Noninvasive predictor of HeartMate XVE pump failure by neural network and waveform analysis.
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.
Mason
Nathanael O
NO
Utah Artificial Heart Program, Intermountain Medical Center part of Intermountain Healthcare, Murray, Utah, USA. nathan.mason@imal.org
Bishop
Corey J
CJ
Kfoury
Abdallah G
AG
Lux
Robert L
RL
Crawford
Caleb
C
Horne
Benjamin D
BD
Stoker
Sandi
S
Clayson
Stephen E
SE
Rasmusson
Brad Y
BY
Reid
Bruce B
BB
D004868:Equipment Failure; D019544:Equipment Failure Analysis / Q000379:methods*; D005260:Female; D006353:Heart-Assist Devices; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D025341:Principal Component Analysis