基于 CT 的胸部肌肉指标预测 COVID-19 患者的预后。
CT-derived Chest Muscle Metrics for Outcome Prediction in Patients with COVID-19.
机构信息
From the Unit of Radiology (S.S., L.A.C., F. Secchi, F. Sardanelli) and High Specialty Center for Dietetics, Nutritional Education and Cardiometabolic Prevention (A.E.M.), Istituto di Ricovero e Cura a Carattere Scientifico Policlinico San Donato, Via Rodolfo Morandi 30, 20097 San Donato Milanese, Milan, Italy; Department of Biomedicine, Neurosciences and Advanced Diagnostics, Section of Radiological Sciences, Università degli Studi di Palermo, Palermo, Italy (D.A.); Unit of Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Ortopedico Galeazzi, Milan, Italy (D.A., C.M., L.M.S.); Department of Biomedical Sciences for Health (A. Cozzi, S.G., F. Secchi, F. Sardanelli, L.M.S.), Postgraduate School in Radiodiagnostics (S.C., E.D., C.D.B., G.D.P.), and Department of Oncology and Hematology-Oncology (G.M., A.V.), Università degli Studi di Milano, Milan, Italy; Division of Radiodiagnostics, Department of Diagnosis and Treatment Services, Azienda Ospedaliero Universitaria Maggiore della Carità, Novara, Italy (R.A., A. Carriero, P.S.C.D., Z.F., A.P., D.Z.); Department of Radiology, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy (C.B., L.M.); Department of Radiology, Ospedale Santissima Annunziata, Cento, Italy (A.B., R.R.); Department of Translational Medicine, Università degli Studi del Piemonte Orientale, Novara, Italy (A. Carriero); Division of Interventional Radiology, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Europeo di Oncologia, Milan, Italy (G.M.); and Azienda Socio-Sanitaria Territoriale (ASST) Grande Ospedale Metropolitano Niguarda, Milan, Italy (A.V., V.T., I.V.).
出版信息
Radiology. 2021 Aug;300(2):E328-E336. doi: 10.1148/radiol.2021204141. Epub 2021 Mar 16.
Background Lower muscle mass is a known predictor of unfavorable outcomes, but its prognostic impact on patients with COVID-19 is unknown. Purpose To investigate the contribution of CT-derived muscle status in predicting clinical outcomes in patients with COVID-19. Materials and Methods Clinical or laboratory data and outcomes (intensive care unit [ICU] admission and death) were retrospectively retrieved for patients with reverse transcriptase polymerase chain reaction-confirmed SARS-CoV-2 infection, who underwent chest CT on admission in four hospitals in Northern Italy from February 21 to April 30, 2020. The extent and type of pulmonary involvement, mediastinal lymphadenopathy, and pleural effusion were assessed. Cross-sectional areas and attenuation by paravertebral muscles were measured on axial CT images at the T5 and T12 vertebral level. Multivariable linear and binary logistic regression, including calculation of odds ratios (ORs) with 95% CIs, were used to build four models to predict ICU admission and death, which were tested and compared by using receiver operating characteristic curve analysis. Results A total of 552 patients (364 men and 188 women; median age, 65 years [interquartile range, 54-75 years]) were included. In a CT-based model, lower-than-median T5 paravertebral muscle areas showed the highest ORs for ICU admission (OR, 4.8; 95% CI: 2.7, 8.5; < .001) and death (OR, 2.3; 95% CI: 1.0, 2.9; = .03). When clinical variables were included in the model, lower-than-median T5 paravertebral muscle areas still showed the highest ORs for both ICU admission (OR, 4.3; 95%: CI: 2.5, 7.7; < .001) and death (OR, 2.3; 95% CI: 1.3, 3.7; = .001). At receiver operating characteristic analysis, the CT-based model and the model including clinical variables showed the same area under the receiver operating characteristic curve (AUC) for ICU admission prediction (AUC, 0.83; = .38) and were not different in terms of predicting death (AUC, 0.86 vs AUC, 0.87, respectively; = .28). Conclusion In hospitalized patients with COVID-19, lower muscle mass on CT images was independently associated with intensive care unit admission and in-hospital mortality. © RSNA, 2021
背景 肌肉量减少是预测不良结局的已知指标，但它对 COVID-19 患者的预后影响尚不清楚。目的 研究 CT 衍生的肌肉状态对预测 COVID-19 患者临床结局的贡献。材料与方法 回顾性检索 2020 年 2 月 21 日至 4 月 30 日意大利北部 4 家医院因逆转录酶聚合酶链反应确诊 SARS-CoV-2 感染而入院的患者的临床或实验室数据和结局（入住重症监护病房[ICU]和死亡）。评估肺部受累程度和类型、纵隔淋巴结病和胸腔积液。在轴向 CT 图像上测量 T5 和 T12 椎体水平的椎旁肌肉的横截面积和衰减。使用多元线性和二项逻辑回归，包括计算 95%置信区间的比值比（OR），建立了 4 个预测 ICU 入住和死亡的模型，通过接受者操作特征曲线分析进行了测试和比较。结果 共纳入 552 例患者（364 例男性和 188 例女性；中位年龄 65 岁[四分位距：54-75 岁]）。在基于 CT 的模型中，低于中位数的 T5 椎旁肌肉面积显示出 ICU 入住的最高 OR（OR：4.8；95%CI：2.7，8.5；<0.001）和死亡（OR：2.3；95%CI：1.0，2.9；=0.03）。当纳入模型的临床变量时，低于中位数的 T5 椎旁肌肉面积仍然显示出 ICU 入住（OR：4.3；95%CI：2.5，7.7；<0.001）和死亡（OR：2.3；95%CI：1.3，3.7；=0.001）的最高 OR。在接受者操作特征分析中，基于 CT 的模型和纳入临床变量的模型对 ICU 入住预测具有相同的接受者操作特征曲线下面积（AUC）（AUC：0.83；=0.38），且在预测死亡方面没有差异（AUC：0.86 与 AUC：0.87，分别；=0.28）。结论 在住院 COVID-19 患者中，CT 图像上的肌肉减少量与入住 ICU 和院内死亡率独立相关。
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