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Koyambo-Konzapa SJ, Oubella A, Altharawi A, Aldakhil T. COVID-19 detection via isobutyric acid biomarker: A DFT computational study on beryllium-doped C60 fullerene. J Mol Graph Model 2025; 137:108987. [PMID: 39985930 DOI: 10.1016/j.jmgm.2025.108987] [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: 12/02/2024] [Revised: 01/18/2025] [Accepted: 02/17/2025] [Indexed: 02/24/2025]
Abstract
The COVID-19 pandemic has underscored the urgent need for rapid, accurate, and non-invasive diagnostic methods. This study explores the potential of beryllium-doped C60 fullerene as a sensor for detecting COVID-19 via isobutyric acid (ISO-But), a biomarker found in the breath of infected individuals. By employing Density Functional Theory (DFT), we analyze the electronic and structural properties of pristine and metal-doped C60 fullerenes (Beryllium (Be) and Calcium (Ca)), focusing on their interactions with isobutyric acid. Our findings reveal that BeC59, combined with isobutyric acid, displays a colorimetric response within the visible spectrum, indicating its suitability for point-of-care diagnostics. With rapid recovery and strong interaction properties, this sensor design promises to advance non-invasive COVID-19 detection, making it accessible and feasible for real-time applications.
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Affiliation(s)
- Stève-Jonathan Koyambo-Konzapa
- Laboratoire Matière, Energie et Rayonnement (LAMER), Université de Bangui, P.O. Box 1450 Bangui, Central African Republic.
| | - Ali Oubella
- Laboratory of Chemistry and Environment, Applied Bioorganic Chemistry Team, Faculty of Sciences, Ibnou Zohr University, Agadir, Morocco.
| | - Ali Altharawi
- Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia
| | - Taibah Aldakhil
- Department of Pharmaceutical Chemistry, College of Pharmacy, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia
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2
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Schachner ER, Lawson AB, Martinez A, Grand Pre CA, Sabottke C, Abou-Issa F, Echols S, Diaz RE, Moore AJ, Grenier JP, Hedrick BP, Spieler B. Perspectives on lung visualization: Three-dimensional anatomical modeling of computed and micro-computed tomographic data in comparative evolutionary morphology and medicine with applications for COVID-19. Anat Rec (Hoboken) 2025; 308:1118-1143. [PMID: 37528640 DOI: 10.1002/ar.25300] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 07/16/2023] [Accepted: 07/19/2023] [Indexed: 08/03/2023]
Abstract
The vertebrate respiratory system is challenging to study. The complex relationship between the lungs and adjacent tissues, the vast structural diversity of the respiratory system both within individuals and between taxa, its mobility (or immobility) and distensibility, and the difficulty of quantifying and visualizing functionally important internal negative spaces have all impeded descriptive, functional, and comparative research. As a result, there is a relative paucity of three-dimensional anatomical information on this organ system in all vertebrate groups (including humans) relative to other regions of the body. We present some of the challenges associated with evaluating and visualizing the vertebrate respiratory system using computed and micro-computed tomography and its subsequent digital segmentation. We discuss common mistakes to avoid when imaging deceased and live specimens and various methods for merging manual and threshold-based segmentation approaches to visualize pulmonary tissues across a broad range of vertebrate taxa, with a particular focus on sauropsids (reptiles and birds). We also address some of the recent work in comparative evolutionary morphology and medicine that have used these techniques to visualize respiratory tissues. Finally, we provide a clinical study on COVID-19 in humans in which we apply modeling methods to visualize and quantify pulmonary infection in the lungs of human patients.
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Affiliation(s)
- Emma R Schachner
- Department of Physiological Sciences, College of Veterinary Medicine, University of Florida, Gainesville, Florida, USA
| | - Adam B Lawson
- Department of Structural and Cellular Biology, School of Medicine, Tulane University, New Orleans, Louisiana, USA
| | - Aracely Martinez
- Department of Cell Biology and Anatomy, School of Medicine, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA
| | - Clinton A Grand Pre
- Department of Cell Biology and Anatomy, School of Medicine, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA
| | - Carl Sabottke
- Department of Medical Imaging, University of Arizona College of Medicine, Tucson, Arizona, USA
| | - Farid Abou-Issa
- Department of Cell Biology and Anatomy, School of Medicine, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA
| | - Scott Echols
- The Medical Center for birds, Oakley, California, USA
| | - Raul E Diaz
- Department of Biological Sciences, California State University Los Angeles, Los Angeles, California, USA
| | - Andrew J Moore
- Department of Anatomical Sciences, Renaissance School of Medicine, Stony Brook University, New York, New York, USA
| | - John-Paul Grenier
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Brandon P Hedrick
- Department of Biomedical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, USA
| | - Bradley Spieler
- Department of Radiology, University Medical Center, Louisiana State University Health Sciences Center, New Orleans, Louisiana, USA
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3
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Tomos I, Antonogiannaki EM, Dimakopoulou K, Raptakis T, Apollonatou V, Kallieri M, Argentos S, Lampadakis S, Blizou M, Krouskos A, Karakatsani A, Manali E, Loukides S, Papiris S. The prognostic role of lung ultrasound in hospitalised patients with COVID-19. Correlation with chest CT findings and clinical markers of severity. Expert Rev Respir Med 2025; 19:363-370. [PMID: 40007128 DOI: 10.1080/17476348.2025.2471776] [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: 10/20/2024] [Revised: 02/08/2025] [Accepted: 02/21/2025] [Indexed: 02/27/2025]
Abstract
BACKGROUND The use of lung ultrasound (LUS) has recently become vital in the diagnosis and prognosis of various respiratory diseases. Its role in COVID-19 requires further investigation. RESEARCH DESIGN AND METHODS Twenty-five consecutive, non-ICU hospitalized COVID-19 patients were included. LUS was performed on admission and sequentially every 3 days at 8 points in the chest. Based on the LUS findings a score was designed. Logarithmic regression models and ROC curve analysis were applied. RESULTS A statistically significant positive correlation was found between LUS score at admission and the severity of SARS-COV-2 infection. Higher LUS score was significantly associated with lower PaO2/FiO2 ratio, use of HFNC, longer hospitalization and greater extent of chest CT infiltrates. A significant association between LUS score and risk of death or intubation or HFNC was found. For one point of increase in the score, risk of death or intubation or HFNC increased 1.93-fold (95% CI 1.02 to 3.65). The predictive role of the score was very satisfactory (area under the ROC curve = 0.87). CONCLUSIONS Lung ultrasound findings were significantly positively associated with clinical and radiological markers of severity of SARS-CoV-2 pneumonia. It therefore constitutes a promising and reliable technique for assessing pneumonia, comparable to chest CT.
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Affiliation(s)
- Ioannis Tomos
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Elvira Markela Antonogiannaki
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Konstantina Dimakopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Thomas Raptakis
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Vasiliki Apollonatou
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Maria Kallieri
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Stylianos Argentos
- 2nd Department of Radiology, ATTIKON University Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Stefanos Lampadakis
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Myrto Blizou
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Antonis Krouskos
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Anna Karakatsani
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Effrosyni Manali
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Stylianos Loukides
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Spyros Papiris
- 2nd Pulmonary Medicine Department, ATTIKON University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
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Chai HX, Bamert RS, Knott GJ. Methods for Cas13a expression and purification for use in CRISPR diagnostics. Methods Enzymol 2025; 712:225-244. [PMID: 40121074 DOI: 10.1016/bs.mie.2025.01.030] [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] [Indexed: 03/25/2025]
Abstract
The threat of emerging infectious diseases (e.g., SARS-CoV-2 the RNA virus responsible for the COVID-19 pandemic) has highlighted the importance of accurate and rapid testing for screening, patient diagnosis, and effective treatment of infectious disease. Nucleic acid diagnostic tools such as qPCR are considered the gold standard, providing a sensitive, accurate, and robust method of detection. However, these conventional diagnostic platforms are resource intensive, limited in some applications, and are almost always confined to laboratory settings. With the increasing demand for low-cost, rapid, and accurate point-of-care diagnostics, CRISPR-based systems have emerged as powerful tools to augment detection capabilities. Of note is the potent RNA detection enzyme, Leptotrichia buccalis (Lbu) Cas13a, which is capable of rapid RNA detection in complex mixtures with or without pre-amplification. To support its wide-spread use, we describe a detailed method for the expression, purification, and validation of LbuCas13a for use in molecular diagnostics.
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Affiliation(s)
- Her Xiang Chai
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Rebecca S Bamert
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia
| | - Gavin J Knott
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC, Australia.
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Sajal SSA, Islam DZ, Khandker SS, Solórzano-Ortiz E, Fardoun M, Ahmed MF, Jamiruddin MR, Azmuda N, Mehta M, Kumar S, Haque M, Adnan N. Strategies to Overcome Erroneous Outcomes in Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Testing: Insights From the COVID-19 Pandemic. Cureus 2024; 16:e72954. [PMID: 39498425 PMCID: PMC11532724 DOI: 10.7759/cureus.72954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2024] [Accepted: 11/03/2024] [Indexed: 11/07/2024] Open
Abstract
The reverse transcription-polymerase chain reaction (RT-PCR) test to detect SARS-CoV-2, the virus causing COVID-19, has been regarded as the diagnostic gold standard. However, the excessive sensitivity of RT-PCR may cause false-positive outcomes from contamination. Again, its technical complexity increases the chances of false-negatives due to pre-analytical and analytical errors. This narrative review explores the elements contributing to inaccurate results during the COVID-19 pandemic and offers strategies to minimize these errors. False-positive results may occur due to specimen contamination, non-specific primer binding, residual viral RNA, and false-negatives, which may arise from improper sampling, timing, labeling, storage, low viral loads, mutations, and faulty test kits. Proposed mitigation strategies to enhance the accuracy of RT-PCR testing include comprehensive staff training in specimen collection, optimizing the timing of tests, analyzing multiple gene targets, incorporating clinical findings, workflow automation, and implementing stringent contamination control measures. Identifying and rectifying sources of error in RT-PCR diagnosis through quality control and standardized protocols is imperative for ensuring quality patient care and effective epidemic control.
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Affiliation(s)
- Sm Shafiul Alam Sajal
- Department of Biochemistry and Molecular Biology, Jahangirnagar University, Dhaka, BGD
| | | | - Shahad Saif Khandker
- Department of Microbiology, Gonoshasthaya Samaj Vittik Medical College, Dhaka, BGD
| | - Elizabeth Solórzano-Ortiz
- Department of Chemical, Biological, Biomedical and Biophysical Research, Mariano Gálvez University, Guatemala City, GTM
| | - Manal Fardoun
- Department of Pharmacology and Toxicology, Faculty of Medicine, American University of Beirut, Beirut, LBN
| | - Md Firoz Ahmed
- Department of Microbiology, Jahangirnagar University, Dhaka, BGD
| | - Mohd Raeed Jamiruddin
- Department of Pharmacy, Bangladesh Rural Advancement Committee (BRAC) University, Dhaka, BGD
| | - Nafisa Azmuda
- Department of Microbiology, Jahangirnagar University, Dhaka, BGD
| | - Miral Mehta
- Department of Pedodontics and Preventive Dentistry, Karnavati School of Dentistry, Karnavati University, Gandhinagar, IND
| | - Santosh Kumar
- Department of Periodontology and Implantology, Karnavati School of Dentistry, Karnavati University, Gandhinagar, IND
| | - Mainul Haque
- Department of Pharmacology and Therapeutics, National Defence University of Malaysia, Kuala Lumpur, MYS
| | - Nihad Adnan
- Department of Microbiology, Jahangirnagar University, Dhaka, BGD
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Mittal RK, Purohit P, Sankaranarayanan M, Muzaffar-Ur-Rehman M, Taramelli D, Signorini L, Dolci M, Basilico N. In-vitro antiviral activity and in-silico targeted study of quinoline-3-carboxylate derivatives against SARS-Cov-2 isolate. Mol Divers 2024; 28:2651-2665. [PMID: 37480422 DOI: 10.1007/s11030-023-10703-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: 06/07/2023] [Accepted: 07/16/2023] [Indexed: 07/24/2023]
Abstract
In recent years, the viral outbreak named COVID-19 showed that infectious diseases have a huge impact on both global health and the financial and economic sectors. The lack of efficacious antiviral drugs worsened the health problem. Based on our previous experience, we investigated in vitro and in silico a series of quinoline-3-carboxylate derivatives against a SARS-CoV-2 isolate. In the present study, the in-vitro antiviral activity of a series of quinoline-3-carboxylate compounds and the in silico target-based molecular dynamics (MD) and metabolic studies are reported. The compounds' activity against SARS-CoV-2 was evaluated using plaque assay and RT-qPCR. Moreover, from the docking scores, it appears that the most active compounds (1j and 1o) exhibit stronger binding affinity to the primary viral protease (NSP5) and the exoribonuclease domain of non structural protein 14 (NSP14). Additionally, the in-silico metabolic analysis of 1j and 1o defines CYP2C9 and CYP3A4 as the major P450 enzymes involved in their metabolism.
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Affiliation(s)
- Ravi Kumar Mittal
- National Institute of Pharmaceutical Education and Research, S A S Nagar Mohali, Punjab, 160062, India
- Galgotias College of Pharmacy, Greater Noida, UttarPradesh, India
| | - Priyank Purohit
- School of Pharmacy, Graphic Era Hill University, Dehradun, Uttarakhand, 248002, India.
| | - Murugesan Sankaranarayanan
- Medicinal Chemistry Research Laboratory, Department of Pharmacy, BITS Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India
| | - Mohammed Muzaffar-Ur-Rehman
- Medicinal Chemistry Research Laboratory, Department of Pharmacy, BITS Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India
| | - Donatella Taramelli
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Pascal Street 36, 20133, Milan, Italy
| | - Lucia Signorini
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Pascal Street 36, 20133, Milan, Italy
| | - Maria Dolci
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Pascal Street 36, 20133, Milan, Italy
| | - Nicoletta Basilico
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Pascal Street 36, 20133, Milan, Italy
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7
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Putra HG, Surja SS, Widowati TA, Ali S, Kaisar MMM. SARS-CoV-2 RT-LAMP in saliva: enhancing the results via a combination of cooling and specimen dilution procedure. Virusdisease 2024; 35:293-301. [PMID: 39071878 PMCID: PMC11269541 DOI: 10.1007/s13337-024-00870-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 05/11/2024] [Indexed: 07/30/2024] Open
Abstract
Colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) is a potential and relatively simple rapid diagnostics method for COVID-19 detection. This study aims to evaluate and optimize the RT-LAMP performance on saliva specimens based on a commercially available kit.Modifications on an established protocol (Protocol A) were used, including Proteinase K supplementation (Protocol B); pre-treatment using nuclease-free water and proteinase K (Protocol C); Saliva cooling (Protocol D); saliva dilution after pre-treatment (Protocol E); lastly a combination of saliva cooling and dilution (Protocol F). Protocol performances were evaluated by comparing success rates (SR), diagnostic accuracy (DA), sensitivity, specificity, and predictive values. Additionally, a correlation between the Ct value by RT-qPCR and RT-LAMP performance was analyzed.. A total of 106 specimens were used in this study. Protocols B and C showed 100% unreadable results, therefore were paused. Protocol F showed the highest SR (87.65%) compared to other protocols, with a slight compromise to DA (81.69%), sensitivity (57.14%), specificity (97.67%), PPV (94.12%), and NPV (77.78%). In the sub-analysis of the low Ct value group (Ct < 30), Protocol F demonstrated a higher success rate (86.57%) compared to protocol A (64.18%); increased 3.08% sensitivity and 2.42% NPV; comparable DA; minor reduction in specificity (A = 100%; F = 97.67%) and PPV (A = 100%; F = 92.31%). A combination of saliva cooling-dilution substantially increased the tested kit's success rate, despite a slight decrease in specificity and PPV. Findings confirmed the saliva cooling-dilution procedure was beneficial to the test's SR, sensitivity, and NPV in the low Ct value group. Supplementary Information The online version contains supplementary material available at 10.1007/s13337-024-00870-1.
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Affiliation(s)
- Henry Gotama Putra
- Undergraduate Study Program, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, 14440 Indonesia
| | - Sem Samuel Surja
- Department of Parasitology, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, 14440 Indonesia
| | - Tria Asri Widowati
- Department of Parasitology, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, 14440 Indonesia
| | - Soegianto Ali
- Department of Medical Biology, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, 14440 Indonesia
- Present Address: Master in Biomedicine Study Program, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, 14440 Indonesia
| | - Maria Mardalena Martini Kaisar
- Department of Parasitology, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, 14440 Indonesia
- Present Address: Master in Biomedicine Study Program, School of Medicine and Health Sciences, Atma Jaya Catholic University of Indonesia, Jakarta, 14440 Indonesia
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8
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Zhang YP, Bu JW, Shu RX, Liu SL. Advances in rapid point-of-care virus testing. Analyst 2024; 149:2507-2525. [PMID: 38630498 DOI: 10.1039/d4an00238e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/30/2024]
Abstract
Outbreaks of viral diseases seriously jeopardize people's health and cause huge economic losses. At the same time, virology provides a new perspective for biology, molecular biology and cancer research, and it is important to study the discovered viruses with potential applications. Therefore, the development of immediate and rapid viral detection methods for the prevention and treatment of viral diseases as well as the study of viruses has attracted extensive attention from scientists. With the continuous progress of science and technology, especially in the field of bioanalysis, a series of new detection techniques have been applied to the on-site rapid detection of viruses, which has become a powerful approach for human beings to fight against viruses. In this paper, the latest research progress of rapid point-of-care detection of viral nucleic acids, antigens and antibodies is presented. In addition, the advantages and disadvantages of these technologies are discussed from the perspective of practical application requirements. Finally, the problems and challenges faced by rapid viral detection methods and their development prospects are discussed.
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Affiliation(s)
- Yu-Peng Zhang
- Technical Center, Shanghai Tobacco Group Co., Ltd, Shanghai 201315, P. R. China.
| | - Jin-Wei Bu
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, P. R. China.
| | - Ru-Xin Shu
- Technical Center, Shanghai Tobacco Group Co., Ltd, Shanghai 201315, P. R. China.
| | - Shu-Lin Liu
- Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan 430074, P. R. China.
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Mohsin AS, Jamiruddin MR, Peyal MMK, Sharmin S, Ahmed A, Puspita AH, Sharfuddin A, Malik A, Hasib A, Suchona SA, Chowdhury AM, Kabir ER. Design optimization and validation of UV-C illumination chamber for filtering facepiece respirators. Heliyon 2024; 10:e26348. [PMID: 38439842 PMCID: PMC10909644 DOI: 10.1016/j.heliyon.2024.e26348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 09/10/2023] [Accepted: 02/12/2024] [Indexed: 03/06/2024] Open
Abstract
In this study, we constructed an UV-C illumination chamber using commercially available germicidal lamps and other locally available low-cost components for general-purpose biological decontamination purposes. The illumination chamber provides uniform illumination of around 1 J/cm2 in under 5 min across the chamber. The control mechanism was developed to automate the on/off process and make it more secure minimizing health and other electrical safety. To validate the decontamination efficacy of the UV-C Illumination Chamber we performed the Geobacillus spore strip culture assay. Additionally, we performed the viral load measurement by identifying the COVID-19-specific N-gene and ORF1 gene on surgical masks. The gold standard RT-qPCR measurement was performed to detect and quantify the COVID-19-specific gene on the mask sample. The biochemical assay was conducted on the control and test group to identify the presence of different types of bacteria, and fungi before and after exposure under the illumination chamber. The findings of our study revealed satisfactory decontamination efficacy test results. Therefore, it could be an excellent device in healthcare settings as a disinfection tool for biological decontamination such as SAR-CoV-2 virus, personal protection equipment (PPE), (including n95, k95 respirators, and surgical masks), and other common pathogens.
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Affiliation(s)
- Abu S.M. Mohsin
- Department of Electrical and Electronics Engineering, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - Mohd. Raeed Jamiruddin
- School of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh
- Gonoshasthaya-RNA Molecular Diagnostic and Research Center, Dhaka, Bangladesh
| | - Md Mahmudul Kabir Peyal
- Department of Electrical and Electronics Engineering, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - Shahana Sharmin
- School of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - Ashfaq Ahmed
- School of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - Afrin Hossain Puspita
- Department of Electrical and Electronics Engineering, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - A.A.M. Sharfuddin
- School of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - Afrida Malik
- Department of Electrical and Electronics Engineering, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - Al Hasib
- School of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | | | - Arshad M. Chowdhury
- Department of Electrical and Electronics Engineering, Brac University, 66 Mohakhali, Dhaka, Bangladesh
| | - Eva Rahman Kabir
- School of Pharmacy, Brac University, 66 Mohakhali, Dhaka, Bangladesh
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Fanni SC, Volpi F, Colligiani L, Chimera D, Tonerini M, Pistelli F, Pancani R, Airoldi C, Bartholmai BJ, Cioni D, Carrozzi L, Neri E, De Liperi A, Romei C. Quantitative CT Texture Analysis of COVID-19 Hospitalized Patients during 3-24-Month Follow-Up and Correlation with Functional Parameters. Diagnostics (Basel) 2024; 14:550. [PMID: 38473022 DOI: 10.3390/diagnostics14050550] [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: 01/25/2024] [Revised: 02/21/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND To quantitatively evaluate CT lung abnormalities in COVID-19 survivors from the acute phase to 24-month follow-up. Quantitative CT features as predictors of abnormalities' persistence were investigated. METHODS Patients who survived COVID-19 were retrospectively enrolled and underwent a chest CT at baseline (T0) and 3 months (T3) after discharge, with pulmonary function tests (PFTs). Patients with residual CT abnormalities repeated the CT at 12 (T12) and 24 (T24) months after discharge. A machine-learning-based software, CALIPER, calculated the CT percentage of the whole lung of normal parenchyma, ground glass (GG), reticulation (Ret), and vascular-related structures (VRSs). Differences (Δ) were calculated between time points. Receiver operating characteristic (ROC) curve analyses were performed to test the baseline parameters as predictors of functional impairment at T3 and of the persistence of CT abnormalities at T12. RESULTS The cohort included 128 patients at T0, 133 at T3, 61 at T12, and 34 at T24. The GG medians were 8.44%, 0.14%, 0.13% and 0.12% at T0, T3, T12 and T24. The Ret medians were 2.79% at T0 and 0.14% at the following time points. All Δ significantly differed from 0, except between T12 and T24. The GG and VRSs at T0 achieved AUCs of 0.73 as predictors of functional impairment, and area under the curves (AUCs) of 0.71 and 0.72 for the persistence of CT abnormalities at T12. CONCLUSIONS CALIPER accurately quantified the CT changes up to the 24-month follow-up. Resolution mostly occurred at T3, and Ret persisting at T12 was almost unchanged at T24. The baseline parameters were good predictors of functional impairment at T3 and of abnormalities' persistence at T12.
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Affiliation(s)
- Salvatore Claudio Fanni
- Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy
| | - Federica Volpi
- Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy
| | - Leonardo Colligiani
- Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy
| | - Davide Chimera
- Pneumology Unit, Pisa University Hospital, 56124 Pisa, Italy
| | - Michele Tonerini
- Department of Surgical, Medical, Molecular and Critical Area Pathology, University of Pisa, 56124 Pisa, Italy
| | | | - Roberta Pancani
- Pneumology Unit, Pisa University Hospital, 56124 Pisa, Italy
| | - Chiara Airoldi
- Department of Translational Medicine, University of Eastern Piemonte, 28100 Novara, Italy
| | | | - Dania Cioni
- Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy
| | - Laura Carrozzi
- Pneumology Unit, Pisa University Hospital, 56124 Pisa, Italy
| | - Emanuele Neri
- Department of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy
| | - Annalisa De Liperi
- 2nd Radiology Unit, Department of Diagnostic Imaging, Pisa University-Hospital, Via Paradisa 2, 56124 Pisa, Italy
| | - Chiara Romei
- 2nd Radiology Unit, Department of Diagnostic Imaging, Pisa University-Hospital, Via Paradisa 2, 56124 Pisa, Italy
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11
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Han J, Xue J, Ye X, Xu W, Jin R, Liu W, Meng S, Zhang Y, Hu X, Yang X, Li R, Meng F. Comparison of Ultrasound and CT Imaging for the Diagnosis of Coronavirus Disease and Influenza A Pneumonia. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2023; 42:2557-2566. [PMID: 37334890 DOI: 10.1002/jum.16289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Revised: 04/14/2023] [Accepted: 05/30/2023] [Indexed: 06/21/2023]
Abstract
OBJECTIVE The outbreak of coronavirus disease (COVID-19) coincided with the season of influenza A pneumonia, a common respiratory infectious disease. Therefore, this study compared ultrasonography and computed tomography (CT) for the diagnosis of the two diseases. METHODS Patients with COVID-19 or influenza A infection hospitalized at our hospital were included. The patients were examined by ultrasonography every day. The CT examination results within 1 day before and after the day of the highest ultrasonography score were selected as the controls. The similarities and differences between the ultrasonography and CT results in the two groups were compared. RESULTS There was no difference between the ultrasonography and CT scores (P = .307) for COVID-19, while there was a difference between ultrasonography and CT scores for influenza A pneumonia (P = .024). The ultrasonography score for COVID-19 was higher than that for influenza A pneumonia (P = .000), but there was no difference between the CT scores (P = .830). For both diseases, there was no difference in ultrasonography and CT scores between the left and right lungs; there were differences between the CT scores of the upper and middle lobes, as well as between the upper and lower lobes of the lungs; however, there was no difference between the lower and middle lobes of the lungs. CONCLUSION Ultrasonography is equivalent to the gold standard CT for diagnosing and monitoring the progression of COVID-19. Because of its convenience, ultrasonography has important application value. Furthermore, the diagnostic value of ultrasonography for COVID-19 is higher than that for influenza A pneumonia.
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Affiliation(s)
- Jing Han
- Ultrasound and Functional Diagnosis Center, Beijing You An Hospital, Capital Medical University, Beijing, China
| | - Jun Xue
- Department of Echocardiography, China Emergency General Hospital, Beijing, China
| | - Xiangyang Ye
- Department of Orthopaedics, Nanyang Central Hospital, Nanyang, China
| | - Wei Xu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Hepato-Pancreato-Biliary Surgery, Peking University Cancer Hospital & Institute, Beijing, China
| | - Ronghua Jin
- Beijing You An Hospital, Capital Medical University, Beijing, China
| | - Weiyuan Liu
- Ultrasound and Functional Diagnosis Center, Beijing You An Hospital, Capital Medical University, Beijing, China
| | - Sha Meng
- Department of Science and Technology Department, Beijing You An Hospital, Capital Medical University, Beijing, China
| | - Yuan Zhang
- Ultrasound and Functional Diagnosis Center, Beijing You An Hospital, Capital Medical University, Beijing, China
| | - Xing Hu
- Ultrasound and Functional Diagnosis Center, Beijing You An Hospital, Capital Medical University, Beijing, China
| | - Xi Yang
- Department of ultrasound, Hanyang Hospital Affiliated to Wuhan University of science and technology, Wuhan, China
| | - Ruili Li
- Radiology Department, Beijing You An Hospital, Capital Medical University, Beijing, China
| | - Fankun Meng
- Ultrasound and Functional Diagnosis Center, Beijing You An Hospital, Capital Medical University, Beijing, China
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12
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Mozaffari J, Amirkhani A, Shokouhi SB. A survey on deep learning models for detection of COVID-19. Neural Comput Appl 2023; 35:1-29. [PMID: 37362568 PMCID: PMC10224665 DOI: 10.1007/s00521-023-08683-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 05/10/2023] [Indexed: 06/28/2023]
Abstract
The spread of the COVID-19 started back in 2019; and so far, more than 4 million people around the world have lost their lives to this deadly virus and its variants. In view of the high transmissibility of the Corona virus, which has turned this disease into a global pandemic, artificial intelligence can be employed as an effective tool for an earlier detection and treatment of this illness. In this review paper, we evaluate the performance of the deep learning models in processing the X-Ray and CT-Scan images of the Corona patients' lungs and describe the changes made to these models in order to enhance their Corona detection accuracy. To this end, we introduce the famous deep learning models such as VGGNet, GoogleNet and ResNet and after reviewing the research works in which these models have been used for the detection of COVID-19, we compare the performances of the newer models such as DenseNet, CapsNet, MobileNet and EfficientNet. We then present the deep learning techniques of GAN, transfer learning, and data augmentation and examine the statistics of using these techniques. Here, we also describe the datasets introduced since the onset of the COVID-19. These datasets contain the lung images of Corona patients, healthy individuals, and the patients with non-Corona pulmonary diseases. Lastly, we elaborate on the existing challenges in the use of artificial intelligence for COVID-19 detection and the prospective trends of using this method in similar situations and conditions. Supplementary Information The online version contains supplementary material available at 10.1007/s00521-023-08683-x.
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Affiliation(s)
- Javad Mozaffari
- School of Electrical Engineering, Iran University of Science and Technology, Tehran, 16846-13114 Iran
| | - Abdollah Amirkhani
- School of Automotive Engineering, Iran University of Science and Technology, Tehran, 16846-13114 Iran
| | - Shahriar B. Shokouhi
- School of Electrical Engineering, Iran University of Science and Technology, Tehran, 16846-13114 Iran
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13
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Xu J, Cao Z, Miao C, Zhang M, Xu X. Predicting omicron pneumonia severity and outcome: a single-center study in Hangzhou, China. Front Med (Lausanne) 2023; 10:1192376. [PMID: 37305146 PMCID: PMC10250627 DOI: 10.3389/fmed.2023.1192376] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 05/08/2023] [Indexed: 06/13/2023] Open
Abstract
Background In December 2022, there was a large Omicron epidemic in Hangzhou, China. Many people were diagnosed with Omicron pneumonia with variable symptom severity and outcome. Computed tomography (CT) imaging has been proven to be an important tool for COVID-19 pneumonia screening and quantification. We hypothesized that CT-based machine learning algorithms can predict disease severity and outcome in Omicron pneumonia, and we compared its performance with the pneumonia severity index (PSI)-related clinical and biological features. Methods Our study included 238 patients with the Omicron variant who have been admitted to our hospital in China from 15 December 2022 to 16 January 2023 (the first wave after the dynamic zero-COVID strategy stopped). All patients had a positive real-time polymerase chain reaction (PCR) or lateral flow antigen test for SARS-CoV-2 after vaccination and no previous SARS-CoV-2 infections. We recorded patient baseline information pertaining to demographics, comorbid conditions, vital signs, and available laboratory data. All CT images were processed with a commercial artificial intelligence (AI) algorithm to obtain the volume and percentage of consolidation and infiltration related to Omicron pneumonia. The support vector machine (SVM) model was used to predict the disease severity and outcome. Results The receiver operating characteristic (ROC) area under the curve (AUC) of the machine learning classifier using PSI-related features was 0.85 (accuracy = 87.40%, p < 0.001) for predicting severity while that using CT-based features was only 0.70 (accuracy = 76.47%, p = 0.014). If combined, the AUC was not increased, showing 0.84 (accuracy = 84.03%, p < 0.001). Trained on outcome prediction, the classifier reached the AUC of 0.85 using PSI-related features (accuracy = 85.29%, p < 0.001), which was higher than using CT-based features (AUC = 0.67, accuracy = 75.21%, p < 0.001). If combined, the integrated model showed a slightly higher AUC of 0.86 (accuracy = 86.13%, p < 0.001). Oxygen saturation, IL-6, and CT infiltration showed great importance in both predicting severity and outcome. Conclusion Our study provided a comprehensive analysis and comparison between baseline chest CT and clinical assessment in disease severity and outcome prediction in Omicron pneumonia. The predictive model accurately predicts the severity and outcome of Omicron infection. Oxygen saturation, IL-6, and infiltration in chest CT were found to be important biomarkers. This approach has the potential to provide frontline physicians with an objective tool to manage Omicron patients more effectively in time-sensitive, stressful, and potentially resource-constrained environments.
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Affiliation(s)
- Jingjing Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zhengye Cao
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chunqin Miao
- Party and Hospital Administration Office, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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14
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Navas-Otero A, Calvache-Mateo A, Martín-Núñez J, Calles-Plata I, Ortiz-Rubio A, Valenza MC, López LL. Characteristics of Frailty in Perimenopausal Women with Long COVID-19. Healthcare (Basel) 2023; 11:healthcare11101468. [PMID: 37239754 DOI: 10.3390/healthcare11101468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 05/12/2023] [Accepted: 05/15/2023] [Indexed: 05/28/2023] Open
Abstract
The aim of this study was to compare the prevalence of risk factors for frailty between perimenopausal women with long COVID-19 syndrome, women having successfully recovered from COVID-19, and controls from the community. Women with a diagnosis of long COVID-19 and at least one symptom related to the perimenopausal period, women who had successfully recovered from COVID-19, and healthy women of comparable age were included in this study. Symptom severity and functional disability were assessed with the COVID-19 Yorkshire Rehabilitation Scale, and the presence of frailty was evaluated considering the Fried criteria. A total of 195 women were included in the study, distributed over the three groups. The long COVID-19 group showed a higher prevalence of perimenopausal symptoms and impact of COVID-19. Statistically significant differences were found between the long COVID-19 group and the other two groups for the frailty variables. When studying the associations between frailty variables and COVID-19 symptom impact, significant positive correlations were found. Perimenopausal women with long COVID-19 syndrome present more frailty-related factors and experience a higher range of debilitating ongoing symptoms. A significant relationship is shown to exist between long COVID-19 syndrome-related disability and symptoms and frailty variables, resulting in an increased chance of presenting disability.
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Affiliation(s)
- Alba Navas-Otero
- Physical Therapy Department, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Andrés Calvache-Mateo
- Physical Therapy Department, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Javier Martín-Núñez
- Physical Therapy Department, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Irene Calles-Plata
- Physical Therapy Department, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Araceli Ortiz-Rubio
- Physical Therapy Department, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Marie Carmen Valenza
- Physical Therapy Department, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
| | - Laura López López
- Physical Therapy Department, Faculty of Health Sciences, University of Granada, 18016 Granada, Spain
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15
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Desta BN, Ota S, Gournis E, Pires SM, Greer AL, Dodd W, Majowicz SE. Estimating the Under-ascertainment of COVID-19 cases in Toronto, Ontario, March to May 2020. J Public Health Res 2023; 12:22799036231174133. [PMID: 37197719 PMCID: PMC10184215 DOI: 10.1177/22799036231174133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 04/16/2023] [Indexed: 05/19/2023] Open
Abstract
Background Public health surveillance data do not always capture all cases, due in part to test availability and health care seeking behaviour. Our study aimed to estimate under-ascertainment multipliers for each step in the reporting chain for COVID-19 in Toronto, Canada. Design and methods We applied stochastic modeling to estimate these proportions for the period from March 2020 (the beginning of the pandemic) through to May 23, 2020, and for three distinct windows with different laboratory testing criteria within this period. Results For each laboratory-confirmed symptomatic case reported to Toronto Public Health during the entire period, the estimated number of COVID-19 infections in the community was 18 (5th and 95th percentile: 12, 29). The factor most associated with under-reporting was the proportion of those who sought care that received a test. Conclusions Public health officials should use improved estimates to better understand the burden of COVID-19 and other similar infections.
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Affiliation(s)
- Binyam N Desta
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada
- Binyam N Desta, School of Public Health Sciences, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada.
| | - Sylvia Ota
- Toronto Public Health, Toronto, ON, Canada
| | | | - Sara M Pires
- Risk-Benefit Research Group, Technical University of Denmark, Lyngby, Denmark
| | - Amy L Greer
- Department of Population Medicine, University of Guelph, Guelph, ON, Canada
| | - Warren Dodd
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Shannon E Majowicz
- School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada
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16
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Rajaram-Gilkes M, Shariff H, Adamski N, Costan S, Taglieri M, Loukas M, Tubbs RS. A Review of Crucial Radiological Investigations in the Management of COVID-19 Cases. Cureus 2023; 15:e36825. [PMID: 37123693 PMCID: PMC10139823 DOI: 10.7759/cureus.36825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/28/2023] [Indexed: 03/30/2023] Open
Abstract
Chest X-ray, chest CT, and lung ultrasound are the most common radiological interventions used in the diagnosis and management of coronavirus disease 2019 (COVID-19) patients. The purpose of this literature review, which was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, is to determine which radiological investigation is crucial for that purpose. PubMed, Medline, American Journal of Radiology (AJR), Public Library of Science (PLOS), Elsevier, National Center for Biotechnology Information (NCBI), and ScienceDirect were explored. Seventy-two articles were reviewed for potential inclusion, including 50 discussing chest CT, 15 discussing chest X-ray, five discussing lung ultrasound, and two discussing COVID-19 epidemiology. The reported sensitivities and specificities for chest CT ranged from 64 to 98% and 25 to 88%, respectively. The reported sensitivities and specificities for chest X-rays ranged from 33 to 89% and 11.1 to 88.9%, respectively. The reported sensitivities and specificities for lung ultrasound ranged from 93 to 96.8% and 21.3 to 95%, respectively. The most common findings on chest CT include ground glass opacities and consolidation. The most common findings on chest X-rays include opacities, consolidation, and pleural effusion. The data indicate that chest CT is the most effective radiological tool for the diagnosis and management of COVID-19 patients. The authors support the continued use of reverse transcription polymerase chain reaction (RT-PCR), along with physical examination and contact history, for such diagnosis. Chest CT could be more appropriate in emergency situations when quick triage of patients is necessary before RT-PCR results are available. CT can also be used to visualize the progression of COVID-19 pneumonia and to identify potential false positive RT-PCR results. Chest X-ray and lung ultrasound are acceptable in situations where chest CT is unavailable or contraindicated.
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Affiliation(s)
| | - Hamzah Shariff
- Medical Education, Geisinger Commonwealth School of Medicine, Scranton, USA
| | - Nevin Adamski
- Medical Education, Geisinger Commonwealth School of Medicine, Scranton, USA
| | - Sophia Costan
- Medical Education, Geisinger Commonwealth School of Medicine, Scranton, USA
| | - Marybeth Taglieri
- Medical Education, Geisinger Commonwealth School of Medicine, Scranton, USA
| | - Marios Loukas
- Anatomical Sciences, St. George's University, St. George, GRD
| | - R Shane Tubbs
- Anatomical Sciences, St. George's University, St. George, GRD
- Neurosurgery/Structural & Cellular Biology, Tulane University School of Medicine, New Orleans, USA
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17
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Uclés J, Cuesta E, Rigual R, Rodríguez-Pardo J, Ruiz-Ares G, Navía P, Fernández-Prieto A, Álvarez-Muelas A, de Leciñana MA, Fuentes B. Neck CT angiography in acute stroke: An open window for fast detection of COVID-19 lung involvement? Applicability in telemedicine. PLoS One 2023; 18:e0281955. [PMID: 36827270 PMCID: PMC9955938 DOI: 10.1371/journal.pone.0281955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 02/03/2023] [Indexed: 02/25/2023] Open
Abstract
BACKGROUND Chest CT has been proposed as a screening test to rule out SARS-CoV-2 lung infection in acute stroke. Our objectives are to analyze the predictive value of neck CT angiography (CTA) source images compared with conventional chest CT, the interobserver concordance and the reliability of the diagnosis using a mobile app. METHODS A retrospective observational study that included acute stroke patients admitted to a stroke center. Two raters blinded to the clinical data evaluated and classified the pulmonary findings in chest CT and neck CTA source images according to the COVID-19 Reporting and Data System (CO-RADS). CTA findings were evaluated using a conventional workstation and the JOIN mobile app. Scores of 3-5 were grouped as appearing typical or indeterminate for COVID-19 lung involvement and 0-2 as appearing atypical or negative for pneumonia. SARS-CoV-2 infection was confirmed by polymerase chain reaction (PCR). RESULTS A total of 242 patients were included (42 with PCR-confirmed COVID-19). In the cohort of 43 patients with both neck CTA and chest CT, the predictive value for COVID-19 was equivalent (sensitivity, 53.8%; specificity, 92.9%). The interobserver agreement in the classification into CO-RADS 3-5 or 1-2 in CTA was good (K = 0.694; standard error, 0.107). In the cohort of 242 patients with neck CTA, the intraobserver agreement between the workstation and the JOIN app was perfect (K = 1.000; standard error 0.000). CONCLUSIONS Neck CTA enables the accurate identification of COVID-19-associated lung abnormalities in acute stroke. CO-RADS evaluations through mobile applications have a predictive value similar to the usual platforms.
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Affiliation(s)
- Jorge Uclés
- Department of Neurology and Stroke Center, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - Emilio Cuesta
- Department of Radiology, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - Ricardo Rigual
- Department of Neurology and Stroke Center, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - Jorge Rodríguez-Pardo
- Department of Neurology and Stroke Center, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - Gerardo Ruiz-Ares
- Department of Neurology and Stroke Center, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - Pedro Navía
- Department of Radiology, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - Andrés Fernández-Prieto
- Department of Radiology, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - Alberto Álvarez-Muelas
- Department of Radiology, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
| | - María Alonso de Leciñana
- Department of Neurology and Stroke Center, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
- * E-mail: (BF); (MAL)
| | - Blanca Fuentes
- Department of Neurology and Stroke Center, Hospital La Paz Institute for Health Research-IdiPAZ (La Paz University Hospital-Universidad Autónoma de Madrid), Madrid, Spain
- * E-mail: (BF); (MAL)
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18
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Nasoufidou A, Kavelidou M, Griva T, Melikidou E, Maskalidis C, Machaira K, Nikolaidou B. Total severity score and age predict long-term hospitalization in COVID-19 pneumonia. Front Med (Lausanne) 2023; 10:1103701. [PMID: 37153106 PMCID: PMC10157639 DOI: 10.3389/fmed.2023.1103701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 03/14/2023] [Indexed: 05/09/2023] Open
Abstract
Background Severe COVID-19 pneumonia implies increased oxygen demands and length of hospitalization (LOS). We aimed to assess a possible correlation between LOS and COVID-19 patients' clinical laboratory data of admission, including the total severity score (TSS) from chest computed tomography (CT). Methods Data were assessed retrospectively at the General Hospital "Agios Pavlos" in Greece. Clinical laboratory data, TSS, and LOS were recorded. Results A total of 317 patients, 136 women and 181 men, with a mean age of 66.58 ± 16.02 years were studied. Significant comorbidities were hypertension (56.5%), dyslipidemia (33.8%), type 2 diabetes mellitus (22.7%), coronary heart disease (12.9%), underlying pulmonary disease (10.1%), and malignancy (4.4%). Inpatient time was related to age (p < 0.001), TSS (p < 0.001), time from symptom onset to hospitalization (p = 0.006), inhaled oxygen fraction (p < 0.001), fibrinogen (p = 0.024), d-dimers (p < 0.001), and C-reactive protein (p = 0.025), as well as a history of hypertension (p < 0.001) and type 2 diabetes mellitus (p < 0.008). The multivariate analysis showed a significant association of the LOS with age (p < 0.001) and TSS (p < 0.001) independent of the above-mentioned factors. Conclusion Early identification of disease severity using the TSS and patients' age could be useful for inpatient resource allocation and for maintaining vigilance for those requiring long-term hospitalizations.
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Affiliation(s)
- Athina Nasoufidou
- Internal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece
| | | | - Theodora Griva
- Internal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece
| | - Eleni Melikidou
- Radiology Department, General Hospital Agios Pavlos, Thessaloniki, Greece
| | | | - Konstantina Machaira
- Internal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece
| | - Barbara Nikolaidou
- Internal Medicine Department, General Hospital Agios Pavlos, Thessaloniki, Greece
- *Correspondence: Barbara Nikolaidou
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19
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Zhang YF, Zhao Q. Comparison of Chest CT and RT-PCR Assay for Indication of Disease Course of Coronavirus Disease 2019 (COVID-19) Pneumonia. Curr Med Imaging 2022; 18:1462-1469. [PMID: 35579141 DOI: 10.2174/1573405618666220509115914] [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: 10/12/2021] [Revised: 02/06/2022] [Accepted: 02/21/2022] [Indexed: 01/25/2023]
Abstract
BACKGROUND COVID-19 patients' courses vary in length, indicating a variable prognosis. The disease duration revealed by different examination methods may differ. OBJECTIVE The study aims to compare the differences in the disease course of patients with COVID-19 by chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) assay and explore the factors that affect the course of the illness. METHODS 106 patients confirmed with COVID-19 were enrolled and divided into two groups (age <60 years and age ≥60 years). The clinical characteristics of the two groups were analyzed. The intervals from symptoms onset to initial positive time point (ISIP), symptoms onset to the initial negative time point (ISIN), and initial positive to initial negative time point (IIPN) indicated by chest CT and RTPCR assay were analyzed. Multiple regression analysis was performed to assess the correlations between independent factors and the intervals. RESULTS Chest CT showed an earlier positive time point, a later negative time point, and a longer disease duration than the RT-PCR assay (P<.001, respectively). Older patients over 60 years old showed a later negative time point and a longer disease duration by chest CT than younger patients (P<.01 vs. P<.05, respectively). The CT score and clinical grades of older patients were greater than those of younger patients (P<.001, respectively). Age and clinical grades were significantly correlated with the disease course shown by chest CT (P<.05, respectively), and CT score was positively correlated with the illness course shown by chest CT and RT-PCR assay (P<.01, respectively). CONCLUSION The disease course revealed by chest CT and RT-PCR assay was asynchronous. Chest CT showed a 17-day longer period compared to the RT-PCR assay. Older patients had a longer duration than younger ones. A prolonged course is predicted by increasing age, CT score, and clinical grades.
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Affiliation(s)
- Yi-Fan Zhang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, P.R. China.,Hubei Province Key Laboratory of Molecular Imaging, Wuhan 430022, P.R. China
| | - Qiong Zhao
- Department of Ultrasonography, the Fifth Hospital in Wuhan, 430050, P.R. China
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Sun CY, Feng JY, Huang JR, Shen HC, Chen YM, Chen WC, Yang KY. Clinical Outcomes and Prolonged SARS-CoV-2 Viral Shedding in ICU Patients with Severe COVID-19 Infection and Nosocomial Bacterial Pneumonia: A Retrospective Cohort Study. J Clin Med 2022; 11:jcm11226796. [PMID: 36431273 PMCID: PMC9693095 DOI: 10.3390/jcm11226796] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 11/13/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES This study explored the clinical outcomes and association of prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shedding in patients with severe coronavirus disease 2019 (COVID-19) infection who developed nosocomial pneumonia. METHODS This was a retrospective study conducted in a medical center in Taiwan. From May to September 2021, patients from four intensive care units were enrolled after SARS-CoV-2 was confirmed through quantitative polymerase chain reaction and all cases were compatible with the definitions of severe COVID-19 infection. Baseline characteristics, disease severity, clinical outcomes, and times of viral shedding were recorded. RESULTS A total of 72 patients were diagnosed as having severe COVID-19 infection and 30 developed nosocomial pneumonia, comprising hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP). The patients with severe COVID-19 infection and concomitant HAP/VAP had longer intensive care unit (ICU) stays and fewer ventilator-free days at Day 28. An independent risk factor for nosocomial pneumonia was a greater SOFA score at admission. Furthermore, the patients with severe COVID-19 infection who developed HAP/VAP had a significantly longer duration of SARS-CoV-2 shedding (19.50 days vs. 15.00 days, p = 0.006). CONCLUSIONS Patients with severe COVID-19 infection who developed nosocomial pneumonia had longer SARS-CoV-2 shedding days, more complications, and worse outcomes.
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Affiliation(s)
- Chuan-Yen Sun
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
| | - Jia-Yih Feng
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Jhong-Ru Huang
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
| | - Hisao-Chin Shen
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
| | - Yuh-Min Chen
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Wei-Chih Chen
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- Institute of Emergency and Critical Care Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
| | - Kuang-Yao Yang
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- Institute of Emergency and Critical Care Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
- Cancer Progression Research Center, National Yang Ming Chiao Tung University, Taipei 11221, Taiwan
- Correspondence: ; Tel.: +886-2-28757455; Fax: +886-2-28757610
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21
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Baldanti F, Ganguly NK, Wang G, Möckel M, O’Neill LA, Renz H, dos Santos Ferreira CE, Tateda K, Van Der Pol B. Choice of SARS-CoV-2 diagnostic test: challenges and key considerations for the future. Crit Rev Clin Lab Sci 2022; 59:445-459. [PMID: 35289222 PMCID: PMC8935452 DOI: 10.1080/10408363.2022.2045250] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 12/15/2021] [Accepted: 02/18/2022] [Indexed: 01/27/2023]
Abstract
A plethora of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic tests are available, each with different performance specifications, detection methods, and targets. This narrative review aims to summarize the diagnostic technologies available and how they are best selected to tackle SARS-CoV-2 infection as the pandemic evolves. Seven key settings have been identified where diagnostic tests are being deployed: symptomatic individuals presenting for diagnostic testing and/or treatment of COVID-19 symptoms; asymptomatic individuals accessing healthcare for planned non-COVID-19-related reasons; patients needing to access emergency care (symptom status unknown); patients being discharged from healthcare following hospitalization for COVID-19; healthy individuals in both single event settings (e.g. airports, restaurants, hotels, concerts, and sporting events) and repeat access settings (e.g. workplaces, schools, and universities); and vaccinated individuals. While molecular diagnostics remain central to SARS-CoV-2 testing strategies, we have offered some discussion on the considerations for when other tools and technologies may be useful, when centralized/point-of-care testing is appropriate, and how the various additional diagnostics can be deployed in differently resourced settings. As the pandemic evolves, molecular testing remains important for definitive diagnosis, but increasingly widespread point-of-care testing is essential to the re-opening of society.
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Affiliation(s)
- Fausto Baldanti
- Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy
| | | | - Guiqiang Wang
- The Center for Liver Diseases, Peking University First Hospital, Beijing, China
| | | | - Luke A. O’Neill
- Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Harald Renz
- Institute of Laboratory Medicine and Pathobiochemistry, Molecular Diagnostics, Philipps University Marburg, University Hospital Giessen and Marburg GmbH, Giessen, Germany
- Department of Clinical Immunology and Allergology, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | | | - Kazuhiro Tateda
- Department of Microbiology and Infectious Diseases, Toho University School of Medicine, Tokyo, Japan
| | - Barbara Van Der Pol
- Department of Medicine, Division of Infectious Diseases, University of Alabama at Birmingham, Birmingham, AL, USA
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22
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Ji D, Guo M, Wu Y, Liu W, Luo S, Wang X, Kang H, Chen Y, Dai C, Kong D, Ma H, Liu Y, Wei D. Electrochemical Detection of a Few Copies of Unamplified SARS-CoV-2 Nucleic Acids by a Self-Actuated Molecular System. J Am Chem Soc 2022; 144:13526-13537. [PMID: 35858825 PMCID: PMC9344789 DOI: 10.1021/jacs.2c02884] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Indexed: 12/14/2022]
Abstract
The existing electrochemical biosensors lack controllable and intelligent merit to modulate the sensing process upon external stimulus, leading to challenges in analyzing a few copies of biomarkers in unamplified samples. Here, we present a self-actuated molecular-electrochemical system that consists of a tentacle and a trunk modification on a graphene microelectrode. The tentacle that contains a probe and an electrochemical label keeps an upright orientation, which increases recognition efficiency while decreasing the pseudosignal. Once the nucleic acids are recognized, the tentacles nearby along with the labels are spontaneously actuated downward, generating electrochemical responses under square wave voltammetry. Thus, it detects unamplified SARS-CoV-2 RNAs within 1 min down to 4 copies in 80 μL, 2-6 orders of magnitude lower than those of other electrochemical assays. Double-blind testing and 10-in-1 pooled testing of nasopharyngeal samples yield high overall agreement with reverse transcription-polymerase chain reaction results. We fabricate a portable prototype based on this system, showing great potential for future applications.
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Affiliation(s)
- Daizong Ji
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Mingquan Guo
- Shanghai
Public Health Clinical Center, Fudan University, Shanghai 201508, China
| | - Yungen Wu
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Wentao Liu
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Shi Luo
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Xuejun Wang
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Hua Kang
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Yiheng Chen
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Changhao Dai
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Derong Kong
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Hongwenjie Ma
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
| | - Yunqi Liu
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
- Institute
of Chemistry, Chinese Academy of Science, Beijing 100190, China
| | - Dacheng Wei
- State
Key Laboratory of Molecular Engineering of Polymers, Department of
Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory
of Molecular Materials and Devices, Fudan
University, Shanghai 200433, China
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23
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Sharma A, Mishra PK. Image enhancement techniques on deep learning approaches for automated diagnosis of COVID-19 features using CXR images. MULTIMEDIA TOOLS AND APPLICATIONS 2022; 81:42649-42690. [PMID: 35938148 PMCID: PMC9340712 DOI: 10.1007/s11042-022-13486-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 09/16/2021] [Accepted: 07/13/2022] [Indexed: 06/15/2023]
Abstract
The outbreak of novel coronavirus (COVID-19) disease has infected more than 135.6 million people globally. For its early diagnosis, researchers consider chest X-ray examinations as a standard screening technique in addition to RT-PCR test. Majority of research work till date focused only on application of deep learning approaches that is relevant but lacking in better pre-processing of CXR images. Towards this direction, this study aims to explore cumulative effects of image denoising and enhancement approaches on the performance of deep learning approaches. Regarding pre-processing, suitable methods for X-ray images, Histogram equalization, CLAHE and gamma correction have been tested individually and along with adaptive median filter, median filter, total variation filter and gaussian denoising filters. Proposed study compared eleven combinations in exploration of most coherent approach in greedy manner. For more robust analysis, we compared ten CNN architectures for performance evaluation with and without enhancement approaches. These models are InceptionV3, InceptionResNetV2, MobileNet, MobileNetV2, Vgg19, NASNetMobile, ResNet101, DenseNet121, DenseNet169, DenseNet201. These models are trained in 4-way (COVID-19 pneumonia vs Viral vs Bacterial pneumonia vs Normal) and 3-way classification scenario (COVID-19 vs Pneumonia vs Normal) on two benchmark datasets. The proposed methodology determines with TVF + Gamma, models achieve higher classification accuracy and sensitivity. In 4-way classification MobileNet with TVF + Gamma achieves top accuracy of 93.25% with 1.91% improvement in accuracy score, COVID-19 sensitivity of 98.72% and F1-score of 92.14%. In 3-way classification our DenseNet201 with TVF + Gamma gains accuracy of 91.10% with improvement of 1.47%, COVID-19 sensitivity of 100% and F1-score of 91.09%. Proposed study concludes that deep learning modes with gamma correction and TVF + Gamma has superior performance compared to state-of-the-art models. This not only minimizes overlapping between COVID-19 and virus pneumonia but advantageous in time required to converge best possible results.
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Affiliation(s)
- Ajay Sharma
- Department of Computer Science, Institute of Science, Banaras Hindu University, Varanasi, 221005 India
| | - Pramod Kumar Mishra
- Department of Computer Science, Institute of Science, Banaras Hindu University, Varanasi, 221005 India
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24
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Evaluation and Clinical Validation of Guanidine-Based Inactivation Transport Medium for Preservation of SARS-CoV-2. Adv Pharmacol Pharm Sci 2022; 2022:1677621. [PMID: 35873075 PMCID: PMC9301760 DOI: 10.1155/2022/1677621] [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: 02/09/2022] [Revised: 06/02/2022] [Accepted: 06/10/2022] [Indexed: 12/02/2022] Open
Abstract
WHO declared the outbreak of COVID-19, caused by SARS-CoV-2, a pandemic in March 2020. More than 223 million cases and approximately 4.6 million deaths have been confirmed. Early diagnosis and immediate treatment became a priority during this pandemic. However, COVID-19 diagnostic testing resources are limited, especially early in the pandemic. Apart from being limited, the COVID-19 diagnostic tests using reverse transcription polymerase chain reaction (RT-PCR) have encountered storage, transportation, and safety issues. These problems are mainly experienced by developing poor countries, countries in the equatorial region, and archipelagic countries. VITPAD® is a guanidine-based inactivation transport medium (ITM) formulated to maintain the RNA quality of SARS-CoV-2 during transportation without cold chains. This study, conducted from September 2020 to March 2021, performed clinical validation of VITPAD® by comparing its performance with a globally commercially available ITM from the NEST brand. Its stability at room temperature, safety, and resistance at high temperatures was also tested using RT-PCR analysis. VITPAD® can reduce the infectious nature of the specimen, preserve the SARS-CoV-2 for 18 days at an ambient temperature, and resist high temperatures (40°C for 3 hours). A guanidine-based transport medium, such as VITPAD®, is compatible and recommended for RT-PCR-based molecular diagnosis of COVID-19.
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25
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Hamidi-Asl E, Heidari-Khoshkelat L, Bakhsh Raoof J, Richard TP, Farhad S, Ghani M. A review on the recent achievements on coronaviruses recognition using electrochemical detection methods. Microchem J 2022; 178:107322. [PMID: 35233118 PMCID: PMC8875855 DOI: 10.1016/j.microc.2022.107322] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 12/14/2022]
Abstract
Various coronaviruses, which cause a wide range of human and animal diseases, have emerged in the past 50 years. This may be due to their abilities to recombine, mutate, and infect multiple species and cell types. A novel coronavirus, which is a family of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), has been termed COVID-19 by the World Health Organization (WHO). COVID-19 is the strain that has not been previously identified in humans. The early identification and diagnosis of the virus is crucial for effective pandemic prevention. In this study, we review shortly various diagnostic methods for virus assay and focus on recent advances in electrochemical biosensors for COVID-19 detection.
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Affiliation(s)
- Ezat Hamidi-Asl
- Advanced Energy & Manufacturing Lab, Department of Mechanical Engineering, University of Akron, Akron, OH 44325, USA
| | - Leyla Heidari-Khoshkelat
- Eletroanalytical Chemistry Research Laboratory, Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran
| | - Jahan Bakhsh Raoof
- Eletroanalytical Chemistry Research Laboratory, Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran
| | - Tara P Richard
- Department of Biological Science, Southeastern Louisiana University, Hammond, LA 70402, USA
| | - Siamak Farhad
- Advanced Energy & Manufacturing Lab, Department of Mechanical Engineering, University of Akron, Akron, OH 44325, USA
| | - Milad Ghani
- Department of Analytical Chemistry, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran
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26
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Dutta D, Naiyer S, Mansuri S, Soni N, Singh V, Bhat KH, Singh N, Arora G, Mansuri MS. COVID-19 Diagnosis: A Comprehensive Review of the RT-qPCR Method for Detection of SARS-CoV-2. Diagnostics (Basel) 2022; 12:diagnostics12061503. [PMID: 35741313 PMCID: PMC9221722 DOI: 10.3390/diagnostics12061503] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 06/15/2022] [Accepted: 06/17/2022] [Indexed: 12/15/2022] Open
Abstract
The world is grappling with the coronavirus disease 2019 (COVID-19) pandemic, the causative agent of which is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 symptoms are similar to the common cold, including fever, sore throat, cough, muscle and chest pain, brain fog, dyspnoea, anosmia, ageusia, and headache. The manifestation of the disease can vary from being asymptomatic to severe life-threatening conditions warranting hospitalization and ventilation support. Furthermore, the emergence of mutecated variants of concern (VOCs) is paramount to the devastating effect of the pandemic. This highly contagious virus and its emergent variants challenge the available advanced viral diagnostic methods for high-accuracy testing with faster result yields. This review is to shed light on the natural history, pathology, molecular biology, and efficient diagnostic methods of COVID-19, detecting SARS-CoV-2 in collected samples. We reviewed the gold standard RT-qPCR method for COVID-19 diagnosis to confer a better understanding and application to combat the COVID-19 pandemic. This comprehensive review may further develop awareness about the management of the COVID-19 pandemic.
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Affiliation(s)
- Debashis Dutta
- Department of Pharmacology and Experimental Neuroscience, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
- Correspondence: (D.D.); (M.S.M.)
| | - Sarah Naiyer
- Department of Microbiology and Immunology, University of Illinois at Chicago, Chicago, IL 60616, USA;
| | | | - Neeraj Soni
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Vandana Singh
- Department of Pathology and Microbiology, College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA;
| | - Khalid Hussain Bhat
- SKUAST Kashmir, Division of Basic Science and Humanities, Faculty of Agriculture, Wadura Sopore 193201, JK, India;
| | - Nishant Singh
- Cell and Gene Therapy Absorption System, Exton, PA 19335, USA;
| | - Gunjan Arora
- Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT 06520, USA;
| | - M. Shahid Mansuri
- Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA
- Correspondence: (D.D.); (M.S.M.)
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27
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Colak A, Oncel D, Altın Z, Turken M, Arslan FD, Iyilikci V, Yilmaz N, Oncel G, Kose S. Usefulness of laboratory parameters and chest CT in the early diagnosis of COVID-19. Rev Inst Med Trop Sao Paulo 2022; 64:e28. [PMID: 35384959 PMCID: PMC8993152 DOI: 10.1590/s1678-9946202264028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 02/07/2022] [Indexed: 12/15/2022] Open
Abstract
In the present study, the importance of laboratory parameters and CT findings in the early diagnosis of COVID-19 was investigated. To this end, 245 patients admitted between April 1st, and May 30th, 2020 with suspected COVID-19 were enrolled. The patients were divided into three groups according to chest CT findings and RT-PCR results. The non-COVID-19 group consisted of 71 patients with negative RT-PCR results and no chest CT findings. Ninety-five patients with positive RT-PCR results and negativechest CT findings were included in the COVID-19 group; 79 patients with positive RT-PCR results and chest CT findings consistent with COVID-19 manifestations were included in COVID-19 pneumonia group. Chest CT findings were positive in 45% of all COVID-19 patients. Patients with positive chest CT findings had mild (n=30), moderate (n=21) andor severe (n=28) lung involvement. In the COVID-19 group, CRP levels and the percentage of monocytes increased significantly. As disease progressed from mild to severe, CRP, LDH and ferritin levels gradually increased. In the ROC analysis, the area under the curve corresponding to the percentage value of monocytes (AUC=0.887) had a very good accuracy in predicting COVID-19 cases. The multinomial logistic regression analysis showed that CRP, LYM and % MONO were independent factors for COVID-19. Furthermore, the chest CT evaluation is a relevant tool in patients with clinical suspicion of COVID-19 pneumonia and negative RT-PCR results. In addition to decreased lymphocyte count, the increased percentage of monocytes may also guide the diagnosis.
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Affiliation(s)
- Ayfer Colak
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Medical Biochemistry, Izmir, Turkey
| | - Dilek Oncel
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Radiology, Izmir, Turkey
| | - Zeynep Altın
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Internal Medicine, Izmir, Turkey
| | - Melda Turken
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey
| | - Fatma Demet Arslan
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Medical Biochemistry, Izmir, Turkey
| | - Veli Iyilikci
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Medical Biochemistry, Izmir, Turkey
| | - Nisel Yilmaz
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Medical Microbiology, Izmir, Turkey
| | - Guray Oncel
- Bakircay University, Cigli Training and Research Hospital, Department of Radiology, Izmir, Turkey
| | - Sukran Kose
- University of Health Sciences, Tepecik Training and Research Hospital, Department of Infectious Diseases and Clinical Microbiology, Izmir, Turkey
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28
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EDNC: Ensemble Deep Neural Network for COVID-19 Recognition. Tomography 2022; 8:869-890. [PMID: 35314648 PMCID: PMC8938826 DOI: 10.3390/tomography8020071] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/15/2022] [Accepted: 03/16/2022] [Indexed: 12/24/2022] Open
Abstract
The automatic recognition of COVID-19 diseases is critical in the present pandemic since it relieves healthcare staff of the burden of screening for infection with COVID-19. Previous studies have proven that deep learning algorithms can be utilized to aid in the diagnosis of patients with potential COVID-19 infection. However, the accuracy of current COVID-19 recognition models is relatively low. Motivated by this fact, we propose three deep learning architectures, F-EDNC, FC-EDNC, and O-EDNC, to quickly and accurately detect COVID-19 infections from chest computed tomography (CT) images. Sixteen deep learning neural networks have been modified and trained to recognize COVID-19 patients using transfer learning and 2458 CT chest images. The proposed EDNC has then been developed using three of sixteen modified pre-trained models to improve the performance of COVID-19 recognition. The results suggested that the F-EDNC method significantly enhanced the recognition of COVID-19 infections with 97.75% accuracy, followed by FC-EDNC and O-EDNC (97.55% and 96.12%, respectively), which is superior to most of the current COVID-19 recognition models. Furthermore, a localhost web application has been built that enables users to easily upload their chest CT scans and obtain their COVID-19 results automatically. This accurate, fast, and automatic COVID-19 recognition system will relieve the stress of medical professionals for screening COVID-19 infections.
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29
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Comparison of CO-RADS Scores Based on Visual and Artificial Intelligence Assessments in a Non-Endemic Area. Diagnostics (Basel) 2022; 12:diagnostics12030738. [PMID: 35328290 PMCID: PMC8946998 DOI: 10.3390/diagnostics12030738] [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: 01/26/2022] [Revised: 03/08/2022] [Accepted: 03/11/2022] [Indexed: 11/17/2022] Open
Abstract
In this study, we first developed an artificial intelligence (AI)-based algorithm for classifying chest computed tomography (CT) images using the coronavirus disease 2019 Reporting and Data System (CO-RADS). Subsequently, we evaluated its accuracy by comparing the calculated scores with those assigned by radiologists with varying levels of experience. This study included patients with suspected SARS-CoV-2 infection who underwent chest CT imaging between February and October 2020 in Japan, a non-endemic area. For each chest CT, the CO-RADS scores, determined by consensus among three experienced chest radiologists, were used as the gold standard. Images from 412 patients were used to train the model, whereas images from 83 patients were tested to obtain AI-based CO-RADS scores for each image. Six independent raters (one medical student, two residents, and three board-certified radiologists) evaluated the test images. Intraclass correlation coefficients (ICC) and weighted kappa values were calculated to determine the inter-rater agreement with the gold standard. The mean ICC and weighted kappa were 0.754 and 0.752 for the medical student and residents (taken together), 0.851 and 0.850 for the diagnostic radiologists, and 0.913 and 0.912 for AI, respectively. The CO-RADS scores calculated using our AI-based algorithm were comparable to those assigned by radiologists, indicating the accuracy and high reproducibility of our model. Our study findings would enable accurate reading, particularly in areas where radiologists are unavailable, and contribute to improvements in patient management and workflow.
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30
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BiebaÛ CM, Desmet JN, Dubbeldam A, Cockmartin L, Coudyzer WM, Coolen J, Verschakelen JA, De Wever W. Radiological findings in low-dose CT for COVID-19 pneumonia in 182 patients: Correlation of signs and severity with patient outcome. Medicine (Baltimore) 2022; 101:e28950. [PMID: 35244053 PMCID: PMC8896423 DOI: 10.1097/md.0000000000028950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 02/10/2022] [Indexed: 01/04/2023] Open
Abstract
To characterize computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) pneumonia and their value in outcome prediction.Chest CTs of 182 patients with a confirmed diagnosis of COVID-19 infection by real-time reverse transcription polymerase chain reaction were evaluated for the presence of CT-abnormalities and their frequency. Regarding the patient outcome each patient was categorized in 5 progressive stages and the duration of hospitalization was determined. Regression analysis was performed to find which CT findings are predictive for patient outcome and to assess prognostic factors for the hospitalization duration.Multivariate statistical analysis confirmed a higher age (OR = 1.023, P = .025), a higher total visual severity score (OR = 1.038, P = .002) and the presence of crazy paving (OR = 2.160, P = .034) as predictive parameters for patient outcome. A higher total visual severity score (+0.134 days; P = .012) and the presence of pleural effusion (+13.985 days, P = 0.005) were predictive parameters for a longer hospitalization duration. Moreover, a higher sensitivity of chest CT (false negatives 10.4%; true positives 78.6%) in comparison to real-time reverse transcription polymerase chain reaction was obtained.An increasing percentage of lung opacity as well as the presence of crazy paving and a higher age are associated with a worse patient outcome. The presence of a higher total visual severity score and pleural effusion are significant predictors for a longer hospitalization duration. These results are underscoring the value of chest CT as a diagnostic and prognostic tool in the pandemic outbreak of COVID-19, to facilitate fast detection and to preserve the limited (intensive) care capacity only for the most vulnerable patients.
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Affiliation(s)
| | - Jeroen N. Desmet
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Adriana Dubbeldam
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Lesley Cockmartin
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | | | - Johan Coolen
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | | | - Walter De Wever
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
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31
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Analysis of the Efficacy of Universal Screening of Coronavirus Disease with Antigen-Detecting Rapid Diagnostic Tests at Point-or-Care Settings and Sharing the Experience of Admission Protocol—A Pilot Study. J Pers Med 2022; 12:jpm12020319. [PMID: 35207807 PMCID: PMC8876277 DOI: 10.3390/jpm12020319] [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: 01/06/2022] [Revised: 02/01/2022] [Accepted: 02/18/2022] [Indexed: 11/17/2022] Open
Abstract
Aims: To introduce the admission protocol of a COVID-19 specialized hospital outlined by the government, including the assessment of reverse transcription polymerase chain reaction (RT-PCR), low dose chest computed tomography (CT) and antigen-detecting rapid diagnostic test (Ag-RDT) for patient screening. Materials and Methods: This was a retrospective cohort study of 646 patients who were admitted between December 2020, and February 2021, during the third wave of COVID-19 in Korea. Ag-RDT and RT-PCR were routinely performed on all patients who required admission, and low-dose chest CT was performed on high-risk patients with associated symptoms. Any patients with high-risk COVID-19 infection according to the Ag-RDT test were quarantined alone in a negative pressured room, and those with low-risk COVID-19 infection remained in the preemptive quarantine room with or without negative pressure. The diagnostic values of the Ag-RDT test and associated cycle threshold (Ct) values of the RT-PCR test were subsequently evaluated. Results: In terms of the diagnostic value, the Ag-RDT for COVID-19 had a sensitivity of 68.3%, specificity of 99.5%, positive predictive value (PPV) of 90.3%, and negative predictive value (NPV) of 97.9%. For the 355 symptomatic patients with low-dose chest CT, the diagnostic values of combined evaluations had a sensitivity of 90.2%, specificity of 99.0%, PPV of 86.1%, and NPV of 99.3%. The cut-off Ct value for positive Ag-RDT was ≤25.67 for the N gene (sensitivity: 89.3%, specificity: 100%), which was regarded as a high viable virus in cell culture. There were no patients or medical staff who had COVID-19 in the hospital. Conclusion: Appropriate patient care was possible by definitive triage of the area, according to the symptoms and using diagnostic tests. Screening protocols, including the Ag-RDT test and low-dose chest CT, could be helpful in emergency point-of-care settings.
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Whitehead HD, Lieberman M. Rapid, instrument-free colorimetric quantification of DNA using Nile Blue. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2022; 14:574-580. [PMID: 35050279 DOI: 10.1039/d1ay01598b] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The use of nucleic acid tests (NAT) for sensitive and rapid detection of pathogens relevant to human health has increased due to the ubiquity of nucleic acid amplification techniques such as polymerase chain reaction. The use of such tools for detection of amplified nucleic acid (NA) in field and clinical settings is limited by the need for complex instrumentation and trained users. To address these limitations we developed a rapid, robust, and instrument-free colorimetric detection method for nucleic acids using a visible region dye, Nile Blue (NB). NB is a cationic benzophenoxazine dye with well-known binding interactions with NA and has been used in instrumental methods for DNA quantification. When combined with dsDNA, the color of NB shifts from blue to purple. Images of this color shift are collected and are subjected to image analysis. Observed changes in the red and green colorimetric intensities are linked to the ratio of dsDNA to NB. By titrating solutions of dsDNA against a series of NB concentrations, we found it possible to quantitate dsDNA at concentrations ranging from 10-100 μg mL-1 using a k-means cluster analysis method. This range is comparable to that of NA concentrations quantified using gold-standard UV-Visible spectroscopy and to the concentrations of NA in biological samples after amplification. Unknown concentrations of dsDNA from yeast extracts were correctly identified within ±5 μg mL-1 of true concentration. Preliminary experiments demonstrate use of the developed NB method on paper-based analytical devices. As an instrument-free detection method, NB allows for rapid and robust quantification of dsDNA in field settings.
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Affiliation(s)
- Heather D Whitehead
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA.
| | - Marya Lieberman
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA.
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Mansour NA, Saleh AI, Badawy M, Ali HA. Accurate detection of Covid-19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy. JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2022; 13:41-73. [PMID: 33469467 PMCID: PMC7809685 DOI: 10.1007/s12652-020-02883-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 12/23/2020] [Indexed: 05/03/2023]
Abstract
The outbreak of Coronavirus (COVID-19) has spread between people around the world at a rapid rate so that the number of infected people and deaths is increasing quickly every day. Accordingly, it is a vital process to detect positive cases at an early stage for treatment and controlling the disease from spreading. Several medical tests had been applied for COVID-19 detection in certain injuries, but with limited efficiency. In this study, a new COVID-19 diagnosis strategy called Feature Correlated Naïve Bayes (FCNB) has been introduced. The FCNB consists of four phases, which are; Feature Selection Phase (FSP), Feature Clustering Phase (FCP), Master Feature Weighting Phase (MFWP), and Feature Correlated Naïve Bayes Phase (FCNBP). The FSP selects only the most effective features among the extracted features from laboratory tests for both COVID-19 patients and non-COVID-19 people by using the Genetic Algorithm as a wrapper method. The FCP constructs many clusters of features based on the selected features from FSP by using a novel clustering technique. These clusters of features are called Master Features (MFs) in which each MF contains a set of dependent features. The MFWP assigns a weight value to each MF by using a new weight calculation method. The FCNBP is used to classify patients based on the weighted Naïve Bayes algorithm with many modifications as the correlation between features. The proposed FCNB strategy has been compared to recent competitive techniques. Experimental results have proven the effectiveness of the FCNB strategy in which it outperforms recent competitive techniques because it achieves the maximum (99%) detection accuracy.
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Affiliation(s)
- Nehal A. Mansour
- Nile Higher Institute for Engineering and Technology, Mansoura, Egypt
| | - Ahmed I. Saleh
- Computers and Control Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt
| | - Mahmoud Badawy
- Computers and Control Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt
| | - Hesham A. Ali
- Computers and Control Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt
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Khashoo R, Vimalesvaran S, Tewari D, Khashu S, Khashu M. Indiscriminate use of CT Chest Imaging during the COVID-19 Pandemic. Clin Radiol 2022; 77:316-317. [PMID: 35181120 PMCID: PMC8801904 DOI: 10.1016/j.crad.2021.12.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 12/22/2021] [Indexed: 11/03/2022]
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Saini V, Kalra P, Sharma M, Rai C, Saini V, Gautam K, Bhattacharya S, Mani S, Saini K, Kumar S. A Cold Chain-Independent Specimen Collection and Transport Medium Improves Diagnostic Sensitivity and Minimizes Biosafety Challenges of COVID-19 Molecular Diagnosis. Microbiol Spectr 2021; 9:e0110821. [PMID: 34878310 PMCID: PMC8653843 DOI: 10.1128/spectrum.01108-21] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 10/21/2021] [Indexed: 01/10/2023] Open
Abstract
Equitable and timely access to COVID-19-related care has emerged as a major challenge, especially in developing and low-income countries. In India, ∼65% of the population lives in villages where infrastructural constraints limit the access to molecular diagnostics of COVID-19 infection. Especially, the requirement of a cold chain transport for sustained sample integrity and associated biosafety challenges pose major bottlenecks to the equitable access. Here, we developed an innovative clinical specimen collection medium, named SupraSens microbial transport medium (SSTM). SSTM allowed a cold chain-independent transport at a wide temperature range (15°C to 40°C) and directly inactivated SARS-CoV-2 (<15 min). Evaluation of SSTM compared to commercial viral transport medium (VTM) in field studies (n = 181 patients) highlighted that, for the samples from same patients, SSTM could capture more symptomatic (∼26.67%, 4/15) and asymptomatic (52.63%, 10/19) COVID-19 patients. Compared to VTM, SSTM yielded significantly lower quantitative PCR (qPCR) threshold cycle (Ct) values (mean ΔCt > -3.50), thereby improving diagnostic sensitivity of SSTM (18.79% [34/181]) versus that of VTM (11.05% [20/181]). Overall, SSTM had detection of COVID-19 patients 70% higher than that of VTM. Since the logistical and infrastructural constraints are not unique to India, our study highlights the invaluable global utility of SSTM as a key to accurately identify those infected and control COVID-19 transmission. Taken together, our data provide a strong justification to the adoption of SSTM for sample collection and transport during the pandemic. IMPORTANCE Approximately forty-four percent of the global population lives in villages, including 59% in Africa (https://unhabitat.org/World%20Cities%20Report%202020). The fast-evolving nature of SARS-CoV-2 and its extremely contagious nature warrant early and accurate COVID-19 diagnostics across rural and urban population as a key to prevent viral transmission. Unfortunately, lack of adequate infrastructure, including the availability of biosafety-compliant facilities and an end-to-end cold chain availability for COVID-19 molecular diagnosis, limits the accessibility of testing in these countries. Here, we fulfill this urgent unmet need by developing a sample collection and transport medium, SSTM, that does not require cold chain, neutralizes the virus quickly, and maintains the sample integrity at broad temperature range without compromising sensitivity. Further, we observed that use of SSTM in field studies during pandemic improved the diagnostic sensitivity, thereby establishing the feasibility of molecular testing even in the infrastructural constraints of remote, hilly, or rural communities in India and elsewhere.
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Affiliation(s)
- Vikram Saini
- Laboratory of Infection Biology and Translational Research, Department of Biotechnology, All India Institute of Medical Sciences, New Delhi, India
- Biosafety Laboratory-3, Centralized Core Research Facility (CCRF), All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Priya Kalra
- Laboratory of Infection Biology and Translational Research, Department of Biotechnology, All India Institute of Medical Sciences, New Delhi, India
| | - Manish Sharma
- Defence Institute of Physiology and Allied Sciences (DIPAS), Defence Research and Development Organization (DRDO), Ministry of Defense, Delhi, India
| | - Chhavi Rai
- Defence Institute of Physiology and Allied Sciences (DIPAS), Defence Research and Development Organization (DRDO), Ministry of Defense, Delhi, India
| | - Vikas Saini
- University College of Medical Sciences and Guru Teg Bahadur Hospital, New Delhi, India
| | - Kamini Gautam
- Laboratory of Infection Biology and Translational Research, Department of Biotechnology, All India Institute of Medical Sciences, New Delhi, India
| | - Sankar Bhattacharya
- Translational Health Science and Technology Institute (THSTI), Faridabad, Haryana, India
| | - Shailendra Mani
- Translational Health Science and Technology Institute (THSTI), Faridabad, Haryana, India
| | - Kanchan Saini
- Laboratory of Infection Biology and Translational Research, Department of Biotechnology, All India Institute of Medical Sciences, New Delhi, India
| | - Sunil Kumar
- Laboratory of Infection Biology and Translational Research, Department of Biotechnology, All India Institute of Medical Sciences, New Delhi, India
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Fu R, Du W, Jin X, Wang R, Lin X, Su Y, Yang H, Shan X, Lv W, Zheng Z, Huang G. Microfluidic Biosensor for Rapid Nucleic Acid Quantitation Based on Hyperspectral Interferometric Amplicon-Complex Analysis. ACS Sens 2021; 6:4057-4066. [PMID: 34694791 DOI: 10.1021/acssensors.1c01491] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Nucleic acid detection plays a vital role in both biomedical research and clinical medicine. The temperature circulation changes of the widely used polymerase chain reaction technique are time-consuming and technically challenging for system development. Recombinase polymerase amplification (RPA) is an isothermal method for rapid nucleic acid detection. However, current RPA amplicon detection methods are complicated and expensive and easily generate false positives, restricting the promotion of RPA techniques. In this work, a hyperspectral interferometric amplicon-complex quantitation method is presented, combined with asymmetric dipole complex strategy optical scattering analysis. GelRed dye was utilized to form amplicon-complex particles, and the Fourier domain spectrum computation contributed to complex scattering quantitation. With this method, a supporting microfluidic chip and automatic system were developed to achieve integrated, rapid, quantitative, and miniscule nucleic acid detection. The Plasmodium falciparum dhfr gene was utilized as an example for targeted nucleic acid quantitation and single nucleotide polymorphism detection. The total reaction time was decreased to merely 20 min, and the limit of detection was only 3.17 ng/μL. The minimum measurable concentration of target was 1.68 copies/μL, 31.67 times more sensitive than turbidity detection, and the single reaction chamber was only 9.33 μL. No scattering increase occurred for template-free control, and thus, false positives caused by primer dimers and nonspecific products could be avoided. The experimental results prove that the provided method and system can detect single-base mutations in the dhfr gene and is a reasonable technique for rapid, automatic, and low-cost nucleic acid detection.
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Affiliation(s)
- Rongxin Fu
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Wenli Du
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Xiangyu Jin
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Ruliang Wang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Xue Lin
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Ya Su
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Han Yang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Xiaohui Shan
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Wenqi Lv
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Zhi Zheng
- Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing 100730, China
| | - Guoliang Huang
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
- National Engineering Research Center for Beijing Biochip Technology, Beijing 102206, China
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Zhang C, Feng YG, Tam C, Wang N, Feng Y. Transcriptional Profiling and Machine Learning Unveil a Concordant Biosignature of Type I Interferon-Inducible Host Response Across Nasal Swab and Pulmonary Tissue for COVID-19 Diagnosis. Front Immunol 2021; 12:733171. [PMID: 34880855 PMCID: PMC8647662 DOI: 10.3389/fimmu.2021.733171] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/28/2021] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND COVID-19, caused by SARS-CoV-2 virus, is a global pandemic with high mortality and morbidity. Limited diagnostic methods hampered the infection control. Since the direct detection of virus mainly by RT-PCR may cause false-negative outcome, host response-dependent testing may serve as a complementary approach for improving COVID-19 diagnosis. OBJECTIVE Our study discovered a highly-preserved transcriptional profile of Type I interferon (IFN-I)-dependent genes for COVID-19 complementary diagnosis. METHODS Computational language R-dependent machine learning was adopted for mining highly-conserved transcriptional profile (RNA-sequencing) across heterogeneous samples infected by SARS-CoV-2 and other respiratory infections. The transcriptomics/high-throughput sequencing data were retrieved from NCBI-GEO datasets (GSE32155, GSE147507, GSE150316, GSE162835, GSE163151, GSE171668, GSE182569). Mathematical approaches for homological analysis were as follows: adjusted rand index-related similarity analysis, geometric and multi-dimensional data interpretation, UpsetR, t-distributed Stochastic Neighbor Embedding (t-SNE), and Weighted Gene Co-expression Network Analysis (WGCNA). Besides, Interferome Database was used for predicting the transcriptional factors possessing IFN-I promoter-binding sites to the key IFN-I genes for COVID-19 diagnosis. RESULTS In this study, we identified a highly-preserved gene module between SARS-CoV-2 infected nasal swab and postmortem lung tissue regulating IFN-I signaling for COVID-19 complementary diagnosis, in which the following 14 IFN-I-stimulated genes are highly-conserved, including BST2, IFIT1, IFIT2, IFIT3, IFITM1, ISG15, MX1, MX2, OAS1, OAS2, OAS3, OASL, RSAD2, and STAT1. The stratified severity of COVID-19 may also be identified by the transcriptional level of these 14 IFN-I genes. CONCLUSION Using transcriptional and computational analysis on RNA-seq data retrieved from NCBI-GEO, we identified a highly-preserved 14-gene transcriptional profile regulating IFN-I signaling in nasal swab and postmortem lung tissue infected by SARS-CoV-2. Such a conserved biosignature involved in IFN-I-related host response may be leveraged for COVID-19 diagnosis.
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Affiliation(s)
- Cheng Zhang
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Yi-Gang Feng
- Guanghua School of Stomatology, Hospital of Stomatology, Sun Yat-Sen University, Guangzhou, China
| | - Chiwing Tam
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Ning Wang
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Yibin Feng
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
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Ibisoglu E, Boyraz B. Comparison of ventricular repolarization parameters of Covid-19 patients diagnosed with chest CT and RT-PCR. Acta Cardiol 2021; 76:1013-1018. [PMID: 34254875 DOI: 10.1080/00015385.2021.1950366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
BACKGROUND AND OBJECTIVES The aim of the comparison is to evaluate the marker of ventricular repolarization parameters such as QT, QTc, cQT, Tp-e, Tp-e/QT, Tp-e/QTc, Tp-e/JT and Tp-e/JTc ratios and the risk of ventricular arrhtythmias in patients with newly diagnosed Covid-19. METHODS The study included 2 separate groups. The first one consisted of 96 positive reverse transcriptase polymerase chain reaction (RT-PCR) Covid-19 patients and the second one of 106 patients with negative PCR but positive chest computed tomography (CT) findings consistent with Covid-19. We measured QTmax, QTmin, QRS, JT and Tp-e intervals and estimated Tp-e/QT max, Tp- e/QTc max, Tp-e/JT and Tp-e/JTc rates and QTc max, QTc min, cQTd and JTc intervals. RESULTS QT max, QT min, JT, cQTd, Tp-e, Tp-e/QT max, Tp-e/QTc max, Tp-e/JT, Tp-e/JTc values were significantly higher in RT-PCR Covid-19 patient group. CONCLUSION Positive RT-PCR Covid-19 patients should be followed more closely, in terms of high ventricular repolarization parameters and preventing ventricular arrhythmias that may develop due to this.
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Affiliation(s)
- Ersin Ibisoglu
- Cardiology Department, Başakşehir Çam and Sakura City Hospital, İstanbul, Turkey
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Churruca M, Martínez-Besteiro E, Couñago F, Landete P. COVID-19 pneumonia: A review of typical radiological characteristics. World J Radiol 2021; 13:327-343. [PMID: 34786188 PMCID: PMC8567439 DOI: 10.4329/wjr.v13.i10.327] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/08/2021] [Accepted: 09/14/2021] [Indexed: 02/06/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19) was first discovered after unusual cases of severe pneumonia emerged by the end of 2019 in Wuhan (China) and was declared a global public health emergency by the World Health Organization in January 2020. The new pathogen responsible for the infection, genetically similar to the beta-coronavirus family, is known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), and the current gold standard diagnostic tool for its detection in respiratory samples is the reverse transcription-polymerase chain reaction test. Imaging findings on COVID-19 have been widely described in studies published throughout last year, 2020. In general, ground-glass opacities and consolidations, with a bilateral and peripheral distribution, are the most typical patterns found in COVID-19 pneumonia. Even though much of the literature focuses on chest computed tomography (CT) and X-ray imaging and their findings, other imaging modalities have also been useful in the assessment of COVID-19 patients. Lung ultrasonography is an emerging technique with a high sensitivity, and thus useful in the initial evaluation of SARS-CoV-2 infection. In addition, combined positron emission tomography-CT enables the identification of affected areas and follow-up treatment responses. This review intends to clarify the role of the imaging modalities available and identify the most common radiological manifestations of COVID-19.
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Affiliation(s)
- María Churruca
- Pulmonology Department, Hospital Universitario de La Princesa, Madrid 28006, Spain
| | | | - Felipe Couñago
- Department of Radiation Oncology, Hospital Universitario Quirónsalud Madrid, Madrid 28223, Spain
- Department of Radiation Oncology, Hospital La Luz, Madrid 28003, Spain
- Clinical Department, Faculty of Biomedicine,Universidad Europea de Madrid, Madrid 28670, Spain
| | - Pedro Landete
- Department of Pneumology, Hospital Universitario de la Princesa, Universidad Autónoma de Madrid, Madrid 28006, Spain
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Konté K, Nur E, Tang MW, Heijmans J, van Tuijn CFJ, Biemond BJ. Incidence of SARS-COV-2 infection in sickle cell patients presenting with a painful crisis: A 12-month prospective cohort study. Int J Lab Hematol 2021; 44:e87-e90. [PMID: 34651455 PMCID: PMC8653089 DOI: 10.1111/ijlh.13739] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 09/22/2021] [Accepted: 09/29/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Kadère Konté
- Department of Clinical Haematology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Erfan Nur
- Department of Clinical Haematology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Man Wai Tang
- Department of Clinical Haematology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Jarom Heijmans
- Department of Clinical Haematology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Charlotte F J van Tuijn
- Department of Clinical Haematology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Bart J Biemond
- Department of Clinical Haematology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
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Gashi A, Kubik-Huch RA, Chatzaraki V, Potempa A, Rauch F, Grbic S, Wiggli B, Friedl A, Niemann T. Detection and characterization of COVID-19 findings in chest CT: Feasibility and applicability of an AI-based software tool. Medicine (Baltimore) 2021; 100:e27478. [PMID: 34731126 PMCID: PMC8519217 DOI: 10.1097/md.0000000000027478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 04/19/2021] [Accepted: 09/17/2021] [Indexed: 01/05/2023] Open
Abstract
ABSTRACT The COVID-19 pandemic has challenged institutions' diagnostic processes worldwide. The aim of this study was to assess the feasibility of an artificial intelligence (AI)-based software tool that automatically evaluates chest computed tomography for findings of suspected COVID-19.Two groups were retrospectively evaluated for COVID-19-associated ground glass opacities of the lungs (group A: real-time polymerase chain reaction positive COVID patients, n = 108; group B: asymptomatic pre-operative group, n = 88). The performance of an AI-based software assessment tool for detection of COVID-associated abnormalities was compared with human evaluation based on COVID-19 reporting and data system (CO-RADS) scores performed by 3 readers.All evaluated variables of the AI-based assessment showed significant differences between the 2 groups (P < .01). The inter-reader reliability of CO-RADS scoring was 0.87. The CO-RADS scores were substantially higher in group A (mean 4.28) than group B (mean 1.50). The difference between CO-RADS scoring and AI assessment was statistically significant for all variables but showed good correlation with the clinical context of the CO-RADS score. AI allowed to predict COVID positive cases with an accuracy of 0.94.The evaluated AI-based algorithm detects COVID-19-associated findings with high sensitivity and may support radiologic workflows during the pandemic.
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Affiliation(s)
- Andi Gashi
- Department of Health Sciences and Technology, Swiss Federal Institute of Technology, ETH Zurich, 101 Rämistrasse, Zurich, Switzerland
| | - Rahel A. Kubik-Huch
- Department of Radiology, Kantonsspital Baden, 1 Im Ergel, Baden, Switzerland
| | - Vasiliki Chatzaraki
- Department of Radiology, Kantonsspital Baden, 1 Im Ergel, Baden, Switzerland
| | - Anna Potempa
- Department of Radiology, Kantonsspital Baden, 1 Im Ergel, Baden, Switzerland
| | - Franziska Rauch
- Siemens Healthcare GmbH, 3 Siemensstrasse, Forchheim, Germany
| | - Sasa Grbic
- Siemens Healthcare GmbH, 3 Siemensstrasse, Forchheim, Germany
| | - Benedikt Wiggli
- Department of Infectious Diseases, Kantonsspital Baden, 1 Im Ergel, Baden, Switzerland
| | - Andrée Friedl
- Department of Infectious Diseases, Kantonsspital Baden, 1 Im Ergel, Baden, Switzerland
| | - Tilo Niemann
- Department of Radiology, Kantonsspital Baden, 1 Im Ergel, Baden, Switzerland
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Diagnostic Techniques for COVID-19: A Mini-review of Early Diagnostic Methods. JOURNAL OF ANALYSIS AND TESTING 2021; 5:314-326. [PMID: 34631199 PMCID: PMC8488931 DOI: 10.1007/s41664-021-00198-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 08/25/2021] [Indexed: 12/26/2022]
Abstract
The outbreak of severe pneumonia at the end of 2019 was proved to be caused by the SARS-CoV-2 virus spreading out the world. And COVID-19 spread rapidly through a terrible transmission way by human-to-human, which led to many suspected cases waiting to be diagnosed and huge daily samples needed to be tested by an effective and rapid detection method. With an increasing number of COVID-19 infections, medical pressure is severe. Therefore, more efficient and accurate diagnosis methods were keen urgently established. In this review, we summarized several methods that can rapidly and sensitively identify COVID-19; some of them are widely used as the diagnostic techniques for SARS-CoV-2 in various countries, some diagnostic technologies refer to SARS (Severe Acute Respiratory Syndrome) or/and MERS (Middle East Respiratory Syndrome) detection, which may provide potential diagnosis ideas.
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Nucera G, Chirico F, Raffaelli V, Marino P. Current challenges in COVID-19 diagnosis: a narrative review and implications for clinical practice. ITALIAN JOURNAL OF MEDICINE 2021. [DOI: 10.4081/itjm.2021.1474] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Early diagnosis of coronavirus disease 2019 (COVID-19) is crucial to early treatment and quarantine measures. In this narrative review, diagnostic tools for COVID-19 diagnosis and their main critical issues were reviewed. The COVID-19 real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test is considered the gold standard test for the qualitative and quantitative detection of viral nucleic acid. In contrast, tests can be used for epidemiological surveys on specific communities, including occupational cohorts, but not for clinical diagnosis as a substitute for swab tests. Computed tomography (CT) scans can be useful for the clinical diagnosis of COVID-19, especially in symptomatic cases. The imaging features of COVID-19 are diverse and depend on the stage of infection after the onset of symptoms. CT sensitivity seems to be higher in patients with positive RT-PCR. Conventional chest sensitivity shows a lower sensitivity. An important diagnostic screening tool is ultrasounds, whose specificity and sensitivity depend on disease severity, patient weight, and operator skills. Nevertheless, ultrasounds could be useful as a screening tool in combination with clinical features and molecular testing to monitor disease progression. Clinical symptoms and non-specific laboratory findings may be useful if used in combination with RT-PCR test and CT-scanning.
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Mihalj M, Mosbahi S, Schmidli J, Heinisch PP, Reineke D, Schoenhoff F, Kadner A, Schefold JC, Räber L, Potapov EV, Luedi MM. Providing safe perioperative care in cardiac surgery during the COVID-19 pandemic. Best Pract Res Clin Anaesthesiol 2021; 35:321-332. [PMID: 34511222 PMCID: PMC7826053 DOI: 10.1016/j.bpa.2021.01.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/12/2021] [Accepted: 01/15/2021] [Indexed: 10/28/2022]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has potentiated the need for implementation of strict safety measures in the medical care of surgical patients - and especially in cardiac surgery patients, who are at a higher risk of COVID-19-associated morbidity and mortality. Such measures not only require minimization of patients' exposure to COVID-19 but also careful balancing of the risks of postponing nonemergent surgical procedures and providing appropriate and timely surgical care. We provide an overview of current evidence for preoperative strategies used in cardiac surgery patients, including risk stratification, telemedicine, logistical challenges during inpatient care, appropriate screening capacity, and decision-making on when to safely operate on COVID-19 patients. Further, we focus on perioperative measures such as safe operating room management and address the dilemma over when to perform cardiovascular surgical procedures in patients at risk.
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Affiliation(s)
- Maks Mihalj
- Department of Cardiovascular Surgery, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Selim Mosbahi
- Department of Cardiovascular Surgery, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Juerg Schmidli
- Department of Cardiovascular Surgery, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Paul Philipp Heinisch
- Department of Cardiovascular Surgery, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - David Reineke
- Department of Cardiovascular Surgery, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Florian Schoenhoff
- Department of Cardiovascular Surgery, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Alexander Kadner
- Department of Cardiovascular Surgery, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Joerg C Schefold
- Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Lorenz Räber
- Department of Cardiology, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
| | - Evgenij V Potapov
- Department of Cardiothoracic and Vascular Surgery, German Heart Center, Berlin, Germany; DZHK (German Centre for Cardiovascular Research), Partner Site, Augustenburger Platz 1, 13353 Berlin, Germany.
| | - Markus M Luedi
- Department of Anaesthesiology and Pain Medicine, Inselspital, Bern University Hospital, University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
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Muljadi R, Yuniarti M, Tan R, Pratama TA, Prasetya IB, Widysanto A, Octavius GS. Descriptive Analysis of Chest Computed Tomography Scan in Coronavirus Disease 2019 Pneumonia: Correlation with Reverse Transcription-polymerase Chain Reaction and Clinical Features. Open Access Maced J Med Sci 2021; 9:865-871. [DOI: 10.3889/oamjms.2021.6224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND: Reverse transcriptase-polymerase chain reaction (RT-PCR) is the primary diagnostic tool to confirm coronavirus disease 2019 (COVID-2019) due to its high specificity. However, it has relatively low sensitivity and time consuming. In contrast, chest computed tomography (CT) has high sensitivity and achieves quick results. It may, therefore, play a critical role in screening and diagnosing COVID-19. A cross-sectional study was done in 212 patients with confirmed cases and patients under surveillance for COVID-19 tested for RT-PCR and chest CT scan. Statistical analysis was performed using SPSS Version 23 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA).
AIM: We aim to investigate the diagnostic value of chest CT in correlation to RT-PCR in Indonesia.
METHODS: A cross-sectional study was done in 212 patients with confirmed cases and patients under surveillance for COVID-19 tested for RT-PCR and chest CT scan. Statistical analysis was performed using SPSS Version 23 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA).
RESULTS: From a total of 212 patients, 92% of them were diagnosed as confirmed cases of COVID-19. It was found that the sensitivity of CT scan for COVID-19 patients was 72.3% (65.5% and 78.5%) with positive predictive value (PPV) of 93.9% (90.9% and 96.0%) and the sensitivity and PPV improve in symptomatic patients. Typical chest CT scan lesions were 8.0 times which were more likely (3.9–16.4; p <0.001) to be detected in symptomatic patients while patients with severe CT scan findings were 4.4 times more likely (3.0–6.5; p <0.001) to be admitted to the intensive care unit.
CONCLUSION: A high PPV suggests that a chest CT scan can detect COVID-19 lesions, but the absence of the lesions would not exclude the disease’s presence.
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Meng Z, Guo S, Zhou Y, Li M, Wang M, Ying B. Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19. Signal Transduct Target Ther 2021; 6:316. [PMID: 34433805 PMCID: PMC8386162 DOI: 10.1038/s41392-021-00731-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 07/21/2021] [Accepted: 07/30/2021] [Indexed: 02/07/2023] Open
Abstract
The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.
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Affiliation(s)
- Zirui Meng
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Shuo Guo
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Yanbing Zhou
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Mengjiao Li
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Minjin Wang
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Binwu Ying
- Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.
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Salaouatchi MT, Mahadeb B, Clevenbergh P, Maillart E, Mesquita M, Nechita I, Collart F. Efficacy of systematic coronavirus screening by PCR and viral cultures in addition to triage in limiting the spread of SARS-CoV-2 within a hemodialysis unit. J Nephrol 2021; 35:113-120. [PMID: 34346033 PMCID: PMC8330470 DOI: 10.1007/s40620-021-01115-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 07/04/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Patients with end-stage-renal-disease (ESRD) undergoing hemodialysis (HD) represent a vulnerable population for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, due to their intrinsic fragility and increased exposure to the virus. Therefore, applying effective screening strategies and infection control measures is essential to control the spread of the epidemic within hemodialysis centers. OBJECTIVE Description and evaluation of the efficacy of systematic screening by rt-PCR and viral cultures, in addition to triage to limit the spread of the epidemic. Evaluation of the performance of these tests using "post-hoc" SARS-CoV-2 serology as a surrogate marker of infection. METHODS One hundred and forty-four patients undergoing hemodialysis in the Nephrology-Hemodialysis center of CHU Brugmann, Brussels, benefited from systematic virological screening using viral cultures in asymptomatic patients, or molecular tests (rt-PCR) for symptomatic ones, in addition to general prevention measures. Post-hoc serology was performed in all patients. RESULTS Thirty-eight (26.3%) individuals were infected with SARS-CoV-2. Seventeen infected patients (44.7%) were asymptomatic and thus detected by viral culture. Our strategy allowed us to detect and isolate 97.4% of the infected patients, as proven by post-hoc serology. Only one patient, missed by clinical screening and sequential viral cultures, had a positive serology. CONCLUSION The implementation of a control and prevention strategy based on a systematic clinical and virological screening showed its effectiveness in limiting (and shortening) the spread of the SARS-CoV-2 epidemic within our hemodialysis unit.
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Affiliation(s)
| | - Bhavna Mahadeb
- Microbiology Department, Laboratoire Hospitalier Universitaire de Bruxelles - Universitairy Laboratorium Brussel (LHUB-ULB); Infection Control Unit, University Hospital Brugmann, Brussels, Belgium
| | | | - Evelyne Maillart
- Infectious Diseases Clinic, University Hospital Brugmann, Brussels, Belgium
| | - Maria Mesquita
- Nephrology Department, University Hospital Brugmann, Brussels, Belgium
| | - Irina Nechita
- Nephrology Department, University Hospital Brugmann, Brussels, Belgium
| | - Frederic Collart
- Nephrology Department, University Hospital Brugmann, Brussels, Belgium
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Spiro JE, Curta A, Mansournia S, Marschner CA, Maurus S, Weckbach LT, Hedderich DM, Dinkel J. Appearance of COVID-19 pneumonia on 1.5 T TrueFISP MRI. Radiol Bras 2021; 54:211-218. [PMID: 34393286 PMCID: PMC8354185 DOI: 10.1590/0100-3984.2021.0028] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 03/16/2021] [Indexed: 12/23/2022] Open
Abstract
Objective To evaluate the performance of 1.5 T true fast imaging with steady state precession (TrueFISP) magnetic resonance imaging (MRI) sequences for the detection and characterization of pulmonary abnormalities caused by coronavirus disease 2019 (COVID-19). Materials and Methods In this retrospective single-center study, computed tomography (CT) and MRI scans of 20 patients with COVID-19 pneumonia were evaluated with regard to the distribution, opacity, and appearance of pulmonary lesions, as well as bronchial changes, pleural effusion, and thoracic lymphadenopathy. McNemar’s test was used in order to compare the COVID-19-associated alterations seen on CT with those seen on MRI. Results Ground-glass opacities were better visualized on CT than on MRI (p = 0.031). We found no statistically significant differences between CT and MRI regarding the visualization/characterization of the following: consolidations; interlobular/intralobular septal thickening; the distribution or appearance of pulmonary abnormalities; bronchial pathologies; pleural effusion; and thoracic lymphadenopathy. Conclusion Pulmonary abnormalities caused by COVID-19 pneumonia can be detected on TrueFISP MRI sequences and correspond to the patterns known from CT. Especially during the current pandemic, the portions of the lungs imaged on cardiac or abdominal MRI should be carefully evaluated to promote the identification and isolation of unexpected cases of COVID-19, thereby curbing further spread of the disease.
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Affiliation(s)
- Judith Eva Spiro
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Adrian Curta
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Shiwa Mansournia
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | | | - Stefan Maurus
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | | | - Dennis Martin Hedderich
- Department of Neuroradiology, Technical University of Munich, School of Medicine, Munich, Germany
| | - Julien Dinkel
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany.,Comprehensive Pneumology Center (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany.,Department of Radiology, Asklepios Lung Center Munich-Gauting, Gauting, Germany
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Nair AV, McInnes M, Jacob B, Kumar D, Soman DK, Subair HSV, Mahajan PS, Shah MAH, Sabawi MAS, Al-Heidous M. Diagnostic accuracy and inter-observer agreement with the CO-RADS lexicon for CT chest reporting in COVID-19. Emerg Radiol 2021; 28:1045-1054. [PMID: 34302561 PMCID: PMC8308071 DOI: 10.1007/s10140-021-01967-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 07/05/2021] [Indexed: 01/19/2023]
Abstract
PURPOSE To measure the diagnostic accuracy and inter-observer agreement with the use of COVID-19 Reporting and Data System (CO-RADS) for detection of COVID-19 on CT chest imaging. METHODS This retrospective study included 164 consecutive patients with clinical suspicion of COVID-19 in whom a CT chest examination was performed at a single institution between April 2020 and July 2020. Of them, 101 patients was RT-PCR positive for COVID-19. Six readers with varying radiological experience (two each of chest radiologists, general radiologists, and radiologists in training) independently assigned a CO-RADS assessment category for each CT chest study. The Fleiss' K was used to quantify inter-observer agreement. The inter-observer agreement was also assessed based on the duration of onset of symptoms to CT scan. ROC curve analysis was used to determine the diagnostic accuracy of CO-RADS. The area under curve was calculated to determine the reader accuracy for detection of COVID-19 lung involvement with RT-PCR as reference standards. The data sets were plotted in ROC space, and Youden's J statistic was calculated to determine the threshold cut-off CO-RADS category for COVID-19 positivity. RESULTS There was overall moderate inter-observer agreement between all readers (Fleiss' K 0.54 [95% CI 0.54, 0.54]), with substantial agreement among chest radiologists (Fleiss' K 0.68 [95% CI 0.67, 0.68]), general radiologists (Fleiss' K 0.61 [95% CI 0.61, 0.61]), and moderate agreement among radiologists-in-training (Fleiss' K 0.56 [95% CI 0.56, 0.56]). There was overall moderate inter-observer agreement in early disease (stages 1 and 2), with cumulative Fleiss' K 0.45 [95% CI 0.45, 0.45]). The overall AUC for CO-RADS lexicon scheme to accurately diagnose COVID-19 yielded 0.92 (95% CI 0.91, 0.94) with strong concordance within and between groups, of chests radiologists with AUC of 0.91 (95% CI 0.88, 0.94), general radiologists with AUC 0.96 (95% CI 0.94, 0.98), and radiologists in training with AUC of 0.90 (95% CI 0.87, 0.94). For detecting COVID-19, ROC curve analysis yielded CO-RADS > 3 as the cut-off threshold with sensitivity 90% (95% CI 0.88, 0.93), and specificity of 87% (95% CI 0.83, 0.91). CONCLUSION Readers across different levels of experience could accurately identify COVID-19 positive patients using the CO-RADS lexicon with moderate inter-observer agreement and high diagnostic accuracy.
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Affiliation(s)
| | | | - Bamil Jacob
- Dept of Clinical Imaging, Hamad Medical Corporation, Doha, Qatar
| | - Devendra Kumar
- Dept of Clinical Imaging, Hamad Medical Corporation, Doha, Qatar
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Bao M, Chen Q, Xu Z, Jensen EC, Liu C, Waitkus JT, Yuan X, He Q, Qin P, Du K. Challenges and Opportunities for Clustered Regularly Interspaced Short Palindromic Repeats Based Molecular Biosensing. ACS Sens 2021; 6:2497-2522. [PMID: 34143608 DOI: 10.1021/acssensors.1c00530] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Clustered regularly interspaced short palindromic repeats, CRISPR, has recently emerged as a powerful molecular biosensing tool for nucleic acids and other biomarkers due to its unique properties such as collateral cleavage nature, room temperature reaction conditions, and high target-recognition specificity. Numerous platforms have been developed to leverage the CRISPR assay for ultrasensitive biosensing applications. However, to be considered as a new gold standard, several key challenges for CRISPR molecular biosensing must be addressed. In this paper, we briefly review the history of biosensors, followed by the current status of nucleic acid-based detection methods. We then discuss the current challenges pertaining to CRISPR-based nucleic acid detection, followed by the recent breakthroughs addressing these challenges. We focus upon future advancements required to enable rapid, simple, sensitive, specific, multiplexed, amplification-free, and shelf-stable CRISPR-based molecular biosensors.
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Affiliation(s)
- Mengdi Bao
- Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States
| | - Qun Chen
- Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China
| | - Zhiheng Xu
- Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States
| | - Erik C. Jensen
- HJ Science & Technology Inc., San Leandro, California 94710, United States
| | - Changyue Liu
- Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China
| | - Jacob T. Waitkus
- Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States
| | - Xi Yuan
- Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China
| | - Qian He
- Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China
| | - Peiwu Qin
- Center of Precision Medicine and Healthcare, Tsinghua-Berkeley Shenzhen Institute, Shenzhen, Guangdong Province 518055, China
| | - Ke Du
- Department of Mechanical Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States
- Department of Microsystems Engineering, Rochester Institute of Technology, Rochester, New York 14623, United States
- School of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, New York 14623, United States
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