A nomogram to predict the risk of unfavourable outcome in COVID-19: a retrospective cohort of 279 hospitalized patients in Paris area
A nomogram to predict the risk of unfavourable outcome in COVID-19: a retrospective cohort of 279 hospitalized patients in Paris area
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DOI：
10.1080/07853890.2020.1803499
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发表时间：
2020-08-12
影响因子：
4.4
通讯作者：
Galy, Adrien
中科院分区：
文献类型：
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作者：
Nguyen, Yann;Corre, Felix;Galy, Adrien
目的探讨新型冠状病毒肺炎住院患者预后不良的预测因素。方法对巴黎地区住院的COVID-19患者进行单中心回顾性队列研究。不良结果定义为需要人工通气和/或死亡。使用多变量Cox比例风险模型分析入院时的特征，以确定预测不良结局的因素。在此基础上，提出了预测14天不良预后概率的nomogram。结果2020年3月15日至4月14日期间，279例新冠肺炎患者在首次出现症状后中位时间为7天后住院。其中88例（31.5%）患者预后不良，48例入住ICU进行人工通气，40例未入住ICU死亡。多变量分析保留了年龄、超重、多呼吸、发烧、高c反应蛋白、肌钙蛋白- 1升高和淋巴细胞减少是不利结果的危险因素。建立了判别能力足够的nomogram (C-index 0.75)，预测值与观测值具有较好的一致性。结论我们确定了7个容易获得的预后因素，并提出了一个简单的nomogram早期发现有加重风险的患者，从而优化临床护理和启动特异性治疗。自2019年新型冠状病毒病大流行以来，少数患者出现严重呼吸窘迫综合征，尽管经过重症监护，仍导致死亡。在欧洲人群中缺乏识别高危患者的工具。在我们的研究中，年龄、呼吸频率、超重、体温、c反应蛋白、肌钙蛋白和淋巴细胞计数是住院成人患者不良预后的危险因素。我们提出了一个易于使用的nomogram来预测住院成人患者的不利结果，以优化临床护理和启动特异性治疗。
Objective To identify predictive factors of unfavourable outcome among patients hospitalized for COVID-19. Methods We conducted a monocentric retrospective cohort study of COVID-19 patients hospitalized in Paris area. An unfavourable outcome was defined as the need for artificial ventilation and/or death. Characteristics at admission were analysed to identify factors predictive of unfavourable outcome using multivariable Cox proportional hazard models. Based on the results, a nomogram to predict 14-day probability of poor outcome was proposed. Results Between March 15th and April 14th, 2020, 279 COVID-19 patients were hospitalized after a median of 7 days after the first symptoms. Among them, 88 (31.5%) patients had an unfavourable outcome: 48 were admitted to the ICU for artificial ventilation, and 40 patients died without being admitted to ICU. Multivariable analyses retained age, overweight, polypnoea, fever, high C-reactive protein, elevated us troponin-I, and lymphopenia as risk factors of an unfavourable outcome. A nomogram was established with sufficient discriminatory power (C-index 0.75), and proper consistence between the prediction and the observation. Conclusion We identified seven easily available prognostic factors and proposed a simple nomogram for early detection of patients at risk of aggravation, in order to optimize clinical care and initiate specific therapies.KEY MESSAGES Since novel coronavirus disease 2019 pandemic, a minority of patients develops severe respiratory distress syndrome, leading to death despite intensive care. Tools to identify patients at risk in European populations are lacking. In our series, age, respiratory rate, overweight, temperature, C-reactive protein, troponin and lymphocyte counts were risk factors of an unfavourable outcome in hospitalized adult patients. We propose an easy-to-use nomogram to predict unfavourable outcome for hospitalized adult patients to optimize clinical care and initiate specific therapies.