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基于早期临床特征的COVID-19肺炎进展为严重症状的预后因素:一项回顾性分析。

Prognostic Factors for COVID-19 Pneumonia Progression to Severe Symptoms Based on Earlier Clinical Features: A Retrospective Analysis.

作者信息

Huang Huang, Cai Shuijiang, Li Yueping, Li Youxia, Fan Yinqiang, Li Linghua, Lei Chunliang, Tang Xiaoping, Hu Fengyu, Li Feng, Deng Xilong

机构信息

Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.

出版信息

Front Med (Lausanne). 2020 Oct 5;7:557453. doi: 10.3389/fmed.2020.557453. eCollection 2020.

Abstract

Approximately 15-20% of COVID-19 patients will develop severe pneumonia, and about 10% of these will die if not properly managed. Earlier discrimination of potentially severe patients basing on routine clinical and laboratory changes and commencement of prophylactical management will not only save lives but also mitigate the otherwise overwhelming healthcare burden. In this retrospective investigation, the clinical and laboratory features were collected from 125 COVID-19 patients who were classified into mild (93 cases) or severe (32 cases) groups according to their clinical outcomes after 3-7 days post-admission. The subsequent analysis with single-factor and multivariate logistic regression methods indicated that 17 factors on admission differed significantly between mild and severe groups but that only comorbidity with underlying diseases, increased respiratory rate (>24/min), elevated C-reactive protein (CRP >10 mg/L), and lactate dehydrogenase (LDH >250 U/L) were independently associated with the later disease development. Finally, we evaluated their prognostic values with receiver operating characteristic curve (ROC) analysis and found that the above four factors could not confidently predict the occurrence of severe pneumonia individually, though a combination of fast respiratory rate and elevated LDH significantly increased the predictive confidence (AUC = 0.944, sensitivity = 0.941, and specificity = 0.902). A combination consisting of three or four factors could further increase the prognostic value. Additionally, measurable serum viral RNA post-admission independently predicted the severe illness occurrence. In conclusion, a combination of general clinical characteristics and laboratory tests could provide a highly confident prognostic value for identifying potentially severe COVID-19 pneumonia patients.

摘要

约15%-20%的新冠病毒疾病(COVID-19)患者会发展为重症肺炎,其中约10%若未得到妥善治疗将会死亡。基于常规临床和实验室变化早期鉴别出潜在的重症患者并开始预防性治疗,不仅能挽救生命,还能减轻原本不堪重负的医疗负担。在这项回顾性研究中,收集了125例COVID-19患者的临床和实验室特征,这些患者根据入院后3-7天的临床结局被分为轻症组(93例)和重症组(32例)。随后采用单因素和多因素逻辑回归方法分析表明,入院时17个因素在轻症组和重症组之间存在显著差异,但只有合并基础疾病、呼吸频率增加(>24次/分钟)、C反应蛋白升高(CRP>10mg/L)和乳酸脱氢酶升高(LDH>250U/L)与疾病后期发展独立相关。最后,我们通过受试者工作特征曲线(ROC)分析评估了它们的预后价值,发现上述四个因素单独不能可靠地预测重症肺炎的发生,尽管呼吸频率加快和LDH升高的组合显著提高了预测可信度(AUC=0.944,灵敏度=0.94^1,特异度=0.902)。由三个或四个因素组成的组合可进一步提高预后价值。此外,入院后可检测到的血清病毒RNA可独立预测重症疾病的发生。总之,综合临床特征和实验室检查可为识别潜在的重症COVID-19肺炎患者提供高度可靠的预后价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/698c/7571455/557d94e1dccc/fmed-07-557453-g0001.jpg

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