| Literature DB >> 32255413 |
Geoffrey D Rubin1, Christopher J Ryerson1, Linda B Haramati1, Nicola Sverzellati1, Jeffrey P Kanne1, Suhail Raoof1, Neil W Schluger1, Annalisa Volpi1, Jae-Joon Yim1, Ian B K Martin1, Deverick J Anderson1, Christina Kong1, Talissa Altes1, Andrew Bush1, Sujal R Desai1, Onathan Goldin1, Jin Mo Goo1, Marc Humbert1, Yoshikazu Inoue1, Hans-Ulrich Kauczor1, Fengming Luo1, Peter J Mazzone1, Mathias Prokop1, Martine Remy-Jardin1, Luca Richeldi1, Cornelia M Schaefer-Prokop1, Noriyuki Tomiyama1, Athol U Wells1, Ann N Leung1.
Abstract
With more than 900 000 confirmed cases worldwide and nearly 50 000 deaths during the first 3 months of 2020, the coronavirus disease 2019 (COVID-19) pandemic has emerged as an unprecedented health care crisis. The spread of COVID-19 has been heterogeneous, resulting in some regions having sporadic transmission and relatively few hospitalized patients with COVID-19 and others having community transmission that has led to overwhelming numbers of severe cases. For these regions, health care delivery has been disrupted and compromised by critical resource constraints in diagnostic testing, hospital beds, ventilators, and health care workers who have fallen ill to the virus exacerbated by shortages of personal protective equipment. Although mild cases mimic common upper respiratory viral infections, respiratory dysfunction becomes the principal source of morbidity and mortality as the disease advances. Thoracic imaging with chest radiography and CT are key tools for pulmonary disease diagnosis and management, but their role in the management of COVID-19 has not been considered within the multivariable context of the severity of respiratory disease, pretest probability, risk factors for disease progression, and critical resource constraints. To address this deficit, a multidisciplinary panel comprised principally of radiologists and pulmonologists from 10 countries with experience managing patients with COVID-19 across a spectrum of health care environments evaluated the utility of imaging within three scenarios representing varying risk factors, community conditions, and resource constraints. Fourteen key questions, corresponding to 11 decision points within the three scenarios and three additional clinical situations, were rated by the panel based on the anticipated value of the information that thoracic imaging would be expected to provide. The results were aggregated, resulting in five main and three additional recommendations intended to guide medical practitioners in the use of chest radiography and CT in the management of COVID-19. © RSNA, 2020; American College of Chest Physicians, published by Elsevier Inc.Editor's note: This article is being simultaneously published in.Entities:
Mesh:
Year: 2020 PMID: 32255413 PMCID: PMC7233395 DOI: 10.1148/radiol.2020201365
Source DB: PubMed Journal: Radiology ISSN: 0033-8419 Impact factor: 11.105
Figure 1:The first of three clinical scenarios presented to the panel with final recommendations. Mild features refer to absence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ventilators with the need to rapidly triage patients. Numbers in blue circles indicate key questions referenced in the text and presented in Figure 4. Contextual detail and considerations for imaging with CXR (chest radiography) versus CT (computed tomography) are presented in the text. (Pos=positive, Neg=negative, Mod=moderate). [Although not covered by this scenario and not shown in the figure, in the presence of significant resources constraints, there is no role for imaging of patients with mild features of COVID-19.]
Figure 2:The second of three clinical scenarios presented to the panel with final recommendations. Moderate-to-severe features refer to evidence of significant pulmonary dysfunction or damage. Pre-test probability is based upon background prevalence of disease and may be further modified by individual’s exposure risk. The absence of resource constraints corresponds to sufficient availability of personnel, personal protective equipment, COVID-19 testing, hospital beds, and/or ventilators with the need to rapidly triage patients. Numbers in blue circles indicate key questions referenced in the text and presented in Figure 4. Contextual detail and considerations for imaging with CXR (chest radiography) versus CT (computed tomography) are presented in the text. (Pos=positive, Neg=negative, Alt Dx=alternate diagnosis).
Figure 3:The third of three clinical scenarios presented to the panel with final recommendations. Moderate-to-severe features refer to evidence of significant pulmonary dysfunction or damage. High pre-test probability is based upon high background prevalence of disease associated with community transmission. Rapid COVID-19 test is a point-of-care test with a less than one-hour turnaround time. Numbers in blue circles indicate key questions referenced in the text and presented in Figure 4. Contextual detail and considerations for imaging with CXR (chest radiography) versus CT (computed tomography) are presented in the text. (Pos=positive, Neg=negative, Alt Dx=alternate diagnosis).
Figure 4:Panel members (total n=27) developed 14 key questions (numerals in left column correspond to question numbers in text and Figures 1-3) that were used to support creation of common scenarios and recommendations related to the use of chest imaging in patients with features of COVID-19. The proportion of panel member votes for each question is presented on a 5-point scale, as well as a summary column that shows the total percentage who voted for or against imaging for each key question, excluding those members who were neutral or who abstained (1 panel member abstained for questions 1 and 2).
Definitions and Criteria for Key Components of Common Clinical Scenarios
Summary of Recommendations for Imaging