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suck abstract from ncbi


10.1016/j.clinimag.2020.11.022

http://scihub22266oqcxt.onion/10.1016/j.clinimag.2020.11.022
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33197713!7655027!33197713
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suck abstract from ncbi

pmid33197713      Clin+Imaging 2021 ; 72 (ä): 22-30
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  • Imaging algorithm for COVID-19: A practical approach #MMPMID33197713
  • Ghosh S; Deshwal H; Saeedan MB; Khanna VK; Raoof S; Mehta AC
  • Clin Imaging 2021[Apr]; 72 (ä): 22-30 PMID33197713show ga
  • The global pandemic of COVID-19 pneumonia caused by the novel coronavirus (SARS-CoV-2) has strained healthcare resources across the world with emerging challenges of mass testing, resource allocation and management. While reverse transcriptase-polymerase chain reaction (RT-PCR) test is the most commonly utilized test and considered the current gold standard for diagnosis, the role of chest imaging has been highlighted by several studies demonstrating high sensitivity of computed tomography (CT). Many have suggested using CT chest as a first-line screening tool for the diagnosis of COVID-19. However, with advancement of laboratory testing and challenges in obtaining a CT scan without significant risk to healthcare providers, the role of imaging in diagnosis has been questioned. Several imaging societies have released consensus statements and guidelines on utilizing imaging resources and optimal reporting. In this review, we highlight the current evidence on various modalities in thoracic imaging for the diagnosis of COVID-19 and describe an algorithm on how to use these resources in an optimal fashion in accordance with the guidelines and statements released by major imaging societies.
  • |*COVID-19[MESH]
  • |Algorithms[MESH]
  • |COVID-19 Testing[MESH]
  • |Clinical Laboratory Techniques[MESH]
  • |Humans[MESH]


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