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Extensive pulmonary perfusion defects compatible with microthrombosis and thromboembolic disease in severe Covid-19 pneumonia
- Source :
- Thrombosis Research, Radiology, Thrombosis research, 196, 135-137. Elsevier Limited
- Publication Year :
- 2020
- Publisher :
- Elsevier BV, 2020.
-
Abstract
- Purpose To introduce the COVID-19 Reporting and Data System (CO-RADS) for standardized assessment of pulmonary involvement of COVID-19 on non-enhanced chest CT and report its initial interobserver agreement and performance. Methods The Dutch Radiological Society (NVvR) developed CO-RADS based on other efforts for standardization, such as Lung-RADS or BI-RADS. CO-RADS assesses the suspicion for pulmonary involvement of COVID-19 on a scale from 1 (very low) to 5 (very high). The system is meant to be used in patients presenting with moderate to severe symptoms of COVID-19. The system was evaluated using 105 chest CTs of patients admitted to the hospital with clinical suspicion of COVID-19 in whom RT-PCR was performed (62 +/- 16 years, 61 men, 53 with positive RT-PCR). Eight observers assessed the scans using CO-RADS. Fleiss’ kappa was calculated, and scores of individual observers were compared to the median of the remaining seven observers. The resulting area under the receiver operating characteristics curve (AUC) was compared to results from RT-PCR and clinical diagnosis of COVID-19. Results There was absolute agreement among observers in 573 (68.2%) of 840 observations. Fleiss’ kappa was 0.47 (95% confidence interval (CI) 0.45-0.47), with the highest kappa for CO-RADS categories 1 (0.58, 95% CI 0.54-0.62) and 5 (0.68, 95% CI 0.65-0.72). The average AUC was 0.91 (95% CI 0.85-0.97) for predicting RT-PCR outcome and 0.95 (95% CI 0.91-0.99) for clinical diagnosis. The false negative rate for CO-RADS 1 was 9/161 (5.6%, 95% CI 1.0-10%), and the false positive rate for CO-RADS 5 was 1/286 (0.3%, 95% CI 0-1.0%). Conclusions CO-RADS is a categorical assessment scheme for pulmonary involvement of COVID-19 on non-enhanced chest CT providing very good performance for predicting COVID-19 in patients with moderate to severe symptoms and has a substantial interobserver agreement, especially for categories 1 and 5.
- Subjects :
- 2019-20 coronavirus outbreak
medicine.medical_specialty
Patients
Coronavirus disease 2019 (COVID-19)
SARS-CoV-2
business.industry
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
COVID-19
Hematology
medicine.disease
Gastroenterology
Article
Perfusion
Pneumonia
Internal medicine
Humans
Medicine
Disease
Thromboembolic disease
Tomography, X-Ray Computed
business
Pandemics
Original Research
Subjects
Details
- Language :
- English
- ISSN :
- 00493848
- Database :
- OpenAIRE
- Journal :
- Thrombosis Research
- Accession number :
- edsair.doi.dedup.....95f844d29b6775c845643f8eca2cb584
- Full Text :
- https://doi.org/10.1016/j.thromres.2020.08.026