Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics.
Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics.
复制标题
胸部CT和临床特征对COVID-19肺炎患者疾病进展的早期预测。
DOI：
10.1038/s41467-020-18786-x
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发表时间：
2020-10-02
影响因子：
16.6
通讯作者：
Wang W
中科院分区：
文献类型：
--
作者：
Feng Z;Yu Q;Yao S;Luo L;Zhou W;Mao X;Li J;Duan J;Yan Z;Yang M;Tan H;Ma M;Li T;Yi D;Mi Z;Zhao H;Jiang Y;He Z;Li H;Nie W;Liu Y;Zhao J;Luo M;Liu X;Rong P;Wang W
2019冠状病毒病（COVID-19）的爆发迅速蔓延，成为全球性的紧急情况。早期识别有进展风险的患者可能有助于更个性化的治疗计划和优化医疗资源的利用。在此，我们对中度COVID-19肺炎患者进行了一项多中心回顾性研究，以研究胸部计算机断层扫描（CT）和临床特征对患者风险分层的实用性。我们的研究结果表明，CT严重程度评分与炎症水平相关，年龄较大，较高的嗜中性粒细胞与淋巴细胞比率（NLR）和入院时的CT严重程度评分是短期进展的独立危险因素。基于这些风险因素的列线图显示了推导和验证队列中的良好校准和区分。这些发现对预测COVID-19肺炎患者入院时的进展风险具有意义。CT检查有助于危险分层和指导入院时机。早期识别有进展风险的COVID-19患者可能有助于制定更个性化的治疗计划。在这里，作者开发了一个在线列线图，结合CT严重程度评分和临床特征，用于早期预测COVID-19肺炎患者的疾病进展风险。
The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread to become a worldwide emergency. Early identification of patients at risk of progression may facilitate more individually aligned treatment plans and optimized utilization of medical resource. Here we conducted a multicenter retrospective study involving patients with moderate COVID-19 pneumonia to investigate the utility of chest computed tomography (CT) and clinical characteristics to risk-stratify the patients. Our results show that CT severity score is associated with inflammatory levels and that older age, higher neutrophil-to-lymphocyte ratio (NLR), and CT severity score on admission are independent risk factors for short-term progression. The nomogram based on these risk factors shows good calibration and discrimination in the derivation and validation cohorts. These findings have implications for predicting the progression risk of COVID-19 pneumonia patients at the time of admission. CT examination may help risk-stratification and guide the timing of admission. Early identification of COVID-19 patients at risk of progression may facilitate more individually aligned treatment plans. Here the authors develop an online nomogram incorporating CT severity score and clinical characteristics for early predicting the disease progression risk among COVID-19 pneumonia patients.
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DOI：
10.1038/nrmicro.2016.81
发表时间：
2016-08
期刊：
Nature reviews. Microbiology
影响因子：
--
作者：
de Wit E;van Doremalen N;Falzarano D;Munster VJ
通讯作者：
Munster VJ
影响因子：
3.7
作者：
Curbelo J;Luquero Bueno S;Galván-Román JM;Ortega-Gómez M;Rajas O;Fernández-Jiménez G;Vega-Piris L;Rodríguez-Salvanes F;Arnalich B;Díaz A;Costa R;de la Fuente H;Lancho Á;Suárez C;Ancochea J;Aspa J
通讯作者：
Aspa J
影响因子：
168.9
作者：
Huang, Chaolin;Wang, Yeming;Cao, Bin
通讯作者：
Cao, Bin
影响因子：
28.2
作者：
Liu, Yuwei;Du, Xuebei;Zhao, Yan
通讯作者：
Zhao, Yan
预测病毒性肺炎患者死亡风险的临床特征：MuLBSTA 评分
影响因子：
5.2
作者：
Guo, Lingxi;Wei, Dong;Qu, Jieming
通讯作者：
Qu, Jieming