statement Reporting and Data System, is a categorical assessment scheme for chest CT in patients suspected of COVID-19, representing the level of suspicion for pulmonary involvement. The substantial agreement among observers and its discriminatory value make it well-suited for use in clinical practice. Key results• CO-RADS, for COVID-19 Reporting and Data System, provides a standardized assessment scheme that simplifies reporting with a five-point scale of suspicion for pulmonary involvement of COVID-19 on chest CT • CO-RADS has a moderate to substantial agreement among observers with an overall Fleiss' kappa of 0.47 (95% CI 0.45-0.49).• The discriminatory power of CO-RADS for diagnosing COVID-19 was high, with a mean area under the ROC curve of 0.91 (95% CI 0.85-0.97) for positive RT-PCR results. AbbreviationsRT-PCR: reverse transcriptase-polymerase chain reaction. ROC: receiver operating characteristics. AUC: area under the ROC curve. CI: confidence interval. CT: computed tomography. IQR: interquartile range. Abstract PurposeTo 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. MethodsThe 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. ResultsThere 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%). ConclusionsCO-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.

CORADS-AI is a freely accessible deep learning algorithm that automatically assigns CO-RADS and CT severity scores to non-contrast CT scans of patients suspected of COVID-19 with high diagnostic performance.

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Several studies have shown high incidence of atherothrombotic events (ATEs) in patients with unprovoked pulmonary embolism. This association remains understudied in patients presenting with deep-vein thrombosis (DVT). We evaluated the risk factors for and the incidence of ATEs in patients with unprovoked proximal DVT, and compared it to patients with provoked DVT and reference patients without DVT. Patients with compression ultrasonography (CUS)-proven unprovoked proximal DVT, provoked DVT, and symptomatic patients in whom DVT was excluded by CUS were followed and scored for the occurrence of ATEs. A total of 1235 patients were enrolled: 170 patients with provoked, 74 patients with unprovoked DVT, and 991 patients without DVT. During follow-up, 128 ATEs occurred (incidence 6.5/100 patient-years). Adjusted hazard ratio was not different between patients with DVT and without DVT [hazard ratio 1.4; 95% confidence interval (CI) 0.76-2.4]. In contrast, patients with unprovoked DVT suffered from ATEs more frequently than provoked DVT patients (hazard ratio 3.16; 95% CI 1.1-9.1) and reference patients (hazard ratio 2.8; 95% CI 1.3-5.7). Notably, when fully adjusted for the known ATE risk factors, the risk differences between references, provoked, and unprovoked DVT patients diminished: hazard ratio 1.1 (95% CI 0.47-2.5) and 1.7 (95% CI 0.80-3.6), respectively. Our study confirms that the risk of ATEs in patients with unprovoked DVT was higher than in those with provoked DVT or reference patients. Interestingly, our results raise the question whether the known risk factors for ATE and venous thromboembolism attribute equally in pulmonary embolism and DVT patients, and contradict a causal relation between ATE and proximal DVT.