title: Continuous Monitoring of Aortic Valve Opening in Rotary Blood Pump Patients.
abstract: Rotary blood pumps (RBPs) typically support the left ventricle by pumping blood from the ventricle to the aorta, partially bypassing the aortic valve (AV). Monitoring the AV opening during RBP support would provide important information about cardiac-pump interaction. However, currently this information is not continuously available. In this study, an algorithm to determine AV opening using available pump signals was evaluated in humans.
  
  
  
  Pump speed changes were performed in 15 RBP patients to elicit opening of the AV. Simultaneously to pump data recordings, the AV was continuously monitored using echocardiography. The algorithm, which classifies the AV state utilizing three features (skewness, kurtosis, and crest factor) calculated from the pump flow waveform, was compared to echocardiography by using cross-validation analysis. Additionally, numerical simulation was used to evaluate effects of different pump characteristics and cannula length, as well as mitral valve insufficiency on the AV opening detection method.
  
  
  
  More than 7000 heart beats were analyzed. The correct classification rate using the developed algorithm was 91.1% (sensitivity 91.0%, specificity 91.2%). Numerical simulations showed that the flow waveform shape used for AV opening detection is preserved under the different conditions studied.
  
  
  
  This study demonstrates that the AV opening can be reliably detected in RBP patients using available pump data.
  
  
  
  Once implemented in RBP controllers, this method will provide a novel tool to improve the management of RBP patients, particularly for adjustments of the pump speed and flow and for the evaluation of the assisted cardiac function.
authors.forename: Marcus
authors.initials: M
authors.lastname: Granegger
authors.forename: Marco
authors.initials: M
authors.lastname: Masetti
authors.forename: Ravi
authors.initials: R
authors.lastname: Laohasurayodhin
authors.forename: Thomas
authors.initials: T
authors.lastname: Schloeglhofer
authors.forename: Daniel
authors.initials: D
authors.lastname: Zimpfer
authors.forename: Heinrich
authors.initials: H
authors.lastname: Schima
authors.forename: Francesco
authors.initials: F
authors.lastname: Moscato
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001021:Aortic Valve / Q000502:physiology*; D003198:Computer Simulation; D005260:Female; D006353:Heart-Assist Devices; D006439:Hemodynamics; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods*; D011446:Prospective Studies; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult