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

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

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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.

Original languageEnglish
Pages (from-to)150-157
Number of pages8
JournalClinical Nutrition
Volume27
Issue number1
DOIs
Publication statusPublished - Feb 2008
Externally publishedYes

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Energy Metabolism
Inpatients
Outpatients
Indirect Calorimetry
Thinness
Weights and Measures

Cite this

Weijs, P. J. M., Kruizenga, H. M., van Dijk, A. E., van der Meij, B. S., Langius, J. A. E., Knol, D. L., ... van Bokhorst-de van der Schueren, M. A. E. (2008). Validation of predictive equations for resting energy expenditure in adult outpatients and inpatients. Clinical Nutrition, 27(1), 150-157. https://doi.org/10.1016/j.clnu.2007.09.001
Weijs, P. J M ; Kruizenga, Hinke M. ; van Dijk, Aimee E. ; van der Meij, Barbara S. ; Langius, Jacqueline A E ; Knol, Dirk L. ; Strack van Schijndel, R. J M ; van Bokhorst-de van der Schueren, Marian A E. / Validation of predictive equations for resting energy expenditure in adult outpatients and inpatients. In: Clinical Nutrition. 2008 ; Vol. 27, No. 1. pp. 150-157.
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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.",
author = "Weijs, {P. J M} and Kruizenga, {Hinke M.} and {van Dijk}, {Aimee E.} and {van der Meij}, {Barbara S.} and Langius, {Jacqueline A E} and Knol, {Dirk L.} and {Strack van Schijndel}, {R. J M} and {van Bokhorst-de van der Schueren}, {Marian A E}",
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Weijs, PJM, Kruizenga, HM, van Dijk, AE, van der Meij, BS, Langius, JAE, Knol, DL, Strack van Schijndel, RJM & van Bokhorst-de van der Schueren, MAE 2008, 'Validation of predictive equations for resting energy expenditure in adult outpatients and inpatients' Clinical Nutrition, vol. 27, no. 1, pp. 150-157. https://doi.org/10.1016/j.clnu.2007.09.001

Validation of predictive equations for resting energy expenditure in adult outpatients and inpatients. / Weijs, P. J M; Kruizenga, Hinke M.; van Dijk, Aimee E.; van der Meij, Barbara S.; Langius, Jacqueline A E; Knol, Dirk L.; Strack van Schijndel, R. J M; van Bokhorst-de van der Schueren, Marian A E.

In: Clinical Nutrition, Vol. 27, No. 1, 02.2008, p. 150-157.

Research output: Contribution to journalArticleResearchpeer-review

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T1 - Validation of predictive equations for resting energy expenditure in adult outpatients and inpatients

AU - Weijs, P. J M

AU - Kruizenga, Hinke M.

AU - van Dijk, Aimee E.

AU - van der Meij, Barbara S.

AU - Langius, Jacqueline A E

AU - Knol, Dirk L.

AU - Strack van Schijndel, R. J M

AU - van Bokhorst-de van der Schueren, Marian A E

PY - 2008/2

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N2 - 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.

AB - 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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U2 - 10.1016/j.clnu.2007.09.001

DO - 10.1016/j.clnu.2007.09.001

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JO - Clinical Nutrition

JF - Clinical Nutrition

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