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Detection of incidental findings on chest CT scans in patients with suspected covid-19 pneumonia
Eastern Journal of Medicine ; 26(4):566-574, 2021.
Article in English | EMBASE | ID: covidwho-1488842
ABSTRACT
This study aimed to evaluate the chest Computed Tomography (CT) scans of COVID-19 suspected patients in the first period of the pandemic, to reveal the frequency of parenchymal-extraparenchymal incidental findings (IFs). Our single-center retrospective observational study was initiated with the approval of the ethics committee. Chest CT records taken during March-August 2020 due to the suspicion of COVID-19 pneumonia were scanned using the imaging archive of our center. The study was conducted with 1540 patients with non-contrast chest CT without prior CT imaging to detect IFs. Histopathological results and clinical-radiological follow-up data of the patients were scanned from medical records. Of the 1540 patients in our study, 902 (58.57%) were male and 638 (41.43%) were female, with a mean age of 41.96±17.08 (5-92) years. While 248 (16.1%) patients had a typical appearance for COVID-19 pneumonia on thorax CT, no findings were found in 1180 (76.6%) patients. Except for COVID-19 pneumonia, parenchymal IFs(primary malignant lung lesions, metastatic lesions, benign pathologies) were detected in 73 patients (4.74%) and extraparenchymal IFs(lymphadenopathy, breast lesions, thyroid nodule, bone, liver and kidney lesions…) in 280 patients (18.8%). Our study showed that the number of patients without any findings in terms of COVID-19 pneumonia on CT scans is high. It is understood that CT scans for pneumonia are unnecessary due to radiation exposure and should be used when clinically necessary. However, due to the ability of CT to detect incidental findings, it is also important to define IFs oth er than pneumonia in patients who underwent chest CT examination during the pandemic.

Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Diagnostic study Language: English Journal: Eastern Journal of Medicine Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Diagnostic study Language: English Journal: Eastern Journal of Medicine Year: 2021 Document Type: Article