A survival prediction model of hemorrhagic shock in rats using a logistic regression equation.
Hemorrhagic shock is a common cause of death in emergency rooms. Since the symptoms of hemorrhagic shock occur after shock has considerably progressed, it is difficult to diagnose shock early. The purpose of this study was to improve early diagnosis of hemorrhagic shock using a survival prediction model in rats. We measured ECG, blood pressure, respiration and temperature in 45 Sprague-Dawley rats, and then obtained a logistic regression equation predicting survival rates. Area under the ROC curves was 0.99. The Hosmer-Lemeshow goodness-of-fit chi-square was 0.86 (degree of freedom=8, p=0.999). Applying the determined optimal boundary value of 0.25, the accuracy of survival prediction was 94.7%.
Lee
Tak Hyung
TH
Graduate Program in Biomedical Engineering, Yonsei University, Seoul, Korea. picf@yuhs.ac
Lee
Ju Hyung
JH
Chung
Sang Won
SW
Noh
Hyung Wook
HW
Shim
Young Woo
YW
Kim
Deok Won
DW
D000818:Animals; D001698:Biomedical Engineering; D004195:Disease Models, Animal; D006801:Humans; D016015:Logistic Models; D008297:Male; D008954:Models, Biological; D008991:Monitoring, Physiologic; D011379:Prognosis; D051381:Rats; D017207:Rats, Sprague-Dawley; D012771:Shock, Hemorrhagic / Q000175:diagnosis* / Q000503:physiopathology