高级检索
当前位置: 首页 > 详情页

CD8+ T cells predicted the conversion of common covid-19 to severe.

文献详情

资源类型:
Pubmed体系:
机构: [1]Department of Liver Disease, The Third People’s Hospital of Kunming City, Yunnan, China [2]Department of Infectious Diseases, The First People’s Hospital of Zaoyang City, Hubei, China
出处:

摘要:
To evaluate the predictive effect of T-lymphoid subsets on the conversion of common covid-19 to severe. The laboratory data were collected retrospectively from common covid-19 patients in the First People's Hospital of Zaoyang, Hubei Province, China and the Third People's Hospital of Kunming, Yunnan Province, China, between January 20, 2020 and March 15, 2020 and divided into training set and validation set. Univariate and multivariate logistic regression was performed to investigate the risk factors for the conversion of common covid-19 to severe in the training set, the prediction model was established and verified externally in the validation set. 60 (14.71%) of 408 patients with common covid-19 became severe in 6-10 days after diagnosis. Univariate and multiple logistic regression analysis revealed that lactate (P = 0.042, OR = 1097.983, 95% CI 1.303, 924,798.262) and CD8+ T cells (P = 0.010, OR = 0.903, 95% CI 0.835, 0.975) were independent risk factors for general type patients to turn to severe type. The area under ROC curve of lactate and CD8+ T cells was 0.754 (0.581, 0.928) and 0.842 (0.713, 0.970), respectively. The actual observation value was highly consistent with the prediction model value in curve fitting. The established prediction model was verified in 78 COVID-19 patients in the verification set, the area under the ROC curve was 0.906 (0.861, 0.981), and the calibration curve was consistent. CD8+ T cells, as an independent risk factor, could predict the transition from common covid-19 to severe.

基金:
语种:
PubmedID:
中科院(CAS)分区:
出版当年[2021]版:
大类 | 3 区 综合性期刊
小类 | 3 区 综合性期刊
最新[2023]版:
大类 | 2 区 综合性期刊
小类 | 2 区 综合性期刊
第一作者:
第一作者机构: [1]Department of Liver Disease, The Third People’s Hospital of Kunming City, Yunnan, China
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:82478 今日访问量:0 总访问量:681 更新日期:2025-01-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 云南省第一人民医院 技术支持:重庆聚合科技有限公司 地址:云南省昆明市西山区金碧路157号