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基于胸部 CT 扫描的 COVID-19 肺炎患者疾病严重程度的识别、监测和预测:一项回顾性研究。

Identification, Monitoring, and Prediction of Disease Severity in Patients with COVID-19 Pneumonia Based on Chest Computed Tomography Scans: A Retrospective Study.

机构信息

Department of Radiology, Health Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.

Gastroenterology and Liver Diseases Research Center,Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

出版信息

Adv Exp Med Biol. 2021;1321:265-275. doi: 10.1007/978-3-030-59261-5_24.

Abstract

Background and Aims Non-contrast chest computed tomography (CT) scans can accurately evaluate the type and extent of lung lesions. The aim of this study was to investigate the chest CT features associated with critical and non-critical patients with coronavirus disease 2019 (COVID-19). Methods A total of 1078 patients with COVID-19 pneumonia who underwent chest CT scans, including 169 critical cases and 909 non-critical cases, were enrolled in this retrospective study. The scans of all participants were reviewed and compared in two groups of study. In addition, the risk factors associated with disease in critical and non-critical patients were analyzed. Results Chest CT scans showed bilateral and multifocal involvement in most (86.4%) of the participants, with 97.6 and 84.3% reported in critical and non-critical patients, respectively. The incidences of pure consolidation (p = 0.019), mixed ground-glass opacities (GGOs) and consolidation (p < 0.001), pleural effusion (p < 0.001), and intralesional traction bronchiectasis (p = 0.007) were significantly higher in critical compared to non-critical patients. However, non-critical patients showed higher incidence of pure GGOs than the critical patients (p < 0.001). Finally, the total opacity scores of the critical patients were significantly higher than those of non-critical patients (13.71 ± 6.26 versus 4.86 ± 3.52, p < 0.001), with an area under the curve of 0.91 (0.88-0.94) for COVID-19 detection. Conclusions Our results revealed that the chest CT examination was an effective means of detecting pulmonary parenchymal abnormalities in the natural course of COVID-19. It can distinguish the critical patients from the non-critical patients (AUC = 0.91), which is helpful for the judgment of clinical condition and has important clinical value for the diagnosis and follow-up of COVID-19 pneumonia.

摘要

背景与目的

非对比胸部 CT 扫描可准确评估肺部病变的类型和范围。本研究旨在探讨与 2019 年冠状病毒病(COVID-19)重症和非重症患者相关的胸部 CT 特征。

方法

本回顾性研究共纳入 1078 例 COVID-19 肺炎患者,包括 169 例重症患者和 909 例非重症患者。对所有患者的 CT 扫描进行回顾性分析,并在两组患者中进行比较。此外,还分析了与重症和非重症患者疾病相关的危险因素。

结果

胸部 CT 扫描显示,大多数患者(86.4%)存在双侧和多灶性受累,重症患者和非重症患者的受累比例分别为 97.6%和 84.3%。纯实变(p=0.019)、混合磨玻璃影(GGO)和实变(p<0.001)、胸腔积液(p<0.001)和支气管内牵引性支扩(p=0.007)的发生率在重症患者中显著高于非重症患者。然而,非重症患者的纯 GGO 发生率高于重症患者(p<0.001)。最后,重症患者的总密度评分明显高于非重症患者(13.71±6.26 与 4.86±3.52,p<0.001),COVID-19 检测的曲线下面积为 0.91(0.88-0.94)。

结论

我们的结果表明,胸部 CT 检查是检测 COVID-19 自然病程中肺实质异常的有效手段。它可以区分重症和非重症患者(AUC=0.91),有助于判断临床病情,对 COVID-19 肺炎的诊断和随访具有重要的临床价值。

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