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Dynamic Changes of Chest CT Follow-up In Coronavirus Disease-19 (COVID-19) Pneumonia: Relationship To Clinical Typing (preprint)
researchsquare; 2020.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-20399.v1
ABSTRACT
ObjectivesTo investigate the  CT changes of  different clinical  types  of  COVID-19 pneumonia.MethodsThis retrospective study included 50 confirmed patients with COVID-19 from 16 January 2020 to 25 February 2020. We analyzed the clinical and CT characteristics of the patients between the moderate group and the severe and critical group, and the dynamic changes of severity with the CT follow-up time.ResultsThere were no differences in the occurrence rate of CT characteristics between the moderate group (n=34) and the severe and critical group (n=16) in the initial CT (all p >0.05). There were differences in the CT score of right lung and total CT score at the initial CT between the two groups (all p <0.05). There was a quadratic relationship between total CT score and CT follow-up time in the severe and critical group (r2=0.137, p=0.008), the total CT severity score peaked at the second follow-up CT. There was no correlation between total CT score and CT follow-up time in the moderate group (p >0.05). The total CT score of the severe and critical group was different between the initial and first follow-up, the second and third follow-ups, the third and fourth follow-ups, and the fourth and fifth follow-ups CT (all p<0.05). The total CT score of the moderate group was different between the second and third follow-ups CT (p<0.05).ConclusionsCOVID-19 pneumonia with the severe and critical types progressed rapidly with the greatest severity at the second follow-up CT, and the moderate type was relatively stable.
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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: Pneumonia / COVID-19 Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: Pneumonia / COVID-19 Language: English Year: 2020 Document Type: Preprint