TITLE:
A neural network-based infection screening system that uses vital signs and percutaneous oxygen saturation for rapid screening of patients with influenza
AUTHORS:
Guanghao Sun, Yukiya Hakozaki, Shigeto Abe, Osamu Takei, Takemi Matsui
KEYWORDS:
Screening; Infection; Influenza; Neural Network; Vital Signs; SpO2
JOURNAL NAME:
Health,
Vol.5 No.8E,
August
20,
2013
ABSTRACT: Objective:
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℃ 2 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
seasons.