Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 1,245

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

The Role of Chest Imaging in Patient Management During the COVID-19 Pandemic

Open access
Rubin, Geoffrey D., Ryerson, Christopher J., Haramati, Linda B., Sverzellati, Nicola, Kanne, Jeffrey P., Raoof, Suhail, Schluger, Neil W., Volpi, Annalisa, Yim, Jae-Joon, Martin, Ian B.K., Anderson, Deverick J., Kong, Christina, Altes, Talissa, Bush, Andrew, Desai, Sujal R., Goldin, Jonathan, Goo, Jin Mo, Humbert, Marc, Inoue, Yoshikazu, Kauczor, Hans-Ulrich, Luo, Fengming, Mazzone, Peter J., Prokop, Mathias, Remy-Jardin, Martine, Richeldi, Luca, Schaefer-Prokop, Cornelia M., Tomiyama, Noriyuki, Wells, Athol U., Leung, Ann N.·2020·Chest
DOI 10.1016/j.chest.2020.04.003
Open this paper in CoChat — free account

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.chest.2020.04.003

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Research works printed but not linked: 21

  1. Ai T, Yang Z, Hou H, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases [published online ahead of print February 26, 2020]. Radiology. https://doi.org/10.1148/radiol.2020200642. · DOI · Paper page
  2. Li Y, Yao L, Li J, et al. Stability issues of RT-PCR testing of SARS-CoV-2 for hospitalized patients clinically diagnosed with COVID-19 [published online ahead of print March 26, 2020]. J Med Virol. https://doi.org/10.1002/jmv.25786. · DOI · Paper page
  3. Wang, 2020, Detection of SARS-CoV-2 in different types of clinical specimens, JAMA, 323, 1843
  4. Zou, 2020, SARS-CoV-2 viral load in upper respiratory specimens of infected patients, N Engl J Med, 382, 1177, 10.1056/NEJMc2001737 · DOI · Paper page
  5. Fang Y, Zhang H, Xie J, et al. Sensitivity of chest CT for COVID-19: comparison to RT-PCR [published online ahead of print February 19, 2020]. Radiology. https://doi.org/10.1148/radiol.2020200432. · DOI · Paper page
  6. Rothe, 2020, Transmission of 2019-nCoV infection from an asymptomatic contact in Germany, N Engl J Med, 382, 970, 10.1056/NEJMc2001468 · DOI · Paper page
  7. Inui, 2020, Findings in cases from the cruise ship “Diamond Princess” with coronavirus disease 2019 (COVID-19), Radiol Cardiothorac Imaging, 2
  8. Kooraki, 2020, Coronavirus (COVID-19) outbreak: what the department of radiology should know, J Am Coll Radiol, 17, 447, 10.1016/j.jacr.2020.02.008 · DOI · Paper page
  9. Dong Y, Mo X, Hu Y, et al. Epidemiological characteristics of 2143 pediatric patients with 2019 coronavirus disease in China. Pediatrics. In press.
  10. Soldati G, Smargiassi A, Inchingolo R, et al. Is there a role for lung ultrasound during the COVID-19 pandemic [published online ahead of print March 20, 2020]? J Ultrasound Med. https://doi.org/10.1002/jum.15284. · DOI · Paper page
  11. Wong HYF, Lam HYS, Fong AH, et al. Frequency and distribution of chest radiographic findings in COVID-19 positive patients [published online ahead of print March 27, 2019]. Radiology. https://doi.org/10.1148/radiol.2020201160. · DOI · Paper page
  12. Driggin, 2020, Cardiovascular considerations for patients, health care workers, and health systems during the coronavirus disease 2019 (COVID-19) pandemic, J Am Coll Cardiol, 75, 2352, 10.1016/j.jacc.2020.03.031 · DOI · Paper page
  13. Orsi, 2020, Radiology department preparedness for COVID-19: facing an unexpected outbreak of the disease, Radiology, 295, E8, 10.1148/radiol.2020201214 · DOI
  14. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention [published online ahead of print February 24, 2020]. JAMA. https://doi.org/10.1001/jama.2020.2648. · DOI · Paper page
  15. Oba, 2010, Abandoning daily routine chest radiography in the intensive care unit: meta-analysis, Radiology, 255, 386, 10.1148/radiol.10090946 · DOI
  16. Hejblum, 2009, Comparison of routine and on-demand prescription of chest radiographs in mechanically ventilated adults: a multicentre, cluster-randomised, two-period crossover study, Lancet, 374, 1687, 10.1016/S0140-6736(09)61459-8 · DOI
  17. Lakhal, 2012, AzuRéa network for the RadioDay study group. Chest radiographs in 104 French ICUs: current prescription strategies and clinical value (the RadioDay study), Intensive Care Med, 38, 1787, 10.1007/s00134-012-2650-9 · DOI
  18. Suh, 2015, ACR Appropriateness Criteria® intensive care unit patients, J Thorac Imaging, 30, W63, 10.1097/RTI.0000000000000174 · DOI
  19. Mizumoto, 2020, Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020, Euro Surveill, 25, 10.2807/1560-7917.ES.2020.25.10.2000180 · DOI · Paper page
  20. Nishiura, 2020, Estimation of the asymptomatic ratio of novel coronavirus infections (COVID-19), Int J Infect Dis, 94, 154, 10.1016/j.ijid.2020.03.020 · DOI · Paper page
  21. Simpson, 2020, Radiological Society of North America expert consensus statement on reporting chest CT findings related to COVID-19. Endorsed by the Society of Thoracic Radiology, the American College of Radiology, and RSNA, Radiol Cardiothorac Imaging, 2, 10.1148/ryct.2020200152 · DOI · Paper page

Cited by

Metadata

Authors
Rubin, G. D., Ryerson, C. J., Haramati, L. B., Sverzellati, N., Kanne, J. P., Raoof, S., Schluger, N. W., Volpi, A., Yim, J.-J., Martin, I. B. K., Anderson, D. J., Kong, C., Altes, T., Bush, A., Desai, S. R., Goldin, J., Goo, J. M., Humbert, M., Inoue, Y., Kauczor, H.-U., Luo, F., Mazzone, P. J., Prokop, M., Remy-Jardin, M., Richeldi, L., Schaefer-Prokop, C. M., Tomiyama, N., Wells, A. U., & Leung, A. N.
Venue
Chest
Publisher
Elsevier BV
Published
2020-07
Volume
158
Issue
1
Pages
106-116
ISSN
0012-3692 (ISSN-L)
DOI
10.1016/j.chest.2020.04.003
OpenAlex
W3014561994
Cited by
1,245
References
4
FWCI
34.92
Type
journal article
Language
en
Open access
bronze
Licence
  • www.elsevier.com/tdm/userlicense/1.0/ (tdm)
  • www.elsevier.com/legal/tdmrep-license (tdm)
Funders
  • Boehringer Ingelheim
  • Roche
  • Centers for Disease Control and Prevention
  • Agency for Healthcare Research and Quality
  • FibroGen

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.