Left heart pressures can be the key to know the limitation of left ventricular assist device support against progression of ... View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-09

AUTHORS

Kei Iizuka, Tomohiro Nishinaka, Noritsugu Naito, Daichi Akiyama, Yoshiaki Takewa, Kenji Yamazaki, Eisuke Tatsumi

ABSTRACT

Aortic insufficiency (AI) is a worrisome complication under left ventricular assist device (LVAD) support. AI progression causes LVAD-left ventricular (LV) recirculation and can require surgical intervention to the aortic valve. However, the limitations of LVAD support are not well known. Using an animal model of LVAD with AI, the effect of AI progression on hemodynamics and myocardial oxygen metabolism were investigated. Five goats (Saanen 48 ± 2 kg) underwent centrifugal type LVAD, EVAHEART, implantation. The AI model was established by placing a vena cava filter in the aortic valve. Cardiac dysfunction was induced by continuous beta-blockade (esmolol) infusion. Hemodynamic values and myocardial oxygen extraction ratio (O2ER) were evaluated while changing the degree of AI which was expressed as the flow rate of LVAD-LV recirculation (recirculation rate). Diastolic aortic pressure was decreased with AI progression and correlated negatively with the recirculation rate (p = 0.00055). Systolic left ventricular pressure (LVP) and mean left atrial pressure (LAP) were increased with AI progression and correlated positively with the recirculation rate (p = 0.010, 0.023, respectively). LVP and LAP showed marked exponential increases when the recirculation rate surpassed 40%. O2ER was also increased with AI progression and had a significant positive correlation with the recirculation rate (p = 0.000043). O2ER was increased linearly, with no exponential increase. AI progression made it difficult to reduce the cardiac pressure load, worsening myocardial oxygen metabolism. The exponential increase of left heart pressures could be the key to know the limitation of LVAD support against AI progression. More... »

PAGES

265-270

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10047-018-1027-4

DOI

http://dx.doi.org/10.1007/s10047-018-1027-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101127382

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29464441


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