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Psoas Muscle Area Predicts Mortality After Left Ventricular Assist Device Implantation

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Journal Life (Basel)
Specialty Biology
Date 2021 Sep 28
PMID 34575071
Citations 3
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Abstract

Several risk scores and classifications are available to predict peri- and post-operative mortality of patients with end stage heart failure receiving Left Ventricular Assist Device (LVAD) therapy. Sarcopenia has been suggested as a sensitive predictor for post-operative mortality. We evaluated whether the psoas muscle area can predict mortality in patients undergoing LVAD implantation. The indexed psoas mean area (PMAi) was obtained by measuring the psoas muscle area at the superior endplate of the third lumbar vertebra correlated to body surface area of 106 adult patients undergoing LVAD implantation (Medtronic HVAD = 41, Abbott HeartMate II = 4, Abbott HeartMate 3 = 61; mean age 65, IQR 12, 90.6% male; INTERMACS Level 1 24.5%; ischemic CMP 64.2%). Patients were divided in two groups: high/moderate and low muscle mass. The primary endpoint was 30-day mortality, assessed using a multivariate Cox proportional hazards model. Baseline characteristics did not differ between patients with high or moderate and low PMAi. Estimated survival calculated a significant higher 30-day mortality in patients with low PMAi ( = 0.04). Multivariable Cox proportional hazards regression analysis indicated low PMAi, history of previous cardiac surgery and levels of bilirubin as independent predictors of mortality in the first 30 days. In conclusion, indexed psoas muscle area predicts mortality after LVAD implantation and can be used as an additional tool for risk stratification.

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References
1.
Roger V . Epidemiology of myocardial infarction. Med Clin North Am. 2007; 91(4):537-52. PMC: 2537993. DOI: 10.1016/j.mcna.2007.03.007. View

2.
Braunwald E . The war against heart failure: the Lancet lecture. Lancet. 2014; 385(9970):812-24. DOI: 10.1016/S0140-6736(14)61889-4. View

3.
Gustafsson F, Rogers J . Left ventricular assist device therapy in advanced heart failure: patient selection and outcomes. Eur J Heart Fail. 2017; 19(5):595-602. DOI: 10.1002/ejhf.779. View

4.
Afilalo J, Eisenberg M, Morin J, Bergman H, Monette J, Noiseux N . Gait speed as an incremental predictor of mortality and major morbidity in elderly patients undergoing cardiac surgery. J Am Coll Cardiol. 2010; 56(20):1668-76. DOI: 10.1016/j.jacc.2010.06.039. View

5.
Hulsmann M, Quittan M, Berger R, Crevenna R, Springer C, Nuhr M . Muscle strength as a predictor of long-term survival in severe congestive heart failure. Eur J Heart Fail. 2004; 6(1):101-7. DOI: 10.1016/j.ejheart.2003.07.008. View