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

Overview of attention for article published in Nutrition & Metabolism, November 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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2 tweeters
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5 Facebook pages

Citations

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45 Dimensions

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82 Mendeley
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Title
Predicting resting energy expenditure in underweight, normal weight, overweight, and obese adult hospital patients
Published in
Nutrition & Metabolism, November 2016
DOI 10.1186/s12986-016-0145-3
Pubmed ID
Authors

Hinke M. Kruizenga, Geesje H. Hofsteenge, Peter J.M. Weijs

Abstract

When indirect calorimetry is not available, predictive equations are used to estimate resing energy expenditure (REE). There is no consensus about which equation to use in hospitalized patients. The objective of this study is to examine the validity of REE predictive equations for underweight, normal weight, overweight, and obese inpatients and outpatients by comparison with indirect calorimetry. Equations were included when based on weight, height, age, and/or gender. REE was measured with indirect calorimetry. A prediction between 90 and 110% of the measured REE was considered accurate. The bias and root-mean-square error (RMSE) were used to evaluate how well the equations fitted the REE measurement. Subgroup analysis was performed for BMI. A new equation was developed based on regression analysis and tested. 513 general hospital patients were included, (253 F, 260 M), 237 inpatients and 276 outpatients. Fifteen predictive equations were used. The most used fixed factors (25 kcal/kg/day, 30 kcal/kg/day and 2000 kcal for female and 2500 kcal for male) were added. The percentage of accurate predicted REE was low in all equations, ranging from 8 to 49%. Overall the new equation performed equal to the best performing Korth equation and slightly better than the well-known WHO equation based on weight and height (49% vs 45% accurate). Categorized by BMI subgroups, the new equation, Korth and the WHO equation based on weight and height performed best in all categories except from the obese subgroup. The original Harris and Benedict (HB) equation was best for obese patients. REE predictive equations are only accurate in about half the patients. The WHO equation is advised up to BMI 30, and HB equation is advised for obese (over BMI 30). Measuring REE with indirect calorimetry is preferred, and should be used when available and feasible in order to optimize nutritional support in hospital inpatients and outpatients with different degrees of malnutrition.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 21%
Student > Bachelor 16 20%
Researcher 8 10%
Other 5 6%
Student > Ph. D. Student 4 5%
Other 11 13%
Unknown 21 26%
Readers by discipline Count As %
Nursing and Health Professions 19 23%
Medicine and Dentistry 15 18%
Agricultural and Biological Sciences 6 7%
Sports and Recreations 4 5%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 8 10%
Unknown 28 34%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 03 April 2017.
All research outputs
#3,844,024
of 9,339,536 outputs
Outputs from Nutrition & Metabolism
#313
of 568 outputs
Outputs of similar age
#114,318
of 315,869 outputs
Outputs of similar age from Nutrition & Metabolism
#7
of 22 outputs
Altmetric has tracked 9,339,536 research outputs across all sources so far. This one has received more attention than most of these and is in the 58th percentile.
So far Altmetric has tracked 568 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.7. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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 315,869 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 22 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 63% of its contemporaries.