Predictive value of chest CT scoring in COVID-19 patients in Wuhan, China: A retrospective cohort study
- PMID: 33296777
- PMCID: PMC7695948
- DOI: 10.1016/j.rmed.2020.106271
Predictive value of chest CT scoring in COVID-19 patients in Wuhan, China: A retrospective cohort study
Abstract
Background: Computed tomography (CT) findings of COVID-19 patients were demonstrated by cases series and descriptive studies, but quantitative analysis performed by clinical doctors and studies on its predictive value were rarely seen. The aim of the study is to analyze CT score in COVID-19 patients and explore its predictive value.
Materials and methods: We conducted a retrospective cohort study among confirmed COVID -19 patients with available CT images between February 8, 2020 and March 7, 2020. The lung was divided into six zones by the level of tracheal carina and the level of inferior pulmonary vein bilaterally on CT. Ground-glass opacity (GGO), consolidation, crazy-paving pattern and overall lung involvement were rated by Likert scale of 0-4 or binary as 0 or 1. Global severity score for each targeted pattern was calculated as total score of six zones.
Results: There were 53 patients and 137 CT scans included in the study. There were 18(34%) of the patients classified as moderate cases while 35(66%) patients were severe/critical cases. Severe/critical patients had higher CT scores in several types of abnormalities than moderate patients from the second week to the fourth week post symptom onset. Overall lung involvement score in the second week demonstrated predictive value for severity with a sensitivity of 81.0% and specificity of 69.2%.
Conclusions: Our modified semi-quantitative CT scoring system for COVID-19 patients demonstrated feasibility. Overall lung involvement score on the second week had predictive value for clinical severity and could be indicator for further treatment.
Keywords: COVID-19; Computed tomography; Pneumonia; Prognosis; Severity of illness.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.
Conflict of interest statement
The authors have disclosed that there is no financial, consultant, institutional, and other relationships that might lead to bias or a conflict of interest.
Figures
References
-
- Johns Hopkins University and Medicine Coronavirus resource center[EB/OL] 2020 April 30. https://coronavirus.jhu.edu/map.html Available from:
-
- National Health Commission & National Administration of Traditional Chinese Medicine Diagnosis and treatment protocol for novel coronavirus pneumonia (trial version 7) [EB/OL] 2020 Mar 29. https://www.chinadaily.com.cn/pdf/2020/1.Clinical.Protocols.for.the.Diag... Available from.
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
