CT differential diagnosis of COVID-19 and non-COVID-19 in symptomatic suspects: a practical scoring method
CT differential diagnosis of COVID-19 and non-COVID-19 in symptomatic suspects: a practical scoring method
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DOI：
10.1186/s12890-020-1170-6
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发表时间：
2020-05-07
影响因子：
3.1
通讯作者：
Shen, Xinping
中科院分区：
文献类型：
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作者：
Luo, Lin;Luo, Zhendong;Shen, Xinping
背景虽然目前的研究报道了COVID-19的典型和非典型CT图像表现，但COVID-19的CT图像特征与病毒性肺炎和其他呼吸道疾病的CT图像特征有重叠。因此，很难做出专属诊断。方法纳入某综合医院确诊的COVID-19病例30例和其他病因或临床确诊的非COVID-19病例43例。收集所有患者的年龄、性别、接触史、实验室指标、病原学诊断等临床资料。使用来自显着的 COVID-19 CT 图像特征的 7 个阳性体征（后部/下叶好发、双侧受累、圆形 GGO、胸膜下带状 GGO、疯狂铺路模式、外周分布和 GGO +/- 实变）和来自其他非 COVID-19 肺炎的 4 个阴性体征（仅 1 个肺叶受累、仅中央分布、树芽征和支气管壁增厚）。比较两组（COVID-19 和非 COVID-19）的 CT 特征评分分析。结果年龄较大、腹泻症状、与武汉相关的接触史以及较低的白细胞和淋巴细胞计数显着提示 COVID-19 而不是非 COVID-19（p4，评分 >0 的敏感性为 100%，特异性为 23.26%，敏感性为 86.67%，评分特异性为67.44%> 2.结论通过基于CT影像特征的简单实用的评分系统，我们可以对COVID-19和非COVID-19进行分级诊断，并提供不同的管理建议。
BackgroundAlthough typical and atypical CT image findings of COVID-19 are reported in current studies, the CT image features of COVID-19 overlap with those of viral pneumonia and other respiratory diseases. Hence, it is difficult to make an exclusive diagnosis.MethodsThirty confirmed cases of COVID-19 and forty-three cases of other aetiology or clinically confirmed non-COVID-19 in a general hospital were included. The clinical data including age, sex, exposure history, laboratory parameters and aetiological diagnosis of all patients were collected. Seven positive signs (posterior part/lower lobe predilection, bilateral involvement, rounded GGO, subpleural bandlike GGO, crazy-paving pattern, peripheral distribution, and GGO +/- consolidation) from significant COVID-19 CT image features and four negative signs (only one lobe involvement, only central distribution, tree-in-bud sign, and bronchial wall thickening) from other non-COVID-19 pneumonia were used. The scoring analysis of CT features was compared between the two groups (COVID-19 and non-COVID-19).ResultsOlder age, symptoms of diarrhoea, exposure history related to Wuhan, and a lower white blood cell and lymphocyte count were significantly suggestive of COVID-19 rather than non-COVID-19 (p4, a sensitivity of 100% and a specificity of 23.26% for a score>0, and a sensitivity of 86.67% and a specificity of 67.44% for a score> 2.ConclusionsWith a simple and practical scoring system based on CT imaging features, we can make a hierarchical diagnosis of COVID-19 and non-COVID-19 with different management suggestions.