↓ Skip to main content

On the imperfect synchrony between patient and ventilator

Overview of attention for article published in Critical Care, August 2012
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
31 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
On the imperfect synchrony between patient and ventilator
Published in
Critical Care, August 2012
DOI 10.1186/cc10300
Pubmed ID
Authors

Paolo Navalesi

Abstract

Because patient-ventilator asynchrony (PVA) is recognized as a major clinical problem for patients undergoing ventilatory assistance, automatic methods of PVA detection have been proposed in recent years. A novel approach is airflow spectral analysis, which, when related to visual inspection of airway pressure and flow waveforms, has been shown to reach a sensitivity and specificity of greater than 80% in detecting an asynchrony index of greater than 10%. The availability of automatic non-invasive methods of PVA detection at the bedside would likely be of benefit in intensive care unit practice, but they may be limited by shortcomings, so clear proof of their effectiveness is needed.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Other 7 23%
Researcher 7 23%
Professor 3 10%
Student > Doctoral Student 3 10%
Student > Ph. D. Student 3 10%
Other 7 23%
Unknown 1 3%
Readers by discipline Count As %
Medicine and Dentistry 21 68%
Engineering 3 10%
Neuroscience 1 3%
Nursing and Health Professions 1 3%
Unknown 5 16%

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 23 August 2012.
All research outputs
#2,015,199
of 3,631,265 outputs
Outputs from Critical Care
#1,399
of 2,157 outputs
Outputs of similar age
#35,547
of 74,958 outputs
Outputs of similar age from Critical Care
#80
of 118 outputs
Altmetric has tracked 3,631,265 research outputs across all sources so far. This one is in the 25th percentile – i.e., 25% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,157 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 20th percentile – i.e., 20% 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 74,958 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.