Article: How accurate are radiography and computed tomography in the diagnosis of COVID-19?-A Bayesian approach.
2022 Volume 11, Issue 11, Page(s) 20584601221142256
Abstract: Background: The role of radiology in patients with clinical suspicion of COVID-19 is evolving with scientific evidence, but there are differences in opinion on when and how the technique should be used for clinical diagnosis.: Purpose: To estimate ... ...
Abstract | Background: The role of radiology in patients with clinical suspicion of COVID-19 is evolving with scientific evidence, but there are differences in opinion on when and how the technique should be used for clinical diagnosis. Purpose: To estimate the pre-test and post-test probability that a patient has COVID-19 in the event of a positive and/or negative result from chest X-ray and chest computed tomography (CT) radiological studies, comparing with those of real time polymerase chain reaction (RT-PCR) tests. Methods: The literature on the sensitivity and specificity of the chest X-ray, chest CT, and RT-PCR was reviewed. Based on these reported data, the likelihood ratios (LR) were estimated and the pre-test probabilities were related to the post-test probabilities after positive or negative results. Results: The chest X-ray has only a confirmatory value in cases of high suspicion. Chest CT analyses showed that when it is used as a general study, it has almost confirmatory value under high clinical suspicion. A chest CT classified with CO-RADS ≥ 4 has almost a diagnostic certainty of COVID-19 even with moderate or low clinical presumptions, and the CO-RADS 5 classification is almost pathognomonic before any clinical presumption. To rule out COVID-19 completely is only possible in very low clinical assumptions with negative RT-PCR and/or CT. Conclusions: Chest X-ray and especially CT are fast studies that have the capacity to report high probability of COVID-19, being a real contribution to the concept of "probable case" and allowing support to be installed in an early and timely manner. |
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Language | English |
Publishing date | 2022-11-24 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 2818429-4 |
ISSN | 2058-4601 |
ISSN | 2058-4601 |
DOI | 10.1177/20584601221142256 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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