Association of Septic Shock with Mortality in Hospitalized COVID-19 Patients in Wuhan, China

IF 1.1 Q4 VIROLOGY Advances in Virology Pub Date : 2022-04-23 DOI:10.1155/2022/3178283
Shaoqiu Chen, Zitong Gao, Ling Hu, Y. Zuo, Yuanyuan Fu, Meilin Wei, Emory Zitello, G. Huang, Youping Deng
{"title":"Association of Septic Shock with Mortality in Hospitalized COVID-19 Patients in Wuhan, China","authors":"Shaoqiu Chen, Zitong Gao, Ling Hu, Y. Zuo, Yuanyuan Fu, Meilin Wei, Emory Zitello, G. Huang, Youping Deng","doi":"10.1155/2022/3178283","DOIUrl":null,"url":null,"abstract":"Purpose Septic shock is a severe complication of COVID-19 patients. We aim to identify risk factors associated with septic shock and mortality among COVID-19 patients. Methods A total of 212 COVID-19 confirmed patients in Wuhan were included in this retrospective study. Clinical outcomes were designated as nonseptic shock and septic shock. Log-rank test was conducted to determine any association with clinical progression. A prediction model was established using random forest. Results The mortality of septic shock and nonshock patients with COVID-19 was 96.7% (29/30) and 3.8% (7/182). Patients taking hypnotics had a much lower chance to develop septic shock (HR = 0.096, p=0.0014). By univariate logistic regression analysis, 40 risk factors were significantly associated with septic shock. Based on multiple regression analysis, eight risk factors were shown to be independent risk factors and these factors were then selected to build a model to predict septic shock with AUC = 0.956. These eight factors included disease severity (HR = 15, p < 0.001), age > 65 years (HR = 2.6, p=0.012), temperature > 39.1°C (HR = 2.9, p=0.047), white blood cell count > 10 × 10⁹ (HR = 6.9, p < 0.001), neutrophil count > 75 × 10⁹ (HR = 2.4, p=0.022), creatine kinase > 5 U/L (HR = 1.8, p=0.042), glucose > 6.1 mmol/L (HR = 7, p < 0.001), and lactate > 2 mmol/L (HR = 22, p < 0.001). Conclusions We found 40 risk factors were significantly associated with septic shock. The model contained eight independent factors that can accurately predict septic shock. The administration of hypnotics could potentially reduce the incidence of septic shock in COVID-19 patients.","PeriodicalId":7473,"journal":{"name":"Advances in Virology","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Virology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2022/3178283","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"VIROLOGY","Score":null,"Total":0}
引用次数: 7

Abstract

Purpose Septic shock is a severe complication of COVID-19 patients. We aim to identify risk factors associated with septic shock and mortality among COVID-19 patients. Methods A total of 212 COVID-19 confirmed patients in Wuhan were included in this retrospective study. Clinical outcomes were designated as nonseptic shock and septic shock. Log-rank test was conducted to determine any association with clinical progression. A prediction model was established using random forest. Results The mortality of septic shock and nonshock patients with COVID-19 was 96.7% (29/30) and 3.8% (7/182). Patients taking hypnotics had a much lower chance to develop septic shock (HR = 0.096, p=0.0014). By univariate logistic regression analysis, 40 risk factors were significantly associated with septic shock. Based on multiple regression analysis, eight risk factors were shown to be independent risk factors and these factors were then selected to build a model to predict septic shock with AUC = 0.956. These eight factors included disease severity (HR = 15, p < 0.001), age > 65 years (HR = 2.6, p=0.012), temperature > 39.1°C (HR = 2.9, p=0.047), white blood cell count > 10 × 10⁹ (HR = 6.9, p < 0.001), neutrophil count > 75 × 10⁹ (HR = 2.4, p=0.022), creatine kinase > 5 U/L (HR = 1.8, p=0.042), glucose > 6.1 mmol/L (HR = 7, p < 0.001), and lactate > 2 mmol/L (HR = 22, p < 0.001). Conclusions We found 40 risk factors were significantly associated with septic shock. The model contained eight independent factors that can accurately predict septic shock. The administration of hypnotics could potentially reduce the incidence of septic shock in COVID-19 patients.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
武汉COVID-19住院患者感染性休克与死亡率的关系
目的感染性休克是新冠肺炎患者的严重并发症。我们的目的是确定与COVID-19患者感染性休克和死亡率相关的危险因素。方法对武汉市212例新冠肺炎确诊患者进行回顾性研究。临床结果分为非感染性休克和感染性休克。进行Log-rank检验以确定是否与临床进展相关。利用随机森林建立预测模型。结果感染性休克和非休克患者病死率分别为96.7%(29/30)和3.8%(7/182)。服用催眠药的患者发生感染性休克的几率较低(HR = 0.096, p=0.0014)。经单因素logistic回归分析,有40个危险因素与脓毒性休克显著相关。经多元回归分析,8个危险因素为独立危险因素,选取这些危险因素建立预测脓毒性休克的模型,AUC = 0.956。这八个因素包括疾病严重程度(HR = 15, p < 0.001),年龄> 65岁(HR = 2.6, p = 0.012),温度> 39.1°C (HR = 2.9, p = 0.047),白细胞计数> 10×10⁹(HR = 6.9, p < 0.001),中性粒细胞计数> 75×10⁹(HR = 2.4, p = 0.022),肌酸激酶> 5 U / L (HR = 1.8, p = 0.042),葡萄糖> 6.1更易/ L (HR = 7, p < 0.001),和乳酸> 2更易与L (HR = 22, p < 0.001)。结论发现有40种危险因素与脓毒性休克显著相关。该模型包含8个独立因素,可准确预测感染性休克。催眠药的使用可能会降低COVID-19患者感染性休克的发生率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
2.30
自引率
0.00%
发文量
23
审稿时长
22 weeks
期刊最新文献
Increased Incidence of Rhinovirus Pneumonia in Children During the COVID-19 Pandemic in Mexico. Measles Outbreaks in the Republic of Congo: Epidemiology of Laboratory-Confirmed Cases Between 2019 and 2022. Support Vector Machine Outperforms Other Machine Learning Models in Early Diagnosis of Dengue Using Routine Clinical Data. In Silico Design of a Trans-Amplifying RNA-Based Vaccine against SARS-CoV-2 Structural Proteins. Hepatitis B Virus (HBV) Genotypes in an Ecuadorian Population: A Preliminary Study.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1