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Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept

Overview of attention for article published in Critical Care, October 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

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19 tweeters
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1 Google+ user

Citations

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47 Dimensions

Readers on

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87 Mendeley
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Title
Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept
Published in
Critical Care, October 2015
DOI 10.1186/s13054-015-1087-2
Pubmed ID
Authors

Sandra N. Stapel, Harm-Jan S. de Grooth, Hoda Alimohamad, Paul W G Elbers, Armand R J Girbes, Peter J M Weijs, Heleen M. Oudemans-van Straaten

Abstract

Measurement of energy expenditure (EE) is recommended to guide nutrition in critically ill patients. Availability of a gold standard indirect calorimetry is limited, and continuous measurement is unfeasible. Equations used to predict EE are inaccurate. The purpose of this study was to provide proof of concept that EE can be accurately assessed on the basis of ventilator-derived carbon dioxide production (VCO2) and to determine whether this method is more accurate than frequently used predictive equations. In 84 mechanically ventilated critically ill patients, we performed 24-h indirect calorimetry to obtain a gold standard EE. Simultaneously, we collected 24-h ventilator-derived VCO2, extracted the respiratory quotient of the administered nutrition, and calculated EE with a rewritten Weir formula. Bias, precision, and accuracy and inaccuracy rates were determined and compared with four predictive equations: the Harris-Benedict, Faisy, and Penn State University equations and the European Society for Clinical Nutrition and Metabolism (ESPEN) guideline equation of 25 kcal/kg/day. Mean 24-h indirect calorimetry EE was 1823 ± 408 kcal. EE from ventilator-derived VCO2 was accurate (bias +141 ± 153 kcal/24 h; 7.7 % of gold standard) and more precise than the predictive equations (limits of agreement -166 to +447 kcal/24 h). The 10 % and 15 % accuracy rates were 61 % and 76 %, respectively, which were significantly higher than those of the Harris-Benedict, Faisy, and ESPEN guideline equations. Large errors of more than 30 % inaccuracy did not occur with EE derived from ventilator-derived VCO2. This 30 % inaccuracy rate was significantly lower than that of the predictive equations. In critically ill mechanically ventilated patients, assessment of EE based on ventilator-derived VCO2 is accurate and more precise than frequently used predictive equations. It allows for continuous monitoring and is the best alternative to indirect calorimetry.

Twitter Demographics

The data shown below were collected from the profiles of 19 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Unknown 86 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 22%
Other 13 15%
Student > Ph. D. Student 9 10%
Student > Master 9 10%
Professor 7 8%
Other 19 22%
Unknown 11 13%
Readers by discipline Count As %
Medicine and Dentistry 50 57%
Nursing and Health Professions 10 11%
Biochemistry, Genetics and Molecular Biology 2 2%
Agricultural and Biological Sciences 2 2%
Engineering 2 2%
Other 4 5%
Unknown 17 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 August 2019.
All research outputs
#1,786,766
of 16,104,892 outputs
Outputs from Critical Care
#1,643
of 5,078 outputs
Outputs of similar age
#39,111
of 286,849 outputs
Outputs of similar age from Critical Care
#166
of 366 outputs
Altmetric has tracked 16,104,892 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,078 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.0. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 286,849 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 366 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.