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CT 对 COVID-19 疑似患者不良结局的预测性能:一项两中心回顾性研究。

Predictive performance of CT for adverse outcomes among COVID-19 suspected patients: a two-center retrospective study.

机构信息

Department of Radiology, Istanbul Medeniyet University Goztepe Education and Research Hospital, Istanbul, Turkey.

Department of Radiology, University of Health Sciences Ankara City Hospital, Ankara, Turkey.

出版信息

Bosn J Basic Med Sci. 2021 Dec 1;21(6):739-745. doi: 10.17305/bjbms.2020.5466.

Abstract

The aim of the study was to compare the performance of various computed tomography (CT) reporting tools, including zonal CT visual score (ZCVS), the number of involved lobes, and Radiological Society of North America (RSNA) categorization in predicting adverse outcomes among patients hospitalized due to the lower respiratory symptoms during the coronavirus disease 2019 (COVID-19) pandemic. A total of 405 patients admitted with severe respiratory symptoms who underwent a chest CT were enrolled. The primary adverse outcome was intensive care unit (ICU) admission of patients. Predictive performances of reporting tools were compared using the area under the receiver operating characteristic curves (AUC ROC). Among the 405 patients, 39 (9.63%) required ICU support during their hospital stay. At least two or more observers reported a typical and indeterminate COVID-19 pneumonia CT pattern according to RSNA categorization in 70% (285/405) of patients. Among these, 63% (179/285) had a positive polymerase chain reaction (PCR test for the SARS-CoV-2 virus. The median number of lobes involved according to CT was higher in patients who required ICU support (median interquartile range [IQR], 5[3; 5] vs. 3[0; 5]). The median ZCVS score was higher among the patients that subsequently required ICU support (median [IQR], 4[0; 12] vs. 13[5.75; 24]). The bootstrap comparisons of AUC ROC showed significant differences between reporting tools, and the ZCVS was found to be superior (AUC ROC, 71-75%). The ZCVS score at the first admission showed a linear and significant association with adverse outcomes among patients with the lower respiratory tract symptoms during the COVID-19 pandemic.

摘要

本研究旨在比较不同 CT 报告工具的性能,包括区域性 CT 视觉评分(ZCVS)、受累肺叶数量和放射学学会北美分类(RSNA)在预测因 2019 年冠状病毒病(COVID-19)大流行而导致下呼吸道症状住院患者不良结局中的作用。共纳入 405 例因严重呼吸症状接受胸部 CT 检查的患者。主要不良结局为患者入住重症监护病房(ICU)。使用受试者工作特征曲线下面积(AUC ROC)比较报告工具的预测性能。在 405 例患者中,39 例(9.63%)在住院期间需要 ICU 支持。根据 RSNA 分类,至少有两名观察者报告了 70%(285/405)患者存在典型和不确定的 COVID-19 肺炎 CT 模式。在这些患者中,63%(179/285)的 SARS-CoV-2 病毒聚合酶链反应(PCR 检测呈阳性。根据 CT 检查,需要 ICU 支持的患者受累肺叶中位数较高(中位数[四分位距],5[3;5]比 3[0;5])。随后需要 ICU 支持的患者的 ZCVS 评分中位数较高(中位数[四分位距],4[0;12]比 13[5.75;24])。AUC ROC 的 bootstrap 比较显示报告工具之间存在显著差异,ZCVS 表现更优(AUC ROC,71-75%)。COVID-19 大流行期间,下呼吸道症状患者首次就诊时的 ZCVS 评分与不良结局呈线性显著相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8382/8554695/e93144d1e090/BJBMS-21-739-g001.jpg

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