Diagnostic Accuracy of Chest Computed Tomography Scans for Suspected Patients with COVID-19: Receiver Operating Characteristic Curve Analysis   [open pdf - 691KB]

From the Abstract: "Computed tomography (CT) scans are increasingly available in clinical care globally. They enable a rapid and detailed assessment of tissue and organ involvement in disease processes that are relevant to diagnosis and management, particularly in the context of the COVID-19 [coronavirus disease 2019] pandemic. [...] The aim of this paper is to identify differences in the CT scan findings of patients who were COVID-19 positive (confirmed via nucleic acid testing) to patients who were confirmed COVID-19 negative. [...] A retrospective cohort study was proposed to compare patient clinical characteristics and CT scan findings in suspected COVID-19 cases. [...] A total of 94 (56%) patients were confirmed positive for COVID-19 from the suspected 167 patients. We found that elderly people were more likely to be infected with COVID-19. Among the 94 confirmed positive patients, 2 (2%) patients were admitted to an intensive care unit. No patients died during the study period. We found that the presence, distribution, and location of CT lesions were associated with the presence of COVID-19. White blood cell count, cough, and a travel history to Wuhan were also the top predictors for COVID-19. [...] Taken together with nucleic acid testing, we found that CT scans can allow for the rapid diagnosis of COVID-19. This study suggests that chest CT scans should be more broadly adopted along with nucleic acid testing in the initial assessment of suspected COVID-19 cases, especially for patients with nonspecific symptoms." The original publication of this article can be found here: [http://publichealth.jmir.org/2020/4/e19424/].

Lianpin Wu, Qike Jin, Jie Chen, Jiawei He, David M Brett-Major, Jianghu James Dong. Posted here with permission. Document is under a Creative Commons license and requires proper attribution and noncommercial use to be shared: [https://creativecommons.org/licenses/by/4.0/].
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JMIR Publications: https://publichealth.jmir.org/
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JMIR Public Health and Surveillance (2020), v.6 issue 4
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