Rapid screening for influenza using a multivariable logistic regression model to save labor at a clinic in Iwaki, Fukushima, Japan.
To lighten the workload of health care professionals, we conducted a clinical test of a newly developed automated infection screening system using a multivariable logistic regression model. The system was tested with 44 influenza patients and 45 healthy control subjects based on 3 vital signs: facial temperature, heart rate and respiratory rate. The system showed a high accuracy for distinguishing influenza patients from control subjects within 15 seconds.
Department of Management System Engineering, Tokyo Metropolitan University, Hino, Tokyo, Japan.
Vinh Quang
VQ
Nguyen
Takasaka Clinic, Iwaki, Fukushima, Japan.
Shigeto
S
Abe
Department of Management System Engineering, Tokyo Metropolitan University, Hino, Tokyo, Japan.
Guanghao
G
Sun
Department of Management System Engineering, Tokyo Metropolitan University, Hino, Tokyo, Japan.
Ayumu
A
Matsuoka
Virus Research Center, Clinical Research Division, Sendai Medical Center, National Hospital Organization, Sendai, Japan.
Hidekazu
H
Nishimura
Research Institute, National Defense Medical College, Tokorozawa, Saitama, Japan.
Masayuki
M
Ishihara
Department of Management System Engineering, Tokyo Metropolitan University, Hino, Tokyo, Japan. Electronic address: tmatsui@sd.tmu.ac.jp.
Takemi
T
Matsui
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001831:Body Temperature; D002648:Child; D015510:Clinical Medicine / Q000379:methods*; D005260:Female; D006339:Heart Rate; D006801:Humans; D007251:Influenza, Human / Q000175:diagnosis* / Q000473:pathology; D007564:Japan; D016015:Logistic Models; D008297:Male; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D056152:Respiratory Rate; D013997:Time Factors; D016526:Workload; D055815:Young Adult
Classification model; Nuclear disaster; Vital sign; Workload