↓ Skip to main content

Using the Electronic Nose to Identify Airway Infection during COPD Exacerbations

Overview of attention for article published in PLOS ONE, September 2015
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
109 Mendeley
Title
Using the Electronic Nose to Identify Airway Infection during COPD Exacerbations
Published in
PLOS ONE, September 2015
DOI 10.1371/journal.pone.0135199
Pubmed ID
Authors

Hanaa Shafiek, Federico Fiorentino, Jose Luis Merino, Carla López, Antonio Oliver, Jaume Segura, Ivan de Paul, Oriol Sibila, Alvar Agustí, Borja G Cosío

Abstract

The electronic nose (e-nose) detects volatile organic compounds (VOCs) in exhaled air. We hypothesized that the exhaled VOCs print is different in stable vs. exacerbated patients with chronic obstructive pulmonary disease (COPD), particularly if the latter is associated with airway bacterial infection, and that the e-nose can distinguish them. Smell-prints of the bacteria most commonly involved in exacerbations of COPD (ECOPD) were identified in vitro. Subsequently, we tested our hypothesis in 93 patients with ECOPD, 19 of them with pneumonia, 50 with stable COPD and 30 healthy controls in a cross-sectional case-controlled study. Secondly, ECOPD patients were re-studied after 2 months if clinically stable. Exhaled air was collected within a Tedlar bag and processed by a Cynarose 320 e-nose. Breath-prints were analyzed by Linear Discriminant Analysis (LDA) with "One Out" technique and Sensor logic Relations (SLR). Sputum samples were collected for culture. ECOPD with evidence of infection were significantly distinguishable from non-infected ECOPD (p = 0.018), with better accuracy when ECOPD was associated to pneumonia. The same patients with ECOPD were significantly distinguishable from stable COPD during follow-up (p = 0.018), unless the patient was colonized. Additionally, breath-prints from COPD patients were significantly distinguished from healthy controls. Various bacteria species were identified in culture but the e-nose was unable to identify accurately the bacteria smell-print in infected patients. E-nose can identify ECOPD, especially if associated with airway bacterial infection or pneumonia.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 108 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 13%
Student > Master 14 13%
Researcher 12 11%
Student > Bachelor 10 9%
Student > Doctoral Student 8 7%
Other 26 24%
Unknown 25 23%
Readers by discipline Count As %
Medicine and Dentistry 29 27%
Engineering 11 10%
Biochemistry, Genetics and Molecular Biology 5 5%
Computer Science 4 4%
Immunology and Microbiology 4 4%
Other 22 20%
Unknown 34 31%
Attention Score in Context

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 11 September 2015.
All research outputs
#12,935,224
of 22,828,180 outputs
Outputs from PLOS ONE
#101,124
of 194,843 outputs
Outputs of similar age
#118,359
of 267,220 outputs
Outputs of similar age from PLOS ONE
#2,554
of 5,806 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 194,843 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one is in the 46th percentile – i.e., 46% 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 267,220 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 54% of its contemporaries.
We're also able to compare this research output to 5,806 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 54% of its contemporaries.