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X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profiles of 51 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 6 | 12% |
| Belgium | 4 | 8% |
| United States | 3 | 6% |
| United Kingdom | 3 | 6% |
| Japan | 2 | 4% |
| Spain | 2 | 4% |
| Portugal | 1 | 2% |
| Switzerland | 1 | 2% |
| Uruguay | 1 | 2% |
| Other | 4 | 8% |
| Unknown | 24 | 47% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 35 | 69% |
| Scientists | 8 | 16% |
| Practitioners (doctors, other healthcare professionals) | 7 | 14% |
| Science communicators (journalists, bloggers, editors) | 1 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 140 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | <1% |
| Unknown | 139 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 22% |
| Other | 15 | 11% |
| Student > Master | 12 | 9% |
| Student > Ph. D. Student | 10 | 7% |
| Professor | 10 | 7% |
| Other | 26 | 19% |
| Unknown | 36 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 64 | 46% |
| Nursing and Health Professions | 11 | 8% |
| Engineering | 4 | 3% |
| Agricultural and Biological Sciences | 2 | 1% |
| Biochemistry, Genetics and Molecular Biology | 2 | 1% |
| Other | 10 | 7% |
| Unknown | 47 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 30. 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 18 May 2023.
All research outputs
#1,323,411
of 25,529,543 outputs
Outputs from Critical Care
#1,123
of 6,580 outputs
Outputs of similar age
#19,313
of 294,614 outputs
Outputs of similar age from Critical Care
#61
of 441 outputs
Altmetric has tracked 25,529,543 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,580 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one has done well, scoring higher than 82% 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 294,614 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 441 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.