Data-driven innovation of left ventricular assist device therapy

Abstract

Heart failure is a global and growing problem that affects 1-2% of people. For patients with end-stage heart failure, a heart transplant is the “gold standard”. Due to the permanent shortage of donor hearts and a growing number of patients on the transplant waiting list, treatment with a left ventricular assist device (LVAD) has become increasingly important. Survival of patients after LVAD implantation has improved significantly over the past two decades. Nevertheless, patients frequently suffer from important complications such as strokes, driveline infections, right heart failure or pump thrombosis. To further improve outcome after LVAD implantation, early detection of deterioration is key to enable early treatment. Therefore, the aim of this thesis was to identify LVAD patients at risk and to explore possibilities of remote monitoring possibilities.

For example, we have demonstrated that outcomes after a HeartMate3 LVAD implantation are better compared to HeartWare LVAD implantation. In addition, we showed that patients with a higher BMI, a longer ICU duration and a history of atrial fibrillation prior to implantation are more likely to develop late right ventricular failure. In addition, it was demonstrated that hyperpolypharmacy (the use of more than 10 medications) occurs regularly in this patient group. There are various ways to monitor LVAD patients (remotely) in order to recognize and treat complications at an early stage. We demonstrated that the biomarker sST2 can play an important role for monitoring purposes. We also developed an algorithm to monitor LVAD parameters which helps in the early recognition of certain complications. In this way, outcomes LVAD implantation can be further improved.