Dataset Information

The Right Ventricular Function After Left Ventricular Assist Device (RVF-LVAD) study: rationale and preliminary results.

ABSTRACT: Despite improved outcomes and lower right ventricular failure (RVF) rates with continuous-flow left ventricular assist devices (LVADs), RVF still occurs in 20-40% of LVAD recipients and leads to worse clinical and patient-centred outcomes and higher utilization of healthcare resources. Preoperative quantification of RV function with echocardiography has only recently been considered for RVF prediction, and RV mechanics have not been prospectively evaluated.In this single-centre prospective cohort study, we plan to enroll a total of 120 LVAD candidates to evaluate standard and mechanics-based echocardiographic measures of RV function, obtained within 7 days of planned LVAD surgery, for prediction of (i) RVF within 90 days; (ii) quality of life (QoL) at 90 days; and (iii) RV function recovery at 90 days post-LVAD. Our primary hypothesis is that an RV echocardiographic score will predict RVF with clinically relevant discrimination (C >0.85) and positive and negative predictive values (>80%). Our secondary hypothesis is that the RV score will predict QoL and RV recovery by 90 days. We expect that RV mechanics will provide incremental prognostic information for these outcomes. The preliminary results of an interim analysis are encouraging.The results of this study may help improve LVAD outcomes and reduce resource utilization by facilitating shared decision-making and selection for LVAD implantation, provide insights into RV function recovery, and potentially inform reassessment of LVAD timing in patients at high risk for RVF.

SUBMITTER: Kalogeropoulos AP

PROVIDER: S-EPMC4793936 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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Publications

The Right Ventricular Function After Left Ventricular Assist Device (RVF-LVAD) study: rationale and preliminary results.

Kalogeropoulos Andreas P AP Al-Anbari Raghda R Pekarek Ann A Wittersheim Kristin K Pernetz Maria A MA Hampton Amber A Steinberg Jerilyn J Georgiopoulou Vasiliki V VV Butler Javed J Vega J David JD Smith Andrew L AL

European heart journal. Cardiovascular Imaging 20150709 4

<h4>Aims</h4>Despite improved outcomes and lower right ventricular failure (RVF) rates with continuous-flow left ventricular assist devices (LVADs), RVF still occurs in 20-40% of LVAD recipients and leads to worse clinical and patient-centred outcomes and higher utilization of healthcare resources. Preoperative quantification of RV function with echocardiography has only recently been considered for RVF prediction, and RV mechanics have not been prospectively evaluated.<h4>Methods and results</h ...[more]

PMID: 26160395

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Project description:This study investigates the use of a Bayesian statistical model to address the limited predictive capacity of existing risk scores derived from multivariate analyses. This is based on the hypothesis that it is necessary to consider the interrelationships and conditional probabilities among independent variables to achieve sufficient statistical accuracy.Right ventricular failure (RVF) continues to be a major adverse event following left ventricular assist device (LVAD) implantation.Data used for this study were derived from 10,909 adult patients from the Inter-Agency Registry for Mechanically Assisted Circulatory Support (INTERMACS) who had a primary LVAD implanted between December 2006 and March 2014. An initial set of 176 pre-implantation variables were considered. RVF post-implant was categorized as acute (<48 h), early (48 h to 14 daysays), and late (>14 days) in onset. For each of these endpoints, a separate tree-augmented naïve Bayes model was constructed using the most predictive variables employing an open source Bayesian inference engine.The acute RVF model consisted of 33 variables including systolic pulmonary artery pressure (PAP), white blood cell count, left ventricular ejection fraction, cardiac index, sodium levels, and lymphocyte percentage. The early RVF model consisted of 34 variables, including systolic PAP, pre-albumin, lactate dehydrogenase level, INTERMACS profile, right ventricular ejection fraction, pro-B-type natriuretic peptide, age, heart rate, tricuspid regurgitation, and body mass index. The late RVF model included 33 variables and was predicted mostly by peripheral vascular resistance, model for end-stage liver disease score, albumin level, lymphocyte percentage, and mean and diastolic PAP. The accuracy of all Bayesian models was between 91% and 97%, with an area under the receiver operator characteristics curve between 0.83 and 0.90, sensitivity of 90%, and specificity between 98% and 99%, significantly outperforming previously published risk scores.A Bayesian prognostic model of RVF based on the large, multicenter INTERMACS registry provided highly accurate predictions of acute, early, and late RVF on the basis of pre-operative variables. These models may facilitate clinical decision making while screening candidates for LVAD therapy.

Dataset Information

The Right Ventricular Function After Left Ventricular Assist Device (RVF-LVAD) study: rationale and preliminary results.

Publications

The Right Ventricular Function After Left Ventricular Assist Device (RVF-LVAD) study: rationale and preliminary results.

Similar Datasets

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