Comparison of the Beacon and Quark indirect calorimetry devices to measure resting energy expenditure in ventilated ICU patients

McClave, 1998, Are patients fed appropriately according to their caloric requirements?, JPEN - J Parenter Enter Nutr, 22, 375, 10.1177/0148607198022006375 Weijs, 2014, Early high protein intake is associated with low mortality and energy overfeeding with high mortality in non-septic mechanically ventilated critically ill patients, Crit Care, 18, 701, 10.1186/s13054-014-0701-z Zusman, 2016, Resting energy expenditure, calorie and protein consumption in critically ill patients: a retrospective cohort study, Crit Care, 20, 367, 10.1186/s13054-016-1538-4 Segadilha, 2017, Energy expenditure in critically ill elderly patients: indirect calorimetry vs predictive equations, JPEN - J Parenter Enter Nutr, 41, 776, 10.1177/0148607115625609 Moonen, 2021, Energy expenditure and indirect calorimetry in critical illness and convalescence: current evidence and practical considerations, J Intensive Care, 9, 8, 10.1186/s40560-021-00524-0 Weijs, 2013, Optimizing energy and protein balance in the ICU, Curr Opin Clin Nutr Metab Care, 16, 194, 10.1097/MCO.0b013e32835bdf7e Schlein, 2014, Best practices for determining resting energy expenditure in critically ill adults, Nutr Clin Pract, 29, 44, 10.1177/0884533613515002 Harris, 1918, A biometric study of human basal metabolism, Proc Natl Acad Sci U S A, 4, 370, 10.1073/pnas.4.12.370 Frankenfield, 2004, Validation of 2 approaches to predicting resting metabolic rate in critically ill patients, JPEN - J Parenter Enter Nutr, 28, 259, 10.1177/0148607104028004259 Melzer, 2007, Comparison of equations for estimating resting metabolic rate in healthy subjects over 70 years of age, Clin Nutr, 26, 498, 10.1016/j.clnu.2007.05.002 Flack, 2016, Cross-validation of resting metabolic rate prediction equations, J Acad Nutr Diet, 116, 1413, 10.1016/j.jand.2016.03.018 De Waele, 2015, Measured versus calculated resting energy expenditure in critically ill adult patients. Do mathematics match the gold standard?, Minerva Anestesiol, 81, 272 Wichansawakun, 2015, Energy requirements and the use of predictive equations versus indirect calorimetry in critically ill patients, Appl Physiol Nutr Metabol, 40, 207, 10.1139/apnm-2014-0276 Tignanelli, 2019, Are predictive energy expenditure equations in ventilated surgery patients accurate?, J Intensive Care Med, 34, 426, 10.1177/0885066617702077 Zusman, 2019, Predictive equations versus measured energy expenditure by indirect calorimetry: a retrospective validation, Clin Nutr, 38, 1206, 10.1016/j.clnu.2018.04.020 Lambell, 2020, Nutrition therapy in critical illness: a review of the literature for clinicians, Crit Care, 24, 35, 10.1186/s13054-020-2739-4 Singer, 2019, ESPEN guideline on clinical nutrition in the intensive care unit, Clin Nutr, 38, 48, 10.1016/j.clnu.2018.08.037 Weir, 1949, New methods for calculating metabolic rate with special reference to protein metabolism, J Physiol, 109, 1, 10.1113/jphysiol.1949.sp004363 Tissot, 1995, Clinical validation of the Deltatrac monitoring system in mechanically ventilated patients, Intensive Care Med, 21, 149, 10.1007/BF01726538 Stapel, 2015, Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept, Crit Care, 19, 370, 10.1186/s13054-015-1087-2 Graf, 2015, Evaluation of three indirect calorimetry devices in mechanically ventilated patients: which device compares best with the Deltatrac II(®)? A prospective observational study, Clin Nutr, 34, 60, 10.1016/j.clnu.2014.01.008 Sundström Rehal, 2013, Indirect calorimetry in mechanically ventilated patients. A systematic comparison of three instruments, Clin Nutr, 32, 118, 10.1016/j.clnu.2012.06.004 Sundström Rehal, 2016, Measuring energy expenditure in the intensive care unit: a comparison of indirect calorimetry by E-sCOVX and Quark RMR with Deltatrac II in mechanically ventilated critically ill patients, Crit Care, 20, 54, 10.1186/s13054-016-1232-6 Care Poulsen, 2019, Reliability of, and agreement between, two breath-by-breath indirect calorimeters at varying levels of inspiratory oxygen, Nutr Clin Pract, 34, 767, 10.1002/ncp.10250 Ranieri, 2012, Acute respiratory distress syndrome: the Berlin Definition, JAMA, 307, 2526 Quark Branson, 1990, The measurement of energy expenditure: instrumentation, practical considerations, and clinical application, Respir Care, 35, 640 Haugen, 2007, Indirect calorimetry: a practical guide for clinicians, Nutr Clin Pract, 22, 377, 10.1177/0115426507022004377 Mifflin, 1990, A new predictive equation for resting energy expenditure in healthy individuals, Am J Clin Nutr, 51, 241, 10.1093/ajcn/51.2.241 Faisy, 2003, Assessment of resting energy expenditure in mechanically ventilated patients, Am J Clin Nutr, 78, 241, 10.1093/ajcn/78.2.241 Walker, 2009, Predictive equations for energy needs for the critically ill, Respir Care, 54, 509 Oshima, 2020, The clinical evaluation of the new indirect calorimeter developed by the ICALIC project, Clin Nutr, 39, 3105, 10.1016/j.clnu.2020.01.017