Radiology Department, Hospital de Clínicas de Porto Alegre (HCPA), RS, Brazil; Postgraduate Program in Pneumological Sciences, Universidade Federal do Rio Grande do Sul, RS, Brazil.
Radiology Department, Hospital de Clínicas de Porto Alegre (HCPA), RS, Brazil.
Braz J Infect Dis. 2022 Jan-Feb;26(1):101665. doi: 10.1016/j.bjid.2021.101665. Epub 2021 Dec 18.
To evaluate the diagnostic accuracy of the Radiological Society of North America (RSNA) classification system for coronavirus disease 2019 (COVID-19) pneumonia compared to pre-pandemic chest computed tomography (CT) scan images to mitigate the risk of bias regarding the reference standard.
This was a retrospective, cross-sectional, diagnostic test accuracy study. Chest CT scans, carried out from May 1 to June 30, 2020, and from May 1 to July 17, 2017, were consecutively selected for the COVID-19 (positive reverse transcription-polymerase chain reaction [RT-PCR] for severe acute respiratory syndrome coronavirus 2 result) and control (pre-pandemic) groups, respectively. Four expert thoracic radiologists blindly interpreted each CT scan image. Sensitivity and specificity were calculated.
A total of 160 chest CT scan images were included: 79 in the COVID-19 group (56 [43.5-67] years old, 41 men) and 81 in the control group (62 [52-72] years old, 44 men). Typically, an estimated specificity of 98.5% (95% confidence interval [CI] 98.1%-98.4%) was obtained. For the indeterminate classification as a diagnostic threshold, an estimated sensitivity of 88.3% (95% CI 84.7%-91.7%) and a specificity of 79.0% (95% CI 74.5%-83.4%), with an area under the curve of 0.865 (95% CI 0.838-0.895), were obtained.
The RSNA classification system shows strong diagnostic accuracy for COVID-19 pneumonia, even against pre-pandemic controls. It can be an important aid in clinical decision-making, especially when a typical or indeterminate pattern is found, possibly advising retesting following an initial negative RT-PCR result and streamlining early management and isolation.
评估北美放射学会 (RSNA) 分类系统对 2019 年冠状病毒病 (COVID-19) 肺炎的诊断准确性，与大流行前的胸部计算机断层扫描 (CT) 图像相比，以减轻参考标准的偏倚风险。
这是一项回顾性、横断面、诊断测试准确性研究。连续选择 2020 年 5 月 1 日至 6 月 30 日和 2017 年 5 月 1 日至 7 月 17 日进行的胸部 CT 扫描，分别用于 COVID-19（严重急性呼吸综合征冠状病毒 2 的逆转录聚合酶链反应 [RT-PCR] 阳性结果）和对照组（大流行前）。四位胸部放射学专家盲法解读每一张 CT 扫描图像。计算敏感性和特异性。
共纳入 160 例胸部 CT 扫描图像：COVID-19 组 79 例（56 [43.5-67] 岁，41 例男性），对照组 81 例（62 [52-72] 岁，44 例男性）。通常，特异性估计值为 98.5%（95%置信区间 [CI] 98.1%-98.4%）。对于不确定分类作为诊断阈值，估计敏感性为 88.3%（95% CI 84.7%-91.7%）和特异性为 79.0%（95% CI 74.5%-83.4%），曲线下面积为 0.865（95% CI 0.838-0.895）。
RSNA 分类系统对 COVID-19 肺炎具有很强的诊断准确性，甚至对大流行前的对照组也是如此。它可以成为临床决策的重要辅助手段，特别是在发现典型或不确定模式时，可能会建议在最初的 RT-PCR 结果为阴性后进行再次检测，并简化早期管理和隔离。
