Body Composition Assessment and Protein Recommendations In Clinical Populations

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Body Composition Assessment and Protein Recommendations In Clinical Populations

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2020-03

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Abstract

Malnutrition, sarcopenia, cachexia, and frailty are terms that rely on muscle assessment, and they all have ongoing refinement in their definition and diagnostic criteria as well as significant clinical overlap. Uncertainties in how best to assess muscle objectively have led to subjectivity in their diagnoses, leading to confusion and misuse of these terms throughout the literature. Additionally, protein recommendations in the hospital which serve as the foundation for nutrition intervention to prevent or treat muscle loss are based on nitrogen balance studies that are non-specific and have known limitations. The clinical Registered Dietitian Nutritionist (RDN) is well-positioned to diagnose, track, and treat muscle wasting disorders in clinical populations, and improvement in both the assessment of muscle as well as protein recommendations to prevent or treat muscle loss will advance the clinical utility of RDN. A detailed look at the history of malnutrition in the medical literature indicates that body composition has long been known to be of critical importance to its diagnosis, and current efforts are underway to utilize body composition technologies to assess muscle in acute care settings. Computed tomography data can indicate best-treatment methods for individuals as well as those who would benefit from targeted nutrition intervention, and this dissertation discusses its utility for predicting outcomes in chronic pancreatitis patients undergoing a total pancreatectomy with islet autotransplantation and heart failure patients undergoing a heart transplant. Finally, this dissertation demonstrates that a multi-step feeding protocol of stable isotope amino acids is feasible to characterize whole body protein kinetics over a single study day to ultimately improve protein recommendations in patients with head and neck cancer. Ultimately, loss of muscle is known to worsen clinical outcomes and increase cost, and advancements in both muscle assessment using body composition technologies and protein recommendations using stable isotope amino acid tracers to prevent or treat muscle loss will improve the ability of the clinical RDN to positively impact patient prognosis.

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University of Minnesota Ph.D. dissertation. March 2020. Major: Nutrition. Advisor: Carrie Earthman. 1 computer file (PDF); 159 pages.

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Price, Kathleen. (2020). Body Composition Assessment and Protein Recommendations In Clinical Populations. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/216117.

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