| Title: | Determination of global chemical patterns in exhaled breath for the discrimination of lung damage in postCOVID patients using olfactory technology |
| Author(s): | Zamora-Mendoza BN; Sandoval-Flores H; Rodriguez-Aguilar M; Jimenez-Gonzalez C; Alcantara-Quintana LE; Berumen-Rodriguez AA; Flores-Ramirez R; |
| Address: | "Faculty of Medicine-Center for Applied Research on Environment and Health (CIAAS), Autonomous University of San Luis Potosi, Avenida Sierra Leona No. 550, CP 78210, Colonia Lomas Segunda Seccion, San Luis Potosi, Mexico. Department of Pharmacy, Health Sciences Division. University of Quintana Roo, Quintana Roo, Mexico. CONACYT Research Fellow, Coordination for Innovation and Application of Science and Technology (CIACYT), Autonomous University of San Luis Potosi, Avenida Sierra Leona No. 550, CP 78210, Colonia Lomas Segunda Seccion, San Luis Potosi, Mexico. CONACYT Research Fellow, Coordination for Innovation and Application of Science and Technology (CIACYT), Autonomous University of San Luis Potosi, Avenida Sierra Leona No. 550, CP 78210, Colonia Lomas Segunda Seccion, San Luis Potosi, Mexico. Electronic address: rfloresra@conacyt.mx" |
| DOI: | 10.1016/j.talanta.2023.124299 |
| ISSN/ISBN: | 1873-3573 (Electronic) 0039-9140 (Linking) |
| Abstract: | "The objective of this work was to evaluate the use of an electronic nose and chemometric analysis to discriminate global patterns of volatile organic compounds (VOCs) in breath of postCOVID syndrome patients with pulmonary sequelae. A cross-sectional study was performed in two groups, the group 1 were subjects recovered from COVID-19 without lung damage and the group 2 were subjects recovered from COVID-19 with impaired lung function. The VOCs analysis was executed using a Cyranose 320 electronic nose with 32 sensors, applying principal component analysis (PCA), Partial Least Square-Discriminant Analysis, random forest, canonical discriminant analysis (CAP) and the diagnostic power of the test was evaluated using the ROC (Receiver Operating Characteristic) curve. A total of 228 participants were obtained, for the postCOVID group there are 157 and 71 for the control group, the chemometric analysis results indicate in the PCA an 84% explanation of the variability between the groups, the PLS-DA indicates an observable separation between the groups and 10 sensors related to this separation, by random forest, a classification error was obtained for the control group of 0.090 and for the postCOVID group of 0.088 correct classification. The CAP model showed 83.8% of correct classification and the external validation of the model showed 80.1% of correct classification. Sensitivity and specificity reached 88.9% (73.9%-96.9%) and 96.9% (83.7%-99.9%) respectively. It is considered that this technology can be used to establish the starting point in the evaluation of lung damage in postCOVID patients with pulmonary sequelae" |
| Keywords: | Humans Cross-Sectional Studies Breath Tests/methods *COVID-19/diagnosis Lung/chemistry Sensitivity and Specificity Exhalation Electronic Nose *Volatile Organic Compounds/analysis Exhaled breath Pulmonary sequelae Volatile organic compounds postCOVID scree; |
| Notes: | "MedlineZamora-Mendoza, Blanca Nohemi Sandoval-Flores, Hannia Rodriguez-Aguilar, Maribel Jimenez-Gonzalez, Carlos Alcantara-Quintana, Luz Eugenia Berumen-Rodriguez, Alejandra Abigail Flores-Ramirez, Rogelio eng Netherlands 2023/01/26 Talanta. 2023 May 1; 256:124299. doi: 10.1016/j.talanta.2023.124299. Epub 2023 Jan 20" |
