From the Editor The Performance of Chest CT in Evaluating the Clinical Severity of COVID-19 Pneumonia: Identifying Critical Cases Based on CT Characteristics

IF 1.1 4区医学 Q3 EDUCATION, SPECIAL

Infants & Young Children Pub Date : 2020-01-01 DOI:10.1097/iyc.000000000000017210.1097/rli.0000000000000689

P. Lyu, Xing Liu, Rui Zhang, Lei Shi, Jianbo Gao

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Abstract

Objectives The aim of this study was to assess the clinical severity of COVID-19 pneumonia using qualitative and/or quantitative chest computed tomography (CT) indicators and identify the CT characteristics of critical cases Materials and Methods Fifty-one patients with COVID-19 pneumonia including ordinary cases (group A, n = 12), severe cases (group B, n = 15), and critical cases (group C, n = 24) were retrospectively enrolled The qualitative and quantitative indicators from chest CT were recorded and compared using Fisher exact test, one-way analysis of variance, Kruskal-Wallis H test, and receiver operating characteristic analysis Results Depending on the severity of the disease, the number of involved lung segments and lobes, the frequencies of consolidation, crazy-paving pattern, and air bronchogram increased in more severe cases Qualitative indicators including total severity score for the whole lung and total score for crazy-paving and consolidation could distinguish groups B and C from A (69% sensitivity, 83% specificity, and 73% accuracy) but were similar between group B and group C Combined qualitative and quantitative indicators could distinguish these 3 groups with high sensitivity (B + C vs A, 90%;C vs B, 92%), specificity (100%, 87%), and accuracy (92%, 90%) Critical cases had higher total severity score (>10) and higher total score for crazy-paving and consolidation (>4) than ordinary cases, and had higher mean lung density (>−779 HU) and full width at half maximum (>128 HU) but lower relative volume of normal lung density (≦50%) than ordinary/severe cases In our critical cases, 8 patients with relative volume of normal lung density smaller than 40% received mechanical ventilation for supportive treatment, and 2 of them had died Conclusions A rapid, accurate severity assessment of COVID-19 pneumonia based on chest CT would be feasible and could provide help for making management decisions, especially for the critical cases

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胸部CT在评估COVID-19肺炎临床严重程度中的作用:基于CT特征识别危重病例

目的采用定性和/或定量胸部计算机断层扫描(CT)指标评估COVID-19肺炎的临床严重程度，确定危重病例的CT特征材料与方法51例COVID-19肺炎患者，包括普通病例(A组，n = 12)、重症病例(B组，n = 15)、危重病例(C组，C组)。采用Fisher精确检验、单因素方差分析、Kruskal-Wallis H检验、受试者工作特征分析等方法，记录胸部CT的定性和定量指标，并进行比较。结果根据疾病的严重程度，累及的肺节段和肺叶数量、实变频率、病理样、定性指标包括全肺严重程度总分、疯狂铺路和夯实总分均能区分B、C组与A组(灵敏度69%、特异性83%、准确率73%)，但B、C组间差异无统计学意义。定性和定量指标结合可区分B、C组与A组具有较高的灵敏度(B + C vs A, 90%;C vs B, 92%)、特异性(100%、87%)、准确性(92%)。危重病例的总严重程度评分(>0)高于普通病例，疯狂铺装和巩固总分(>4)高于普通病例，平均肺密度(>−779 HU)和一半最大全宽(>128 HU)高于普通/重症病例，但正常肺密度相对体积(≦50%)低于正常肺密度。我们的危重病例中，有8例正常肺密度相对体积小于40%的患者接受了机械通气支持治疗。结论基于胸部CT快速、准确地评估COVID-19肺炎的严重程度是可行的，可以为制定管理决策提供帮助，特别是对危重病例

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来源期刊

Infants & Young Children Multiple-

CiteScore

1.90

自引率

9.10%

发文量

期刊介绍： Infants & Young Children is an interdisciplinary journal focusing on vulnerable children from birth to five years of age and their families. Of special interest are articles involving innovative interventions, summaries of important research developments and their implications for practice, updates for high priority topic areas, balanced presentations of controversial issues, and articles that address issues involving policy, professional training, new conceptual models, and related matters. Although data are often presented primarily to illustrate points, some types of data-based articles may be appropriate.