Department of Emergency Medicine, Peking University Third Hospital, Beijing, China.
Department of Orthopedics, Peking University Third Hospital, Beijing, China.
Respir Med. 2021 Jan;176:106271. doi: 10.1016/j.rmed.2020.106271. Epub 2020 Nov 28.
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.
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.
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%.
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.
COVID-19 患者的计算机断层扫描(CT)表现已有病例系列和描述性研究进行了展示,但很少有临床医生进行定量分析和研究其预测价值。本研究旨在分析 COVID-19 患者的 CT 评分并探讨其预测价值。
我们对 2020 年 2 月 8 日至 3 月 7 日期间有 CT 图像的确诊 COVID-19 患者进行了回顾性队列研究。在 CT 上,通过气管隆嵴水平和双侧肺下静脉水平将肺分为六个区。通过 0-4 分或二进制(0 或 1)的李克特量表对磨玻璃影(GGO)、实变、铺路石征和整体肺受累进行评分。每个靶模式的总体严重程度评分计算为六个区的总分。
共纳入 53 例患者和 137 次 CT 扫描。18 例(34%)患者为中度病例,35 例(66%)患者为重度/危重症病例。从症状出现后第二周到第四周,重度/危重症患者的几种异常类型的 CT 评分均高于中度患者。第二周的整体肺受累评分对严重程度具有预测价值,敏感性为 81.0%,特异性为 69.2%。
我们改良的 COVID-19 患者半定量 CT 评分系统具有可行性。第二周的整体肺受累评分对临床严重程度具有预测价值,可作为进一步治疗的指标。