Sporadic coronavirus lower respiratory tract infection in adults: chest CT imaging features and comparison with other viruses

Marinari, Lawrence A.; Danny, Madeline A.; Miller, Wallace T.

doi:10.1183/13993003.congress-2019.pa4547

Cited by 7 publications

(7 citation statements)

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“…The results coincide with other studies wherein it has been reported that fever, cough, fatigue, and shortness of breath are common symptoms in severe COVID-19 patients (Durrani et al 2020;Al Mutair et al 2020). The association of the lower respiratory system in affecting the severity of COVID-19 patients has also been reported in different studies (Brosnahan et al 2020;Hannawi et al 2021;Marinari, Danny, and Miller 2019).…”

Section: Clinical Featuressupporting

confidence: 90%

Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2 infected Pakistani Patients

Omer

Sarwar

Roman

et al. 2021

Preprint

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SARS-CoV-2 is a causative agent for COVI-19 disease, initially reported from Wuhan, China. Infected Patients experienced mild to severe symptoms, resulting in several fatalities due to a weak understanding of its pathogenesis, which is the same even to date. This cross-sectional study has been designed on four hundred and fifty-two symptomatic, mild-to-moderate, and severe/critical patients to understand the epidemiology and clinical characteristics of COVID-19 patients with their comorbidities and response to treatment. The mean age of studied patients was (58±14.42) years, and the overall male to female ratio was 61.7 to 38.2%, respectively. 27.3% of the patients had a history of exposure, 11.9% travel history, while for 60% of patients, the source of infection was unknown. The most prevalent signs and symptoms in ICU patients were dry coughs, myalgias, shortness of breath, gastrointestinal discomfort, and abnormal Chest X-ray (p<0.001), along with the high percentage of hypertension (p=0.007) and COPD (p=0.029) as leading comorbidities. Complete Blood Counts indicators were significantly increased in severe patients, while the Coagulation Profile and D-dimer values were significantly higher in mild-to-moderate (non-ICU) patients (p < 0.001). Serum Creatinine (1.22 umole L-1; p = 0.016) and LDH (619 umol L-1; p < 0.001) indicators were significantly high in non-ICU patients while, raised values of Total Bilirubin (0.91 umol L-1; p = 0.054), CRP (84.68 mg L-1; p = 0.001) and Ferritin (996.81 mg L-1; p < 0.001) were found in ICU patients. Drug Dexamethasone was the leading prescribed and administrated medicine to the COVID-19 patients, followed by Remdesivir, Meropenem, Heparin, and Tocilizumab, respectively. A characteristic pattern of Ground glass opacities (GGO), consolidation, and interlobular septal thickening were prominent in severely infected patients. These findings could be used for future research, control, and prevention of SARS-CoV-2 infected patients.

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Section: Clinical Featuressupporting

confidence: 90%

Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2 infected Pakistani Patients

Omer

Sarwar

Roman

et al. 2021

Preprint

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“…In addition, the number of patients mentioned in certain previous studies and in the study, sample was less than the number of patients in this study. For example, in [5], there were 61 patients, and in [7], there were 77 patients, whereas in this study, there were128 patients. Furthermore, some previous studies, including [10], dealt with the study of a number of viruses, including the corona virus.…”

Section: Introductioncontrasting

confidence: 57%

“…Of these patients, 11 (18%) showed bronchial thickening, 15 (25%) experienced GGO, 12 (20%) showed lung consolidation, and 13 (21%) suffered from tree-in-bud opacity. Twenty-eight (46%) had no immediate chest-related results, showing the virus to share traits with both influenza PIV [5].…”

Section: Introductionmentioning

confidence: 99%

Development of a novel computational method using computed tomography images for the early detection and severity classification of COVID-19 cases

Abbas

Alqahtani

Alkulib

et al. 2021

XST

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BACKGROUND: Recent occurrence of the 2019 coronavirus disease (COVID-19) outbreak, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has highlighted the need for fast, accurate, and simple strategies to identify cases on a large scale. OBJECTIVE: This study aims to develop and test an accurate detection and severity classification methodology that may help medical professionals and non-radiologists recognize the behavior and propagation mechanisms of the virus by viewing computed tomography (CT) images of the lungs with implicit materials. METHODS: In this study, the process of detecting the virus began with the deployment of a virtual material inside CT images of the lungs of 128 patients. Virtual material is a hypothetical material that can penetrate the healthy regions in the image by performing sequential numerical measurements to interpret images with high data accuracy. The proposed method also provides a segmented image of only the healthy parts of the lung. RESULTS: The resulting segmented images, which represent healthy parts of the lung, are classified into six levels of severity. These levels are classified according to physical symptoms. The results of the proposed methodology are compared with those of the radiologists’ reports. This comparison revealed that the gold-standard reports correlated with the results of the proposed methodology with a high accuracy rate of 93%. CONCLUSION: The study results indicate the possibility of relying on the proposed methodology for discovering the effects of the SARS-CoV-2 virus in the lungs through CT imaging analysis with limited dependency on radiologists.

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“…The use of CT findings for discriminating COVID-19 pneumonia from other pneumonia has attracted considerable attention. Upon reviewing coronavirus cases associated with severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), GGO and/or lung consolidation were typically characterized on chest CT, which is different from the characteristics of other viruses [40]. Similarly, the typical radiological features of COVID-19, multiple lobular GGO and subsegmental areas of consolidation are met more often [41].…”

Section: ) Use Of Ct Characteristics For Discriminating Covid-19 Pnementioning

confidence: 99%

The Role of Imaging in the Detection and Management of COVID-19: A Review

Dong

Tang

Wang

et al. 2021

IEEE Rev. Biomed. Eng.

346

247

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Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnoses and treatment assessment of the disease. Herein, we review the use of imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography -CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play an important role in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.

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Sporadic coronavirus lower respiratory tract infection in adults: chest CT imaging features and comparison with other viruses

Cited by 7 publications

References 0 publications

Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2 infected Pakistani Patients

Epidemiology, Clinico-Pathological Characteristics, and Comorbidities of SARS-CoV-2 infected Pakistani Patients

Development of a novel computational method using computed tomography images for the early detection and severity classification of COVID-19 cases

The Role of Imaging in the Detection and Management of COVID-19: A Review

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