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Long GA, Xu Q, Sunkara J, Woodbury R, Brown K, Huang JJ, Xie Z, Chen X, Fu XA, Huang J. A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds. Diagn Microbiol Infect Dis 2024; 109:116309. [PMID: 38692202 DOI: 10.1016/j.diagmicrobio.2024.116309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 05/03/2024]
Abstract
BACKGROUND The COVID-19 pandemic had profound global impacts on daily lives, economic stability, and healthcare systems. Diagnosis of COVID-19 infection via RT-PCR was crucial in reducing spread of disease and informing treatment management. While RT-PCR is a key diagnostic test, there is room for improvement in the development of diagnostic criteria. Identification of volatile organic compounds (VOCs) in exhaled breath provides a fast, reliable, and economically favorable alternative for disease detection. METHODS This meta-analysis analyzed the diagnostic performance of VOC-based breath analysis in detection of COVID-19 infection. A systematic review of twenty-nine papers using the grading criteria from Newcastle-Ottawa Scale (NOS) and PRISMA guidelines was conducted. RESULTS The cumulative results showed a sensitivity of 0.92 (95 % CI, 90 %-95 %) and a specificity of 0.90 (95 % CI 87 %-93 %). Subgroup analysis by variant demonstrated strong sensitivity to the original strain compared to the Omicron and Delta variant in detection of SARS-CoV-2 infection. An additional subgroup analysis of detection methods showed eNose technology had the highest sensitivity when compared to GC-MS, GC-IMS, and high sensitivity-MS. CONCLUSION Overall, these results support the use of breath analysis as a new detection method of COVID-19 infection.
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Affiliation(s)
- Grace A Long
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Qian Xu
- Biometrics and Data Science, Fosun Pharma, Beijing, PR China
| | - Jahnavi Sunkara
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Reagan Woodbury
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Katherine Brown
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | | | - Zhenzhen Xie
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - Xiaoyu Chen
- Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY, USA.
| | - Xiao-An Fu
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
| | - Jiapeng Huang
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA..
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2
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Glöckler J, Mizaikoff B, Díaz de León-Martínez L. SARS CoV-2 infection screening via the exhaled breath fingerprint obtained by FTIR spectroscopic gas-phase analysis. A proof of concept. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 302:123066. [PMID: 37356392 PMCID: PMC10286574 DOI: 10.1016/j.saa.2023.123066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 05/30/2023] [Accepted: 06/20/2023] [Indexed: 06/27/2023]
Abstract
The COVID-19 pandemic remains a global challenge now with the long-COVID arising. Mitigation measures focused on case counting, assessment and determination of variants and their likely targets of infection and transmission, the pursuit of drug treatments, use and enhancement of masks, social distancing, vaccination, post-infection rehabilitation, and mass screening. The latter is of utmost importance given the current scenario of infections, reinfections, and long-term health effects. Research on screening platforms has been developed to provide more sensitive, specific, and reliable tests that are accessible to the entire population and can be used to assess the prognosis of the disease as well as the subsequent health follow-up of patients with sequelae of COVID-19. Therefore, the aim of the present study was the simulation of exhaled breath of COVID-19 patients by evaluation of three identified COVID-19 indicator breath biomarkers (acetone (ACE), acetaldehyde (ACH) and nitric oxide (NO)) by gas-phase infrared spectroscopy as a proof-of-concept principle for the detection of infected patients' exhaled breath fingerprint and subsequent follow-up. The specific fingerprints of each of the compounds and the overall fingerprint were obtained. The synthetic exhaled breath evaluation concept revealed a linearity of r = 0.99 for all compounds, and LODs of 6.42, 13.81, 9.22 ppm, and LOQs of 42.26, 52.57, 69.23 ppm for NO, ACE, and ACH, respectively. This study proves the fundamental feasibility of gas-phase infrared spectroscopy for fingerprinting lung damage biomarkers in exhaled breath of patients with COVID-19. This analysis would allow faster and cheaper screening and follow-up of infected individuals, which could improve mass screening in POC settings.
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Affiliation(s)
- Johannes Glöckler
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany
| | - Boris Mizaikoff
- 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
| | - Lorena Díaz de León-Martínez
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081 Ulm, Germany.
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3
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Roquencourt C, Salvator H, Bardin E, Lamy E, Farfour E, Naline E, Devillier P, Grassin-Delyle S. Enhanced real-time mass spectrometry breath analysis for the diagnosis of COVID-19. ERJ Open Res 2023; 9:00206-2023. [PMID: 37727677 PMCID: PMC10505950 DOI: 10.1183/23120541.00206-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 06/21/2023] [Indexed: 09/21/2023] Open
Abstract
Background Although rapid screening for and diagnosis of coronavirus disease 2019 (COVID-19) are still urgently needed, most current testing methods are long, costly or poorly specific. The objective of the present study was to determine whether or not artificial-intelligence-enhanced real-time mass spectrometry breath analysis is a reliable, safe, rapid means of screening ambulatory patients for COVID-19. Methods In two prospective, open, interventional studies in a single university hospital, we used real-time, proton transfer reaction time-of-flight mass spectrometry to perform a metabolomic analysis of exhaled breath from adults requiring screening for COVID-19. Artificial intelligence and machine learning techniques were used to build mathematical models based on breath analysis data either alone or combined with patient metadata. Results We obtained breath samples from 173 participants, of whom 67 had proven COVID-19. After using machine learning algorithms to process breath analysis data and further enhancing the model using patient metadata, our method was able to differentiate between COVID-19-positive and -negative participants with a sensitivity of 98%, a specificity of 74%, a negative predictive value of 98%, a positive predictive value of 72% and an area under the receiver operating characteristic curve of 0.961. The predictive performance was similar for asymptomatic, weakly symptomatic and symptomatic participants and was not biased by COVID-19 vaccination status. Conclusions Real-time, noninvasive, artificial-intelligence-enhanced mass spectrometry breath analysis might be a reliable, safe, rapid, cost-effective, high-throughput method for COVID-19 screening.
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Affiliation(s)
| | - Hélène Salvator
- Exhalomics, Hôpital Foch, Suresnes, France
- Service de Pneumologie, Hôpital Foch, Suresnes, France
- Laboratoire de Recherche en Pharmacologie Respiratoire – VIM Suresnes, UMR 0892, Université Paris-Saclay, Suresnes, France
| | - Emmanuelle Bardin
- Exhalomics, Hôpital Foch, Suresnes, France
- Université Paris-Saclay, UVSQ, INSERM, Infection et inflammation (2I), U1173, Département de Biotechnologie de la Santé, Montigny le Bretonneux, France
- Institut Necker Enfants Malades, U1151, Paris, France
| | - Elodie Lamy
- Université Paris-Saclay, UVSQ, INSERM, Infection et inflammation (2I), U1173, Département de Biotechnologie de la Santé, Montigny le Bretonneux, France
| | - Eric Farfour
- Service de Biologie Clinique, Hôpital Foch, Suresnes, France
| | | | - Philippe Devillier
- Exhalomics, Hôpital Foch, Suresnes, France
- Laboratoire de Recherche en Pharmacologie Respiratoire – VIM Suresnes, UMR 0892, Université Paris-Saclay, Suresnes, France
| | - Stanislas Grassin-Delyle
- Exhalomics, Hôpital Foch, Suresnes, France
- Université Paris-Saclay, UVSQ, INSERM, Infection et inflammation (2I), U1173, Département de Biotechnologie de la Santé, Montigny le Bretonneux, France
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4
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Ghazaly C, Biletska K, Thevenot EA, Devillier P, Naline E, Grassin-Delyle S, Scorsone E. Assessment of an e-nose performance for the detection of COVID-19 specific biomarkers. J Breath Res 2023; 17. [PMID: 36749983 DOI: 10.1088/1752-7163/acb9b2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 02/07/2023] [Indexed: 02/09/2023]
Abstract
Early, rapid and non-invasive diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is needed for the prevention and control of coronavirus disease 2019 (COVID-19). COVID-19 mainly affects the respiratory tract and lungs. Therefore, analysis of exhaled breath could be an alternative scalable method for reliable SARS-CoV-2 screening. In the current study, an experimental protocol using an electronic-nose ('e-nose') for attempting to identify a specific respiratory imprint in COVID-19 patients was optimized. Thus the analytical performances of the Cyranose®, a commercial e-nose device, were characterized under various controlled conditions. In addition, the effect of various experimental conditions on its sensor array response was assessed, including relative humidity, sampling time and flow rate, aiming to select the optimal parameters. A statistical data analysis was applied to e-nose sensor response using common statistical analysis algorithms in an attempt to demonstrate the possibility to detect the presence of low concentrations of spiked acetone and nonanal in the breath samples of a healthy volunteer. Cyranose®reveals a possible detection of low concentrations of these two compounds, in particular of 25 ppm nonanal, a possible marker of SARS-CoV-2 in the breath.
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Affiliation(s)
| | | | - Etienne A Thevenot
- Département Médicaments et Technologies pour la Santé (DMTS), Université Paris-Saclay, CEA, INRAE, MetaboHUB, 91191 Gif-sur-Yvette, France
| | - Philippe Devillier
- Département des maladies des voies respiratoires, Hôpital Foch, Exhalomics, Suresnes, France.,VIM Suresnes, UMR-0892, Université Paris-Saclay, UVSQ, Suresnes, France
| | - Emmanuel Naline
- Département des maladies des voies respiratoires, Hôpital Foch, Exhalomics, Suresnes, France.,VIM Suresnes, UMR-0892, Université Paris-Saclay, UVSQ, Suresnes, France
| | - Stanislas Grassin-Delyle
- Département des maladies des voies respiratoires, Hôpital Foch, Exhalomics, Suresnes, France.,Infection et inflammation, Département de Biotechnologie de la Santé, Université Paris-Saclay, UVSQ, INSERM, Montigny le Bretonneux, France
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5
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Meller S, Al Khatri MSA, Alhammadi HK, Álvarez G, Alvergnat G, Alves LC, Callewaert C, Caraguel CGB, Carancci P, Chaber AL, Charalambous M, Desquilbet L, Ebbers H, Ebbers J, Grandjean D, Guest C, Guyot H, Hielm-Björkman A, Hopkins A, Kreienbrock L, Logan JG, Lorenzo H, Maia RDCC, Mancilla-Tapia JM, Mardones FO, Mutesa L, Nsanzimana S, Otto CM, Salgado-Caxito M, de los Santos F, da Silva JES, Schalke E, Schoneberg C, Soares AF, Twele F, Vidal-Martínez VM, Zapata A, Zimin-Veselkoff N, Volk HA. Expert considerations and consensus for using dogs to detect human SARS-CoV-2-infections. Front Med (Lausanne) 2022; 9:1015620. [PMID: 36569156 PMCID: PMC9773891 DOI: 10.3389/fmed.2022.1015620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 11/17/2022] [Indexed: 12/13/2022] Open
Affiliation(s)
- Sebastian Meller
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany,*Correspondence: Sebastian Meller,
| | | | - Hamad Khatir Alhammadi
- International Operations Department, Ministry of Interior of the United Arab Emirates, Abu Dhabi, United Arab Emirates
| | - Guadalupe Álvarez
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Guillaume Alvergnat
- International Operations Department, Ministry of Interior of the United Arab Emirates, Abu Dhabi, United Arab Emirates
| | - Lêucio Câmara Alves
- Department of Veterinary Medicine, Federal Rural University of Pernambuco, Recife, Brazil
| | - Chris Callewaert
- Center for Microbial Ecology and Technology, Department of Biotechnology, Ghent University, Ghent, Belgium
| | - Charles G. B. Caraguel
- School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, SA, Australia
| | - Paula Carancci
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Anne-Lise Chaber
- School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy, SA, Australia
| | - Marios Charalambous
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Loïc Desquilbet
- École Nationale Vétérinaire d’Alfort, IMRB, Université Paris Est, Maisons-Alfort, France
| | | | | | - Dominique Grandjean
- École Nationale Vétérinaire d’Alfort, Université Paris-Est, Maisons-Alfort, France
| | - Claire Guest
- Medical Detection Dogs, Milton Keynes, United Kingdom
| | - Hugues Guyot
- Clinical Department of Production Animals, Fundamental and Applied Research for Animals & Health Research Unit, Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Anna Hielm-Björkman
- Department of Equine and Small Animal Medicine, University of Helsinki, Helsinki, Finland
| | - Amy Hopkins
- Medical Detection Dogs, Milton Keynes, United Kingdom
| | - Lothar Kreienbrock
- Department of Biometry, Epidemiology and Information Processing, University of Veterinary Medicine Hannover, Hanover, Germany
| | - James G. Logan
- Department of Disease Control, London School of Hygiene and Tropical Medicine, London, United Kingdom,Arctech Innovation, The Cube, Dagenham, United Kingdom
| | - Hector Lorenzo
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | | | | | - Fernando O. Mardones
- Escuela de Medicina Veterinaria, Facultad de Agronomía e Ingeniería Forestal and Facultad de Ciencias Biológicas y Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Leon Mutesa
- Center for Human Genetics, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda,Rwanda National Joint Task Force COVID-19, Kigali, Rwanda
| | | | - Cynthia M. Otto
- Penn Vet Working Dog Center, Department of Clinical Sciences and Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Marília Salgado-Caxito
- Escuela de Medicina Veterinaria, Facultad de Agronomía e Ingeniería Forestal and Facultad de Ciencias Biológicas y Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | | | | | - Esther Schalke
- Bundeswehr Medical Service Headquarters, Koblenz, Germany
| | - Clara Schoneberg
- Department of Biometry, Epidemiology and Information Processing, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Anísio Francisco Soares
- Department of Animal Morphology and Physiology, Federal Rural University of Pernambuco, Recife, Brazil
| | - Friederike Twele
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany
| | - Victor Manuel Vidal-Martínez
- Laboratorio de Parasitología y Patología Acuática, Departamento de Recursos del Mar, Centro de Investigación y de Estudios Avanzados del IPN Unidad Mérida, Mérida, Yucatán, Mexico
| | - Ariel Zapata
- Faculty of Veterinary Science, University of Buenos Aires, Buenos Aires, Argentina
| | - Natalia Zimin-Veselkoff
- Escuela de Medicina Veterinaria, Facultad de Agronomía e Ingeniería Forestal and Facultad de Ciencias Biológicas y Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Holger A. Volk
- Department of Small Animal Medicine & Surgery, University of Veterinary Medicine Hannover, Hanover, Germany,Center for Systems Neuroscience Hannover, Hanover, Germany
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6
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Alcántara-Quintana LE, López-Mendoza CM, Rodríguez-Aguilar M, Medellín-Castillo N, Mizaikoff B, Flores-Ramírez R, Galván-Romero VS, Díaz de León-Martínez L. One-Drop Serum Screening Test for Anal Cancer in Men via Infrared Attenuated Total Reflection Spectroscopy. Anal Chem 2022; 94:15250-15260. [PMID: 36197692 DOI: 10.1021/acs.analchem.2c02439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Rare cancers are a challenge for clinical practice, the treatment experience at major centers to which rare cancers are referred is limited and are the most difficult to diagnose. Research to identify causes or develop prevention and early detection strategies is extremely challenging. Anal cancer is an example of a rare cancer, with the human papillomavirus (HPV) infection being the most important risk factor associated. In the early stages, anal cancer does not exhibit evident symptoms. This disease is diagnosed by means of anoscopy, which diagnoses some cases of early cancer; nevertheless, sensitivity of this test ranges between 47 and 89%. Therefore, the development of new, effective, and evidence-based screening methodologies for the early detection of rare cancers is of great relevance. In this study, the potential of ATR-FTIR spectroscopy has been explored as a sensitive, nondestructive, and inexpensive analytical method for developing disease screening platforms in serum. Spectral differences were found in the regions of 1700-1100 and 1700-1400 cm-1 between the control group and the anal cancer group related to the presence of proteins and nucleic acids. The chemometric analysis presented differences in the spectral fingerprints for both spectral regions with a high sensitivity ranging from 95.2 to 99.9% and a specificity ranging from 99.2 to 100%. This is the first step that we report for a methodology that is fast, nondestructive, and easy to perform, and the high sensitivity and specificity of the method are the basis for extensive research studies to implement these technologies in the clinical field.
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Affiliation(s)
- Luz Eugenia Alcántara-Quintana
- Unidad de Innovación en Diagnóstico Celular y Molecular, Coordinación para la Innovación y la Aplicación de la Ciencia y Tecnología, Universidad Autónoma de San Luis, Potosí Av. Sierra Leona 550, Lomas 2a sección, 78120San Luis Potosí, México
| | - Carlos Miguel López-Mendoza
- Unidad de Innovación en Diagnóstico Celular y Molecular, Coordinación para la Innovación y la Aplicación de la Ciencia y Tecnología, Universidad Autónoma de San Luis, Potosí Av. Sierra Leona 550, Lomas 2a sección, 78120San Luis Potosí, México
| | - Maribel Rodríguez-Aguilar
- Departamento de Farmacia, División de Ciencias de la Salud, Universidad de Quintana Roo, Quintana Roo, Mexico Av. Erick Paolo Martínez S/N, Magisterial, 17 de Octubre, 77039Chetumal, Q.R., México
| | - Nahum Medellín-Castillo
- Centro de Investigación y Estudios de Posgrado, Facultad de Ingeniería, Universidad Autónoma de San Luis Potosí, Dr. Manuel Nava No. 8 Colonia Zona Universitaria Poniente, San Luis Potosí, SLP78290, México
| | - Boris Mizaikoff
- Institute of Analytical and Bioanalytical Chemistry, Ulm University, Albert-Einstein-Allee 11, 89081Ulm, Germany.,Hahn-Schickard, Sedanstrasse 14, 89077Ulm, Germany
| | - Rogelio Flores-Ramírez
- Centro de Investigación Aplicada en Ambiente y Salud (CIAAS), Avenida Sierra Leona No. 550, 78210Colonia Lomas Segunda Sección, San Luis Potosí, SLP, México.,CONACYT Research Fellow, Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACYT), Avenida Sierra Leona No. 550, 78210Colonia Lomas Segunda Sección, San Luis Potosí, SLP, México
| | - Vanessa Sarahí Galván-Romero
- Unidad de Innovación en Diagnóstico Celular y Molecular, Coordinación para la Innovación y la Aplicación de la Ciencia y Tecnología, Universidad Autónoma de San Luis, Potosí Av. Sierra Leona 550, Lomas 2a sección, 78120San Luis Potosí, México
| | - Lorena Díaz de León-Martínez
- LABINNOVA Inc., Research Center for Early Diseases Screening, Susana Gómez Palafox, No. 5505, Colonia Paseos del Sol, 45079Zapopan, Jalisco, México
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7
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Kwiatkowski A, Borys S, Sikorska K, Drozdowska K, Smulko JM. Clinical studies of detecting COVID-19 from exhaled breath with electronic nose. Sci Rep 2022; 12:15990. [PMID: 36163492 PMCID: PMC9512806 DOI: 10.1038/s41598-022-20534-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 09/14/2022] [Indexed: 11/17/2022] Open
Abstract
The COVID-19 pandemic has attracted numerous research studies because of its impact on society and the economy. The pandemic has led to progress in the development of diagnostic methods, utilizing the polymerase chain reaction (PCR) as the gold standard for coronavirus SARS-CoV-2 detection. Numerous tests can be used at home within 15 min or so but of with lower accuracy than PCR. There is still a need for point-of-care tests available for mass daily screening of large crowds in airports, schools, and stadiums. The same problem exists with fast and continuous monitoring of patients during their medical treatment. The rapid methods can use exhaled breath analysis which is non-invasive and delivers the result quite fast. Electronic nose can detect a cocktail of volatile organic com-pounds (VOCs) induced by virus infection and disturbed metabolism in the human body. In our exploratory studies, we present the results of COVID-19 detection in a local hospital by applying the developed electronic setup utilising commercial VOC gas sensors. We consider the technical problems noticed during the reported studies and affecting the detection results. We believe that our studies help to advance the proposed technique to limit the spread of COVID-19 and similar viral infections.
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Affiliation(s)
- Andrzej Kwiatkowski
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Narutowicza 11/12, 80-233, Gdańsk, Poland
| | - Sebastian Borys
- University Center of Maritime and Tropical Medicine, Powstania Styczniowego 9B, 81-519, Gdynia, Poland
| | - Katarzyna Sikorska
- University Center of Maritime and Tropical Medicine, Powstania Styczniowego 9B, 81-519, Gdynia, Poland.,Division of Tropical and Parasitic Diseases, Faculty of Health Sciences, Medical University of Gdańsk, Powstania Styczniowego 9B, 81-519, Gdynia, Poland
| | - Katarzyna Drozdowska
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Narutowicza 11/12, 80-233, Gdańsk, Poland
| | - Janusz M Smulko
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Narutowicza 11/12, 80-233, Gdańsk, Poland.
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8
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Zhang P, Ren T, Chen H, Li Q, He M, Feng Y, Wang L, Huang T, Yuan J, Deng G, Lu H. A feasibility study of COVID-19 detection using breath analysis by high-pressure photon ionization time-of-flight mass spectrometry. J Breath Res 2022; 16. [PMID: 36052728 DOI: 10.1088/1752-7163/ac8ea1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 08/11/2022] [Indexed: 11/11/2022]
Abstract
BACKGROUND SARS-CoV-2 has caused a tremendous threat to global health. PCR and antigen testing have played a prominent role in the detection of SARS-CoV-2-infected individuals and disease control. An efficient, reliable detection tool is still urgently needed to halt the global COVID-19 pandemic. Recently, FDA emergency approved VOC as an alternative test for COVID-19 detection. METHODS AND MATERIALS In this case-control study, we prospectively and consecutively recruited 95 confirmed COVID-19 patients and 106 healthy controls in the designated hospital for treatment of COVID-19 patients in Shenzhen, China. Exhaled breath samples were collected and stored in customized bags and then detected by HPPI-TOFMS for volatile organic components (VOCs). Machine learning (ML) algorithms were employed for COVID-19 detection model construction. Participants were randomly assigned in a 5:2:3 ratio to the training, validation, and blinded test sets. The sensitivity (SEN), specificity (SPE), and other general metrics were employed for the VOCs based COVID-19 detection model performance evaluation. RESULTS The VOCs based COVID-19 detection model achieved good performance, with a SEN of 92.2% (95% CI: 83.8%, 95.6%), a SPE of 86.1% (95% CI: 74.8%, 97.4%) on blinded test set. Five potential VOC ions related to COVID-19 infection were discovered, which are significantly different between COVID-19 infected patients and controls. CONCLUSIONS This study evaluated a simple, fast, non-invasive VOCs-based COVID-19 detection method and demonstrated that it has good sensitivity and specificity in distinguishing COVID-19 infected patients from controls. It has great potential for fast and accurate COVID-19 detection.
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Affiliation(s)
- Peize Zhang
- Department of Pulmonary medicine and Tuberculosis, Shenzhen Third People's Hospital, No. 29, Bulan Road, Longgang District, Shenzhen, 518112, CHINA
| | - Tantan Ren
- Department of Pulmonary medicine and Tuberculosis, Shenzhen Third People's Hospital, No. 29, Bulan Road, Longgang District, Shenzhen, 518112, CHINA
| | - Haibin Chen
- Breax Laboratory, PCAB Research Center of Breath and Metabolism, 3rd Gangnanli, Fengtai Distinct, Beijing, 100071, CHINA
| | - Qingyun Li
- Breax Laboratory, PCAB Research Center of Breath and Metabolism, 3rd Gangnanli, Fengtai Distinct, Beijing, 100071, CHINA
| | - Mengqi He
- Breax Laboratory, PCAB Research Center of Breath and Metabolism, 3rd Gangnanli, Fengtai Distinct, Beijing, 100071, CHINA
| | - Yong Feng
- Breax Laboratory, PCAB Research Center of Breath and Metabolism,, 3rd Gangnanli, Fengtai Distinct, Beijing, 100071, CHINA
| | - Lei Wang
- Breax Laboratory, PCAB Research Center of Breath and Metabolism, 3rd Gangnanli, Fengtai Distinct, Beijing, 100071, CHINA
| | - Ting Huang
- Department of Disease Control, Shenzhen Third People's Hospital, No. 29, Bulan Road, Longgang District, Beijing, 100071, CHINA
| | - Jing Yuan
- Department of Infectious Disease, Shenzhen Third People's Hospital, No. 29, Bulan Road, Longgang District, Shenzhen, 518112, CHINA
| | - Guofang Deng
- Department of Pulmonary medicine and Tuberculosis,, Shenzhen Third People's Hospital, No. 29, Bulan Road, Longgang District, Shenzhen, Shenzhen, 518112, CHINA
| | - Hongzhou Lu
- Department of Infectious Disease, Shenzhen Third People's Hospital, No. 29, Bulan Road, Longgang District, Shenzhen, 518112, CHINA
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Forecasting the Post-Pandemic Effects of the SARS-CoV-2 Virus Using the Bullwhip Phenomenon Alongside Use of Nanosensors for Disease Containment and Cure. MATERIALS 2022; 15:ma15145078. [PMID: 35888544 PMCID: PMC9317545 DOI: 10.3390/ma15145078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 07/07/2022] [Accepted: 07/11/2022] [Indexed: 11/16/2022]
Abstract
The COVID-19 pandemic has the tendency to affect various organizational paradigm alterations, which civilization hasyet to fully comprehend. Personal to professional, individual to corporate, and across most industries, the spectrum of transformations is vast. Economically, the globe has never been more intertwined, and it has never been subjected to such widespread disruption. While many people have felt and acknowledged the pandemic’s short-term repercussions, the resultant paradigm alterations will certainly have long-term consequences with an unknown range and severity. This review paper aims at acknowledging various approaches for the prevention, detection, and diagnosis of the SARS-CoV-2 virus using nanomaterials as a base material. A nanostructure is a material classification based on dimensionality, in proportion to the characteristic diameter and surface area. Nanoparticles, quantum dots, nanowires (NW), carbon nanotubes (CNT), thin films, and nanocomposites are some examples of various dimensions, each acting as a single unit, in terms of transport capacities. Top-down and bottom-up techniques are used to fabricate nanomaterials. The large surface-to-volume ratio of nanomaterials allows one to create extremely sensitive charge or field sensors (electrical sensors, chemical sensors, explosives detection, optical sensors, and gas sensing applications). Nanowires have potential applications in information and communication technologies, low-energy lightning, and medical sensors. Carbon nanotubes have the best environmental stability, electrical characteristics, and surface-to-volume ratio of any nanomaterial, making them ideal for bio-sensing applications. Traditional commercially available techniques have focused on clinical manifestations, as well as molecular and serological detection equipment that can identify the SARS-CoV-2 virus. Scientists are expressing a lot of interest in developing a portable and easy-to-use COVID-19 detection tool. Several unique methodologies and approaches are being investigated as feasible advanced systems capable of meeting the demands. This review article attempts to emphasize the pandemic’s aftereffects, utilising the notion of the bullwhip phenomenon’s short-term and long-term effects, and it specifies the use of nanomaterials and nanosensors for detection, prevention, diagnosis, and therapy in connection to the SARS-CoV-2.
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10
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Hidayat SN, Julian T, Dharmawan AB, Puspita M, Chandra L, Rohman A, Julia M, Rianjanu A, Nurputra DK, Triyana K, Wasisto HS. Hybrid learning method based on feature clustering and scoring for enhanced COVID-19 breath analysis by an electronic nose. Artif Intell Med 2022; 129:102323. [PMID: 35659391 PMCID: PMC9110307 DOI: 10.1016/j.artmed.2022.102323] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 05/05/2022] [Accepted: 05/12/2022] [Indexed: 01/31/2023]
Abstract
Breath pattern analysis based on an electronic nose (e-nose), which is a noninvasive, fast, and low-cost method, has been continuously used for detecting human diseases, including the coronavirus disease 2019 (COVID-19). Nevertheless, having big data with several available features is not always beneficial because only a few of them will be relevant and useful to distinguish different breath samples (i.e., positive and negative COVID-19 samples). In this study, we develop a hybrid machine learning-based algorithm combining hierarchical agglomerative clustering analysis and permutation feature importance method to improve the data analysis of a portable e-nose for COVID-19 detection (GeNose C19). Utilizing this learning approach, we can obtain an effective and optimum feature combination, enabling the reduction by half of the number of employed sensors without downgrading the classification model performance. Based on the cross-validation test results on the training data, the hybrid algorithm can result in accuracy, sensitivity, and specificity values of (86 ± 3)%, (88 ± 6)%, and (84 ± 6)%, respectively. Meanwhile, for the testing data, a value of 87% is obtained for all the three metrics. These results exhibit the feasibility of using this hybrid filter-wrapper feature-selection method to pave the way for optimizing the GeNose C19 performance.
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Affiliation(s)
- Shidiq Nur Hidayat
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia,Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, BLS 21, Yogyakarta 55281, Indonesia
| | - Trisna Julian
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia
| | - Agus Budi Dharmawan
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia,Faculty of Information Technology, Universitas Tarumanagara, Jl. Letjen S. Parman No. 1, Jakarta 11440, Indonesia
| | - Mayumi Puspita
- PT Nanosense Instrument Indonesia, Umbulharjo, Yogyakarta 55167, Indonesia
| | - Lily Chandra
- RS Bhayangkara Polda Daerah Istimewa Yogyakarta, Jl. Raya Solo-Yogyakarta KM. 14, Sleman 55571, Indonesia
| | - Abdul Rohman
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia
| | - Madarina Julia
- Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia
| | - Aditya Rianjanu
- Department of Materials Engineering, Institut Teknologi Sumatera, Terusan Ryacudu, Way Hui, Jati Agung, Lampung 35365, Indonesia
| | - Dian Kesumapramudya Nurputra
- Department of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Jl. Farmako Sekip Utara, Yogyakarta 55281, Indonesia
| | - Kuwat Triyana
- Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, BLS 21, Yogyakarta 55281, Indonesia,Corresponding author
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11
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Devillier P, Gallet C, Salvator H, Julien C, Naline E, Roisse D, Levert C, Breton E, Galtat A, Decourtray S, Prevel L, Grassin-Delyle S, Grandjean D. Biomedical detection dogs for the identification of SARS-CoV-2 Infections from axillary sweat and breath samples. J Breath Res 2022; 16. [PMID: 35287115 DOI: 10.1088/1752-7163/ac5d8c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 03/14/2022] [Indexed: 01/08/2023]
Abstract
A PCR test of a nasal swab is still the "gold standard" for detecting a SARS-CoV-2 infection. However, PCR testing could be usefully complemented by non-invasive, fast, reliable, cheap methods for detecting infected individuals in busy areas (e.g. airports and railway stations) or remote areas. Detection of the volatile, semivolatile and non-volatile compound signature of SARS-CoV-2 infection by trained sniffer dogs might meet these requirements. Previous studies have shown that well-trained dogs can detect SARS-CoV-2 in sweat, saliva and urine samples. The objective of the present study was to assess the performance of dogs trained to detect the presence of SARS-CoV-2 in axillary-sweat-stained gauzes and on expired breath trapped in surgical masks. The samples were provided by individuals suffering from mild-to-severe coronavirus disease 2019 (COVID-19), asymptomatic individuals, and individuals vaccinated against COVID-19. Results: Seven trained dogs tested on 886 presentations of sweat samples from 241 subjects and detected SARS-CoV-2 with a diagnostic sensitivity (relative to the PCR test result) of 89.6% (95% confidence interval (CI): 86.4-92.2%) and a specificity of 83.9% (95% CI: 80.3-87.0%) - even when people with a low viral load were included in the analysis. When considering the 207 presentations of sweat samples from vaccinated individuals, the sensitivity and specificity were respectively 85.7% (95% CI: 68.5-94.3) and 86.0% (95% CI: 80.2-90.3%). The likelihood of a false-positive result was greater in the two weeks immediately after COVID-19 vaccination. Four of the seven dogs also tested on 262 presentations of mask samples from 98 subjects; the diagnostic sensitivity was 83.1% (95% CI: 73.2-89.9) and the specificity was 88.6% (95% CI: 83.3-92.4%). There was no difference (McNemar's test P=0.999) in the dogs' abilities to detect the presence of SARS-CoV-2 in paired samples of sweat-stained gauzes vs. surgical masks worn for only 10 minutes. Conclusion: Our findings confirm the promise of SARS-CoV-2 screening by detection dogs and broaden the method's scope to vaccinated individuals and easy-to-obtain face masks, and suggest that a "dogs + confirmatory rapid antigen detection tests" screening strategy might be worth investigating.
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Affiliation(s)
- Philippe Devillier
- Exhalomics, Hôpitaux Universitaires Paris Ile-de-France Ouest, 11 rue Guillaume Lenoir, Suresnes, 92150, FRANCE
| | - Capucine Gallet
- Ecole Nationale Vétérinaire d'Alfort (Alfort School of Veterinary Medicine) , University Paris-Est Créteil Val de Marne, Maisons-Alfort, Creteil, Île-de-France, 94010, FRANCE
| | - Hélène Salvator
- Service de Pneumologie, Hôpital Foch, Suresnes, Suresnes, Île-de-France, 92151, FRANCE
| | - Clothilde Julien
- Ecole Nationale Vétérinaire d'Alfort (Alfort School of Veterinary Medicine) , University Paris-Est Créteil Val de Marne, Maisons-Alfort, Creteil, Île-de-France, 94010, FRANCE
| | - Emmanuel Naline
- Service de Pneumologie, Hôpital Foch, Suresnes, Suresnes, Île-de-France, 92151, FRANCE
| | - Didier Roisse
- Service Départemental d'Incendie et de Secours 60 (Oise County Fire and Rescue Service), SDIS60, Tillé, Tillé, 60639, FRANCE
| | - Clément Levert
- Service Départemental d'Incendie et de Secours 78 (Yvelines County Fire and Rescue Service), SDIS78, Versailles, Versailles, 78000, FRANCE
| | - Erwan Breton
- Service Départemental d'Incendie et de Secours 78 (Yvelines County Fire and Rescue Service), SDIS78, Versailles, Versailles, 78000, FRANCE
| | - Arnaud Galtat
- Service Départemental d'Incendie et de Secours 78 (Yvelines County Fire and Rescue Service), SDIS78, Versailles, Versailles, 78000, FRANCE
| | - Sandra Decourtray
- Service d'accueil des Urgences, Hôpital Foch, Suresnes, Suresnes, Île-de-France, 92151, FRANCE
| | - Laura Prevel
- Délégation à la Recherche Clinique et à l'Innovation, Hôpital Foch, Suresnes, Suresnes, Île-de-France, 92151, FRANCE
| | - Stanislas Grassin-Delyle
- Exhalomics, service de Pneumologie, Hôpital Foch, Suresnes, Suresnes, Île-de-France, 92151, FRANCE
| | - Dominique Grandjean
- Ecole Nationale Vétérinaire d'Alfort (Alfort School of Veterinary Medicine) , University Paris-Est Créteil Val de Marne, Maisons-Alfort, Creteil, Île-de-France, 94010, FRANCE
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Zamora-Mendoza BN, Díaz de León-Martínez L, Rodríguez-Aguilar M, Mizaikoff B, Flores-Ramírez R. 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. Talanta 2022; 236:122832. [PMID: 34635222 PMCID: PMC8411592 DOI: 10.1016/j.talanta.2021.122832] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 08/21/2021] [Accepted: 08/28/2021] [Indexed: 11/04/2022]
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% (PC1 = 95.9%, PC2 = 1.0%, PC3 = 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.
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Affiliation(s)
- Blanca Nohemí Zamora-Mendoza
- Faculty of Medicine-Center for Applied Research on Environment and Health (CIAAS), Autonomous University of San Luis Potosí, Avenida Sierra Leona No. 550, Colonia Lomas Segunda Sección, CP, 78210, San Luis Potosí, SLP, Mexico
| | - Lorena Díaz de León-Martínez
- Faculty of Medicine-Center for Applied Research on Environment and Health (CIAAS), Autonomous University of San Luis Potosí, Avenida Sierra Leona No. 550, Colonia Lomas Segunda Sección, CP, 78210, San Luis Potosí, SLP, Mexico.
| | | | - Boris Mizaikoff
- 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
| | - Rogelio Flores-Ramírez
- CONACYT Research Fellow, Coordination for Innovation and Application of Science and Technology (CIACYT), Autonomous University of San Luis Potosí, Avenida Sierra Leona No. 550, CP, 78210, Colonia Lomas Segunda Sección, San Luis Potosí, SLP, Mexico.
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13
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Liangou A, Tasoglou A, Huber HJ, Wistrom C, Brody K, Menon PG, Bebekoski T, Menschel K, Davidson-Fiedler M, DeMarco K, Salphale H, Wistrom J, Wistrom S, Lee RJ. A method for the identification of COVID-19 biomarkers in human breath using Proton Transfer Reaction Time-of-Flight Mass Spectrometry. EClinicalMedicine 2021; 42:101207. [PMID: 34841237 PMCID: PMC8604657 DOI: 10.1016/j.eclinm.2021.101207] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 10/28/2021] [Accepted: 11/03/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND COVID-19 has caused a worldwide pandemic, making the early detection of the virus crucial. We present an approach for the determination of COVID-19 infection based on breath analysis. METHODS A high sensitivity mass spectrometer was combined with artificial intelligence and used to develop a method for the identification of COVID-19 in human breath within seconds. A set of 1137 positive and negative subjects from different age groups, collected in two periods from two hospitals in the USA, from 26 August, 2020 until 15 September, 2020 and from 11 September, 2020 until 11 November, 2020, was used for the method development. The subjects exhaled in a Tedlar bag, and the exhaled breath samples were subsequently analyzed using a Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS). The produced mass spectra were introduced to a series of machine learning models. 70% of the data was used for these sub-models' training and 30% was used for testing. FINDINGS A set of 340 samples, 95 positives and 245 negatives, was used for the testing. The combined models successfully predicted 77 out of the 95 samples as positives and 199 out of the 245 samples as negatives. The overall accuracy of the model was 81.2%. Since over 50% of the total positive samples belonged to the age group of over 55 years old, the performance of the model in this category was also separately evaluated on 339 subjects (170 negative and 169 positive). The model correctly identified 166 out of the 170 negatives and 164 out of the 169 positives. The model accuracy in this case was 97.3%. INTERPRETATION The results showed that this method for the identification of COVID-19 infection is a promising tool, which can give fast and accurate results.
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Affiliation(s)
| | - Antonios Tasoglou
- RJ Lee Group Inc., Monroeville, PA, USA
- Corresponding author: Antonios Tasoglou, PhD, 5031 Somerville St, Pittsburgh, PA, USA, 15201
| | | | | | | | - Prahlad G Menon
- QuantMD, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
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14
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Díaz de León-Martínez L, Flores-Ramírez R, López-Mendoza CM, Rodríguez-Aguilar M, Metha G, Zúñiga-Martínez L, Ornelas-Rebolledo O, Alcántara-Quintana LE. Identification of volatile organic compounds in the urine of patients with cervical cancer. Test concept for timely screening. Clin Chim Acta 2021; 522:132-140. [PMID: 34418363 DOI: 10.1016/j.cca.2021.08.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/19/2021] [Accepted: 08/13/2021] [Indexed: 01/15/2023]
Abstract
The objective of this research was to identify a global chemical pattern of volatile organic compounds (VOCs) in urine capable of discriminating between women with cervical cancer (CC) and control women using an electronic nose and to elucidate potential biomarkers by gas chromatography-mass spectrometry (GC-MS). A cross-sectional study was performed, with 12 control women, 5 women with CIN (Cervical Intraepithelial Neoplasia) and 12 women with CC. Global VOCs in urine were assessed using an electronic nose and specific by GC-MS. Multivariate analysis was performed: Principal Component Analysis (PCA), Canonical Principal Coordinate Analysis (CAP) and Partial Least Squares Discriminant Analysis (PLS-DA) and the test's diagnostic power was evaluated through ROC (Receiver Operating Characteristic) curves. Results from the PCA between the control group compared to the CC present variability of 98.4% (PC1 = 93.9%, PC2 = 2.3% and PC3 = 2.1%). CAP model shows a separation between the overall VOCs profile of the control and CC group with a correct classification of 94.7%. PLS-DA indicated that 8 sensors have a higher contribution in the CC group. The sensitivity, specificity, value reached 91.6% (61.5%-99.7%) and 100% (73.5%-100%) respectively, according to the ROC curve. GC-MS analysis indicated that 33 compounds occur only in the CC group and some of them have been found in other types of cancer. In all, this study provides the basis for the development of an accessible, non-invasive, sensitive and specific screening platform for cervical cancer through the application of electronic nose and chemometric analysis.
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Affiliation(s)
- Lorena Díaz de León-Martínez
- Centro de Investigación Aplicada en Ambiente y Salud (CIAAS), Avenida Sierra Leona No. 550, CP 78210, Colonia Lomas Segunda Sección, San Luis Potosí, SLP, México
| | - Rogelio Flores-Ramírez
- Centro de Investigación Aplicada en Ambiente y Salud (CIAAS), Avenida Sierra Leona No. 550, CP 78210, Colonia Lomas Segunda Sección, San Luis Potosí, SLP, México.
| | - Carlos Miguel López-Mendoza
- Unidad de Innovación en Diagnóstico Celular y Molecular. Coordinación para la Innovación y la Aplicación de la Ciencia y Tecnología, Universidad Autónoma de San Luis Potosí, Av. Sierra Leona 550, Lomas 2a sección, 78120 San Luis Potosí, México
| | | | - Garima Metha
- CEO of Altus Lifescience, San José, CA, United States
| | - Lourdes Zúñiga-Martínez
- Unidad de Innovación en Diagnóstico Celular y Molecular. Coordinación para la Innovación y la Aplicación de la Ciencia y Tecnología, Universidad Autónoma de San Luis Potosí, Av. Sierra Leona 550, Lomas 2a sección, 78120 San Luis Potosí, México
| | - Omar Ornelas-Rebolledo
- Labinnova Center of Research in Breath for early diseases detection, Guadalajara, Mexico
| | - Luz Eugenia Alcántara-Quintana
- Unidad de Innovación en Diagnóstico Celular y Molecular. Coordinación para la Innovación y la Aplicación de la Ciencia y Tecnología, Universidad Autónoma de San Luis Potosí, Av. Sierra Leona 550, Lomas 2a sección, 78120 San Luis Potosí, México.
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