Hysteretic device characteristics indicate cardiac contractile state for guiding mechanical circulatory support device use.

backgroundAcute heart failure and cardiogenic shock remain highly morbid conditions despite prompt medical therapy in critical care settings. Mechanical circulatory support (MCS) is a promising therapy for these patients, yet remains managed with open-loop control. Continuous measure of cardiac function would support and optimize MCS deployment and weaning. The nature of indwelling MCS provides a platform for attaining this information. This study investigates how hysteresis modeling derived from MCS device signals can be used to assess contractility changes to provide continuous indication of changing cardiac state. Load-dependent MCS devices vary their operation with cardiac state to yield a device-heart hysteretic interaction. Predicting and examining this hysteric relation provides insight into cardiac state and can be separated by cardiac cycle phases. Here, we demonstrate this by predicting hysteresis and using the systolic portion of the hysteresis loop to estimate changes in native contractility. This study quantified this measurement as the enclosed area of the systolic portion of the hysteresis loop and correlated it with other widely accepted contractility metrics in animal studies (n = 4) using acute interventions that alter inotropy, including a heart failure model. Clinical validation was performed in patients (n = 8) undergoing Impella support.

resultsHysteresis is well estimated from device signals alone (r = 0.92, limits of agreement: - 0.18 to 0.18). Quantified systolic area was well correlated in animal studies with end-systolic pressure-volume relationship (r = 0.84), preload recruitable stroke work index (r = 0.77), and maximum slope of left ventricular pressure (dP/dt

conclusionsMechanical circulatory support hysteretic behavior can be well modeled using device signals and used to estimate contractility changes. Contractility estimate is correlated with other accepted metrics, captures temporal trends that elucidate changing cardiac state, and is able to accurately indicate changes in inotropy. Inherently available during MCS deployment, this measure will guide titration and inform need for further intervention.