential Collection from
Children and Young Adults
0
50
100
150
200
250
300
350
0 5 10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
Age of Patient
No
. o
f S
pecim
en
s Range: 0 – 103 years
55.6% female
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PredictorsWorking definition of ILI
F+CorST F = Fever on symptom checklist
No requirement for level or documentation
CorST = Cough and/or Sore Throat
sF+CorST (includes seasonality) December through March Period with > 90% of influenza cases
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Outcomesinfluenza isolation
Paradigm 1: “clinical primary care” Influenza (+) vs. all other specimens
Influenza = 1230 Non-influenza + no virus isolated = 2566
Paradigm 2: “ideal virus capture” Influenza (+) vs. non-influenza virus (+)
Influenza = 1230 Non-influenza = 523
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Distribution of outcomes
Reference
population
Season
included
Criteria
used
Influenza (+)
Influenza (-)
All ARI specimens
Yes
sF+CorST (+)
1020 1034
sF+CorST (-)
210 1532
No
sF+CorST (+)
1082 1529
sF+CorST (-)
148 1037
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Reference
population
Season
included
Criteria
used
Influenza (+)
Influenza (-)
Virus (+) specimens
Yes
sF+CorST (+)
1020 188
sF+CorST (-)
210 335
No
sF+CorST (+)
1082 302
sF+CorST (-)
148 221
Distribution of outcomes
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Performance Characteristics
Criteria Referencepopulation
OR
flu
Sens Spec PPV NPV
F+CorST All ARI 4.96 0.88 0.40 0.41 0.88
F+CorST Virus (+) 5.25 0.88 0.42 0.78 0.60
sF+CorST All ARI 7.20 0.83 0.60 0.50 0.88
sF+CorST Virus (+) 8.66 0.83 0.64 0.84 0.62
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Additional Fiddlingassessing effects of age
Concentrate on seasonal data Clinician informed by surveillance
Concentrate on virus (+) specimens Symptomatic patient Early in illness Collection technique good
Concentrate on age categories 0-4 5-24 25-64 65+
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Effects of age(reference age = 25-64 years)Binary logistic regression via Minitab –
Release 13.1Factor Odds Ratio 95% CI
sF+CorST 7.55* 5.81 – 9.80
0-4 years 0.10* 0.07 – 0.14
5-24 years 1.21 0.90 – 1.65
25-64 years reference
65+ years 1.67 0.86 – 3.25
* P<0.001
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What about little kids?the percent of ILI cases due to:
Virus 0-4 years 5+ years
Influenza 34.8 84.7
Adenovirus 6.6 3.2
Parainfluenza 14.4 3.3
Rhinovirus 1.7 3.7
RSV 37.0 1.4
Herpes simplex 1.1 2.0
Enterovirus 2.9 0.8
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Conclusions ILI (F+CorST) performs well
Public health tool for surveillance Early detection of influenza High sensitivity ( 0.88) Limited by low specificity (0.40)
but fined tuned by virological methods
ILI (sF+CorST) performs well Clinician tool for diagnosis of influenza Informed by public health surveillance High PPV (0.84); moderate NPV Excluding young children raises PPV to 0.90
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Conclusions
Influenza is the primary cause of ILI in patients age 5+ years
Many viruses can cause ILI in children 0-4 years of age. ILI should not be used for diagnosis alone in this group.
ILI for predicting influenza infection has been validated in a primary care, community-based population
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Final WordsIf influenza is in the community and
your patient is over 4 years oldIs it influenza?
F+CorST
“Of Course”
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Acknowledgements
Wisconsin Primary Care Clinicians UW-DFM residency clinics Numerous private physicians
UW-DFM Summer Student Research and Clinical Assistantship Program Ms. Alexis Eastman
Wisconsin State Laboratory of Hygiene
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Additional Material
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Basic Characteristics of Surveillance System
Mean age of patient = 26.6 years Range [ 0 to 103 years]
Sex Female = 55.6% Male = 44.4%
Time between illness onset and collection Mean = 3.86 days Median = 2 days
Rate of virus isolation = 44.6%
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Specimens Collected during
“Respiratory Virus” Season
0
50
100
150
200
250
300
350
0 4 8 12 16 20 24 28 32 36 40 44 48 52
Weeks after July 1st
Nu
mb
er
of
Sp
ecim
en
s
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Collection Day(Monday through Thursday
Preferred)
0
5
10
15
20
25
SUN MON TUE WED THU FRI SAT
% o
f S
pec
imen
s
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Most SpecimensCollected at Optimal Time
0102030405060708090
100
0 3 6 9 12 15 18 21 24 27 30
Days after Onset of Illness
Cu
mu
lati
ve P
erce
nta
ge
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Percent of Specimens with Positive Virus
Isolation
0
0.1
0.2
0.3
0.4
0.5
0.6
0 1 2 3 4 5 6 7
Days after Onset of Illness
% p
osit
ive