Energy Expenditure in Critically Ill Adult Patients With Acute Brain Injury: Indirect Calorimetry vs. Predictive Equations

Kathryn A Morbitzer; William S Wilson; Alex C Chaben; Adrienne Darby; Kelly A Dehne; Emily R Brown; Denise H Rhoney; J Dedrick Jordan

doi:10.3389/fneur.2019.01426

Energy Expenditure in Critically Ill Adult Patients With Acute Brain Injury: Indirect Calorimetry vs. Predictive Equations

Front Neurol. 2020 Jan 23:10:1426. doi: 10.3389/fneur.2019.01426. eCollection 2019.

Authors

Kathryn A Morbitzer¹, William S Wilson², Alex C Chaben², Adrienne Darby¹, Kelly A Dehne^{1

2}, Emily R Brown³, Denise H Rhoney¹, J Dedrick Jordan⁴

Affiliations

¹ Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, Chapel Hill, NC, United States.
² Department of Pharmacy, University of North Carolina Health Care, Chapel Hill, NC, United States.
³ Department of Nutrition and Food Services, University of North Carolina Health Care, Chapel Hill, NC, United States.
⁴ Departments of Neurology and Neurosurgery, University of North Carolina School of Medicine, Chapel Hill, NC, United States.

Abstract

Introduction: Predictive equations (PE) are used in lieu of indirect calorimetry (IC) due to cost and limited resources; however, these equations may not be as accurate as IC in estimating resting energy expenditure (REE) in critically ill patients, putting them at risk of malnutrition. The purpose of this study is to compare predicted and measured energy expenditure (MEE) in critically ill adults with acute brain injury. Materials and Methods: This was a retrospective review of adult patients admitted to the Neurosciences ICU with acute brain injury between May 1st, 2014 and April 1st, 2016 who had IC performed. The Harris Benedict (HBE), Penn State University, and Mifflin St Jeor (MSJ) PE were used in comparison to IC results. Subgroup analyses stratified patients based on BMI and type of acute brain injury. Results: One hundred and forty-four patients met inclusion criteria. Comparing predicted and MEE found no significant difference (p = 0.1). High degrees of interpatient variability were discovered, with standard deviations ranging from 17 to 29% of each PE. Pearson's correlations indicated weak associations when HBE, Penn State, and MSJ were individually compared to MEE (r = 0.372, 0.409, and 0.372, respectively). A significant difference was found between predicted and MEE in patients with a BMI < 30 kg/m² (p < 0.01) and in those with aneurysmal subarachnoid hemorrhage (p < 0.01). Discussion: Due to interpatient variability that exists among REE of critically ill patients with acute brain injury, IC should be used when feasible.

Keywords: acute brain injury; critically ill; energy expenditure; indirect calorimetry; predictive equations.