Title :
Early detection of vasovagal syncope in tilt-up test with hemodynamic and autonomic study
Author :
Cheng, Chun-An ; Chu, Hsin ; Chiu, Hung-Wen
Author_Institution :
Grad. Inst. of Biomed. Inf., Taipei Med. Univ., Taiwan
Abstract :
The diagnosis of vasovagal syncope (VVS) is according to history, tilt table test and blood pressure change with postural stress. We collected 30 patients below 55 years-old, received tilt table test without pharmacological challenge from 2005 to 2010. Due to this disorder is the heterogeneity, multiple factor. The pathophysological pathway was not fully understood. We used logistic regression and neural network to evaluate variables during baseline and first 3 minutes tilt table test to early detect vasovagal syncope with tilt table test. We found using parameters of baseline heart rate, body mass index and mean blood pressure, cardiac index, left ventricular work index during 3 minutes of tilt up test for neural network model, the model revealed good train and test performance (accuracy:95.5%) with good sensitivity and specificity.
Keywords :
cardiology; haemodynamics; medical computing; neural nets; patient diagnosis; regression analysis; autonomic study; baseline heart rate; blood pressure change; body mass index; cardiac index; early vasovagal syncope detection; hemodynamic study; left ventricular work index; logistic regression; mean blood pressure; neural network; postural stress; tilt table test; tilt-up test; Artificial neural networks; Heart rate; Hemodynamics; Indexes; Neurons; Sensitivity;
Conference_Titel :
Computing in Cardiology, 2011
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4577-0612-7