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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Temperature variability analysis using wavelets and multiscale entropy in patients with systemic inflammatory response syndrome, sepsis, and septic shock
|
|---|---|
| Published in |
Critical Care, March 2012
|
| DOI | 10.1186/cc11255 |
| Pubmed ID | |
| Authors |
Vasilios E Papaioannou, Ioanna G Chouvarda, Nikos K Maglaveras, Ioannis A Pneumatikos |
| Abstract |
Even though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature complexity in patients with systemic inflammation during a suspected ICU-acquired infection, by using wavelets transformation and multiscale entropy of temperature signals, in a cohort of mixed critically ill patients. |
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 % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| France | 1 | 1% |
| Romania | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 70 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 19% |
| Student > Ph. D. Student | 8 | 11% |
| Other | 7 | 9% |
| Student > Postgraduate | 7 | 9% |
| Student > Master | 6 | 8% |
| Other | 17 | 23% |
| Unknown | 15 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 31 | 42% |
| Biochemistry, Genetics and Molecular Biology | 6 | 8% |
| Nursing and Health Professions | 4 | 5% |
| Computer Science | 4 | 5% |
| Engineering | 4 | 5% |
| Other | 7 | 9% |
| Unknown | 18 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 31 October 2017.
All research outputs
#7,959,659
of 25,373,627 outputs
Outputs from Critical Care
#4,224
of 6,554 outputs
Outputs of similar age
#51,658
of 171,640 outputs
Outputs of similar age from Critical Care
#47
of 122 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 6,554 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one is in the 34th percentile – i.e., 34% 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 171,640 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 68% of its contemporaries.
We're also able to compare this research output to 122 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 59% of its contemporaries.