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