Influenza is a highly infectious viral disease,
which occurs epidemically almost every winter in Japan. Rapid screening
of patients with suspected influenza in places of mass gathering is important
to delay or prevent transmission of the infection. The aim of this study was to
assess the effectiveness of our newly developed infection screening system
that employed vital signs and percutaneous
oxygen saturation (SpO2) as parameters in a clinical setting.
Methods: Since SpO2 accurately reflects respiratory status during
influenza virus infection, we upgraded our previous system by adding SpO2 as a new parameter to improve the screening accuracy. This system instantly
measures SpO2 and vital signs (i.e.,
heart rate, respiration rate, and facial temperature), which automatically
detects infected individuals via a neural network-based nonlinear discriminant
function using these derived parameters. We tested the system on 45 patients
with seasonal influenza (35.8℃ < body temperature < 40.0℃, 18-35
years) and 64 normal control subjects (35.0℃ < body temperature < 37.5℃,
18-30 years) at Japan Self-Defense Central Hospital in 2012. Results: The
system identified 40/45 patients with influenza and 60/64 normal control
subjects, and provided sensitivity, specificity, and positive and negative predictive value (PPV, NPV) of 88.8%, 93.8%, 90.9%, and 92.3%, respectively. By including
SpO2 as a screening parameter, we achieved superior sensitivity
and NPV compared to that reported in our previous paper (sensitivity = 88%; NPV
= 82%). Conclusions: Our results suggest that SpO2 is a good
screening parameter that improves the accuracy of infection screening. The
proposed system has the potential to efficiently identify infected individuals,
thereby delaying or preventing the spread of infection during epidemic
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