Abstract
AIMS: Despite the excellent clinical outcomes of the HeartMate 3 (HM3) left ventricular assist device, the current pump monitoring limits in-depth pump data analysis. This study investigated HM3 pump parameters collected non-invasively with HM3 Snoopy during orthostatic transitions (OTs). METHODS AND RESULTS: In this single-centre cohort study, a standardized OT protocol was developed, involving postural changes between supine, seated, and standing. Data were recorded using the HM3 Snoopy and a Holter electrocardiogram. Pump flows (Q(MIN), Q(MEAN), Q(MAX)), pulsatility index (PI), pump speed, MagLev parameters, and heart rate were synchronized per second. The primary outcome was the identification of distinct orthostatic pump flow response phenotypes. Further, a binary classifier using MagLev parameters, to differentiate between supine and upright patient positions, was developed and assessed. In 25 HM3 patients (age: 61.2 ± 9.6 years, female: 12%, body mass index: 26.8 ± 4.7 kg/m(2)), greater flow alterations were observed during transitions from supine to standing vs. seated to standing, with most significant changes in Q(MIN) [3 (-13; 10)%]. Phenotypes were identified across 75 OTs as no flow response (60%), undesired unloading with a loss in Q(MIN) ≥ 50% (20%), and loss of pulsatility ≥ 50% (16%). The MagLev patient position classifier achieved a median sensitivity of 88% and specificity of 86% across the entire cohort. CONCLUSION: Three HM3 pump flow response phenotypes were identified in response to OTs, challenging the utilization of PI events to detect undesired unloading events. A MagLev-based position classifier revealed potential for differentiation of HM3 patient position.