1
|
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 PMCID: PMC11405072 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.
Collapse
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..
| |
Collapse
|
2
|
Xie Z, Morris JD, Pan J, Cooke EA, Sutaria SR, Balcom D, Marimuthu S, Parrish LW, Aliesky H, Huang JJ, Rai SN, Arnold FW, Huang J, Nantz MH, Fu XA. Detection of COVID-19 by quantitative analysis of carbonyl compounds in exhaled breath. Sci Rep 2024; 14:14568. [PMID: 38914586 PMCID: PMC11196736 DOI: 10.1038/s41598-024-61735-7] [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: 12/06/2023] [Accepted: 05/09/2024] [Indexed: 06/26/2024] Open
Abstract
COVID-19 has caused a worldwide pandemic, creating an urgent need for early detection methods. Breath analysis has shown great potential as a non-invasive and rapid means for COVID-19 detection. The objective of this study is to detect patients infected with SARS-CoV-2 and even the possibility to screen between different SARS-CoV-2 variants by analysis of carbonyl compounds in breath. Carbonyl compounds in exhaled breath are metabolites related to inflammation and oxidative stress induced by diseases. This study included a cohort of COVID-19 positive and negative subjects confirmed by reverse transcription polymerase chain reaction between March and December 2021. Carbonyl compounds in exhaled breath were captured using a microfabricated silicon microreactor and analyzed by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). A total of 321 subjects were enrolled in this study. Of these, 141 (85 males, 60.3%) (mean ± SD age: 52 ± 15 years) were COVID-19 (55 during the alpha wave and 86 during the delta wave) positive and 180 (90 males, 50%) (mean ± SD age: 45 ± 15 years) were negative. Panels of a total of 34 ketones and aldehydes in all breath samples were identified for detection of COVID-19 positive patients. Logistic regression models indicated high accuracy/sensitivity/specificity for alpha wave (98.4%/96.4%/100%), for delta wave (88.3%/93.0%/84.6%) and for all COVID-19 positive patients (94.7%/90.1%/98.3%). The results indicate that COVID-19 positive patients can be detected by analysis of carbonyl compounds in exhaled breath. The technology for analysis of carbonyl compounds in exhaled breath has great potential for rapid screening and detection of COVID-19 and for other infectious respiratory diseases in future pandemics.
Collapse
Affiliation(s)
- Zhenzhen Xie
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - James D Morris
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - Jianmin Pan
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- The Cancer Data Science Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Biostatistics and Informatics Shared Resource, University of Cincinnati Cancer Center, Cincinnati, OH, USA
| | - Elizabeth A Cooke
- Department of Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Saurin R Sutaria
- Department of Chemistry, University of Louisville, Louisville, KY, USA
| | - Dawn Balcom
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Subathra Marimuthu
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Leslie W Parrish
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Holly Aliesky
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | | | - Shesh N Rai
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- The Cancer Data Science Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Biostatistics and Informatics Shared Resource, University of Cincinnati Cancer Center, Cincinnati, OH, USA
| | - Forest W Arnold
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Jiapeng Huang
- Department of Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY, USA.
| | - Michael H Nantz
- Department of Chemistry, University of Louisville, Louisville, KY, USA.
| | - Xiao-An Fu
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
| |
Collapse
|
3
|
Padawer D, Qadan A, Karameh M, Darawshy F, Laor A, Banker S, Fridlender ZG. Breath of Health: spectroscopy-based breath test for the detection of SARS-CoV-2. Infect Dis (Lond) 2024; 56:376-383. [PMID: 38424673 DOI: 10.1080/23744235.2024.2313020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 01/27/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND Nucleic acid amplification tests (NAAT) are considered the gold standard for COVID-19 diagnosis. These tests require professional manpower and equipment, long processing and swab sampling which is unpleasant to the patients. Several volatile organic compounds (VOCs) have been identified in the breath of COVID-19 patients. Detection of these VOCs using a breath test could help rapidly identify COVID-19 patients. OBJECTIVE Assess the accuracy of 'Breath of Health' (BOH) COVID-19 Fourier-transform infra-red (FTIR) Spectroscopy-based breath test. METHODS Breath samples from patients with or without symptoms suggestive for COVID-19 who had NAAT results were collected using Tedlar bags and were blindly analysed using BOH FTIR spectroscopy. BOH Measures several VOCs simultaneously and differentiating positive and negative results. BOH results were compared to NAAT results as gold standard. RESULTS Breath samples from 531 patients were analysed. The sensitivity of BOH breath test was found to be 79.5% and specificity was 87.2%. Positive predictive value (PPV) was 74.7% and negative predictive value (NPV) 90.0%. Calculated accuracy rate was 84.8% and area under the curve 0.834. Subgroup analysis revealed that the NPV of patients without respiratory symptoms was superior over the NPV of symptomatic patients (94.7% vs 80.7%, P-value < 0.0001) and PPV of patients with respiratory symptoms outranks the PPV of individuals without symptoms (85.3% vs 69.2%, P-value 0.0196). CONCLUSION We found BOH COVID-19 breath test to be a patient-friendly, rapid, non-invasive diagnostic test with high accuracy rate and NPV that could efficiently rule out COVID-19 especially among individuals with low pre-test probability.
Collapse
Affiliation(s)
- Dan Padawer
- Institute of Pulmonary Medicine, Hadassah Medical Center, Jerusalem, Israel
- Department of Internal Medicine D, Hadassah Medical Center, Jerusalem, Israel
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Abed Qadan
- Department of Internal Medicine D, Hadassah Medical Center, Jerusalem, Israel
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Mutaz Karameh
- Department of Internal Medicine D, Hadassah Medical Center, Jerusalem, Israel
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
- Heart Institute, Hadassah Medical Center, Jerusalem, Israel
| | - Fares Darawshy
- Institute of Pulmonary Medicine, Hadassah Medical Center, Jerusalem, Israel
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Arie Laor
- Breath of Health Ltd, Rehovot, Israel
| | | | - Zvi G Fridlender
- Institute of Pulmonary Medicine, Hadassah Medical Center, Jerusalem, Israel
- Department of Internal Medicine D, Hadassah Medical Center, Jerusalem, Israel
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| |
Collapse
|
4
|
Cusack RP, Larracy R, Morrell CB, Ranjbar M, Le Roux J, Whetstone CE, Boudreau M, Poitras PF, Srinathan T, Cheng E, Howie K, Obminski C, O'Shea T, Kruisselbrink RJ, Ho T, Scheme E, Graham S, Beydaghyan G, Gavreau GM, Duong M. Machine learning enabled detection of COVID-19 pneumonia using exhaled breath analysis: a proof-of-concept study. J Breath Res 2024; 18:026009. [PMID: 38382095 DOI: 10.1088/1752-7163/ad2b6e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 02/21/2024] [Indexed: 02/23/2024]
Abstract
Detection of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) relies on real-time-reverse-transcriptase polymerase chain reaction (RT-PCR) on nasopharyngeal swabs. The false-negative rate of RT-PCR can be high when viral burden and infection is localized distally in the lower airways and lung parenchyma. An alternate safe, simple and accessible method for sampling the lower airways is needed to aid in the early and rapid diagnosis of COVID-19 pneumonia. In a prospective unblinded observational study, patients admitted with a positive RT-PCR and symptoms of SARS-CoV-2 infection were enrolled from three hospitals in Ontario, Canada. Healthy individuals or hospitalized patients with negative RT-PCR and without respiratory symptoms were enrolled into the control group. Breath samples were collected and analyzed by laser absorption spectroscopy (LAS) for volatile organic compounds (VOCs) and classified by machine learning (ML) approaches to identify unique LAS-spectra patterns (breathprints) for SARS-CoV-2. Of the 135 patients enrolled, 115 patients provided analyzable breath samples. Using LAS-breathprints to train ML classifier models resulted in an accuracy of 72.2%-81.7% in differentiating between SARS-CoV2 positive and negative groups. The performance was consistent across subgroups of different age, sex, body mass index, SARS-CoV-2 variants, time of disease onset and oxygen requirement. The overall performance was higher than compared to VOC-trained classifier model, which had an accuracy of 63%-74.7%. This study demonstrates that a ML-based breathprint model using LAS analysis of exhaled breath may be a valuable non-invasive method for studying the lower airways and detecting SARS-CoV-2 and other respiratory pathogens. The technology and the ML approach can be easily deployed in any setting with minimal training. This will greatly improve access and scalability to meet surge capacity; allow early and rapid detection to inform therapy; and offers great versatility in developing new classifier models quickly for future outbreaks.
Collapse
Affiliation(s)
- Ruth P Cusack
- Department of Respiratory Medicine, Galway University Hospital, Galway, Ireland
- School of Medicine, University of Galway, Galway, Ireland
| | - Robyn Larracy
- Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada
| | - Christian B Morrell
- Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada
| | - Maral Ranjbar
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Jennifer Le Roux
- Department of Medicine, Juravinski Hospital and Cancer Centre, Hamilton Health Sciences, Hamilton, Ontario, Canada
| | | | | | | | - Thiviya Srinathan
- Firestone Institute for Respiratory Health, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, L8N 4A6, Canada
| | - Eric Cheng
- Firestone Institute for Respiratory Health, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, L8N 4A6, Canada
| | - Karen Howie
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Catie Obminski
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Tim O'Shea
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | | | - Terence Ho
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - Erik Scheme
- Institute of Biomedical Engineering, University of New Brunswick, Fredericton, New Brunswick, Canada
| | | | | | - Gail M Gavreau
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
| | - MyLinh Duong
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
- Firestone Institute for Respiratory Health, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, L8N 4A6, Canada
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Ghumra D, Shetty N, McBrearty KR, Puthussery JV, Sumlin BJ, Gardiner WD, Doherty BM, Magrecki JP, Brody DL, Esparza TJ, O’Halloran JA, Presti RM, Bricker TL, Boon ACM, Yuede CM, Cirrito JR, Chakrabarty RK. Rapid Direct Detection of SARS-CoV-2 Aerosols in Exhaled Breath at the Point of Care. ACS Sens 2023; 8:3023-3031. [PMID: 37498298 PMCID: PMC10463275 DOI: 10.1021/acssensors.3c00512] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 07/12/2023] [Indexed: 07/28/2023]
Abstract
Airborne transmission via virus-laden aerosols is a dominant route for the transmission of respiratory diseases, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Direct, non-invasive screening of respiratory virus aerosols in patients has been a long-standing technical challenge. Here, we introduce a point-of-care testing platform that directly detects SARS-CoV-2 aerosols in as little as two exhaled breaths of patients and provides results in under 60 s. It integrates a hand-held breath aerosol collector and a llama-derived, SARS-CoV-2 spike-protein specific nanobody bound to an ultrasensitive micro-immunoelectrode biosensor, which detects the oxidation of tyrosine amino acids present in SARS-CoV-2 viral particles. Laboratory and clinical trial results were within 20% of those obtained using standard testing methods. Importantly, the electrochemical biosensor directly detects the virus itself, as opposed to a surrogate or signature of the virus, and is sensitive to as little as 10 viral particles in a sample. Our platform holds the potential to be adapted for multiplexed detection of different respiratory viruses. It provides a rapid and non-invasive alternative to conventional viral diagnostics.
Collapse
Affiliation(s)
- Dishit
P. Ghumra
- Center
for Aerosol Science and Engineering, Department of Energy, Environmental
and Chemical Engineering, Washington University
in St. Louis, St. Louis, Missouri 63130, United States
| | - Nishit Shetty
- Center
for Aerosol Science and Engineering, Department of Energy, Environmental
and Chemical Engineering, Washington University
in St. Louis, St. Louis, Missouri 63130, United States
| | - Kevin R. McBrearty
- Department
of Neurology, Hope Center for Neurological Disease, Knight Alzheimer’s
Disease Research Center, Washington University, St. Louis, Missouri 63110, United States
| | - Joseph V. Puthussery
- Center
for Aerosol Science and Engineering, Department of Energy, Environmental
and Chemical Engineering, Washington University
in St. Louis, St. Louis, Missouri 63130, United States
| | - Benjamin J. Sumlin
- Center
for Aerosol Science and Engineering, Department of Energy, Environmental
and Chemical Engineering, Washington University
in St. Louis, St. Louis, Missouri 63130, United States
| | - Woodrow D. Gardiner
- Department
of Neurology, Hope Center for Neurological Disease, Knight Alzheimer’s
Disease Research Center, Washington University, St. Louis, Missouri 63110, United States
| | - Brookelyn M. Doherty
- Department
of Neurology, Hope Center for Neurological Disease, Knight Alzheimer’s
Disease Research Center, Washington University, St. Louis, Missouri 63110, United States
| | - Jordan P. Magrecki
- Department
of Neurology, Hope Center for Neurological Disease, Knight Alzheimer’s
Disease Research Center, Washington University, St. Louis, Missouri 63110, United States
| | - David L. Brody
- National
Institute of Neurological Disorders and Stroke, Bethesda, Maryland 20892, United States
- Department
of Neurology, Uniformed Services University
of the Health Sciences, Bethesda, Maryland 20814, United States
| | - Thomas J. Esparza
- National
Institute of Neurological Disorders and Stroke, Bethesda, Maryland 20892, United States
| | - Jane A. O’Halloran
- Department
of Medicine, Washington University, St. Louis, Missouri 63110, United States
| | - Rachel M. Presti
- Department
of Medicine, Washington University, St. Louis, Missouri 63110, United States
| | - Traci L. Bricker
- Department
of Medicine, Washington University, St. Louis, Missouri 63110, United States
- Departments
Molecular Microbiology, and Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri 63110, United States
| | - Adrianus C. M. Boon
- Department
of Medicine, Washington University, St. Louis, Missouri 63110, United States
- Departments
Molecular Microbiology, and Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri 63110, United States
| | - Carla M. Yuede
- Department
of Psychiatry, Washington University School
of Medicine, Campus Box
8134, 660 South Euclid Avenue, St. Louis, Missouri 63110, United States
| | - John R. Cirrito
- Department
of Neurology, Hope Center for Neurological Disease, Knight Alzheimer’s
Disease Research Center, Washington University, St. Louis, Missouri 63110, United States
| | - Rajan K. Chakrabarty
- Center
for Aerosol Science and Engineering, Department of Energy, Environmental
and Chemical Engineering, Washington University
in St. Louis, St. Louis, Missouri 63130, United States
| |
Collapse
|
7
|
Kim HS, Lee H, Kang S, Kim WJ, Shin S. Diagnostic performance of respirators for collection and detection of SARS-CoV-2. Sci Rep 2023; 13:13277. [PMID: 37582958 PMCID: PMC10427661 DOI: 10.1038/s41598-023-39789-w] [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: 04/04/2023] [Accepted: 07/31/2023] [Indexed: 08/17/2023] Open
Abstract
Respirators, called as face mask, have been used to protect the wearer from the outside harmful air environment and prevent any virus from being released to neighbors from potentially infected exhaled breath. The antiviral effectiveness of respirators has not only been researched scientifically, but has also become a global issue due to society's obligation to wear respirators. In this paper, we report the results of a study on the collection and detection of viruses contained in exhaled breath using respirators. The inner electrostatic filter was carefully selected for virus collection because it does not come in direct contact with either human skin or the external environment. In the study of a healthy control group, it was confirmed that a large amount of DNA and biomolecules such as exosomes were collected from the respirator exposed to exhalation, and the amount of collection increased in proportion to the wearing time. We conducted experiments using a total of 72 paired samples with nasopharyngeal swabs and respirator samples. Out of these samples, fifty tested positive for SARS-CoV-2 and twenty-two tested negative. The PCR results of the NPS and respirator samples showed a high level of agreement, with a positive percent agreement of ≥ 90% and a negative percent agreement of ≥ 99%. Furthermore, there was a notable level of concordance between RCA-flow tests and PCR when examining the respirator samples. These results suggest that this is a non-invasive, quick and easy method of collecting samples from subjects using a respirator, which can significantly reduce the hassle of waiting at airports or public places and concerns about cross-contamination. Furthermore, we expect miniaturized technologies to integrate PCR detection into respirators in the near future.
Collapse
Affiliation(s)
- Hwang-Soo Kim
- Department of Micro-nano System Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Hansol Lee
- Asia Pacific Influenza Institute, Korea University College of Medicine, Seoul, 08308, Republic of Korea
| | - Seonghui Kang
- Division of Infectious Diseases, Department of Internal Medicine, Konyang University Hospital, Daejeon, 35365, Republic of Korea
| | - Woo Joo Kim
- Division of Infectious Diseases, Department of Internal Medicine, Korea University College of Medicine, Seoul, 08308, Republic of Korea.
| | - Sehyun Shin
- Department of Micro-nano System Engineering, Korea University, Seoul, 02841, Republic of Korea.
- School of Mechanical Engineering, Korea University, Seoul, 02841, Republic of Korea.
| |
Collapse
|
8
|
Kiss H, Örlős Z, Gellért Á, Megyesfalvi Z, Mikáczó A, Sárközi A, Vaskó A, Miklós Z, Horváth I. Exhaled Biomarkers for Point-of-Care Diagnosis: Recent Advances and New Challenges in Breathomics. MICROMACHINES 2023; 14:391. [PMID: 36838091 PMCID: PMC9964519 DOI: 10.3390/mi14020391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 01/29/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
Cancers, chronic diseases and respiratory infections are major causes of mortality and present diagnostic and therapeutic challenges for health care. There is an unmet medical need for non-invasive, easy-to-use biomarkers for the early diagnosis, phenotyping, predicting and monitoring of the therapeutic responses of these disorders. Exhaled breath sampling is an attractive choice that has gained attention in recent years. Exhaled nitric oxide measurement used as a predictive biomarker of the response to anti-eosinophil therapy in severe asthma has paved the way for other exhaled breath biomarkers. Advances in laser and nanosensor technologies and spectrometry together with widespread use of algorithms and artificial intelligence have facilitated research on volatile organic compounds and artificial olfaction systems to develop new exhaled biomarkers. We aim to provide an overview of the recent advances in and challenges of exhaled biomarker measurements with an emphasis on the applicability of their measurement as a non-invasive, point-of-care diagnostic and monitoring tool.
Collapse
Affiliation(s)
- Helga Kiss
- National Koranyi Institute for Pulmonology, Koranyi F Street 1, 1121 Budapest, Hungary
| | - Zoltán Örlős
- National Koranyi Institute for Pulmonology, Koranyi F Street 1, 1121 Budapest, Hungary
| | - Áron Gellért
- National Koranyi Institute for Pulmonology, Koranyi F Street 1, 1121 Budapest, Hungary
| | - Zsolt Megyesfalvi
- National Koranyi Institute for Pulmonology, Koranyi F Street 1, 1121 Budapest, Hungary
| | - Angéla Mikáczó
- Department of Pulmonology, University of Debrecen, Nagyerdei krt 98, 4032 Debrecen, Hungary
| | - Anna Sárközi
- Department of Pulmonology, University of Debrecen, Nagyerdei krt 98, 4032 Debrecen, Hungary
| | - Attila Vaskó
- Department of Pulmonology, University of Debrecen, Nagyerdei krt 98, 4032 Debrecen, Hungary
| | - Zsuzsanna Miklós
- National Koranyi Institute for Pulmonology, Koranyi F Street 1, 1121 Budapest, Hungary
| | - Ildikó Horváth
- National Koranyi Institute for Pulmonology, Koranyi F Street 1, 1121 Budapest, Hungary
- Department of Pulmonology, University of Debrecen, Nagyerdei krt 98, 4032 Debrecen, Hungary
| |
Collapse
|
9
|
Sharma R, Zang W, Tabartehfarahani A, Lam A, Huang X, Sivakumar AD, Thota C, Yang S, Dickson RP, Sjoding MW, Bisco E, Mahmood CC, Diaz KM, Sautter N, Ansari S, Ward KR, Fan X. Portable Breath-Based Volatile Organic Compound Monitoring for the Detection of COVID-19 During the Circulation of the SARS-CoV-2 Delta Variant and the Transition to the SARS-CoV-2 Omicron Variant. JAMA Netw Open 2023; 6:e230982. [PMID: 36853606 PMCID: PMC9975913 DOI: 10.1001/jamanetworkopen.2023.0982] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 01/12/2023] [Indexed: 03/01/2023] Open
Abstract
Importance Breath analysis has been explored as a noninvasive means to detect COVID-19. However, the impact of emerging variants of SARS-CoV-2, such as Omicron, on the exhaled breath profile and diagnostic accuracy of breath analysis is unknown. Objective To evaluate the diagnostic accuracies of breath analysis on detecting patients with COVID-19 when the SARS-CoV-2 Delta and Omicron variants were most prevalent. Design, Setting, and Participants This diagnostic study included a cohort of patients who had positive and negative test results for COVID-19 using reverse transcriptase polymerase chain reaction between April 2021 and May 2022, which covers the period when the Delta variant was overtaken by Omicron as the major variant. Patients were enrolled through intensive care units and the emergency department at the University of Michigan Health System. Patient breath was analyzed with portable gas chromatography. Main Outcomes and Measures Different sets of VOC biomarkers were identified that distinguished between COVID-19 (SARS-CoV-2 Delta and Omicron variants) and non-COVID-19 illness. Results Overall, 205 breath samples from 167 adult patients were analyzed. A total of 77 patients (mean [SD] age, 58.5 [16.1] years; 41 [53.2%] male patients; 13 [16.9%] Black and 59 [76.6%] White patients) had COVID-19, and 91 patients (mean [SD] age, 54.3 [17.1] years; 43 [47.3%] male patients; 11 [12.1%] Black and 76 [83.5%] White patients) had non-COVID-19 illness. Several patients were analyzed over multiple days. Among 94 positive samples, 41 samples were from patients in 2021 infected with the Delta or other variants, and 53 samples were from patients in 2022 infected with the Omicron variant, based on the State of Michigan and US Centers for Disease Control and Prevention surveillance data. Four VOC biomarkers were found to distinguish between COVID-19 (Delta and other 2021 variants) and non-COVID-19 illness with an accuracy of 94.7%. However, accuracy dropped substantially to 82.1% when these biomarkers were applied to the Omicron variant. Four new VOC biomarkers were found to distinguish the Omicron variant and non-COVID-19 illness (accuracy, 90.9%). Breath analysis distinguished Omicron from the earlier variants with an accuracy of 91.5% and COVID-19 (all SARS-CoV-2 variants) vs non-COVID-19 illness with 90.2% accuracy. Conclusions and Relevance The findings of this diagnostic study suggest that breath analysis has promise for COVID-19 detection. However, similar to rapid antigen testing, the emergence of new variants poses diagnostic challenges. The results of this study warrant additional evaluation on how to overcome these challenges to use breath analysis to improve the diagnosis and care of patients.
Collapse
Affiliation(s)
- Ruchi Sharma
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
| | - Wenzhe Zang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
| | - Ali Tabartehfarahani
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
| | - Andres Lam
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
| | - Xiaheng Huang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor
| | - Anjali Devi Sivakumar
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor
| | - Chandrakalavathi Thota
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
| | - Shuo Yang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
| | - Robert P. Dickson
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Internal Medicine, Division of Pulmonary Critical Care Medicine, University of Michigan, Ann Arbor
| | - Michael W. Sjoding
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Internal Medicine, Division of Pulmonary Critical Care Medicine, University of Michigan, Ann Arbor
| | - Erin Bisco
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Emergency Medicine, University of Michigan, Ann Arbor
| | - Carmen Colmenero Mahmood
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Emergency Medicine, University of Michigan, Ann Arbor
| | - Kristen Machado Diaz
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Emergency Medicine, University of Michigan, Ann Arbor
| | - Nicholas Sautter
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor
| | - Sardar Ansari
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Emergency Medicine, University of Michigan, Ann Arbor
| | - Kevin R. Ward
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
- Department of Emergency Medicine, University of Michigan, Ann Arbor
| | - Xudong Fan
- Department of Biomedical Engineering, University of Michigan, Ann Arbor
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor
| |
Collapse
|
10
|
Laird S, Debenham L, Chandla D, Chan C, Daulton E, Taylor J, Bhat P, Berry L, Munthali P, Covington JA. Breath Analysis of COVID-19 Patients in a Tertiary UK Hospital by Optical Spectrometry: The E-Nose CoVal Study. BIOSENSORS 2023; 13:bios13020165. [PMID: 36831932 PMCID: PMC9953365 DOI: 10.3390/bios13020165] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 01/06/2023] [Accepted: 01/11/2023] [Indexed: 05/31/2023]
Abstract
Throughout the SARS-CoV-2 pandemic, diagnostic technology played a crucial role in managing outbreaks on a national and global level. One diagnostic modality that has shown promise is breath analysis, due to its non-invasive nature and ability to give a rapid result. In this study, a portable FTIR (Fourier Transform Infra-Red) spectrometer was used to detect chemical components in the breath from Covid positive symptomatic and asymptomatic patients versus a control cohort of Covid negative patients. Eighty-five patients who had a nasopharyngeal polymerase chain reaction (PCR) test for the detection of SARS-CoV-2 within the last 5 days were recruited to the study (36 symptomatic PCR positive, 23 asymptomatic PCR positive and 26 asymptomatic PCR negative). Data analysis indicated significant difference between the groups, with SARS-CoV-2 present on PCR versus the negative PCR control group producing an area under the curve (AUC) of 0.87. Similar results were obtained comparing symptomatic versus control and asymptomatic versus control. The asymptomatic results were higher than the symptomatic (0.88 vs. 0.80 AUC). When analysing individual chemicals, we found ethanol, methanol and acetaldehyde were the most important, with higher concentrations in the COVID-19 group, with symptomatic patients being higher than asymptomatic patients. This study has shown that breath analysis can provide significant results that distinguish patients with or without COVID-19 disease/carriage.
Collapse
Affiliation(s)
- Steven Laird
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
- Coventry and Warwickshire Pathology Service, University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
- Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK
| | - Luke Debenham
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
- Warwick Medical School, University of Warwick, Coventry CV4 7AL, UK
| | - Danny Chandla
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
| | - Cathleen Chan
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
- Coventry and Warwickshire Pathology Service, University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
| | - Emma Daulton
- School of Engineering, University of Warwick, Coventry CV4 7AL, UK
| | - Johnathan Taylor
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
- Coventry and Warwickshire Pathology Service, University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
| | - Palashika Bhat
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
| | - Lisa Berry
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
- Coventry and Warwickshire Pathology Service, University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
| | - Peter Munthali
- University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
- Coventry and Warwickshire Pathology Service, University of Coventry and Warwickshire Hospital Trust, Clifford Bridge Road, Coventry CV2 2DX, UK
| | | |
Collapse
|
11
|
Kamalabadi M, Ghoorchian A, Derakhshandeh K, Gholyaf M, Ravan M. Design and Fabrication of a Gas Sensor Based on a Polypyrrole/Silver Nanoparticle Film for the Detection of Ammonia in Exhaled Breath of COVID-19 Patients Suffering from Acute Kidney Injury. Anal Chem 2022; 94:16290-16298. [DOI: 10.1021/acs.analchem.2c02760] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Affiliation(s)
- Mahdie Kamalabadi
- Department of Pharmaceutics, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
- Medicinal Plants and Natural Products Research Center, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
| | - Arash Ghoorchian
- Department of Pharmaceutics, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
- Medicinal Plants and Natural Products Research Center, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
| | - Katayoun Derakhshandeh
- Department of Pharmaceutics, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
- Medicinal Plants and Natural Products Research Center, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
| | - Mahmoud Gholyaf
- Urology & Nephrology Research Center, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
| | - Maryam Ravan
- Department of Pharmaceutics, School of Pharmacy, Hamadan University of Medical Sciences, Hamadan 6517838736, Iran
| |
Collapse
|
12
|
Horng RH, Lin SH, Hung DR, Chao PH, Fu PK, Chen CH, Chen YC, Shao JH, Huang CY, Tarntair FG, Liu PL, Hsiao CL. Structure Effect on the Response of ZnGa 2O 4 Gas Sensor for Nitric Oxide Applications. NANOMATERIALS (BASEL, SWITZERLAND) 2022; 12:3759. [PMID: 36364533 PMCID: PMC9653968 DOI: 10.3390/nano12213759] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 10/19/2022] [Accepted: 10/22/2022] [Indexed: 06/16/2023]
Abstract
We fabricated a gas sensor with a wide-bandgap ZnGa2O4 (ZGO) epilayer grown on a sapphire substrate by metalorganic chemical vapor deposition. The ZGO presented (111), (222) and (333) phases demonstrated by an X-ray diffraction system. The related material characteristics were also measured by scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. This ZGO gas sensor was used to detect nitric oxide (NO) in the parts-per-billion range. In this study, the structure effect on the response of the NO gas sensor was studied by altering the sensor dimensions. Two approaches were adopted to prove the dimension effect on the sensing mechanism. In the first approach, the sensing area of the sensors was kept constant while both channel length (L) and width (W) were varied with designed dimensions (L × W) of 60 × 200, 80 × 150, and 120 ×100 μm2. In the second, the dimensions of the sensing area were altered (60, 40, and 20 μm) with W kept constant. The performance of the sensors was studied with varying gas concentrations in the range of 500 ppb~10 ppm. The sensor with dimensions of 20 × 200 μm2 exhibited a high response of 11.647 in 10 ppm, and 1.05 in 10 ppb for NO gas. The sensor with a longer width and shorter channel length exhibited the best response. The sensing mechanism was provided to explain the above phenomena. Furthermore, the reaction between NO and the sensor surface was simulated by O exposure of the ZGO surface in air and calculated by first principles.
Collapse
Affiliation(s)
- Ray-Hua Horng
- Institute of Electronics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Shu-Hsien Lin
- Institute of Electronics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Dun-Ru Hung
- Graduate Institute of Precision Engineering, National Chung Hsing University, Taichung 402, Taiwan
| | - Po-Hsiang Chao
- Institute of Electronics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Pin-Kuei Fu
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung 402010, Taiwan
- Integrated Care Center of Interstitial Lung Disease, Taichung Veterans General Hospital, Taichung 407219, Taiwan
- Department of Critical Care Medicine, Taichung Veterans General Hospital, Taichung 407219, Taiwan
| | - Cheng-Hsu Chen
- Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung 402010, Taiwan
| | - Yi-Che Chen
- Graduate Institute of Precision Engineering, National Chung Hsing University, Taichung 402, Taiwan
| | - Jhih-Hong Shao
- Graduate Institute of Precision Engineering, National Chung Hsing University, Taichung 402, Taiwan
| | - Chiung-Yi Huang
- Institute of Electronics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Fu-Gow Tarntair
- Institute of Electronics, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Po-Liang Liu
- Graduate Institute of Precision Engineering, National Chung Hsing University, Taichung 402, Taiwan
| | - Ching-Lien Hsiao
- Thin Film Physics Division, Department of Physics, Chemistry, and Biology, Linköping University, 58183 Linköping, Sweden
| |
Collapse
|
13
|
Sukul P, Trefz P, Schubert JK, Miekisch W. Advanced setup for safe breath sampling and patient monitoring under highly infectious conditions in the clinical environment. Sci Rep 2022; 12:17926. [PMID: 36289276 PMCID: PMC9606119 DOI: 10.1038/s41598-022-22581-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 10/17/2022] [Indexed: 01/20/2023] Open
Abstract
Being the proximal matrix, breath offers immediate metabolic outlook of respiratory infections. However, high viral load in exhalations imposes higher transmission risk that needs improved methods for safe and repeatable analysis. Here, we have advanced the state-of-the-art methods for real-time and offline mass-spectrometry based analysis of exhaled volatile organic compounds (VOCs) under SARS-CoV-2 and/or similar respiratory conditions. To reduce infection risk, the general experimental setups for direct and offline breath sampling are modified. Certain mainstream and side-stream viral filters are examined for direct and lab-based applications. Confounders/contributions from filters and optimum operational conditions are assessed. We observed immediate effects of infection safety mandates on breath biomarker profiles. Main-stream filters induced physiological and analytical effects. Side-stream filters caused only systematic analytical effects. Observed substance specific effects partly depended on compound's origin and properties, sampling flow and respiratory rate. For offline samples, storage time, -conditions and -temperature were crucial. Our methods provided repeatable conditions for point-of-care and lab-based breath analysis with low risk of disease transmission. Besides breath VOCs profiling in spontaneously breathing subjects at the screening scenario of COVID-19/similar test centres, our methods and protocols are applicable for moderately/severely ill (even mechanically-ventilated) and highly contagious patients at the intensive care.
Collapse
Affiliation(s)
- Pritam Sukul
- grid.10493.3f0000000121858338Rostock Medical Breath Research Analytics and Technologies (ROMBAT), Department of Anaesthesiology and Intensive Care, University Medicine Rostock, Schillingallee 35, 18057 Rostock, Germany
| | - Phillip Trefz
- grid.10493.3f0000000121858338Rostock Medical Breath Research Analytics and Technologies (ROMBAT), Department of Anaesthesiology and Intensive Care, University Medicine Rostock, Schillingallee 35, 18057 Rostock, Germany
| | - Jochen K. Schubert
- grid.10493.3f0000000121858338Rostock Medical Breath Research Analytics and Technologies (ROMBAT), Department of Anaesthesiology and Intensive Care, University Medicine Rostock, Schillingallee 35, 18057 Rostock, Germany
| | - Wolfram Miekisch
- grid.10493.3f0000000121858338Rostock Medical Breath Research Analytics and Technologies (ROMBAT), Department of Anaesthesiology and Intensive Care, University Medicine Rostock, Schillingallee 35, 18057 Rostock, Germany
| |
Collapse
|
14
|
Khosla NK, Lesinski JM, Colombo M, Bezinge L, deMello AJ, Richards DA. Simplifying the complex: accessible microfluidic solutions for contemporary processes within in vitro diagnostics. LAB ON A CHIP 2022; 22:3340-3360. [PMID: 35984715 PMCID: PMC9469643 DOI: 10.1039/d2lc00609j] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 08/15/2022] [Indexed: 05/02/2023]
Abstract
In vitro diagnostics (IVDs) form the cornerstone of modern medicine. They are routinely employed throughout the entire treatment pathway, from initial diagnosis through to prognosis, treatment planning, and post-treatment surveillance. Given the proven links between high quality diagnostic testing and overall health, ensuring broad access to IVDs has long been a focus of both researchers and medical professionals. Unfortunately, the current diagnostic paradigm relies heavily on centralized laboratories, complex and expensive equipment, and highly trained personnel. It is commonly assumed that this level of complexity is required to achieve the performance necessary for sensitive and specific disease diagnosis, and that making something affordable and accessible entails significant compromises in test performance. However, recent work in the field of microfluidics is challenging this notion. By exploiting the unique features of microfluidic systems, researchers have been able to create progressively simple devices that can perform increasingly complex diagnostic assays. This review details how microfluidic technologies are disrupting the status quo, and facilitating the development of simple, affordable, and accessible integrated IVDs. Importantly, we discuss the advantages and limitations of various approaches, and highlight the remaining challenges within the field.
Collapse
Affiliation(s)
- Nathan K Khosla
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, Zürich, 8093, Switzerland.
| | - Jake M Lesinski
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, Zürich, 8093, Switzerland.
| | - Monika Colombo
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, Zürich, 8093, Switzerland.
| | - Léonard Bezinge
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, Zürich, 8093, Switzerland.
| | - Andrew J deMello
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, Zürich, 8093, Switzerland.
| | - Daniel A Richards
- Institute for Chemical and Bioengineering, ETH Zürich, Vladimir Prelog Weg 1, Zürich, 8093, Switzerland.
| |
Collapse
|
15
|
Calvo-Gomez O, Calvo H, Cedillo-Barrón L, Vivanco-Cid H, Alvarado-Orozco JM, Fernandez-Benavides DA, Arriaga-Pizano L, Ferat-Osorio E, Anda-Garay JC, López-Macias C, López MG. Potential of ATR-FTIR-Chemometrics in Covid-19: Disease Recognition. ACS OMEGA 2022; 7:30756-30767. [PMID: 36092630 PMCID: PMC9453986 DOI: 10.1021/acsomega.2c01374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The COVID-19 pandemic has caused major disturbances to human health and economy on a global scale. Although vaccination campaigns and important advances in treatments have been developed, an early diagnosis is still crucial. While PCR is the golden standard for diagnosing SARS-CoV-2 infection, rapid and low-cost techniques such as ATR-FTIR followed by multivariate analyses, where dimensions are reduced for obtaining valuable information from highly complex data sets, have been investigated. Most dimensionality reduction techniques attempt to discriminate and create new combinations of attributes prior to the classification stage; thus, the user needs to optimize a wealth of parameters before reaching reliable and valid outcomes. In this work, we developed a method for evaluating SARS-CoV-2 infection and COVID-19 disease severity on infrared spectra of sera, based on a rather simple feature selection technique (correlation-based feature subset selection). Dengue infection was also evaluated for assessing whether selectivity toward a different virus was possible with the same algorithm, although independent models were built for both viruses. High sensitivity (94.55%) and high specificity (98.44%) were obtained for assessing SARS-CoV-2 infection with our model; for severe COVID-19 disease classification, sensitivity is 70.97% and specificity is 94.95%; for mild disease classification, sensitivity is 33.33% and specificity is 94.64%; and for dengue infection assessment, sensitivity is 84.27% and specificity is 94.64%.
Collapse
Affiliation(s)
- Octavio Calvo-Gomez
- Centro
de Investigación y de Estudios Avanzados del IPN, Km. 9.6 Libramiento Norte Carretera
Irapuato León, 36824 Irapuato, Guanajuato, Mexico
| | - Hiram Calvo
- Center
for Computing Research, Instituto Politécnico
Nacional, 07738 Mexico City, Mexico
| | - Leticia Cedillo-Barrón
- Centro
de Investigación y de Estudios Avanzados del IPN. Avenida IPN #2508, Col. San Pedro
Zacatenco, CP 07360 Mexico, Distrito Federal, Mexico
| | - Héctor Vivanco-Cid
- Laboratorio
Multidisciplinario en Ciencias Biomédicas, Instituto de Investigaciones
Médico-Biológicas, Universidad
Veracruzana, 91000Veracruz, Mexico
| | - Juan Manuel Alvarado-Orozco
- Centro
de Ingeniería y Desarrollo Industrial, Avenida Playa Pie de la Cuesta No.
702, Desarrollo San Pablo, 76125 Santiago de Querétaro, Mexico
| | - David Andrés Fernandez-Benavides
- Centro
de Ingeniería y Desarrollo Industrial, Avenida Playa Pie de la Cuesta No.
702, Desarrollo San Pablo, 76125 Santiago de Querétaro, Mexico
| | - Lourdes Arriaga-Pizano
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Eduardo Ferat-Osorio
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Juan Carlos Anda-Garay
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Constantino López-Macias
- Unidad
de
Investigación Médica en Inmunoquímica, UMAE,
Hospital de Especialidades del Centro Médico Nacional Siglo
XXI. Instituto Mexicano del Seguro Social
(IMSS), 06600 Mexico City, Mexico
| | - Mercedes G. López
- Centro
de Investigación y de Estudios Avanzados del IPN, Km. 9.6 Libramiento Norte Carretera
Irapuato León, 36824 Irapuato, Guanajuato, Mexico
| |
Collapse
|
16
|
Progress and Challenges of Point-of-Need Photonic Biosensors for the Diagnosis of COVID-19 Infections and Immunity. BIOSENSORS 2022; 12:bios12090678. [PMID: 36140063 PMCID: PMC9496547 DOI: 10.3390/bios12090678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 08/13/2022] [Accepted: 08/16/2022] [Indexed: 11/25/2022]
Abstract
The new coronavirus disease, COVID-19, caused by SARS-CoV-2, continues to affect the world and after more than two years of the pandemic, approximately half a billion people are reported to have been infected. Due to its high contagiousness, our life has changed dramatically, with consequences that remain to be seen. To prevent the transmission of the virus, it is crucial to diagnose COVID-19 accurately, such that the infected cases can be rapidly identified and managed. Currently, the gold standard of testing is polymerase chain reaction (PCR), which provides the highest accuracy. However, the reliance on centralized rapid testing modalities throughout the COVID-19 pandemic has made access to timely diagnosis inconsistent and inefficient. Recent advancements in photonic biosensors with respect to cost-effectiveness, analytical performance, and portability have shown the potential for such platforms to enable the delivery of preventative and diagnostic care beyond clinics and into point-of-need (PON) settings. Herein, we review photonic technologies that have become commercially relevant throughout the COVID-19 pandemic, as well as emerging research in the field of photonic biosensors, shedding light on prospective technologies for responding to future health outbreaks. Therefore, in this article, we provide a review of recent progress and challenges of photonic biosensors that are developed for the testing of COVID-19, consisting of their working fundamentals and implementation for COVID-19 testing in practice with emphasis on the challenges that are faced in different development stages towards commercialization. In addition, we also present the characteristics of a biosensor both from technical and clinical perspectives. We present an estimate of the impact of testing on disease burden (in terms of Disability-Adjusted Life Years (DALYs), Quality Adjusted Life Years (QALYs), and Quality-Adjusted Life Days (QALDs)) and how improvements in cost can lower the economic impact and lead to reduced or averted DALYs. While COVID19 is the main focus of these technologies, similar concepts and approaches can be used and developed for future outbreaks of other infectious diseases.
Collapse
|