Impact of Muscle Mass as a Prognostic Factor for Failed Waiting Time Prior to Heart Transplantation - Roehrich, Luise; Suendermann, Simon H.; Just, Isabell Anna; Kopp Fernandes, Laurenz; Schnettler, Jessica; Kelle, Sebastian; Solowjowa, Natalia; Stein, Julia; Hummel, Manfred; Knierim, Jan; Potapov, Evgenij; Knosalla, Christoph; et al. (Frontiers in Cardiovascular Medicine, 2021)
Objectives: Clinical deterioration during the waiting time impairs the prognosis of patients listed for heart transplantation. Reduced muscle mass increases the risk for mortality after cardiac surgery, but its impact on resilience against deterioration during the waiting time remains unclear. Methods: We retrospectively analyzed data from 93 patients without a VAD who were listed in Eurotransplant status “high urgent (HU)” for heart transplantation between January 2015 and October 2020. The axial muscle area of the erector spinae muscles at the level of thoracic vertebra 12 indexed to body surface area (TMESA/BSA) measured in the preoperative thoracic computed tomography scan was used to measure muscle mass. Results: Forty patients (43%) underwent emergency VAD implantation during the waiting time and four patients (4%) died during the waiting time. The risk of emergency VAD implantation/death during the waiting time decreased by 10% for every cm2/m2 increase in muscle area [OR 0.901 (95% CI: 0.808–0.996); p = 0.049]. After adjusting for gender [OR 0.318 (95% CI: 0.087–1.073); p = 0.072], mean pulmonary artery pressure [OR 1.061 (95% CI: 0.999–1.131); p = 0.060], C-reactive protein [OR 1.352 (95% CI: 0.986–2.027); p = 0.096], and hemoglobin [OR 0.862 (95% CI: 0.618–1.177); p = 0.360], TMESA/BSA [OR 0.815 (95% CI: 0.698–0.936); p = 0.006] remained an independent risk factor for emergency VAD implantation/death during the HU waiting time. Conclusion: Muscle area of the erector spinae muscle appears to be a potential, easily identifiable risk factor for emergency VAD implantation or death in patients on the HU waiting list for heart transplantation. Identifying patients at risk could help optimize the outcome and the timing of VAD support.