Comparison of computational algorithms applied on transthoracic impedance waveforms to predict head-up tilt table testing outcome

The goal of the present study was to develop and evaluate new algorithms for the prediction of the outcome of a head-upright tilt test (HUTT). Using transthoracic impedance and its first derivative, we attempted to determine if indexes computed on these waveforms could detect a positive outcome to a...

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Bibliographic Details
Published in:Computers in biology and medicine 2006-03, Vol.36 (3), p.225-240
Main Authors: Schang, D., Bellard, E., Plantier, G., Dupuis, J.M., Victor, J., Leftheriotis, G.
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Algorithms
Artificial neural networks
Cardiography
Cardiography, Impedance
Computer applications
Diagnosis
Engineering Sciences
Female
Head up tilt test
Health care
Humans
Impedance cardiography
Male
Medicine
Middle Aged
Neural networks
Neural Networks (Computer)
Predictive Value of Tests
Principal Component Analysis
Prospective Studies
Reproducibility of Results
Retrospective Studies
Sensitivity and Specificity
Signal and Image processing
Signal processing
Syncope
Syncope - diagnosis
Tilt-Table Test
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Summary:The goal of the present study was to develop and evaluate new algorithms for the prediction of the outcome of a head-upright tilt test (HUTT). Using transthoracic impedance and its first derivative, we attempted to determine if indexes computed on these waveforms could detect a positive outcome to a 70°–45 min HUTT with reliable sensitivity and specificity. The methods were evaluated retrospectively in a group of 70 patients and validated prospectively in a group of 59 patients. The best detector obtained used a neural network. It compares very favorably with published results for other syncope detectors.
ISSN:0010-4825
1879-0534
DOI:10.1016/j.compbiomed.2004.09.004