| Title: | Post-COVID syndrome screening through breath analysis using electronic nose technology |
| Author(s): | V RN; Mohapatra AK; V KU; Lukose J; Kartha VB; Chidangil S; |
| Address: | "Centre of Excellence for Biophotonics, Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal, Karnataka, India, 576104. Department of Respiratory Medicine, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India, 576104. Centre of Excellence for Biophotonics, Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Manipal, Karnataka, India, 576104. santhosh.cls@manipal.edu" |
| DOI: | 10.1007/s00216-022-03990-z |
| ISSN/ISBN: | 1618-2650 (Electronic) 1618-2642 (Print) 1618-2642 (Linking) |
| Abstract: | "There is an urgent need to have reliable technologies to diagnose post-coronavirus disease syndrome (PCS), as the number of people affected by COVID-19 and related complications is increasing worldwide. Considering the amount of risks associated with the two chronic lung diseases, asthma and chronic obstructive pulmonary disease (COPD), there is an immediate requirement for a screening method for PCS, which also produce symptoms similar to these conditions, especially since very often, many COVID-19 cases remain undetected because a good share of such patients is asymptomatic. Breath analysis techniques are getting attention since they are highly non-invasive methods for disease diagnosis, can be implemented easily for point-of-care applications even in primary health care centres. Electronic (E-) nose technology is coming up with better reliability, ease of operation, and affordability to all, and it can generate signatures of volatile organic compounds (VOCs) in exhaled breath as markers of diseases. The present report is an outcome of a pilot study using an E-nose device on breath samples of cohorts of PCS, asthma, and normal (control) subjects. Match/no-match and k-NN analysis tests have been carried out to confirm the diagnosis of PCS. The prediction model has given 100% sensitivity and specificity. Receiver operating characteristics (ROC) has been plotted for the prediction model, and the area under the curve (AUC) is obtained as 1. The E-nose technique is found to be working well for PCS diagnosis. Our study suggests that the breath analysis using E-nose can be used as a point-of-care diagnosis of PCS.Trial registrationBreath samples were collected from the Kasturba Hospital, Manipal. Ethical clearance was obtained from the Institutional Ethics Committee, Kasturba Medical College, Manipal (IEC 60/2021, 13/01/2021) and Indian Council of Medical Research (ICMR) (CTRI/2021/02/031357, 06/02/2021) Government of India; trials were prospectively registered" |
| Keywords: | *Asthma/diagnosis Breath Tests/methods *COVID-19/diagnosis Electronic Nose Exhalation Humans Pilot Projects Reproducibility of Results Technology *Volatile Organic Compounds/analysis Biosensor Breath analysis Chemometrics E-nose Post-COVID syndrome; |
| Notes: | "MedlineV R, Nidheesh Mohapatra, Aswini Kumar V K, Unnikrishnan Lukose, Jijo Kartha, Vasudevan Baskaran Chidangil, Santhosh eng Germany 2022/03/19 Anal Bioanal Chem. 2022 May; 414(12):3617-3624. doi: 10.1007/s00216-022-03990-z. Epub 2022 Mar 18" |
