Ye Wenjing, Lu Weiwei, Tang Yanping, Chen Guoxi, Li Xiaopan, Ji Chen, Hou Min, Zeng Guangwang, Lan Xing, Wang Yaling, Deng Xiaoqin, Cai Yuyang, Huang Hai, Yang Ling
Department of Respiratory Medicine, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Department of Emergency, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Front Med (Lausanne). 2020 Nov 12;7:570614. doi: 10.3389/fmed.2020.570614. eCollection 2020.
COVID-19 has been quickly spreading, making it a serious public health threat. It is important to identify phenotypes to predict the severity of disease and design an individualized treatment. We collected data from 213 COVID-19 patients in Wuhan Pulmonary Hospital from January 1 to March 30, 2020. Principal component analysis (PCA) and cluster analysis were used to classify patients. We identified three distinct subgroups of COVID-19. Cluster 1 was the largest group (52.6%) and characterized by oldest age, lowest cellular immune function, and albumin levels. 38.5% of subjects were grouped into Cluster 2. Most of the lab results in Cluster 2 fell between those of Clusters 1 and 3. Cluster 3 was the smallest cluster (8.9%), characterized by youngest age and highest cellular immune function. The incidence of respiratory failure, acute respiratory distress syndrome (ARDS), heart failure, and usage of non-invasive mechanical ventilation in Cluster 1 was significantly higher than others ( < 0.05). Cluster 1 had the highest death rate of 30.4% ( = 0.005). Although there were significant differences in age between Clusters 2 and 3 ( < 0.001), we found that there was no difference in demand for medical resources. We identified three distinct clusters of the COVID-19 patients. The results show that age alone could not be used to assess a patient's condition. Specifically, management of albumin, and immune function are important in reducing the severity of disease.
新型冠状病毒肺炎（COVID-19）迅速传播，构成严重的公共卫生威胁。识别表型对于预测疾病严重程度和设计个体化治疗至关重要。我们收集了2020年1月1日至3月30日期间武汉肺科医院213例COVID-19患者的数据。采用主成分分析（PCA）和聚类分析对患者进行分类。我们识别出COVID-19的三个不同亚组。第1组是最大的组（52.6%），其特征为年龄最大、细胞免疫功能最低和白蛋白水平最低。38.5%的受试者被归入第2组。第2组的大多数实验室结果介于第1组和第3组之间。第3组是最小的组（8.9%），其特征为年龄最小和细胞免疫功能最高。第1组呼吸衰竭、急性呼吸窘迫综合征（ARDS）、心力衰竭的发生率以及无创机械通气的使用率均显著高于其他组（<0.05）。第1组的死亡率最高，为30.4%（=0.005）。尽管第2组和第3组在年龄上存在显著差异（<0.001），但我们发现两组在医疗资源需求方面没有差异。我们识别出COVID-19患者的三个不同聚类。结果表明，仅年龄不能用于评估患者病情。具体而言，白蛋白管理和免疫功能在降低疾病严重程度方面很重要。
