Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19
Autor: | Mukundhan Gopalan, Praveen Dhoss, Gopinath, Senthil Jeyapal, Ethirajan Narayanan, Kamalanthan Muthukrishnan, Baskaran Rajalingam, Praveen K Nirmalan, Vijay Khanna, Saravanan Kumaravelu, Vivek Sundaram, Bavaharan Rajalingam |
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Rok vydání: | 2021 |
Předmět: |
High-resolution computed tomography
medicine.medical_specialty Coronavirus disease 2019 (COVID-19) Cross-sectional study R895-920 crazy pavement pattern Ground-glass opacity 030218 nuclear medicine & medical imaging Medical physics. Medical radiology. Nuclear medicine 03 medical and health sciences 0302 clinical medicine ground glass opacity Parenchyma medicine Radiology Nuclear Medicine and imaging Lung medicine.diagnostic_test business.industry respiratory system respiratory tract diseases medicine.anatomical_structure 030220 oncology & carcinogenesis Radiological weapon HRCT Original Article Radiology Tomography medicine.symptom business COVID 19 |
Zdroj: | The Indian Journal of Radiology & Imaging Indian Journal of Radiology and Imaging, Vol 31, Pp S110-S118 (2021) |
ISSN: | 1998-3808 0971-3026 |
Popis: | Aim: To describe the distribution of lung patterns determined by High Resolution Computed Tomography (HRCT) in COVID patients with mild and moderate lung involvement and outcomes after early identification and management with steroids and anticoagulants. Material and Methods: A cross sectional study of COVID-19 patients with mild and moderate lung involvement presenting at 5 healthcare centres in Trichy district of South TamilNadu in India. Patients underwent HRCT to assess patterns and severity of lung involvement, Inflammatory markers (LDH/Ferritin) and D-Dimer assay and clinical correlation with signs and symptoms. Patients were assessed for oxygen, steroid and anticoagulant therapy, clinical recovery or progression on follow up and details on mortality were collected. The RSNA, Fleischer Society guidelines and CORADS score was used for radiological reporting. New potential classification of patterns of percentage of lung parenchyma involvement in Covid patients is being suggested. Results: The study included 7,340 patients with suspected COVID and 3,963 (53.9%) patients had lung involvement based on HRCT. RT PCR was positive in 74.1% of the CT Positive cases. Crazy Pavement pattern was predominant (n = 2022, 51.0%) and Ground Glass Opacity (GGO) was found in 1,941 (49.0%) patients in the study. Severe lung involvement was more common in the Crazy Pavement pattern. Patients with GGO in moderate lung involvement were significantly more likely to recover faster compared to Crazy Pavement pattern (P value |
Databáze: | OpenAIRE |
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