| Title: | "Chemometric analysis of the global pattern of volatile organic compounds in the exhaled breath of patients with COVID-19, post-COVID and healthy subjects. Proof of concept for post-COVID assessment" |
| Author(s): | Zamora-Mendoza BN; Diaz de Leon-Martinez L; Rodriguez-Aguilar M; Mizaikoff B; 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, Colonia Lomas Segunda Seccion, CP, 78210, San Luis Potosi, SLP, Mexico. Faculty of Medicine-Center for Applied Research on Environment and Health (CIAAS), Autonomous University of San Luis Potosi, Avenida Sierra Leona No. 550, Colonia Lomas Segunda Seccion, CP, 78210, San Luis Potosi, SLP, Mexico. Electronic address: loredldv@gmail.com. Department of Pharmacy, Health Sciences Division. University of Quintana Roo, Quintana Roo, Mexico. Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081, Ulm, Germany; Hahn-Schickard Institute for Microanalysis Systems, Sedanstrasse 14, 89077, Ulm, Germany. 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, SLP, Mexico. Electronic address: rfloresra@conacyt.mx" |
| DOI: | 10.1016/j.talanta.2021.122832 |
| ISSN/ISBN: | 1873-3573 (Electronic) 0039-9140 (Print) 0039-9140 (Linking) |
| Abstract: | "The objective of this research was to evaluate the application of an electronic nose and chemometric analysis to discriminate volatile organic compounds between patients with COVID-19, post-COVID syndrome and controls in exhaled breath samples. A cross-sectional study was performed on 102 exhaled breath samples, 42 with COVID-19, 30 with the post-COVID syndrome and 30 control subjects. Breath-print analysis was performed by the Cyranose 320 electronic nose with 32 sensors. Group data were evaluated by Principal Component Analysis (PCA), Canonical Discriminant Analysis (CDA), and Support Vector Machine (SVM), and the test's diagnostic power was evaluated through a Receiver Operaring Characteristic curve(ROC curve). The results of the chemometric analysis indicate in the PCA a 97.6% (PC(1) = 95.9%, PC(2) = 1.0%, PC(3) = 0.7%) of explanation of the variability between the groups by means of 3 PCs, the CDA presents a 100% of correct classification of the study groups, SVM a 99.4% of correct classification, finally the PLS-DA indicates an observable separation between the groups and the 12 sensors that were related. The sensitivity, specificity of post-COVID vs. controls value reached 97.6% (87.4%-99.9%) and 100% (88.4%-100%) respectively, according to the ROC curve. As a perspective, we consider that this technology, due to its simplicity, low cost and portability, can support strategies for the identification and follow-up of post-COVID patients. The proposed classification model provides the basis for evaluating post-COVID patients; therefore, further studies are required to enable the implementation of this technology to support clinical management and mitigation of effects" |
| Keywords: | *covid-19 Cross-Sectional Studies Healthy Volunteers Humans SARS-CoV-2 *Volatile Organic Compounds Covid-19 Chemometric data analysis Electronic nose system Exhaled breath analysis Post-COVID syndrome Volatile organic compounds; |
| Notes: | "MedlineZamora-Mendoza, Blanca Nohemi Diaz de Leon-Martinez, Lorena Rodriguez-Aguilar, Maribel Mizaikoff, Boris Flores-Ramirez, Rogelio eng Netherlands 2021/10/13 Talanta. 2022 Jan 1; 236:122832. doi: 10.1016/j.talanta.2021.122832. Epub 2021 Sep 2" |
