ArticleEmergency radiology2021
Diagnostic accuracy and inter-observer agreement with the CO-RADS lexicon for CT chest reporting in COVID-19.
Article in Emergency radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Do COVID-19 CT features vary between patients from within and outside mainland China? Findings from a meta-analysis.Frontiers in public health · 2022Pooled it
- Inter-observer Variability in the Analysis of CO-RADS Classification for COVID-19 Patients.Tropical medicine and infectious disease · 2023Article
- Diagnostic performance of standardized typical CT findings for COVID-19: a systematic review and meta-analysis.Insights into imaging · 2023Article
- Utility of chest radiograph severity scoring in emergency department for predicting outcomes in COVID-19: A study of 1275 patients.Clinical imaging · 2023Article
- A Systematic Review of Chest Imaging Findings in Long COVID Patients.Journal of personalized medicine · 2023Review
- Chest computed tomography of suspected COVID-19 pneumonia in the Emergency Department: comparative analysis between patients with different vaccination status.Polish journal of radiology · 2023Article
- Diagnostic Performance in Differentiating COVID-19 from Other Viral Pneumonias on CT Imaging: Multi-Reader Analysis Compared with an Artificial Intelligence-Based Model.Tomography (Ann Arbor, Mich.) · 2022Article
- Chest imaging in pregnant patients with COVID-19: Recommendations, justification, and optimization.Acta radiologica open · 2022Review
- Spectrum of opportunistic fungal lung co-infections in COVID-19: What the radiologist needs to know.RadiologiaArticle
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Authors and funding
10 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo measure the diagnostic accuracy and inter-observer agreement with the use of COVID-19 Reporting and Data System (CO-RADS) for detection of COVID-19 on CT chest imaging.
methodsThis retrospective study included 164 consecutive patients with clinical suspicion of COVID-19 in whom a CT chest examination was performed at a single institution between April 2020 and July 2020. Of them, 101 patients was RT-PCR positive for COVID-19. Six readers with varying radiological experience (two each of chest radiologists, general radiologists, and radiologists in training) independently assigned a CO-RADS assessment category for each CT chest study. The Fleiss' K was used to quantify inter-observer agreement. The inter-observer agreement was also assessed based on the duration of onset of symptoms to CT scan. ROC curve analysis was used to determine the diagnostic accuracy of CO-RADS. The area under curve was calculated to determine the reader accuracy for detection of COVID-19 lung involvement with RT-PCR as reference standards. The data sets were plotted in ROC space, and Youden's J statistic was calculated to determine the threshold cut-off CO-RADS category for COVID-19 positivity.
resultsThere was overall moderate inter-observer agreement between all readers (Fleiss' K 0.54 [95% CI 0.54, 0.54]), with substantial agreement among chest radiologists (Fleiss' K 0.68 [95% CI 0.67, 0.68]), general radiologists (Fleiss' K 0.61 [95% CI 0.61, 0.61]), and moderate agreement among radiologists-in-training (Fleiss' K 0.56 [95% CI 0.56, 0.56]). There was overall moderate inter-observer agreement in early disease (stages 1 and 2), with cumulative Fleiss' K 0.45 [95% CI 0.45, 0.45]). The overall AUC for CO-RADS lexicon scheme to accurately diagnose COVID-19 yielded 0.92 (95% CI 0.91, 0.94) with strong concordance within and between groups, of chests radiologists with AUC of 0.91 (95% CI 0.88, 0.94), general radiologists with AUC 0.96 (95% CI 0.94, 0.98), and radiologists in training with AUC of 0.90 (95% CI 0.87, 0.94). For detecting COVID-19, ROC curve analysis yielded CO-RADS > 3 as the cut-off threshold with sensitivity 90% (95% CI 0.88, 0.93), and specificity of 87% (95% CI 0.83, 0.91).
conclusionReaders across different levels of experience could accurately identify COVID-19 positive patients using the CO-RADS lexicon with moderate inter-observer agreement and high diagnostic accuracy.
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