Literature DB >> 32512553

Electronic nose: a pilot study to discriminate of children with uncontrolled asthma.

Laura Tenero1, Marco Sandri1, Michele Piazza1, Giulia Paiola1, Marco Zaffanello1, Giorgio L Piacentini1.   

Abstract

BACKGROUND: Measuring biomarkers (e.g., volatile organic compounds [VOCs]) in exhaled breath is an attractive approach to monitor airway inflammation in asthma and other lung diseases. E-Nose technology has been studied to identify VOCs in exhaled breath.
OBJECTIVE: We compared e-Nose respiratory patterns in a pediatric cohort with asthma to classificate children with different asthma control.
METHODS: This cross-sectional study involved 38 children: 28 with asthma and 10 healthy controls . The asthmatic patients were categorized as having controlled (AC), partially controlled (APC) or uncontrolled asthma (ANC). Clinical exams, exhaled breath collection for generating e-Nose VOC profiles, and spirometry were performed. Exhaled breath samples were obtained using a commercial electronic nose (Cyranose 320; Smith Detections, Pasadena, CA, USA). The discriminative ability of breathprints werinvestigated by principal component analysis and penalized logistic regression.
RESULTS: The E-nose was able to discriminate between the CON (controls)+AC and the ANC+APC group with an area under the curve [AUC] of 0.85 (95% confidence interval [CI] 0.72 to 0.98) and a cross-validated AUC of 0.80 (95% CI 0.70 to 0.85). Sensitivity and specificity calculated using the Youden index were 0.79 and 0.84, respectively.
CONCLUSION: Exhaled biomarker patterns were easy to obtain with the device and were able to differentiate children with uncontrolled symptomatic asthma from asymptomatic controls.
© 2020 IOP Publishing Ltd.

Entities:  

Keywords:  asthma; children; electronic nose; volatile organic compounds

Year:  2020        PMID: 32512553     DOI: 10.1088/1752-7163/ab9ab0

Source DB:  PubMed          Journal:  J Breath Res        ISSN: 1752-7155            Impact factor:   3.262


  5 in total

Review 1.  Breath Analysis: A Promising Tool for Disease Diagnosis-The Role of Sensors.

Authors:  Maria Kaloumenou; Evangelos Skotadis; Nefeli Lagopati; Efstathios Efstathopoulos; Dimitris Tsoukalas
Journal:  Sensors (Basel)       Date:  2022-02-06       Impact factor: 3.576

2.  Assessing Gut Microbiota in an Infant with Congenital Propionic Acidemia before and after Probiotic Supplementation.

Authors:  Andrea Bordugo; Elisa Salvetti; Giulia Rodella; Michele Piazza; Alice Dianin; Angela Amoruso; Giorgio Piacentini; Marco Pane; Sandra Torriani; Nicola Vitulo; Giovanna E Felis
Journal:  Microorganisms       Date:  2021-12-16

Review 3.  Potential of the Electronic Nose for the Detection of Respiratory Diseases with and without Infection.

Authors:  Johann-Christoph Licht; Hartmut Grasemann
Journal:  Int J Mol Sci       Date:  2020-12-10       Impact factor: 5.923

Review 4.  The smell of lung disease: a review of the current status of electronic nose technology.

Authors:  I G van der Sar; N Wijbenga; M E Hellemons; C C Moor; G Nakshbandi; J G J V Aerts; O C Manintveld; M S Wijsenbeek
Journal:  Respir Res       Date:  2021-09-17

Review 5.  Application of Machine Learning Algorithms for Asthma Management with mHealth: A Clinical Review.

Authors:  Kevin C H Tsang; Hilary Pinnock; Andrew M Wilson; Syed Ahmar Shah
Journal:  J Asthma Allergy       Date:  2022-06-29
  5 in total

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