Haemodynamics from Induction to Cardiopulmonary Bypass Improve Prediction of Right Ventricular Failure Following Left...

Right ventricular failure (RVF) remains a frequent complication following left ventricular assist device (LVAD) implantation. Conventional risk scores rely on preoperative data acquired under stable conditions, which may overlook early signs of RV decompensation that emerge under perioperative stress. This study evaluates whether perioperative haemodynamic markers prior to cardiopulmonary bypass (CPB) improve RVF prediction compared to preoperative assessment obtained by right heart catheterization (RHC), echocardiographic parameters, and scoring systems such as the European Registry for Patients with Mechanical Circulatory Support (EUROMACS) RHF score.

We conducted a retrospective single-centre study of 203 LVAD patients (2013-2023). The primary outcome was RVF. Preoperative data included clinical variables, echocardiography, and RHC. Perioperative data included vasoactive-inotropic score (VIS), pulmonary artery (PA) catheter, and arterial-line monitoring between induction and start of CPB. Two multivariable models were developed using least absolute shrinkage-and-selection operator (LASSO) logistic regression: (1) Preoperative model; (2) Pre-CPB model. Model performance was assessed using area under the curve (AUC) and compared against EUROMACS-RHF using DeLong tests.

Thirty-six patients (17.7%) developed RVF. No preoperative RHC-derived parameter independently predicted RVF. The Preoperative model achieved moderate discrimination (AUC: 0.747). Incorporating intraoperative mean arterial pressure (MAP), pulmonary artery pulsatility index (PAPi), and maximum VIS yielded a Pre-CPB model with strong discrimination (AUC: 0.834). The Pre-CPB model significantly outperformed both EUROMACS-RHF (P = 0.0299) and the Preoperative model (P = 0.049), with no significant difference between our Preoperative model and EUROMACS-RHF (P = 0.222).

Perioperative markers prior to CPB significantly outperform preoperative prediction of RVF post-LVAD. Incorporating these into real-time risk stratification can improve decision-making, enabling earlier RV support in the operating theatre for high-risk LVAD patients.