Brazilian Redcross - Parana Chapter, Vicente Machado, 1310, Curitiba, Parana 80420-011, Brazil.
Brazilian Redcross - Parana Chapter, Vicente Machado, 1310, Curitiba, Parana 80420-011, Brazil; Federal University of Parana, Department of Radiology, Internal Medicine Branch, R. General Carneiro, 181, Curitiba, PR 80060-900, Brazil.
Clin Imaging. 2022 Jun;86:7-12. doi: 10.1016/j.clinimag.2022.02.005. Epub 2022 Feb 17.
COVID-19 Reporting and Data System (CO-RADS) is a tool for standardizing the reports of patients with suspected or confirmed Sars-CoV-2 infection. We performed a study of the performance of the CO-RADS in a triage scenario of patients in Brazil.
Data from 426 Computed Tomography (CT) scans from March 2020 through December 2020 were assessed in an ambidirectional, both retrospective and prospective, for the assessment in one of the six categories of the CO-RADS. We assessed sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR) Youden's index, Positive and Negative Clinical Utility Index (UC + and UC- respectively) and diagnostic odds ratio (DOR). We also plotted Receiver Operating Characteristics (ROC) curve with Area Under the Curve (AUC) for CO-RADS of >4 (4 + 5).
For CO-RADS classification > 4 (4 + 5) considered positive, the AUC obtained was of 0.89 (95% CI of 0.02), sensitivity of 78% (95% CI of 0.3), specificity of 91% (95% CI of 0.3), PPV of 0.92 (95% CI of 0.02), NPV of 0.41 (95% CI of 0.03), PLR of 0.85 (95% CI of 0.2), and NLR of 0.23 (95% CI of 0.02).
CO-RADS demonstrated overall good diagnostic performance in stratifying patients with suspected Sars-CoV-2 infection, even those without confirmed laboratorial diagnosis, therefore being useful in a triage scenario with lack of resources.
COVID-19 报告和数据系统(CO-RADS)是一种用于规范疑似或确诊 SARS-CoV-2 感染患者报告的工具。我们对巴西分诊场景中的患者进行了 CO-RADS 表现的研究。
在回顾性和前瞻性双向评估中,对 2020 年 3 月至 2020 年 12 月期间的 426 例 CT 扫描数据进行评估,以评估 CO-RADS 的六个类别之一。我们评估了敏感性、特异性、阳性预测值(PPV)、阴性预测值(NPV)、阳性似然比(PLR)、阴性似然比(NLR)、Youden 指数、阳性和阴性临床实用指数(UC+和 UC-)和诊断优势比(DOR)。我们还绘制了 CO-RADS >4(4+5)的接收者操作特征(ROC)曲线及其曲线下面积(AUC)。
对于 CO-RADS 分类>4(4+5)考虑为阳性,获得的 AUC 为 0.89(95%CI 为 0.02),敏感性为 78%(95%CI 为 0.3),特异性为 91%(95%CI 为 0.3),PPV 为 0.92(95%CI 为 0.02),NPV 为 0.41(95%CI 为 0.03),PLR 为 0.85(95%CI 为 0.2),NLR 为 0.23(95%CI 为 0.02)。
CO-RADS 在分层疑似 SARS-CoV-2 感染患者方面表现出总体良好的诊断性能,即使是那些没有确诊实验室诊断的患者,因此在资源不足的分诊场景中很有用。