2022
DOI: 10.3389/fcvm.2022.848789
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Use of machine learning techniques to identify risk factors for RV failure in LVAD patients

Abstract: September CITATION Nair N () Use of machine learning techniques to identify risk factors for RV failure in LVAD patients.

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Cited by 3 publications
(2 citation statements)
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“…This should be evaluated with regular echocardiograms and cautious volume optimization with LVAD speed adjustments, diuresis, or ultrafiltration. Pulmonary hypertension should be treated with phosphodiesterase-5 inhibitors or inhaled nitric oxide [30].…”
Section: Post-operative Care and Monitoringmentioning
confidence: 99%
“…This should be evaluated with regular echocardiograms and cautious volume optimization with LVAD speed adjustments, diuresis, or ultrafiltration. Pulmonary hypertension should be treated with phosphodiesterase-5 inhibitors or inhaled nitric oxide [30].…”
Section: Post-operative Care and Monitoringmentioning
confidence: 99%
“…Determining which LVAD patient requires mechanical RV support remains challenging, and the decision should be the result of a multidisciplinary team approach, taking into consideration detailed clinical, advanced echocardiographic, and hemodynamic assessment. Due to the complexity and multiple factors involved, it has been proposed that artificial intelligence (AI) technology might be able to predict the risk of right ventricular failure post-LVAD implantation more accurately [67].…”
Section: Post-operative Temporary Mechanical Rv Supportmentioning
confidence: 99%