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Breath-print analysis by e-nose for classifying and monitoring chronic liver disease: a proof-of-concept study

Overview of attention for article published in Scientific Reports, May 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
13 news outlets
blogs
1 blog
twitter
2 tweeters
patent
1 patent

Citations

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26 Dimensions

Readers on

mendeley
46 Mendeley
Title
Breath-print analysis by e-nose for classifying and monitoring chronic liver disease: a proof-of-concept study
Published in
Scientific Reports, May 2016
DOI 10.1038/srep25337
Pubmed ID
Authors

Antonio De Vincentis, Giorgio Pennazza, Marco Santonico, Umberto Vespasiani-Gentilucci, Giovanni Galati, Paolo Gallo, Chiara Vernile, Claudio Pedone, Raffaele Antonelli Incalzi, Antonio Picardi

Abstract

Since the liver plays a key metabolic role, volatile organic compounds in the exhaled breath might change with type and severity of chronic liver disease (CLD). In this study we analysed breath-prints (BPs) of 65 patients with liver cirrhosis (LC), 39 with non-cirrhotic CLD (NC-CLD) and 56 healthy controls by the e-nose. Distinctive BPs characterized LC, NC-CLD and healthy controls, and, among LC patients, the different Child-Pugh classes (sensitivity 86.2% and specificity 98.2% for CLD vs healthy controls, and 87.5% and 69.2% for LC vs NC-CLD). Moreover, the area under the BP profile, derived from radar-plot representation of BPs, showed an area under the ROC curve of 0.84 (95% CI 0.76-0.91) for CLD, of 0.76 (95% CI 0.66-0.85) for LC, and of 0.70 (95% CI 0.55-0.81) for decompensated LC. By applying the cut-off values of 862 and 812, LC and decompensated LC could be predicted with high accuracy (PPV 96.6% and 88.5%, respectively). These results are proof-of-concept that the e-nose could be a valid non-invasive instrument for characterizing CLD and monitoring hepatic function over time. The observed classificatory properties might be further improved by refining stage-specific breath-prints and considering the impact of comorbidities in a larger series of patients.

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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 17%
Student > Ph. D. Student 6 13%
Student > Master 6 13%
Researcher 5 11%
Other 5 11%
Other 8 17%
Unknown 8 17%
Readers by discipline Count As %
Medicine and Dentistry 8 17%
Engineering 6 13%
Chemistry 5 11%
Biochemistry, Genetics and Molecular Biology 5 11%
Nursing and Health Professions 3 7%
Other 6 13%
Unknown 13 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 118. 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 13 July 2021.
All research outputs
#227,149
of 19,069,422 outputs
Outputs from Scientific Reports
#2,653
of 102,616 outputs
Outputs of similar age
#6,606
of 304,567 outputs
Outputs of similar age from Scientific Reports
#145
of 5,203 outputs
Altmetric has tracked 19,069,422 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 102,616 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.1. This one has done particularly well, scoring higher than 97% of its peers.
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 304,567 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 5,203 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.