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Are Predictive Energy Expenditure Equations Accurate in Cirrhosis?
Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equati...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412603/ https://www.ncbi.nlm.nih.gov/pubmed/30720726 http://dx.doi.org/10.3390/nu11020334 |
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author | Eslamparast, Tannaz Vandermeer, Benjamin Raman, Maitreyi Gramlich, Leah Den Heyer, Vanessa Belland, Dawn Ma, Mang Tandon, Puneeta |
author_facet | Eslamparast, Tannaz Vandermeer, Benjamin Raman, Maitreyi Gramlich, Leah Den Heyer, Vanessa Belland, Dawn Ma, Mang Tandon, Puneeta |
author_sort | Eslamparast, Tannaz |
collection | PubMed |
description | Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equations (predicted REE, pREE) versus REE measured using gold-standard, indirect calorimetry (IC) (measured REE, mREE). We included full-text English language studies in adults with cirrhosis comparing pREE versus mREE. The mean differences across studies were pooled with RevMan 5.3 software. A total of 17 studies (1883 patients) were analyzed. The pooled cohort was comprised of 65% men with a mean age of 53 ± 7 years. Only 45% of predictive equations estimated energy requirements to within 90–110% of mREE using IC. Eighty-three percent of predictive equations underestimated and 28% overestimated energy needs by ±10%. When pooled, the mean difference between the mREE and pREE was lowest for the Harris–Benedict equation, with an underestimation of 54 (95% CI: 30–137) kcal/d. The pooled analysis was associated with significant heterogeneity (I(2) = 94%). In conclusion, predictive equations calculating REE have limited accuracy in patients with cirrhosis, most commonly underestimating energy requirements and are associated with wide variations in individual comparative data. |
format | Online Article Text |
id | pubmed-6412603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64126032019-03-29 Are Predictive Energy Expenditure Equations Accurate in Cirrhosis? Eslamparast, Tannaz Vandermeer, Benjamin Raman, Maitreyi Gramlich, Leah Den Heyer, Vanessa Belland, Dawn Ma, Mang Tandon, Puneeta Nutrients Review Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equations (predicted REE, pREE) versus REE measured using gold-standard, indirect calorimetry (IC) (measured REE, mREE). We included full-text English language studies in adults with cirrhosis comparing pREE versus mREE. The mean differences across studies were pooled with RevMan 5.3 software. A total of 17 studies (1883 patients) were analyzed. The pooled cohort was comprised of 65% men with a mean age of 53 ± 7 years. Only 45% of predictive equations estimated energy requirements to within 90–110% of mREE using IC. Eighty-three percent of predictive equations underestimated and 28% overestimated energy needs by ±10%. When pooled, the mean difference between the mREE and pREE was lowest for the Harris–Benedict equation, with an underestimation of 54 (95% CI: 30–137) kcal/d. The pooled analysis was associated with significant heterogeneity (I(2) = 94%). In conclusion, predictive equations calculating REE have limited accuracy in patients with cirrhosis, most commonly underestimating energy requirements and are associated with wide variations in individual comparative data. MDPI 2019-02-04 /pmc/articles/PMC6412603/ /pubmed/30720726 http://dx.doi.org/10.3390/nu11020334 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Eslamparast, Tannaz Vandermeer, Benjamin Raman, Maitreyi Gramlich, Leah Den Heyer, Vanessa Belland, Dawn Ma, Mang Tandon, Puneeta Are Predictive Energy Expenditure Equations Accurate in Cirrhosis? |
title | Are Predictive Energy Expenditure Equations Accurate in Cirrhosis? |
title_full | Are Predictive Energy Expenditure Equations Accurate in Cirrhosis? |
title_fullStr | Are Predictive Energy Expenditure Equations Accurate in Cirrhosis? |
title_full_unstemmed | Are Predictive Energy Expenditure Equations Accurate in Cirrhosis? |
title_short | Are Predictive Energy Expenditure Equations Accurate in Cirrhosis? |
title_sort | are predictive energy expenditure equations accurate in cirrhosis? |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412603/ https://www.ncbi.nlm.nih.gov/pubmed/30720726 http://dx.doi.org/10.3390/nu11020334 |
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