Itai Bendavid1, Dileep N Lobo2, Rocco Barazzoni3, Tommy Cederholm4, Moïse Coëffier5, Marian de van der Schueren6, Eric Fontaine7, Michael Hiesmayr8, Alessandro Laviano9, Claude Pichard10, Pierre Singer11. 1. Department of General Intensive Care and Institute for Nutrition Research, Rabin Medical Center, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Israel. 2. Gastrointestinal Surgery, Nottingham Digestive Diseases Centre, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and University of Nottingham, Queen's Medical Centre, Nottingham, NG7 2UH, UK; MRC Versus Arthritis Centre for Musculoskeletal Ageing Research, School of Life Sciences, University of Nottingham, Queen's Medical Centre, Nottingham, NG7 2UH, UK. 3. Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy. 4. Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden; Theme Ageing, Karolinska University Hospital, Stockholm, Sweden. 5. Department of Nutrition, CIC1404, Rouen University Hospital and Normandie University, UNIROUEN, Inserm UMR1073, Rouen, France. 6. Department of Nutrition and Dietetics, HAN University of Applied Sciences, School of Allied Health, Nijmegen, the Netherlands. 7. Université Grenoble Alpes, LBFA, INSERM U1055, Grenoble, France. 8. Division of Cardiac, Thoracic, Vascular Anesthesia and Intensive Care Medicine, Medical University of Vienna, Waehringerguertel 18-20, 1090 Vienna, Austria. 9. Department of Translational and Precision Medicine, Sapienza University, Rome, Italy. 10. Clinical Nutrition, Geneva University Hospital, Rue Gabrielle-Perret-Gentil 4, 1211 Geneva 14, Switzerland. 11. Department of General Intensive Care and Institute for Nutrition Research, Rabin Medical Center, Beilinson Hospital, Sackler School of Medicine, Tel Aviv University, Israel. Electronic address: psinger@clalit.org.il.
Abstract
BACKGROUND & AIMS: The year 2019 marked the centenary of the publication of the Harris and Benedict equations for estimation of energy expenditure. In October 2019 a Scientific Symposium was organized by the European Society for Clinical Nutrition and Metabolism (ESPEN) in Vienna, Austria, to celebrate this historical landmark, looking at what is currently known about the estimation and measurement of energy expenditure. METHODS: Current evidence was discussed during the symposium, including the scientific basis and clinical knowledge, and is summarized here to assist with the estimation and measurement of energy requirements that later translate into energy prescription. RESULTS: In most clinical settings, the majority of predictive equations have low to moderate performance, with the best generally reaching an accuracy of no more than 70%, and often lead to large errors in estimating the true needs of patients. Generally speaking, the addition of body composition measurements did not add to the accuracy of predictive equations. Indirect calorimetry is the most reliable method to measure energy expenditure and guide energy prescription, but carries inherent limitations, greatly restricting its use in real life clinical practice. CONCLUSIONS: While the limitations of predictive equations are clear, their use is still the mainstay in clinical practice. It is imperative to recognize specific patient populations for whom a specific equation should be preferred. When available, the use of indirect calorimetry is advised in a variety of clinical settings, aiming to avoid under-as well as overfeeding.
BACKGROUND & AIMS: The year 2019 marked the centenary of the publication of the Harris and Benedict equations for estimation of energy expenditure. In October 2019 a Scientific Symposium was organized by the European Society for Clinical Nutrition and Metabolism (ESPEN) in Vienna, Austria, to celebrate this historical landmark, looking at what is currently known about the estimation and measurement of energy expenditure. METHODS: Current evidence was discussed during the symposium, including the scientific basis and clinical knowledge, and is summarized here to assist with the estimation and measurement of energy requirements that later translate into energy prescription. RESULTS: In most clinical settings, the majority of predictive equations have low to moderate performance, with the best generally reaching an accuracy of no more than 70%, and often lead to large errors in estimating the true needs of patients. Generally speaking, the addition of body composition measurements did not add to the accuracy of predictive equations. Indirect calorimetry is the most reliable method to measure energy expenditure and guide energy prescription, but carries inherent limitations, greatly restricting its use in real life clinical practice. CONCLUSIONS: While the limitations of predictive equations are clear, their use is still the mainstay in clinical practice. It is imperative to recognize specific patient populations for whom a specific equation should be preferred. When available, the use of indirect calorimetry is advised in a variety of clinical settings, aiming to avoid under-as well as overfeeding.
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