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Noninvasive predictor of HeartMate XVE pump failure by neural network and waveform analysis.

Authors :
Mason NO
Bishop CJ
Kfoury AG
Lux RL
Crawford C
Horne BD
Stoker S
Clayson SE
Rasmusson BY
Reid BB
Source :
ASAIO journal (American Society for Artificial Internal Organs : 1992) [ASAIO J] 2010 Jan-Feb; Vol. 56 (1), pp. 1-5.
Publication Year :
2010

Abstract

Patients increasingly require longer durations of left ventricular assist device (LVAD) therapy. Despite a recent trend toward continuous flow VADs, the HeartMate XVE is still commonly used, but its longevity remains a significant limitation. Existing surveillance methods of pump failure often give inconclusive results. XVE electrical current waveforms were collected regularly (2001-2008) and sorted into quartiles according to number of days until pump failure (Q1, 0-34; Q2, 34-160; Q3, 160-300; and Q4, 300-390 days). Thoratec waveform files were converted into text files. The 10-second electrical current, voltage waveform was identified and isolated for analysis. Waveforms were analyzed by principal component analysis (PCA) and with a fast Fourier transform. Quartiles were compared with analysis of variance (ANOVA). Waveforms (n = 454) were collected for 21 patients with failed pumps. An artificial neural network was used to predict pump failure within 30 days from the waveform characteristics identified though signal processing.

Details

Language :
English
ISSN :
1538-943X
Volume :
56
Issue :
1
Database :
MEDLINE
Journal :
ASAIO journal (American Society for Artificial Internal Organs : 1992)
Publication Type :
Academic Journal
Accession number :
20019597
Full Text :
https://doi.org/10.1097/MAT.0b013e3181c440f3