Predicting Right Ventricular Failure Following Left Ventricular Assist Device Support: A Derivation-Validation Multicenter Risk Score

Autor: Adithya Peruri, Craig H. Selzman, Jennifer A Cowger, Iosif Taleb, Naila Ijaz, Zachary Demertzis, Rami Alharethi, K. S. Shah, Elizabeth Dranow, Josef Stehlik, L. Kemeyou, D.G. Tang, S.G. Drakos, M.Y. Yin, Palak Shah, Antigone G. Koliopoulou, Hassan Nemeh, James C. Fang, A.G. Kfoury, T.J. Richins, Christos P. Kyriakopoulos, Omar Wever-Pinzon, William T. Caine
Rok vydání: 2021
Předmět:
Zdroj: The Journal of Heart and Lung Transplantation. 40:S98
ISSN: 1053-2498
Popis: Purpose Despite several models predicting right ventricular failure (RVF) after durable left ventricular assist device (LVAD) support, poor performance when externally validated has limited their widespread use. We sought to derive a predictive model for RVF after LVAD implantation, and ascertain its performance in an independent cohort. Methods End-stage heart failure (HF) patients requiring continuous-flow LVAD were prospectively enrolled at one US program (n=477, derivation cohort), with two other US medical centers forming the validation cohort (n=321). The primary outcome was RVF incidence, defined as the need for right ventricular assist device or inotropes for >14 days. Multivariable logistic regression in the derivation set yielded a RVF predictive model, which was subsequently applied to the validation cohort, and a risk score was ultimately developed. Results Derivation cohort included patients less likely to be African-Americans (7% vs 37%; p Conclusion We propose a novel scoring system to predict post-LVAD RVF, achieving high discriminative performance in distinct, heterogeneous LVAD cohorts.
Databáze: OpenAIRE