Type of Document	Master's Thesis
Author	Uber, Bronwyn
Author's Email Address	bronwyn_uber@yahoo.com
URN	etd-03282006-104153
Title	Decision Aid to Determine the Necessity of Right Ventricular Support for Patients Receiving a Left Ventricular Assist Device
Degree	MSBeng
Program	Bioengineering
School	School of Engineering
Advisory Committee	Advisor Name Title James F. Antaki Committee Chair Harvey S. Borovetz Committee Member Marwan A. Simaan Committee Member
Keywords	Right Ventricle Decision Aid Patient Selection Ventricular Assist Device
Date of Defense	2006-03-29
Availability	unrestricted
Abstract The purpose of this study was to improve the efficacy of VAD therapy for patients intended for VAD insertion. The study focused on the specific decision whether an LVAD or BiVAD is appropriate. A hierarchical decision model was constructed using an influence diagram of clinical risk factors derived through interviews with expert cardiologists and cardiac surgeons. Most of the variables are summarized by two independent criteria: risk of surgery and risk of right ventricular (RV) failure. These risks are computed from various patient demographics, tests, and hemodynamics using expert physician-selected weighted linear and weighted non-linear relationships. The model was validated with retrospective data from patient records at University of Pittsburgh Medical Center (UPMC) for patients implanted after 1990 and explanted before 2006. In total 239 patients were implanted and explanted during this time, of those 168 had sufficient information to be used in this analysis. 48 patients received biventricular assistance (BiVADs), 119 patients received only left ventricular assistance (LVADs). Of these 119 LVAD patients, 19 subsequently received an RVAD due to unanticipated RV dysfunction. Pre-implant data were used as input to the model. The model parameters were derived from two different physicians. The models based on individual physician’s weightings predicted 63% (47%) of the patients who required an RVAD after implant. However, these decision models also recommended BiVAD implantation for 40% (43%) of patients who were treated successfully with an LVAD alone. A nonlinear numerical optimizer was used to improve the model parameters to optimize the agreement with eventual outcomes. The optimized model predicted 74% of the patients who required an RVAD post-implant and recommended the implantation of BiVADs in 21% of patients who were treated successfully with an LVAD alone. In conclusion, the decision model provided a more aggressive use of biventricular assistance, which retrospectively would have benefited patients who required an RVAD at a later date, but would have unnecessarily implanted RVADs in some patients that survived with an LVAD alone. However the model also identified that 48% of the patients who initially received BiVADs to be candidates for LVAD alone.
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