Literature DB >> 17961867

Validation of predictive equations for resting energy expenditure in adult outpatients and inpatients.

Peter J M Weijs1, Hinke M Kruizenga, Aimee E van Dijk, Barbara S van der Meij, Jacqueline A E Langius, Dirk L Knol, Robert J M Strack van Schijndel, Marian A E van Bokhorst-de van der Schueren.   

Abstract

BACKGROUND & AIMS: When individual energy requirements of adult patients cannot be measured by indirect calorimetry, they have to be predicted with an equation. The aim of this study was to analyze which resting energy expenditure (REE) predictive equation was the best alternative to indirect calorimetry in adult patients.
METHODS: Predictive equations were included when based on weight, height, gender and/or age. REE was measured with indirect calorimetry. The mean squared prediction error was used to evaluate how well the equations fitted the REE measurement.
RESULTS: Eighteen predictive equations were included. Indirect calorimetry data were available for 48 outpatients and 45 inpatients. Also a subgroup of 42 underweight patients (BMI<18.5) was analyzed. The mean squared prediction error was 233-426 kcal/d and the percentage of patients with acceptable prediction was 28-52% for adult patients depending on the equation used. The FAO/WHO/UNU (1985) equation including both weight and height had the smallest prediction error in adult patients (233 kcal/d), outpatients (182 kcal/d), inpatients (277 kcal/d) as well as underweight patients (219 kcal/d).
CONCLUSIONS: The REE of adult outpatients, inpatients and underweight patients can best be estimated with the FAO/WHO/UNU equation including weight and height, when indirect calorimetry is not available.

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Year:  2007        PMID: 17961867     DOI: 10.1016/j.clnu.2007.09.001

Source DB:  PubMed          Journal:  Clin Nutr        ISSN: 0261-5614            Impact factor:   7.324


  13 in total

1.  Malnutrition in patients treated for oral or oropharyngeal cancer--prevalence and relationship with oral symptoms: an explorative study.

Authors:  Harriët Jager-Wittenaar; Pieter U Dijkstra; Arjan Vissink; Rob P van Oort; Bernard F A M van der Laan; Jan L N Roodenburg
Journal:  Support Care Cancer       Date:  2010-09-16       Impact factor: 3.603

2.  Clinical Correlates of Measured and Predicted Resting Energy Expenditure in Patients with Anorexia Nervosa: A Retrospective Cohort Study.

Authors:  Rami Bou Khalil; Ariane Sultan; Maude Seneque; Sami Richa; Patrick Lefebvre; Eric Renard; Philippe Courtet; Laurent Maimoun; Sebastien Guillaume
Journal:  Nutrients       Date:  2022-06-30       Impact factor: 6.706

3.  Composition of personalized and standard nutritional mixtures in patients on home parenteral nutrition.

Authors:  C Scanzano; R Iacone; L Alfonsi; M R Galeotalanza; D Sgambati; E Pastore; A D'Isanto; F Fierro; F Contaldo; L Santarpia
Journal:  Eur J Clin Nutr       Date:  2014-02-12       Impact factor: 4.016

4.  Comparison of five equations for estimating resting energy expenditure in Chinese young, normal weight healthy adults.

Authors:  Zhi-yong Rao; Xiao-ting Wu; Bin-miao Liang; Mao-yun Wang; Wen Hu
Journal:  Eur J Med Res       Date:  2012-09-01       Impact factor: 2.175

5.  Resting energy expenditure prediction in recreational athletes of 18-35 years: confirmation of Cunningham equation and an improved weight-based alternative.

Authors:  Twan ten Haaf; Peter J M Weijs
Journal:  PLoS One       Date:  2014-10-02       Impact factor: 3.240

6.  Predicting resting energy expenditure in underweight, normal weight, overweight, and obese adult hospital patients.

Authors:  Hinke M Kruizenga; Geesje H Hofsteenge; Peter J M Weijs
Journal:  Nutr Metab (Lond)       Date:  2016-11-24       Impact factor: 4.169

7.  Validity of predictive equations to estimate RMR in females with varying BMI.

Authors:  George Thom; Konstantinos Gerasimidis; Eleni Rizou; Hani Alfheeaid; Nick Barwell; Eirini Manthou; Sadia Fatima; Jason M R Gill; Michael E J Lean; Dalia Malkova
Journal:  J Nutr Sci       Date:  2020-05-26

Review 8.  Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?

Authors:  Tannaz Eslamparast; Benjamin Vandermeer; Maitreyi Raman; Leah Gramlich; Vanessa Den Heyer; Dawn Belland; Mang Ma; Puneeta Tandon
Journal:  Nutrients       Date:  2019-02-04       Impact factor: 5.717

9.  Predictors for achieving adequate protein and energy intake in nursing home rehabilitation patients.

Authors:  J I van Zwienen-Pot; M Visser; H M Kruizenga
Journal:  Aging Clin Exp Res       Date:  2017-11-17       Impact factor: 3.636

10.  An approach to quantifying abnormalities in energy expenditure and lean mass in metabolic disease.

Authors:  L P E Watson; P Raymond-Barker; C Moran; N Schoenmakers; C Mitchell; L Bluck; V K Chatterjee; D B Savage; P R Murgatroyd
Journal:  Eur J Clin Nutr       Date:  2013-11-27       Impact factor: 4.016

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