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Talebi A, Borumandnia N, Jafari R, Pourhoseingholi MA, Jafari NJ, Ashtari S, Roozpeykar S, RahimiBashar F, Karimi L, Guest PC, Jamialahmadi T, Vahedian-Azimi A, Gohari-Moghadam K, Sahebkar A. Predicting the COVID-19 Patients Status Using Chest CT Scan Findings: A Risk Assessment Model Based on Decision Tree Analysis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1412:237-250. [PMID: 37378771 DOI: 10.1007/978-3-031-28012-2_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/29/2023]
Abstract
BACKGROUND The role of chest computed tomography (CT) to diagnose coronavirus disease 2019 (COVID-19) is still an open field to be explored. The aim of this study was to apply the decision tree (DT) model to predict critical or non-critical status of patients infected with COVID-19 based on available information on non-contrast CT scans. METHODS This retrospective study was performed on patients with COVID-19 who underwent chest CT scans. Medical records of 1078 patients with COVID-19 were evaluated. The classification and regression tree (CART) of decision tree model and k-fold cross-validation were used to predict the status of patients using sensitivity, specificity, and area under the curve (AUC) assessments. RESULTS The subjects comprised of 169 critical cases and 909 non-critical cases. The bilateral distribution and multifocal lung involvement were 165 (97.6%) and 766 (84.3%) in critical patients, respectively. According to the DT model, total opacity score, age, lesion types, and gender were statistically significant predictors for critical outcomes. Moreover, the results showed that the accuracy, sensitivity and specificity of the DT model were 93.3%, 72.8%, and 97.1%, respectively. CONCLUSIONS The presented algorithm demonstrates the factors affecting health conditions in COVID-19 disease patients. This model has the potential characteristics for clinical applications and can identify high-risk subpopulations that need specific prevention. Further developments including integration of blood biomarkers are underway to increase the performance of the model.
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Affiliation(s)
- Atefeh Talebi
- Colorectal Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Nasrin Borumandnia
- Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ramezan Jafari
- Department of Radiology, Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Mohamad Amin Pourhoseingholi
- Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Nematollah Jonaidi Jafari
- Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Sara Ashtari
- Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Saeid Roozpeykar
- Department of Radiology, Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Farshid RahimiBashar
- Anesthesia and Critical Care Department, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Leila Karimi
- Behavioral Sciences Research Center, LifeStyle Institute, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Paul C Guest
- Department of Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Laboratory of Translational Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Tannaz Jamialahmadi
- Surgical Oncology Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
- Applied Biomedical Research Center, Mashhad University of Medical Sciences, Vakilabad blvd., Mashhad, Iran
| | - Amir Vahedian-Azimi
- Trauma Research Center, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Keivan Gohari-Moghadam
- Medical ICU and Pulmonary unit, Shariati hospital, Tehran University of Medical Sciences, Tehran, Iran.
| | - Amirhossein Sahebkar
- Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
- Department of Biotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
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Alam MA, Gani MA, Shama G, Sofi G, Quamri MA. Possible role of Unani Pharmacology in COVID-19 - a narrative review. REVIEWS ON ENVIRONMENTAL HEALTH 2021; 36:391-396. [PMID: 33155997 DOI: 10.1515/reveh-2020-0106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 10/03/2020] [Indexed: 06/11/2023]
Abstract
According to the World Health Organization (WHO), viral diseases continue to rise, and pose a significant public health problem. Novel coronavirus disease (COVID-19) is an infectious disease caused by SARS-CoV-2. The pathogenesis and clinical manifestations of COVID-19 is close to Amraz-e-Wabai (epidemic diseases) which was described by Hippocrates, Galen, Aristotle, Razes, Haly Abbas, Avicenna, Jurjani etc. Presently, there is no specific or challenging treatment available for COVID-19. Renowned Unani Scholars recommended during epidemic situation to stay at home, and fumigate the shelters with aromatics herbs like Ood kham (Aquilaria agallocha Roxb.), Kundur (Boswellia serrata Roxb), Kafoor (Cinnamomum camphora L.), Sandal (Santalum album L), Hing (Ferula foetida L.) etc. Use of specific Unani formulations are claimed effective for the management of such epidemic or pandemic situation like antidotes (Tiryaqe Wabai, Tiryaqe Arba, Tiryaqe Azam, Gile Armani), Herbal Decoction (Joshandah), along with Sharbate Khaksi, Habbe Bukhar, Sharbate Zanjabeel, Khamira Marwareed, Jawarish Jalinus, and Sirka (vinegar). Such drugs are claimed for use as antioxidant, immunomodulatory, cardiotonic, and general tonic actions. The study enumerates the literature regarding management of epidemics in Unani medicine and attempts to look the same in the perspective of COVID-19 prevention and management.
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Affiliation(s)
- Md Anzar Alam
- Department of Medicine, National Institute of Unani Medicine, Bangalore, India
| | - Mohd Abdul Gani
- Department of Pharmacology, National Institute of Unani Medicine, Bangalore, India
| | - G Shama
- Department of Preventive and Social Medicine, Government Unani Medical College, Bangalore, India
| | - Ghulamuddin Sofi
- Department of Pharmacology, National Institute of Unani Medicine, Bangalore, India
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The Characteristics, Manifestations and Cardiopulmonary Imaging (CT/MRI) of COVID-19 in SARS-CoV-2 Infection. JOURNAL OF INTERDISCIPLINARY MEDICINE 2021. [DOI: 10.2478/jim-2020-0035] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Abstract
The World Health Organization (WHO) declared the transmission of SARS-CoV-2 a Public Health Emergency of International Concern. The novel coronavirus has diverse manifestations, usually similar to a common cold or influenza. The majority of patients with coronavirus disease have typical imaging features. The typical CT characteristics of patients with COVID-19 pneumonia are ground-glass opacities and consolidative lesions with a peripheral and posterior distribution. Noninvasive imaging methods are precise and rapid means of diagnosing pneumonia and cardiovascular complications caused by COVID-19 infection. Therefore, it is important for clinicians to understand the implications of this pandemic and to be familiar with the different imaging aspects of the novel coronavirus disease. This review focuses on the most commonly reported imaging findings of COVID-19 infection in different patients from different countries, the expert recommendations, and the cardiac manifestations of SARS-CoV-2 infection.
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An isolated spontaneous pneumomediastinum as a rare complication of COVID 19. LA TUNISIE MEDICALE 2021; 99:764-766. [PMID: 35261009 PMCID: PMC8796666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The Coronavirus Disease 2019 (COVID-19) pandemic has displayed heterogeneity in disease manifestations and complications. This case report illustrates a rare issue : the spontaneous pneumomediastinum. A 73-year-old male presented with chills, and respiratory symptoms. A reverse transcriptase polymerase chain reaction (RT-PCR) test- confirmed COVID19. At admission, the patient was in severe respiratory distress. C reactive protein was 54 mg/l (normal: 0-5 mg/l), , troponin were negative, brain natriuretic peptid 55 pg/ml (normal range <100 pg/ml) and D-dimer 700 mcg/l (normal: 0-500 mcg/l). Arterial blood gases showed pH 7.49 (normal: 7.35-7.45), PCO2 33,8 mmHg (normal: 34-46 mmHg) and PO2 56 mmHg (normal: 80-97 mmHg) with 16 liter per minute of oxygen. Computed tomography of the chest (CT chest) showed diffuse groundglass opacities (60-70%) without pulmonary embolism. Diagnosis of acute respiratory distress syndrome (ARDS) was made. Low flow oxygen was provided (Oxygen saturation target ≥ 94%), intermediate dose of low molecular weight heparin and 8mg of dexamethason were administarted daily. On day 10, worsening hemodynamics and blood oxygen levels was noted. CT chest showed moderate bilateral pneumomediastinum, without pneumothorax, persistent groundglass opacities (75%) with early fibrosis elements. The patient recovered with no pulmonary sequelae. This case report encourages health workers to get used with infrequent clinical and radiological manifestations of COVID-19 that is still surprising the world.
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Role of Chest Computed Tomography versus Real Time Reverse Transcription Polymerase Chain Reaction for Diagnosis of COVID-19: A Systematic Review and Meta-Analysis. Interdiscip Perspect Infect Dis 2021; 2021:8798575. [PMID: 34194491 PMCID: PMC8184322 DOI: 10.1155/2021/8798575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 12/31/2020] [Accepted: 02/01/2021] [Indexed: 01/08/2023] Open
Abstract
Background The current global pandemic of COVID-19 is considered a public health emergency. The diagnosis of COVID-19 depends on detection of the viral nucleic acid by real time reverse transcription polymerase chain reaction (RT-PCR). However, false-negative RT-PCR tests are reported and could hinder the control of the pandemic. Chest computed tomography could achieve a more reliable diagnosis and represent a complementary diagnostic tool. Aim To perform a meta-analysis and systematic review to find out the role of chest computed tomography versus RT-PCR for precise diagnosis of COVID-19 infection. Methods We searched three electronic databases (PubMed, ScienceDirect, and Scopus) from April 1 to April 20, 2020, to find out articles including the accuracy of chest computed tomography scan versus RT-PCR for diagnosis of SARS-CoV-2 infection. Observational studies, case series, and case reports were included. Results A total of 238 articles were retrieved from the search strategy. Following screening, 39 articles were chosen for full text assessment and finally 35 articles were included for qualitative and quantitative analysis. Chest computed tomography showed a wide range of sensitivity varied from 12%–100%. Conclusion Chest computed tomography is playing a key role for diagnosis and detection of COVID-19 infection. Computed tomography image findings may precede the initially positive RT-PCR assay.
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de Carvalho LS, da Silva Júnior RT, Oliveira BVS, de Miranda YS, Rebouças NLF, Loureiro MS, Pinheiro SLR, da Silva RS, Correia PVSLM, Silva MJS, Ribeiro SN, da Silva FAF, de Brito BB, Santos MLC, Leal RAOS, Oliveira MV, de Melo FF. Highlighting COVID-19: What the imaging exams show about the disease. World J Radiol 2021; 13:122-136. [PMID: 34141092 PMCID: PMC8188839 DOI: 10.4329/wjr.v13.i5.122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/16/2021] [Accepted: 05/07/2021] [Indexed: 02/06/2023] Open
Abstract
Coronavirus disease 2019 (COVID-19), a global emergency, is caused by severe acute respiratory syndrome coronavirus 2. The gold standard for its diagnosis is the reverse transcription polymerase chain reaction, but considering the high number of infected people, the low availability of this diagnostic tool in some contexts, and the limitations of the test, other tools that aid in the identification of the disease are necessary. In this scenario, imaging exams such as chest X-ray (CXR) and computed tomography (CT) have played important roles. CXR is useful for assessing disease progression because it allows the detection of extensive consolidations, besides being a fast and cheap method. On the other hand, CT is more sensitive for detecting lung changes in the early stages of the disease and is also useful for assessing disease progression. Of note, ground-glass opacities are the main COVID-19-related CT findings. Positron emission tomography combined with CT can be used to evaluate chronic and substantial damage to the lungs and other organs; however, it is an expensive test. Lung ultrasound (LUS) has been shown to be a promising technique in that context as well, being useful in the screening and monitoring of patients, disease classification, and management related to mechanical ventilation. Moreover, LUS is an inexpensive alternative available at the bedside. Finally, magnetic resonance imaging, although not usually requested, allows the detection of pulmonary, cardiovascular, and neurological abnormalities associated with COVID-19. Furthermore, it is important to consider the challenges faced in the radiology field in the adoption of control measures to prevent infection and in the follow-up of post-COVID-19 patients.
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Affiliation(s)
- Lorena Sousa de Carvalho
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | | | - Bruna Vieira Silva Oliveira
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Yasmin Silva de Miranda
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Nara Lúcia Fonseca Rebouças
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Matheus Sande Loureiro
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Samuel Luca Rocha Pinheiro
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Regiane Santos da Silva
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | | | - Maria José Souza Silva
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Sabrina Neves Ribeiro
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Filipe Antônio França da Silva
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Breno Bittencourt de Brito
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Maria Luísa Cordeiro Santos
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | | | - Márcio Vasconcelos Oliveira
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
| | - Fabrício Freire de Melo
- Department of Instituto Multidisciplinar em Saúde, Universidade Federal da Bahia, Vitória da Conquista 45029-094, Bahia, Brazil
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Razek A, Fouda N, Fahmy D, Tanatawy MS, Sultan A, Bilal M, Zaki M, Abdel-Aziz M, Sobh D. Computed tomography of the chest in patients with COVID-19: what do radiologists want to know? Pol J Radiol 2021; 86:e122-e135. [PMID: 33758638 PMCID: PMC7976235 DOI: 10.5114/pjr.2021.104049] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 08/15/2020] [Indexed: 12/14/2022] Open
Abstract
We aim in the current study to review pulmonary and extra-pulmonary imaging features in patients infected with COVID-19. COVID-19 appears to be a highly contagious viral disease that attacks the respiratory system causing pneumonia. Since the beginning of the outbreak, several reports have been published describing various radiological patterns related to COVID-19. Radiological features of COVID-19 are classified into; pulmonary signs of which ground glass opacities are considered the characteristic followed by consolidation, and extra-pulmonary signs such as pulmonary embolism and pneumothorax, which are far less common and appear later in progressive disease. We review the different structured reporting systems that are published by different groups of radiologists using simple unified terms to enable good communication between the radiologist and the referring physician. Computed tomography of the chest is beneficial for early diagnosis of COVID-19 pneumonia, assessment of disease progression and guide to therapy, surveillance of patients with response to therapy, prediction of overlying bacterial infection, differentiation from simulating lesions, and screening with prevention and controls of the disease.
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Affiliation(s)
- Ahmed Razek
- Correspondence address: Ahmed Razek, MD, Mansoura University Hospital, Egypt, e-mail:
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Soltani S, Tabibzadeh A, Zakeri A, Zakeri AM, Latifi T, Shabani M, Pouremamali A, Erfani Y, Pakzad I, Malekifar P, Valizadeh R, Zandi M, Pakzad R. COVID-19 associated central nervous system manifestations, mental and neurological symptoms: a systematic review and meta-analysis. Rev Neurosci 2021; 32:351-361. [PMID: 33618441 DOI: 10.1515/revneuro-2020-0108] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 10/23/2020] [Indexed: 01/16/2023]
Abstract
The ongoing pandemic of Coronavirus disease 2019 (COVID-19) has infected more than 27 million confirmed cases and 8,90,000 deaths all around the world. Verity of viral infections can infect the nervous system; these viral infections can present a wide range of manifestation. The aim of the current study was to systematically review the COVID-19 associated central nervous system manifestations, mental and neurological symptoms. For that we conducted a comprehensive systematic literature review of four online databases, including Web of Science, PubMed, Scopus and Embase. All relevant articles that reported psychiatric/psychological symptoms or disorders in COVID-19 without considering time and language restrictions were assessed. All the study procedures were performed based on the PRISMA criteria. Due to the screening, 14 studies were included. The current study result indicated that, the pooled prevalence of CNS or mental associated disorders with 95% CI was 50.68% (6.68-93.88). The most prevalence symptoms were hyposmia/anosmia/olfactory dysfunction (number of study: 10) with 36.20% (14.99-60.51). Only one study reported numbness/paresthesia and dysphonia. Pooled prevalence of numbness/paresthesia and dysphonia was 5.83% (2.17-12.25) and 2.39% (10.75-14.22). The pooled prevalence of depression and anxiety was 3.52% (2.62-4.54) and 13.92% (9.44-19.08). Our findings demonstrate that COVID-19 has a certain relation with neurological symptoms. The hypsomia, anosmia or olfactory dysfunction was most frequent symptom. Other symptoms were headache or dizziness, dysgeusia or ageusia, dysphonia and fatigue. Depression, anxiety, and confusion were less frequent symptoms.
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Affiliation(s)
- Saber Soltani
- Department of Virology, School of Public Health, Tehran University of Medical Sciences, 1417613151, Tehran, Iran.,Research Center for Clinical Virology, Tehran University of Medical Sciences, 1417613151, Tehran, Iran
| | - Alireza Tabibzadeh
- Department of Virology, Iran University of Medical Sciences, 1449614535, Tehran, Iran
| | - Armin Zakeri
- Department of Hematology, Faculty of Medical Sciences, Tarbiat Modares University, 111-14115, Tehran, Iran
| | - Amir Mohammad Zakeri
- Pediatric Surgery Research Center, Research Institute for Children's Health, Shahid Beheshti University of Medical Sciences, 22439962,Tehran, Iran
| | - Tayebeh Latifi
- Department of Virology, School of Public Health, Tehran University of Medical Sciences, 1417613151, Tehran, Iran
| | - Mahdi Shabani
- Department of Virology, School of Public Health, Tehran University of Medical Sciences, 1417613151, Tehran, Iran
| | - Amir Pouremamali
- Department of Medical Virology, Faculty of Medical Sciences, Tarbiat Modares University, 111-14115, Tehran, Iran
| | - Yousef Erfani
- Department of Medical Laboratory Sciences, School of Allied Medical Sciences, Tehran University Medical Sciences, 1417613151, Tehran, Iran
| | - Iraj Pakzad
- Department of Microbiology, School of Allied Medical Sciences, Ilam University Medical Sciences, 6939177143, Ilam, Iran
| | - Pooneh Malekifar
- Department of Epidemiology, School of Public Health, Tehran University Medical Sciences, 1417613151, Tehran, Iran
| | - Reza Valizadeh
- Department of Psychiatry, Psychosocial Injures Research Center, Ilam University Medical Sciences, 6939177143, Ilam, Iran
| | - Milad Zandi
- Department of Virology, School of Public Health, Tehran University of Medical Sciences, 1417613151, Tehran, Iran.,Students' Scientific Research Center, Tehran University of Medical Sciences, 1417613151, Tehran, Iran
| | - Reza Pakzad
- Department of Epidemiology, Faculty of Health, Ilam University Medical Sciences, 6939177143, Ilam, Iran.,Noor Research Center for Ophthalmic Epidemiology, Noor Eye Hospital, 1417613151, Tehran, Iran
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Lin P, Chen W, Huang H, Lin Y, Cai M, Lin D, Cai H, Su Z, Zhuang X, Yu X. Delayed discharge is associated with higher complement C3 levels and a longer nucleic acid-negative conversion time in patients with COVID-19. Sci Rep 2021; 11:1233. [PMID: 33441900 PMCID: PMC7806718 DOI: 10.1038/s41598-021-81010-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 01/01/2021] [Indexed: 02/06/2023] Open
Abstract
To determine factors associated with delayed discharge of hospitalized patients with coronavirus disease (COVID-19). This retrospective cohort study included 47 patients with COVID-19 admitted to three hospitals in Quanzhou City, Fujian Province, China, between January 21, 2020 and March 6, 2020. Univariate and multivariate logistic regression analyses were conducted to identify factors associated with delayed discharge. The median length of hospital stay was 22 days. Patients in the delayed discharge group (length of hospital stay ≥ 21 days, n = 27) were more likely to have diarrhea, anorexia, decreased white blood cell counts, increased complement C3 and C-reactive protein levels, air bronchograms, undergo thymalfasin treatment, and take significantly longer to convert to a severe acute respiratory syndrome coronavirus (SARS-CoV-2) RNA-negative status than those in the control group (length of hospital stay, < 21 days; n = 20). In multivariate logistic regression analysis, the time to SARS-CoV-2 RNA-negative conversion (odds ratio [OR]: 1.48, 95% confidence interval [CI] 1.09–2.04, P = 0.01) and complement C3 levels (OR 1.14 95% CI 1.02–1.27, P = 0.03) were the only risk factors independently associated with delayed discharge from the hospital. Dynamic monitoring of complement C3 and SARS-CoV-2 RNA levels is useful for predicting delayed discharge of patients.
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Affiliation(s)
- Peihuang Lin
- Department of Basic Medicine, Quanzhou Medical College, Quanzhou, China
| | - Wenhuang Chen
- Department of Infectious Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, No. 250 East Street, Licheng District, Quanzhou, 362000, Fujian, China
| | - Hongbo Huang
- Department of Respiratory Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, No. 250 East Street, Licheng District, Quanzhou, 362000, Fujian, China
| | - Yijian Lin
- Department of Respiratory Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, No. 250 East Street, Licheng District, Quanzhou, 362000, Fujian, China
| | - Maosheng Cai
- Department of Respiratory Diseases, Shishi City General Hospital, Quanzhou, China
| | - Dongheng Lin
- Department of Respiratory Diseases, Anxi County Hospital, Quanzhou, China
| | - Hehui Cai
- Department of Clinical Laboratory, The First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, China
| | - Zhijun Su
- Department of Infectious Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, No. 250 East Street, Licheng District, Quanzhou, 362000, Fujian, China
| | - Xibin Zhuang
- Department of Respiratory Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, No. 250 East Street, Licheng District, Quanzhou, 362000, Fujian, China.
| | - Xueping Yu
- Department of Infectious Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, No. 250 East Street, Licheng District, Quanzhou, 362000, Fujian, China.
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Pourhoseingholi A, Vahedi M, Chaibakhsh S, Pourhoseingholi MA, Vahedian-Azimi A, Guest PC, Rahimi-Bashar F, Sahebkar A. Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1327:139-147. [PMID: 34279835 DOI: 10.1007/978-3-030-71697-4_11] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into two groups of critical and non-critical according to their CT features. Methods This was carried out as a retrospective study from March to April 2020 in Baqiyatallah Hospital, Tehran, Iran. From total of 1078 patients with COVID-19 pneumonia who underwent chest CT, 169 were critical cases and 909 were non-critical. Deep learning neural networks were used to classify samples into critical or non-critical ones according to the chest CT results. Results The best accuracy of prediction was seen by the presence of diffuse opacities and lesion distribution (both=0.91, 95% CI: 0.83-0.99). The largest sensitivity was achieved using lesion distribution (0.74, 95% CI: 0.55-0.93), and the largest specificity was for presence of diffuse opacities (0.95, 95% CI: 0.9-1). The total model showed an accuracy of 0.89 (95% CI: 0.79-0.99), and the corresponding sensitivity and specificity were 0.71 (95% CI: 0.51-0.91) and 0.93 (95% CI: 0.87-0.96), respectively. Conclusions The results showed that CT scan can accurately classify and predict critical and non-critical COVID-19 cases.
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Affiliation(s)
- Asma Pourhoseingholi
- Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohsen Vahedi
- Department of Biostatistics, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Samira Chaibakhsh
- Eye Research Center, The five Senses Institute, Rassoul Akram Hospital, Iran University of Medical Sciences, Tehran, Iran.
| | - Mohamad Amin Pourhoseingholi
- Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amir Vahedian-Azimi
- Trauma Research Center, Nursing Faculty, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Paul C Guest
- Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Farshid Rahimi-Bashar
- Anesthesia and Critical Care Department, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Amirhossein Sahebkar
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran.
- Applied Biomedical Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
- Polish Mother's Memorial Hospital Research Institute (PMMHRI), Lodz, Poland.
- School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran.
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11
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Quispe-Cholan A, Anticona-De-La-Cruz Y, Cornejo-Cruz M, Quispe-Chirinos O, Moreno-Lazaro V, Chavez-Cruzado E. Tomographic findings in patients with COVID-19 according to evolution of the disease. EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2020. [PMCID: PMC7590569 DOI: 10.1186/s43055-020-00329-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Background The tomographic findings in COVID-19, its classification, a brief overview of the application of artificial intelligence, and the stages during the course of the disease in patients with moderate COVID-19 Main body Chest CT allows us to follow the course of COVID-19 in an objective way; each phase has characteristic imaging findings and, consequently, takes the corresponding measures. A search was made in the PubMed database with the keywords extracted from the DeCs and the combinations of these. Only articles published between December 2019 and June 2020 were included. The search was limited to the English language. Conclusions CT serves to monitor the course of the disease since it assesses the severity of lung involvement. The most frequent finding is bilateral ground glass opacities with a subpleural distribution. The progression occurs in two phases: one slow and one fast. At discharge, the patient may have ground glass opacities or areas that will later become fibrosis, leaving sequelae for life.
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12
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Komolafe TE, Agbo J, Olaniyi EO, Komolafe K, Yang X. Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis. Diagnostics (Basel) 2020; 10:E1023. [PMID: 33260639 PMCID: PMC7759864 DOI: 10.3390/diagnostics10121023] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/16/2020] [Accepted: 11/26/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The pooled prevalence of chest computed tomography (CT) abnormalities and other detailed analysis related to patients' biodata like gender and different age groups have not been previously described for patients with coronavirus disease 2019 (COVID-19), thus necessitating this study. Objectives: To perform a meta-analysis to evaluate the diagnostic performance of chest CT, common CT morphological abnormalities, disease prevalence, biodata information, and gender prevalence of patients. METHODS Studies were identified by searching PubMed and Science Direct libraries from 1 January 2020 to 30 April 2020. Pooled CT positive rate of COVID-19 and RT-PCR, CT-imaging features, history of exposure, and biodata information were estimated using the quality effect (QE) model. RESULTS Out of 36 studies included, the sensitivity was 89% (95% CI: 80-96%) and 98% (95% CI: 90-100%) for chest CT and reverse transcription-polymerase chain reaction (RT-PCR), respectively. The pooled prevalence across lesion distribution were 72% (95% CI: 62-80%), 92% (95% CI: 84-97%) for lung lobe, 88% (95% CI: 81-93%) for patients with history of exposure, and 91% (95% CI: 85-96%) for patients with all categories of symptoms. Seventy-six percent (95% CI: 67-83%) had age distribution across four age groups, while the pooled prevalence was higher in the male with 54% (95% CI: 50-57%) and 46% (95% CI: 43-50%) in the female. CONCLUSIONS The sensitivity of RT-PCR was higher than chest CT, and disease prevalence appears relatively higher in the elderly and males than children and females, respectively.
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Affiliation(s)
- Temitope Emmanuel Komolafe
- Division of Life Sciences and Medicine, School of Biomedical Engineering (Suzhou), University of Science and Technology of China, Hefei 230026, China;
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
| | - John Agbo
- CAS Key Laboratory for Brain Function and Disease, Department of Neurobiology, University of Science and Technology of China, Hefei 230026, China;
- Department of Neuropharmacology, Faculty of Basic Medical Sciences, Abubakar Tafawa Balewa University, Bauchi 740272, Nigeria
| | - Ebenezer Obaloluwa Olaniyi
- Department of Biomedical Engineering, Shenzhen University, Shenzhen 518060, China;
- Department of Electrical and Electronic Engineering, Adeleke University, Ede 232103, Nigeria
| | - Kayode Komolafe
- Department of Biochemistry, Federal University of Oye Ekiti, Oye 371104, Nigeria;
| | - Xiaodong Yang
- Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
- Jihua Laboratory, Foshan 528000, China
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13
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Singh DD, Han I, Choi EH, Yadav DK. Immunopathology, host-virus genome interactions, and effective vaccine development in SARS-CoV-2. Comput Struct Biotechnol J 2020; 18:3774-3787. [PMID: 33235690 PMCID: PMC7677077 DOI: 10.1016/j.csbj.2020.11.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 11/06/2020] [Accepted: 11/08/2020] [Indexed: 02/06/2023] Open
Abstract
Coronaviruses are a group of enveloped RNA viruses that are diversely found in humans and now declared a global pandemic by the World Health Organization in March 2020. The population's susceptibility to these highly pathogenic coronaviruses has contributed to large outbreaks, evolved into public health events, and rapidly transmitted globally. Thus, there is an urgent need to develop effective therapies and vaccines against this disease. In the primary stage of severe acute respiratory syndrome coronavirus (SARS-COV-2) infection, the signs and symptoms are nonspecific, and many more cases have been observed than initially expected. Genome sequencing is performed regularly to identify genetic changes to SARS-COV-2, and vaccine development is focused on manufacture, production, and based on specific problems, and very few are available on recent developments in the prevention of outbreaks. The aim of this review article to explore recent updates on SARS-COV-2 in the context of pathogenesis during disease progression, and innate acquired mechanisms of defense, This includes advances in diagnostics, susceptibility, and severity of host-virus genome interactions, modes of transmission, active compounds being used in pre-clinical and clinical trials for the treatment of patients, vaccine developments, and the effectiveness of SARS-COV-2 prevention and control measures. We have summarized the importance of pathophysiology immune response, Diagnostics, vaccine development currently approaches explored for SARS-COV-2.
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Affiliation(s)
- Desh Deepak Singh
- Amity Institute of Biotechnology, Amity University Rajasthan, Jaipur, India
| | - Ihn Han
- Plasma Bioscience Research Center, Applied Plasma Medicine Center, Department of Electrical & Biological Physics, Kwangwoon University, Seoul, Republic of Korea
| | - Eun-Ha Choi
- Plasma Bioscience Research Center, Applied Plasma Medicine Center, Department of Electrical & Biological Physics, Kwangwoon University, Seoul, Republic of Korea
| | - Dharmendra Kumar Yadav
- Gachon Institute of Pharmaceutical Science and Department of Pharmacy, College of Pharmacy, Hambakmoeiro 191, Yeonsu-gu, Gachon University, Incheon, Republic of Korea
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14
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Gandhi D, Ahuja K, Grover H, Sharma P, Solanki S, Gupta N, Patel L. Review of X-ray and computed tomography scan findings with a promising role of point of care ultrasound in COVID-19 pandemic. World J Radiol 2020; 12:195-203. [PMID: 33033574 PMCID: PMC7523085 DOI: 10.4329/wjr.v12.i9.195] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/22/2020] [Accepted: 09/25/2020] [Indexed: 02/06/2023] Open
Abstract
As healthcare professionals continue to combat the coronavirus disease 2019 (COVID-19) infection worldwide, there is an increasing interest in the role of imaging and the relevance of various modalities. Since imaging not only helps assess the disease at the time of diagnosis but also aids evaluation of response to management, it is critical to examine the role of different modalities currently in use, such as baseline X-rays and computed tomography scans carefully. In this article, we will draw attention to the critical findings for the radiologist. Further, we will look at point of care ultrasound, an increasingly a popular tool in diagnostic medicine, as a component of COVID-19 management.
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Affiliation(s)
- Darshan Gandhi
- Department of Radiology, Northwestern Memorial Hospital, Chicago, IL 60611, United States
| | - Kriti Ahuja
- Department of Internal Medicine, John H Stroger Jr. Hospital of Cook County, Chicago, IL 60612, United States
| | - Hemal Grover
- Department of Diagnostic Radiology, Icahn School of Medicine at Mount Sinai West, New York, NY 10029, United States
| | - Pranav Sharma
- Department of Diagnostic Radiology, Vascular and Interventional Radiology, University of Minnesota Medical Center, Minneapolis, MN 55455, United States
| | - Shantanu Solanki
- Department of Internal Medicine, Guthrie Robert Packer Hospital, Sayre, PA 18840, United States
| | - Nishant Gupta
- Department of Radiology, Bassett Healthcare, Cooperstown, NY 13326, United States
| | - Love Patel
- Division of Hospital Medicine, Abbott Northwestern Hospital, Allina Health, Minneapolis, MN 55407, United States
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15
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Gillespie M, Dincher N, Fazio P, Okorji O, Finkle J, Can A. Coronavirus disease 2019 (COVID-19) complicated by Spontaneous Pneumomediastinum and Pneumothorax. Respir Med Case Rep 2020; 31:101232. [PMID: 32989414 PMCID: PMC7510447 DOI: 10.1016/j.rmcr.2020.101232] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 09/19/2020] [Indexed: 01/08/2023] Open
Abstract
The first reports of severe acute respiratory symptoms from a novel coronavirus called coronavirus disease 2019 (COVID-19) occurred in Wuhan, Hubei Province, China in December 2019.1 The World Health Organization declared COVID-19 a global pandemic by March 2020.1 The COVID-19 outbreak has resulted in a current global health emergency. Clinical information about the findings of COVID-19 and its associated complications are constantly evolving and becoming more widely available. Providers should be familiar with both typical symptoms and image study results for COVID-19 as well as less commonly reported complications of progressive COVID-19, such as spontaneous pneumomediastinum and spontaneous pneumothorax as highlighted in this case.
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Affiliation(s)
- Megan Gillespie
- Department of Emergency Medicine, Jefferson Health - Northeast, Philadelphia, PA, USA
| | - Nathan Dincher
- Department of Emergency Medicine, Jefferson Health - Northeast, Philadelphia, PA, USA.,Department of Critical Care, Jefferson Health - Northeast, Philadelphia, PA, USA
| | - Pamela Fazio
- Department of Internal Medicine, Jefferson Health - Northeast, Philadelphia, PA, USA
| | - Onyinyechukwu Okorji
- Department of Emergency Medicine, Jefferson Health - Northeast, Philadelphia, PA, USA.,Department of Internal Medicine, Jefferson Health - Northeast, Philadelphia, PA, USA
| | - Jacob Finkle
- Department of Emergency Medicine, Jefferson Health - Northeast, Philadelphia, PA, USA
| | - Argun Can
- Department of Critical Care, Jefferson Health - Northeast, Philadelphia, PA, USA
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16
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Reiss AB, De Leon J, Dapkins IP, Shahin G, Peltier MR, Goldberg ER. A Telemedicine Approach to Covid-19 Assessment and Triage. MEDICINA (KAUNAS, LITHUANIA) 2020; 56:E461. [PMID: 32927589 PMCID: PMC7559216 DOI: 10.3390/medicina56090461] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 08/18/2020] [Accepted: 08/27/2020] [Indexed: 12/31/2022]
Abstract
Covid-19 is a new highly contagious RNA viral disease that has caused a global pandemic. Human-to-human transmission occurs primarily through oral and nasal droplets and possibly through the airborne route. The disease may be asymptomatic or the course may be mild with upper respiratory symptoms, moderate with non-life-threatening pneumonia, or severe with pneumonia and acute respiratory distress syndrome. The severe form is associated with significant morbidity and mortality. While patients who are unstable and in acute distress need immediate in-person attention, many patients can be evaluated at home by telemedicine or videoconferencing. The more benign manifestations of Covid-19 may be managed from home to maintain quarantine, thus avoiding spread to other patients and health care workers. This document provides an overview of the clinical presentation of Covid-19, emphasizing telemedicine strategies for assessment and triage of patients. Advantages of the virtual visit during this time of social distancing are highlighted.
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Affiliation(s)
- Allison B Reiss
- Department of Medicine, NYU Long Island School of Medicine, Mineola, NY 11501, USA
- Department of Foundations of Medicine, NYU Long Island School of Medicine, Mineola, NY 11501, USA
| | - Joshua De Leon
- Department of Medicine, NYU Long Island School of Medicine, Mineola, NY 11501, USA
| | - Isaac P Dapkins
- Department of Population Health and Department of Internal Medicine, NYU Langone Health, New York, NY 10016, USA
| | - George Shahin
- Department of Internal Medicine, NYU Langone Health, New York, NY 10016, USA
| | - Morgan R Peltier
- Department of Foundations of Medicine, NYU Long Island School of Medicine, Mineola, NY 11501, USA
| | - Eric R Goldberg
- Department of Medicine, NYU Grossman School of Medicine, Mineola, NY 11501, USA
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17
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Nagpal P, Narayanasamy S, Vidholia A, Guo J, Shin KM, Lee CH, Hoffman EA. Imaging of COVID-19 pneumonia: Patterns, pathogenesis, and advances. Br J Radiol 2020; 93:20200538. [PMID: 32758014 PMCID: PMC7465853 DOI: 10.1259/bjr.20200538] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Revised: 07/07/2020] [Accepted: 07/09/2020] [Indexed: 12/20/2022] Open
Abstract
COVID-19 pneumonia is a newly recognized lung infection. Initially, CT imaging was demonstrated to be one of the most sensitive tests for the detection of infection. Currently, with broader availability of polymerase chain reaction for disease diagnosis, CT is mainly used for the identification of complications and other defined clinical indications in hospitalized patients. Nonetheless, radiologists are interpreting lung imaging in unsuspected patients as well as in suspected patients with imaging obtained to rule out other relevant clinical indications. The knowledge of pathological findings is also crucial for imagers to better interpret various imaging findings. Identification of the imaging findings that are commonly seen with the disease is important to diagnose and suggest confirmatory testing in unsuspected cases. Proper precautionary measures will be important in such unsuspected patients to prevent further spread. In addition to understanding the imaging findings for the diagnosis of the disease, it is important to understand the growing set of tools provided by artificial intelligence. The goal of this review is to highlight common imaging findings using illustrative examples, describe the evolution of disease over time, discuss differences in imaging appearance of adult and pediatric patients and review the available literature on quantitative CT for COVID-19. We briefly address the known pathological findings of the COVID-19 lung disease that may help better understand the imaging appearance, and we provide a demonstration of novel display methodologies and artificial intelligence applications serving to support clinical observations.
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Affiliation(s)
- Prashant Nagpal
- Department of Radiology, University of Iowa, Carver College of Medicine, Iowa City, Iowa, USA
| | - Sabarish Narayanasamy
- Department of Radiology, University of Iowa, Carver College of Medicine, Iowa City, Iowa, USA
| | - Aditi Vidholia
- Department of Pathology, University of Iowa, Carver College of Medicine, Iowa City, Iowa, USA
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18
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Borkowski AA, Viswanadhan NA, Thomas LB, Guzman RD, Deland LA, Mastorides SM. Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis. Fed Pract 2020; 37:398-404. [PMID: 33029064 PMCID: PMC7535959 DOI: 10.12788/fp.0045] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Coronavirus disease-19 (COVID-19), caused by a novel member of the coronavirus family, is a respiratory disease that rapidly reached pandemic proportions with high morbidity and mortality. In only a few months, it has had a dramatic impact on society and world economies. COVID-19 has presented numerous challenges to all aspects of health care, including reliable methods for diagnosis, treatment, and prevention. Initial efforts to contain the spread of the virus were hampered by the time required to develop reliable diagnostic methods. Artificial intelligence (AI) is a rapidly growing field of computer science with many applications for health care. Machine learning is a subset of AI that uses deep learning with neural network algorithms. It can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans. METHODS In this article, we explore the potential for the simple and widely available chest X-ray (CXR) to be used with AI to diagnose COVID-19 reliably. Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services. We utilized publicly available CXR images for patients with COVID-19 pneumonia, pneumonia from other etiologies, and normal CXRs as a dataset to train Microsoft CustomVision. RESULTS Our trained model overall demonstrated 92.9% sensitivity (recall) and positive predictive value (precision), with results for each label showing sensitivity and positive predictive value at 94.8% and 98.9% for COVID-19 pneumonia, 89% and 91.8% for non-COVID-19 pneumonia, 95% and 88.8% for normal lung. We then validated the program using CXRs of patients from our institution with confirmed COVID-19 diagnoses along with non-COVID-19 pneumonia and normal CXRs. Our model performed with 100% sensitivity, 95% specificity, 97% accuracy, 91% positive predictive value, and 100% negative predictive value. CONCLUSIONS We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward.
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Affiliation(s)
- Andrew A Borkowski
- is Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida
| | - Narayan A Viswanadhan
- is Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida
| | - L Brannon Thomas
- is Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida
| | - Rodney D Guzman
- is Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida
| | - Lauren A Deland
- is Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida
| | - Stephen M Mastorides
- is Chief of the Molecular Diagnostics Laboratory, is Chief of the Microbiology Laboratory, is a Research Coordinator, and is Chief of Pathology; is Assistant Chief of Radiology; all at the James A. Haley Veterans' Hospital in Tampa, Florida. is a Cofounder of InterKnowlogy, LLC in Carlsbad, California. Andrew Borkowski and Stephen Mastorides are Professors and L. Brannon Thomas is an Assistant Professor, all in the Department of Pathology and Cell Biology, University of South Florida, Morsani College of Medicine in Tampa, Florida
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19
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Alexander A, Hunter K, Passerini S, Bhat R, Bhat AP. Appendiceal diverticulosis in a patient with family history of Birt-Hogg-Dubé syndrome--a case report. Radiol Case Rep 2020; 15:1317-1322. [PMID: 32612732 PMCID: PMC7322125 DOI: 10.1016/j.radcr.2020.05.071] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 05/28/2020] [Accepted: 05/29/2020] [Indexed: 12/12/2022] Open
Abstract
Birt-Hogg-Dubé syndrome (BHD) is a rare autosomal dominant disorder that predisposes patients to cutaneous tumors, pulmonary cysts with recurrent spontaneous pneumothoraces, and a variety of renal neoplasms including hybrid oncocytic and chromophobe renal cell carcinomas. There has been much debate regarding the genetic link with the occurrence of colorectal cancer and other colonic anomalies. Associations between BHD and intestinal adenomatous polyposis and sigmoid diverticulosis have been described in the literature, but there have been no prior reports of appendiceal diverticulosis in patients with BHD. Here, we present a 40-year-old female patient with a known family history of BHD, who was found to have diverticulosis of the appendix and pulmonary blebs on computed tomography upon routine screening for renal and pulmonary abnormalities, suggesting additional focus be given to the gastrointestinal tract (including the appendix) at the time of CT assessment.
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Affiliation(s)
- Alan Alexander
- Renaissance Imaging Medical Associates, Northridge, CA, USA
| | - Kyle Hunter
- Department of Radiology, Cleveland Clinic, OH, USA
| | | | - Roopa Bhat
- Department of Radiology, Section of Vascular and Interventional Radiology, University of Missouri- Columbia, One Hospital Drive, Columbia, MO, 65212, USA
| | - Ambarish P. Bhat
- Department of Radiology, Section of Vascular and Interventional Radiology, University of Missouri- Columbia, One Hospital Drive, Columbia, MO, 65212, USA
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20
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Tahvildari A, Arbabi M, Farsi Y, Jamshidi P, Hasanzadeh S, Calcagno TM, Nasiri MJ, Mirsaeidi M. Clinical Features, Diagnosis, and Treatment of COVID-19 in Hospitalized Patients: A Systematic Review of Case Reports and Case Series. Front Med (Lausanne) 2020; 7:231. [PMID: 32574328 PMCID: PMC7242615 DOI: 10.3389/fmed.2020.00231] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 05/04/2020] [Indexed: 01/08/2023] Open
Abstract
Introduction: The 2019 novel coronavirus (COVID-19) has been declared a public health emergency worldwide. The objective of this systematic review was to characterize the clinical, diagnostic, and treatment characteristics of hospitalized patients presenting with COVID-19. Methods: We conducted a structured search using PubMed/Medline, Embase, and Web of Science to collect both case reports and case series on COVID-19 published up to April 24, 2020. There were no restrictions regarding publication language. Results: Eighty articles were included analyzing a total of 417 patients with a mean age of 48 years. The most common presenting symptom in patients who tested positive for COVID-19 was fever, reported in up to 62% of patients from 82% of the analyzed studies. Other symptoms including rhinorrhea, dizziness, and chills were less frequently reported. Additionally, in studies that reported C-reactive protein (CRP) measurements, a large majority of patients displayed an elevated CRP (60%). Progression to acute respiratory distress syndrome (ARDS) was the most common complication of patients testing positive for COVID-19 (21%). CT images displayed ground-glass opacification (GGO) patterns (80%) as well as bilateral lung involvement (69%). The most commonly used antiviral treatment modalities included, lopinavir (HIV protease inhibitor), arbidiol hydrochloride (influenza fusion inhibitor), and oseltamivir (neuraminidase inhibitor). Conclusions: Development of ARDS may play a role in estimating disease progression and mortality risk. Early detection of elevations in serum CRP, combined with a clinical COVID-19 symptom presentation may be used as a surrogate marker for the presence and severity of the disease. There is a paucity of data surrounding the efficacy of treatments. There is currently not a well-established gold standard therapy for the treatment of diagnosed COVID-19. Further prospective investigations are necessary.
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Affiliation(s)
- Azin Tahvildari
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahta Arbabi
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Yeganeh Farsi
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Parnian Jamshidi
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Saba Hasanzadeh
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Tess Moore Calcagno
- Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Javad Nasiri
- Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Mehdi Mirsaeidi
- Department of Microbiology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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