COVID-19 的胸部 CT 研究：STOIC 项目。
Study of Thoracic CT in COVID-19: The STOIC Project.
机构信息
From the Department of Radiology, Université de Paris, APHP, Hôpital Cochin, 27 rue du Fg Saint Jacques, 75014 Paris, France (M.P.R., I.S., G.C., S. Bennani, F.B., S.D., C.H., C.J.); Department of Radiology, Sorbonne Université, APHP, Hôpital Pitié Salpétrière, Paris, France (S. Boussouar, A.R.); Department of Radiology, Université de Paris, APHP, Hôpital Saint-Louis, Paris, France (C.d.M.M.); Department of Radiology, Université Rennes 1, Hôpital Pontchaillou, Rennes, France (T.L., M.L.); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Raymond Poincaré, Garches, France (D.M.); Department of Radiology, Sorbonne Université, APHP, Hôpital Tenon, Paris, France (A.M.); Department of Radiology, Université de Strasbourg, Hôpital de Hautepierre, Strasbourg, France (S.M.); Department of Radiology, Université de Paris, APHP, Hôpital Bichat, Paris, France (M.P.D., A.K.); Department of Radiology, Université de Strasbourg, Nouvel Hôpital Civil, Strasbourg, France (M.O.); Department of Radiology, Université de Montpellier, Hôpital Arnaud de Villeneuve, Montpellier France (S. Bommart); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Ambroise Paré, Boulogne, France (M.E.H.); Department of Radiology, Université de Lorraine, Hôpital Brabois, Vandoeuvre, France (I.P.); Department of Radiology, Université de Paris, APHP, Hôpital Européen Georges Pompidou, INSERM U970, PARCC, Paris, France (L.F.); Department of Radiology, Sorbonne Université, APHP, Hôpital Avicenne, Bobigny, France (P.Y.B.); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Bicêtre, Le Kremlin-Bicêtre, France (M.F.B.); Department of Radiology, Université Paris-Saclay, APHP, Hôpital Antoine Béclère, Clamart, France (L.R.); Department of Radiology, Université de Paris, APHP, Hôpital Lariboisière, Paris, France (V.B.); Department of Radiology, Université Claude Bernard Lyon 1, Hospices Civils de Lyon, Hôpital Lyon Sud, Pierre-Benite, France (P.R.); Department of Radiology, Université de Paris, APHP, Hôpital Beaujon, Clichy, France (J.G.); Department of Radiology, Université Paris Est, APHP, Hôpital Henri Mondor, Créteil, France (J.F.D.); Departments of Radiology (E.D.) and Clinical Epidemiology (R.P.), Université de Paris, APHP, Hôtel-Dieu, Paris, France; Sorbonne Université, APHP, Hôpital Avicenne, Department of Pneumology, INSERM UMR 1272, Bobigny, France (D.V.); and Université de Paris APHP, Clinical Research Unit Paris Centre, Paris, France (L.J., H.A.).
出版信息
Radiology. 2021 Oct;301(1):E361-E370. doi: 10.1148/radiol.2021210384. Epub 2021 Jun 29.
Background There are conflicting data regarding the diagnostic performance of chest CT for COVID-19 pneumonia. Disease extent at CT has been reported to influence prognosis. Purpose To create a large publicly available data set and assess the diagnostic and prognostic value of CT in COVID-19 pneumonia. Materials and Methods This multicenter, observational, retrospective cohort study involved 20 French university hospitals. Eligible patients presented at the emergency departments of the hospitals involved between March 1 and April 30th, 2020, and underwent both thoracic CT and reverse transcription-polymerase chain reaction (RT-PCR) testing for suspected COVID-19 pneumonia. CT images were read blinded to initial reports, RT-PCR, demographic characteristics, clinical symptoms, and outcome. Readers classified CT scans as either positive or negative for COVID-19 based on criteria published by the French Society of Radiology. Multivariable logistic regression was used to develop a model predicting severe outcome (intubation or death) at 1-month follow-up in patients positive for both RT-PCR and CT, using clinical and radiologic features. Results Among 10 930 patients screened for eligibility, 10 735 (median age, 65 years; interquartile range, 51-77 years; 6147 men) were included and 6448 (60%) had a positive RT-PCR result. With RT-PCR as reference, the sensitivity and specificity of CT were 80.2% (95% CI: 79.3, 81.2) and 79.7% (95% CI: 78.5, 80.9), respectively, with strong agreement between junior and senior radiologists (Gwet AC1 coefficient, 0.79). Of all the variables analyzed, the extent of pneumonia at CT (odds ratio, 3.25; 95% CI: 2.71, 3.89) was the best predictor of severe outcome at 1 month. A score based solely on clinical variables predicted a severe outcome with an area under the curve of 0.64 (95% CI: 0.62, 0.66), improving to 0.69 (95% CI: 0.6, 0.71) when it also included the extent of pneumonia and coronary calcium score at CT. Conclusion Using predefined criteria, CT reading is not influenced by reader's experience and helps predict the outcome at 1 month. ClinicalTrials.gov identifier: NCT04355507 Published under a CC BY 4.0 license. See also the editorial by Rubin in this issue.
背景 关于胸部 CT 对 COVID-19 肺炎的诊断性能，存在相互矛盾的数据。据报道，CT 上的疾病程度会影响预后。目的 创建一个大型的公开可用数据集，并评估 CT 在 COVID-19 肺炎中的诊断和预后价值。材料与方法 这项多中心、观察性、回顾性队列研究涉及 20 家法国大学医院。符合条件的患者于 2020 年 3 月 1 日至 4 月 30 日期间在参与医院的急诊科就诊，均接受了胸部 CT 和逆转录-聚合酶链反应（RT-PCR）检测，以疑似 COVID-19 肺炎。CT 图像由法国放射学会发布的标准进行阅读，以评估是否为 COVID-19 阳性。多变量逻辑回归用于在 RT-PCR 和 CT 均为阳性的患者中，使用临床和影像学特征，建立预测 1 个月随访时严重结局（插管或死亡）的模型。结果 在筛选出的 10930 名符合条件的患者中，有 10735 名（中位年龄 65 岁；四分位距 51-77 岁；6147 名男性）被纳入研究，其中 6448 名（60%）的 RT-PCR 结果为阳性。以 RT-PCR 为参考，CT 的灵敏度和特异度分别为 80.2%（95%CI：79.3，81.2）和 79.7%（95%CI：78.5，80.9），初级和高级放射科医生之间的一致性很强（Gwet AC1 系数，0.79）。在分析的所有变量中，CT 上肺炎的范围（比值比，3.25；95%CI：2.71，3.89）是预测 1 个月时严重结局的最佳指标。仅基于临床变量的评分预测严重结局的曲线下面积为 0.64（95%CI：0.62，0.66），当它还包括 CT 上肺炎的范围和冠状动脉钙评分时，曲线下面积提高到 0.69（95%CI：0.6，0.71）。结论 使用预定义的标准，CT 阅读不受读者经验的影响，并有助于预测 1 个月时的结局。临床试验.gov 标识符：NCT04355507 在 CC BY 4.0 许可下发布。请参阅本期杂志中 Rubin 的社论。
Zotero 插件