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Accepted (AM)Open Access (License Unspecified), Open
Journal article
A Bayesian Model to Predict Survival After Left Ventricular Assist Device Implantation
JACC. Heart failure, v 6(9), pp 771-779
Sep 2018
PMID: 30098967
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
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) implantation.
LVADs are being increasingly used in patients with end-stage heart failure. Appropriate patient selection continues to be key in optimizing post-LVAD outcomes.
Data used for this study were derived from 10,277 adult patients from the INTERMACS (Inter-Agency Registry for Mechanically Assisted Circulatory Support) who had a primary LVAD implanted between January 2012 and December 2015. Risk for mortality was calculated retrospectively for various time points (1, 3, and 12 months) after LVAD implantation, using multiple pre-implantation variables. For each of these endpoints, a separate tree-augmented naïve Bayes model was constructed using the most predictive variables.
A set of 29, 26, and 31 pre-LVAD variables were found to be predictive at 1, 3, and 12 months, respectively. Predictors of 1-month mortality included low Inter-Agency Registry for Mechanically Assisted Circulatory Support profile, number of acute events in the 48 h before surgery, temporary mechanical circulatory support, and renal and hepatic dysfunction. Variables predicting 12-month mortality included advanced age, frailty, device strategy, and chronic renal disease. The accuracy of all Bayesian models was between 76% and 87%, with an area under the receiver operative characteristics curve of between 0.70 and 0.71.
A Bayesian prognostic model for predicting survival based on the comprehensive INTERMACS registry provided highly accurate predictions of mortality based on pre-operative variables. These models may facilitate clinical decision-making while screening candidates for LVAD therapy.
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Details
- Title
- A Bayesian Model to Predict Survival After Left Ventricular Assist Device Implantation
- Creators
- Manreet K. Kanwar - Allegheny Health NetworkLisa C. Lohmueller - Carnegie Mellon UniversityRobert L. Kormos - University of Pittsburgh Medical CenterJeffrey J. Teuteberg - Stanford UniversityJoseph G. Rogers - Duke UniversityJoAnn Lindenfeld - Vanderbilt University Medical CenterStephen H. Bailey - Allegheny Health NetworkColleen K. McIlvennan - University of Colorado Anschutz Medical CampusRaymond Benza - Allegheny Health NetworkSrinivas Murali - Allegheny Health NetworkJames Antaki - Carnegie Mellon University
- Publication Details
- JACC. Heart failure, v 6(9), pp 771-779
- Publisher
- Elsevier
- Number of pages
- 9
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Cardiothoracic Surgery; Medicine (Graduate); Cardiology
- Web of Science ID
- WOS:000442786300007
- Scopus ID
- 2-s2.0-85053836811
- Other Identifier
- 991021932196904721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Cardiac & Cardiovascular Systems