Khan, Sohail Ahmed and Manohar, Murli and Khan, Maria and Asad, Samita and Adil, Syed Omair (2021) Radiological profile of patients undergoing Chest X-ray and computed tomography scans during COVID-19 outbreak. Pakistan Journal of Medical Sciences, 37 (5). ISSN 1682-024X
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Abstract
Background & Objective: Radiology has played a significant role in the diagnosis and quantifying the severity of COVID 19 pulmonary disease. This study was conducted to assess patterns and severity of COVID-19 pulmonary disease based on radiological imaging.
Methods: A prospective observational study was conducted in a large tertiary care public sector teaching hospital of Karachi, Pakistan from June 2020 till August 2020. All confirmed and suspected COVID-19 patients referred for chest X-rays and computed tomography (CT) scans were evaluated along with RT-PCR results. Suspected patients were followed for RT-PCR. Radiological features and severity of imaging studies were determined.
Results: Of 533 patients in whom X-rays were performed, majority had severe/critical findings, i.e., 304 (57.03%). Of 97 patients in whom CT scan was performed, mild/moderate findings were observed in 63 (64.94%) patients. Of 472 patients with abnormal X-rays, majority presented with alveolar pattern 459 (97.2%), bilateral lung involvement 453 (89.6%), and consolidation 356 (75.4%). Moreover, lobar predominance showed lower zone preponderance in 446 (94.5%) patients. Of 88 patients with abnormal CT findings, ground-glass opacity (GGO) 87 (98.9%) and crazy paving 69 (78.4%) were the most common findings. An insignificantly higher association of PCR positive cases was observed with severe/critical X-rays (p-value 0.076) and CT scan findings (p-value 0.431).
Conclusion: Most common patterns on CT scans were GGO and crazy paving. While on chest radiographs, bilateral lung involvement with alveolar pattern and consolidation were most common findings. On X-rays, majority had severe/critical whereas CT scan had mild/moderate findings.
Item Type: | Article |
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Subjects: | OA STM Library > Medical Science |
Depositing User: | Unnamed user with email support@oastmlibrary.com |
Date Deposited: | 13 Apr 2023 06:42 |
Last Modified: | 17 Jun 2024 06:52 |
URI: | http://geographical.openscholararchive.com/id/eprint/529 |