Literature DB >> 29088023

Accelerometer Detects Pump Thrombosis and Thromboembolic Events in an In vitro HVAD Circuit.

Itai Schalit1,2, Andreas Espinoza3, Fred-Johan Pettersen4, Amrit P S Thiara5, Hilde Karlsen1, Gro Sørensen5, Erik Fosse1,2, Arnt E Fiane2,5, Per S Halvorsen1.   

Abstract

Pump thrombosis and stroke are serious complications of left ventricular assist device (LVAD) support. The aim of this study was to test the ability of an accelerometer to detect pump thrombosis and thromboembolic events (TEs) using real-time analysis of pump vibrations. An accelerometer sensor was attached to a HeartWare HVAD and tested in three in vitro experiments using different pumps for each experiment. Each experiment included thrombi injections sized 0.2-1.0 mL and control interventions: pump speed change, afterload increase, preload decrease, and saline bolus injections. A spectrogram was calculated from the accelerometer signal, and the third harmonic amplitude was used to test the sensitivity and specificity of the method. The third harmonic amplitude was compared with the pump energy consumption. The acceleration signals were of high quality. A significant change was identified in the accelerometer third harmonic during the thromboembolic interventions. The third harmonic detected thromboembolic events with higher sensitivity/specificity than LVAD energy consumption: 92%/94% vs. 72%/58%, respectively. A total of 60% of thromboembolic events led to a prolonged third harmonic amplitude change, which is indicative of thrombus mass residue on the impeller. We concluded that there is strong evidence to support the feasibility of real-time continuous LVAD monitoring for thromboembolic events and pump thrombosis using an accelerometer. Further in vivo studies are needed to confirm these promising findings.

Entities:  

Mesh:

Year:  2018        PMID: 29088023     DOI: 10.1097/MAT.0000000000000699

Source DB:  PubMed          Journal:  ASAIO J        ISSN: 1058-2916            Impact factor:   2.872


  2 in total

1.  A New Mathematical Numerical Model to Evaluate the Risk of Thrombosis in Three Clinical Ventricular Assist Devices.

Authors:  Yuan Li; Hongyu Wang; Yifeng Xi; Anqiang Sun; Xiaoyan Deng; Zengsheng Chen; Yubo Fan
Journal:  Bioengineering (Basel)       Date:  2022-05-27

Review 2.  Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management.

Authors:  Chayakrit Krittanawong; Albert J Rogers; Kipp W Johnson; Zhen Wang; Mintu P Turakhia; Jonathan L Halperin; Sanjiv M Narayan
Journal:  Nat Rev Cardiol       Date:  2020-10-09       Impact factor: 32.419

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.