Objectives: This study investigates the use of a Bayesian statistical models to predict survival
at various time points in patients undergoing left ventricular assist device (LVAD) …

Abstract Purpose of Review In this review, we discuss risk assessment of advanced heart
failure (HF) patients as a referral guide for advanced HF therapies, including left ventricular …

Challenges and Future Directions in Left Ventricular Assist Device Therapy - Critical Care
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Background We have previously demonstrated that pectoralis muscle mass and tissue
attenuation obtained on preoperative CT scans were powerful predictors of mortality after left …

Artificial intelligence (AI) refers to the ability of machines to perform intelligent tasks, and
machine learning (ML) is a subset of AI describing the ability of machines to learn …

BACKGROUND The purpose of this study is to evaluate the utility of vasoactive-inotropic
score (VIS) in predicting outcomes after left ventricular assist device (LVAD) implantation …

Objectives Adoption of implantable left ventricular assist devices has dramatically improved
survival and quality of life in suitable patients with end-stage heart failure. In the era of value …

Current risk stratification models to predict outcomes after a left ventricular assist device
(LVAD) are limited in scope. We assessed the performance of Bayesian models to stratify …

CRP is an established inflammatory biomarker with prognostic value in patients with chronic
heart failure, yet its role in continuous-flow left ventricular assist device (LVAD) patients is …

HeartMate 3 is the only durable left ventricular assist devices (LVAD) currently implanted in
the United States. The purpose of this study was to develop a predictive model for 1 year …