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Right Heart Failure (RHF) is a severe complication that can occur after left ventricular assist device (LVAD) implantation, increasing early and late mortality. Although numerous RHF predictive scores have been developed, limited data exist on the external validation of these models. We therefore aimed at comparing existent risk score models and identifying predictors of severe RHF at our center.In this retrospective, single-center analysis, clinical, biological and functional data were collected in patients implanted with a LVAD between 2011 and 2020. Early severe RHF was defined as the use of inotropes for ≥ 14 days, nitric oxide use for ≥ 48 h or unplanned right-sided circulatory support. Risk models were evaluated for the primary outcome of RHF or RVAD implantation by means of logistic regression and receiver operating characteristic curves.Among 92 patients implanted, 24 (26%) developed early severe RHF. The EUROMACS-RHF risk score performed the best in predicting RHF (C = 0.82-95% CI: 0.68-0.90), compared with the other scores (Michigan, CRITT). In addition, we developed a new model, based on four variables selected for the best reduced logistic model: the INTERMACS level, the number of inotropes used, the ratio of right atrial/pulmonary capillary wedge pressure and the ratio of right ventricle/left ventricle diameters by echocardiography. This model demonstrated significant discrimination of RHF (C = 0.9-95% CI: 0.76-0.96).Amongst available risk scores, EUROMACS-RHF performs best to predict the occurrence of RHF after LVAD implantation. Our model's performance compares well to the EUROMACS-RHF score, adding a more objective parameter to RV function evaluation.© 2022. The Japanese Society for Artificial Organs.


Federica Valente, Constantin Stefanidis, Jean-Luc Vachiéry, Céline Dewachter, Edgard Engelman, Frédéric Vanden Eynden, Ana Roussoulières. A novel metrics to predict right heart failure after left ventricular assist device implantation. Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs. 2022 Apr 28

PMID: 35482120

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