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Attention Score in Context
| Title |
Applicability of predictive equations for resting energy expenditure in obese patients with obstructive sleep apnea
|
|---|---|
| Published in |
Archives of Endocrinology and Metabolism, November 2016
|
| DOI | 10.1590/2359-3997000000228 |
| Pubmed ID | |
| Authors |
Mariana Pantaleão del Re, Camila Maria de Melo, Marcus Vinicius dos Santos, Sergio Tufik, Marco Túlio de Mello |
| Abstract |
To investigate the applicability of predictive equations for resting energy expenditure (REE) in obese individuals with obstructive sleep apnea (OSA) and the effects of OSA severity on REE. Twenty-nine obese men, 41.5 ± 7 years old, with moderate and severe OSA were recruited. All subjects were submitted to a clinical polysomnography, body composition, and indirect calorimetry measurements. REE was also predicted by three different equations: Harris and Benedict (1919), Cunningham (1990), and DRI (2002). No effects of OSA severity on REE were found. The measured REE (2416.0 ± 447.1 kcal/day) and the REE predicted by equations were different from each other (F = 2713.88; p < 0.05): Harris and Benedict (2128.0 ± 245.8 kcal/day), Cunningham (1789.1 ± 167.8 kcal/day) and DRI (2011.1 ± 181.4 kcal/day). Pearson correlations showed a moderate positive correlation between the REE measured and predicted by all equations. Our findings suggest that predictive equations for REE underestimate the energy expenditure in obese patients with sleep apnea. Also, no effects of OSA severity on REE were found. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 14% |
| Student > Bachelor | 4 | 14% |
| Researcher | 3 | 10% |
| Student > Doctoral Student | 2 | 7% |
| Other | 2 | 7% |
| Other | 5 | 17% |
| Unknown | 9 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 28% |
| Nursing and Health Professions | 3 | 10% |
| Social Sciences | 2 | 7% |
| Computer Science | 1 | 3% |
| Psychology | 1 | 3% |
| Other | 4 | 14% |
| Unknown | 10 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 26 September 2017.
All research outputs
#22,759,452
of 25,374,647 outputs
Outputs from Archives of Endocrinology and Metabolism
#648
of 800 outputs
Outputs of similar age
#355,244
of 415,346 outputs
Outputs of similar age from Archives of Endocrinology and Metabolism
#9
of 10 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 800 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one.