This study aimed to compare the chest computed tomography (CT) findings between survivors and non-survivors with Coronavirus Disease 2019 (COVID-19). Between 12 January 2020 and 20 February 2020, the records of 124 consecutive patients diagnosed with COVID-19 were retrospectively reviewed and divided into survivor (83/124) and non-survivor (41/124) groups. Chest CT findings were qualitatively compared on admission and serial chest CT scans were semi-quantitively evaluated between two groups using curve estimations. On admission, significantly more bilateral (97.6% vs. 73.5%, p = 0.001) and diffuse lesions (39.0% vs. 8.4%, p < 0.001) with higher total CT score (median 10 vs. 4, p < 0.001) were observed in non-survivor group compared with survivor group. Besides, crazy-paving pattern was more predominant in non-survivor group than survivor group (39.0% vs. 12.0%, p < 0.001). From the prediction of curve estimation, in survivor group total CT score increased in the first 20 days reaching a peak of 6 points and then gradually decreased for more than other 40 days (R = 0.545, p < 0.001). In non-survivor group, total CT score rapidly increased over 10 points in the first 10 days and gradually increased afterwards until ARDS occurred with following death events (R = 0.711, p < 0.001). In conclusion, persistent progression with predominant crazy-paving pattern was the major manifestation of COVID-19 in non-survivors. Understanding this CT feature could help the clinical physician to predict the prognosis of the patients.
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http://dx.doi.org/10.1038/s41598-020-68057-4 | DOI Listing |
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Department of Biomedical Sciences, Humanitas University, Milan, Italy; Department of Hepatobiliary & General Surgery, IRCCS Humanitas Research Hospital, Milan, Italy. Electronic address:
Background: Communicating vessels among hepatic veins in patients with tumors invading/compressing hepatic veins at their caval confluence facilitate new surgical solutions. Although their recognition by intraoperative ultrasound has been described, the possibility of preoperative detection still remains uncertain. We aimed to develop a model to predict their presence before surgery.
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Chiba University Center for Frontier Medical Engineering, 1-33 Yayoi-cho, Inage-ku, Chiba, Chiba, 263-8522, JAPAN.
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Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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View Article and Find Full Text PDFMedicine (Baltimore)
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Department of Medical Imaging, Jincheng People's Hospital, Shanxi, China.
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