Abstract
Background
Early, rapid, and accurate identification of those patients who have severe influenza
is important for emergency physicians. Influenza viral load, which has been proposed
as a predictor of severe influenza, could be useful in facilitating decision making
of resource use. We aimed to derive a clinical prediction rule to indicate probability
for inpatient hospitalization for patients with influenza, which includes influenza
viral load in addition to other clinical information commonly collected in the emergency
department (ED).
Methods
We conducted a 3-year prospective cohort study (2007-2009) of patients with probable
influenza infection as suspected by the emergency physician from 3 study sites. Eligible
patients were those with excess nasopharyngeal aspirate samples. Influenza viral load
was measured using reverse transcription polymerase chain reaction and electrospray
ionization mass spectrometry. Clinical information including demographics, underlying
illness, vaccination history, hospitalization, and results from clinical laboratory
were abstracted from electronic patient records and questionnaires. The prediction
rule for hospitalization was derived by the recursive partitioning algorithm (decision
tree–type approach) and evaluated by internal 10-fold cross-validation for performance
characteristics.
Results
Of 424 ED patients with nasopharyngeal aspirates, 146 infected with influenza were
enrolled (median age, 10 years [interquartile range, 4-26]; race, 55% African American;
median inpatient length of stay, 3 days [interquartile range, 1-4]; high viral load
group [defined as >2.5 million genome copies/mL], 34%). Predictors for hospitalization included underlying
illness, age, influenza viral load level, and vaccination history (c statistics, 0.84; sensitivity, 83%; specificity, 76%).
Conclusions
The clinical prediction rule incorporating influenza viral load into the clinical
information was indicative of hospitalization and merits further evaluation for determination
of ED resource use for patients with influenza.
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Article Info
Publication History
Published online: February 04, 2013
Accepted:
October 16,
2012
Received in revised form:
October 10,
2012
Received:
August 28,
2012
Footnotes
☆This manuscript has been presented at Society of Academic Emergency Medicine annual meeting; Phoenix, AZ; June 2010.
☆☆The research grant was supported by Middle Atlantic RCE Program, National Institute of Allergy and Infectious Diseases/National Institutes of Health ( 5U54AI057168 ) and Chang Gung Memorial Hospital ( CMRPCMRPG2B0271 ).
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© 2013 Elsevier Inc. Published by Elsevier Inc. All rights reserved.
