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.
Original language | English |
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Title of host publication | Computing in Cardiology |
Pages | 529-532 |
Number of pages | 4 |
Volume | 38 |
Publication status | Published - 2011 |
Event | Computing in Cardiology 2011, CinC 2011 - Hangzhou, China Duration: Sept 18 2011 → Sept 21 2011 |
Other
Other | Computing in Cardiology 2011, CinC 2011 |
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Country/Territory | China |
City | Hangzhou |
Period | 9/18/11 → 9/21/11 |
ASJC Scopus subject areas
- Computer Science Applications
- Cardiology and Cardiovascular Medicine