Cardiac health risk stratification system (CHRiSS): A Bayesian-based decision support system for left ventricular assist device (LVAD) therapy

This study investigated the use of Bayesian Networks (BNs) for left ventricular assist device (LVAD) therapy; a treatment for end-stage heart failure that has been steadily growing in popularity over the past decade. Despite this growth, the number of LVAD implants performed annually remains a small fraction of the estimated population of patients who might benefit from this treatment. We believe that this demonstrates a need for an accurate stratification tool that can help identify LVAD candidates at the most appropriate point in the course of their disease. We derived BNs to predict mortality at five endpoints utilizing the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) database: containing over 12,000 total enrolled patients from 153 hospital sites, collected since 2006 to the present day, and consisting of approximately 230 pre-implant clinical variables. Synthetic minority oversampling technique (SMOTE) was employed to address the uneven proportion of patients with negative outcomes and to improve the performance of the models. The resulting accuracy and area under the ROC curve (%) for predicted mortality were 30 day: 94.9 and 92.5; 90 day: 84.2 and 73.9; 6 month: 78.2 and 70.6; 1 year: 73.1 and 70.6; and 2 years: 71.4 and 70.8. To foster the translation of these models to clinical practice, they have been incorporated into a web-based application, the Cardiac Health Risk Stratification System (CHRiSS). As clinical experience with LVAD therapy continues to grow, and additional data is collected, we aim to continually update these BN models to improve their accuracy and maintain their relevance. Ongoing work also aims to extend the BN models to predict the risk of adverse events post-LVAD implant as additional factors for consideration in decision making

Device Thrombogenicity Emulation: A Novel Method for Optimizing Mechanical Circulatory Support Device Thromboresistance

Mechanical circulatory support (MCS) devices provide both short and long term hemodynamic support for advanced heart failure patients. Unfortunately these devices remain plagued by thromboembolic complications associated with chronic platelet activation – mandating complex, lifelong anticoagulation therapy. To address the unmet need for enhancing the thromboresistance of these devices to extend their long term use, we developed a universal predictive methodology entitled Device Thrombogenicity Emulation (DTE) that facilitates optimizing the thrombogenic performance of any MCS device – ideally to a level that may obviate the need for mandatory anticoagulation

Ritual plants of Muslim graveyards in northern Israel

This article surveys the botanical composition of 40 Muslim graveyards in northern Israel, accompanied by an ethnobotanical study of the folkloristic traditions of the use of these plants in cemeteries. Three groups of plants were found to be repeated systematically and were also recognized for their ritual importance: aromatics herbs (especially Salvia fruticosa and Rosmarinus officinalis), white flowered plants (mainly Narcissus tazetta, Urginea maritima, Iris spp. and Pancratium spp.) and Cupressus sempervirens as the leading cemetery tree. As endemic use we can indicate the essential role of S. fruticosa as the main plant used in all human rites of passage symbolizing the human life cycle. The rosemary is of European origin while the use of basil is of Indian influence. The use of white flowers as cemeteries plants reflects an old European influence and almost the same species are used or their congeners. Most of the trees and shrubs that are planted in Muslim cemeteries in Israel have the same use in ancient as well in modern European cultures. In conclusion, our findings on the occurrence of plants in graveyards reflect the geographic situation of Israel as a crossroads in the cultural arena between Asia and Europe. Most of the traditions are common to the whole Middle East showing high relatedness to the classical world as well as to the present-day Europe

The importance of dQ/dt on the flow field in a turbodynamic pump with pulsatile flow

Fluid dynamic analysis of turbodynamic blood pumps (TBPs) is often conducted under steady flow conditions. However, the preponderance of clinical applications for ventricular assistance involves unsteady, pulsatile flow—due to the residual contractility of the native heart. This study was undertaken to demonstrate the importance of pulsatility and the associated time derivative of the flow rate (dQ/dt) on hemodynamics within a clinical-scale TBP. This was accomplished by performing flow visualization studies on a transparent model of a centrifugal TBP interposed within a cardiovascular simulator with controllable heart rate and stroke volume. Particle image velocimetry triggered to both the rotation angle of the impeller and phase of the cardiac cycle was used to quantify the velocity field in the outlet volute and in between the impeller blades for 16 phases of the cardiac cycle. Comparison of the unsteady flow fields to corresponding steady conditions at the same (instantaneous) flow rates revealed marked differences. In particular, deceleration of flow was found to promote separation within the outlet diffuser, while acceleration served to stabilize the velocity field. The notable differences between the acceleration and deceleration phases illustrated the prominence of inertial fluid forces. These studies emphasize the importance of dQ/dt as an independent variable for thorough preclinical validation of TBPs intended for use as a ventricular assist device

Development of a hybrid decision support model for optimal ventricular assist device weaning

Background: Despite the small but promising body of evidence for cardiac recovery in patients that have received ventricular assist device (VAD) support, the criteria for identifying and selecting candidates who might be weaned from a VAD have not been established. Methods: A clinical decision support system was developed based on a Bayesian Belief Network that combined expert knowledge with multivariate statistical analysis. Expert knowledge was derived from interviews of 11 members of the Artificial Heart Program at the University of Pittsburgh Medical Center. This was supplemented by retrospective clinical data from the 19 VAD patients considered for weaning between 1996 and 2004. Artificial Neural Networks and Natural Language Processing were used to mine these data and extract sensitive variables. Results: Three decision support models were compared. The model exclusively based on expert-derived knowledge was the least accurate and most conservative. It underestimated the incidence of heart recovery, incorrectly identifying 4 of the successfully weaned patients as transplant candidates. The model derived exclusively from clinical data performed better but misidentified 2 patients: 1 weaned successfully, and 1 that needed a cardiac transplant ultimately. An expert-data hybrid model performed best, with 94.74% accuracy and 75.37% to 99.07% confidence interval, misidentifying only 1 patient weaned from support. Conclusions: A clinical decision support system may facilitate and improve the identification of VAD patients who are candidates for cardiac recovery and may benefit from VAD removal. It could be potentially used to translate success of active centers to those less established and thereby expand use of VAD therapy. © 2010 The Society of Thoracic Surgeons