• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

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.

DOI:10.3389/fmed.2020.557453
PMID:33123541
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7571455/
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
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/698c/7571455/557d94e1dccc/fmed-07-557453-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/698c/7571455/557d94e1dccc/fmed-07-557453-g0001.jpg

相似文献

1
Prognostic Factors for COVID-19 Pneumonia Progression to Severe Symptoms Based on Earlier Clinical Features: A Retrospective Analysis.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。
Front Med (Lausanne). 2020 Oct 5;7:557453. doi: 10.3389/fmed.2020.557453. eCollection 2020.
2
Predictive role of clinical features in patients with coronavirus disease 2019 for severe disease.2019冠状病毒病患者临床特征对重症疾病的预测作用
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2020 May 28;45(5):536-541. doi: 10.11817/j.issn.1672-7347.2020.200384.
3
Prognostic value of lactate dehydrogenase for in-hospital mortality in severe and critically ill patients with COVID-19.COVID-19 重症和危重症患者血乳酸脱氢酶水平对住院患者病死率的预测价值。
Int J Med Sci. 2020 Aug 19;17(14):2225-2231. doi: 10.7150/ijms.47604. eCollection 2020.
4
Combination of serum lactate dehydrogenase and sex is predictive of severe disease in patients with COVID-19.血清乳酸脱氢酶与性别相结合可预测COVID-19患者的重症疾病。
Medicine (Baltimore). 2020 Oct 16;99(42):e22774. doi: 10.1097/MD.0000000000022774.
5
Lactate dehydrogenase/albumin ratio as a prognostic factor in severe acute respiratory distress syndrome cases associated with COVID-19.乳酸脱氢酶/白蛋白比值作为 COVID-19 相关严重急性呼吸窘迫综合征患者的预后因素。
Medicine (Baltimore). 2022 Sep 23;101(38):e30759. doi: 10.1097/MD.0000000000030759.
6
Clinical characteristics and the risk factors for severe events of elderly coronavirus disease 2019 patients.2019年冠状病毒病老年患者的临床特征及严重事件的危险因素
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2020 May 28;45(5):542-548. doi: 10.11817/j.issn.1672-7347.2020.200292.
7
[Clinical features and risk factors for secondary hemophagocytic lymphohistiocytosis in elderly patients with severe SARS-CoV-2 infection: a multicenter retrospective cohort study].[老年重症新型冠状病毒肺炎患者继发噬血细胞性淋巴组织细胞增生症的临床特征及危险因素:一项多中心回顾性队列研究]
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2023 Aug;35(8):793-799. doi: 10.3760/cma.j.cn121430-20230510-00158.
8
Persistent lymphocyte reduction and interleukin-6 levels are independently associated with death in patients with COVID-19.持续性淋巴细胞减少和白细胞介素 6 水平与 COVID-19 患者的死亡独立相关。
Clin Exp Med. 2023 Nov;23(7):3719-3728. doi: 10.1007/s10238-023-01114-0. Epub 2023 Jun 13.
9
Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.在流行地区,服用抗叶酸抗疟药物的人群中,叶酸补充剂与疟疾易感性和严重程度的关系。
Cochrane Database Syst Rev. 2022 Feb 1;2(2022):CD014217. doi: 10.1002/14651858.CD014217.
10
Early prediction model for progression and prognosis of severe patients with coronavirus disease 2019.2019年冠状病毒病重症患者病情进展及预后的早期预测模型
Medicine (Baltimore). 2021 Feb 26;100(8):e24901. doi: 10.1097/MD.0000000000024901.

引用本文的文献

1
Machine Learning-Based Identification of Risk Factors for ICU Mortality in 8902 Critically Ill Patients with Pandemic Viral Infection.基于机器学习对8902例大流行性病毒感染重症患者ICU死亡风险因素的识别
J Clin Med. 2025 Jul 30;14(15):5383. doi: 10.3390/jcm14155383.
2
Clinical Features Predicting COVID-19 Severity Risk at the Time of Hospitalization.住院时预测COVID-19严重程度风险的临床特征。
Cureus. 2024 Mar 31;16(3):e57336. doi: 10.7759/cureus.57336. eCollection 2024 Mar.
3
The Disconnect Between Development and Intended Use of Clinical Prediction Models for Covid-19: A Systematic Review and Real-World Data Illustration.

本文引用的文献

1
The Epidemiological Characteristics of an Outbreak of 2019 Novel Coronavirus Diseases (COVID-19) - China, 2020.2019新型冠状病毒病(COVID-19)疫情的流行病学特征 - 中国,2020年
China CDC Wkly. 2020 Feb 21;2(8):113-122.
2
Mutations, Recombination and Insertion in the Evolution of 2019-nCoV.2019新型冠状病毒进化中的突变、重组与插入
bioRxiv. 2020 Mar 2:2020.02.29.971101. doi: 10.1101/2020.02.29.971101.
3
Detection of SARS-CoV-2 in Different Types of Clinical Specimens.SARS-CoV-2 在不同类型临床标本中的检测。
新型冠状病毒肺炎临床预测模型的开发与预期用途之间的脱节:系统评价与真实世界数据例证
Front Epidemiol. 2022 Jun 27;2:899589. doi: 10.3389/fepid.2022.899589. eCollection 2022.
4
Impact of vaccination on morbidity and mortality in adults hospitalized with COVID-19 during the omicron wave in the Jazan Region, Saudi Arabia.奥密克戎变异株流行期间沙特阿拉伯吉赞地区住院 COVID-19 成人患者的疫苗接种对发病率和死亡率的影响。
Saudi Med J. 2024 Feb;45(2):179-187. doi: 10.15537/smj.2024.45.2.20230530.
5
Wireless, battery-free, multifunctional integrated bioelectronics for respiratory pathogens monitoring and severity evaluation.用于呼吸病原体监测和严重程度评估的无线、无电池、多功能集成生物电子学。
Nat Commun. 2023 Nov 20;14(1):7539. doi: 10.1038/s41467-023-43189-z.
6
Validation of a risk prediction model for COVID-19: the PERIL prospective cohort study.新型冠状病毒肺炎风险预测模型的验证:PERIL前瞻性队列研究
Future Virol. 2023 Oct. doi: 10.2217/fvl-2023-0036. Epub 2023 Nov 7.
7
Protection against Severe Illness versus Immunity-Redefining Vaccine Effectiveness in the Aftermath of COVID-19.预防重症与免疫——重新定义新冠疫情后的疫苗效力
Microorganisms. 2023 Jul 31;11(8):1963. doi: 10.3390/microorganisms11081963.
8
Is Age the Most Important Risk Factor in COVID-19 Patients? The Relevance of Comorbidity Burden: A Retrospective Analysis of 10,551 Hospitalizations.年龄是新冠病毒肺炎患者最重要的风险因素吗?合并症负担的相关性:对10551例住院病例的回顾性分析
Clin Epidemiol. 2023 Jun 30;15:811-825. doi: 10.2147/CLEP.S408510. eCollection 2023.
9
Assessment of the Suitability of the Fleischner Society Imaging Guidelines in Evaluating Chest Radiographs of COVID-19 Patients.评估 Fleischner 学会影像学指南在评估 COVID-19 患者胸部 X 光片的适用性。
J Korean Med Sci. 2023 Jul 3;38(26):e199. doi: 10.3346/jkms.2023.38.e199.
10
Deciding When to Intubate a COVID-19 Patient.确定新冠病毒肺炎患者何时进行气管插管
Anesth Pain Med. 2022 Jun 21;12(3):e123350. doi: 10.5812/aapm-123350. eCollection 2022 Jun.
JAMA. 2020 May 12;323(18):1843-1844. doi: 10.1001/jama.2020.3786.
4
Clinical Characteristics of Coronavirus Disease 2019 in China.《中国 2019 年冠状病毒病临床特征》
N Engl J Med. 2020 Apr 30;382(18):1708-1720. doi: 10.1056/NEJMoa2002032. Epub 2020 Feb 28.
5
Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2.新型冠状病毒 2019 年 SARS-CoV-2 患者的影像学和临床特征。
Eur J Nucl Med Mol Imaging. 2020 May;47(5):1275-1280. doi: 10.1007/s00259-020-04735-9. Epub 2020 Feb 28.
6
Detectable 2019-nCoV viral RNA in blood is a strong indicator for the further clinical severity.血液中可检测到的 2019-nCoV 病毒 RNA 是进一步临床严重程度的强烈指标。
Emerg Microbes Infect. 2020 Feb 26;9(1):469-473. doi: 10.1080/22221751.2020.1732837. eCollection 2020.
7
Pathological findings of COVID-19 associated with acute respiratory distress syndrome.与急性呼吸窘迫综合征相关的新型冠状病毒肺炎的病理表现
Lancet Respir Med. 2020 Apr;8(4):420-422. doi: 10.1016/S2213-2600(20)30076-X. Epub 2020 Feb 18.
8
Initial CT findings and temporal changes in patients with the novel coronavirus pneumonia (2019-nCoV): a study of 63 patients in Wuhan, China.新型冠状病毒肺炎(2019-nCoV)患者的初始 CT 表现及时间演变:中国武汉 63 例患者研究。
Eur Radiol. 2020 Jun;30(6):3306-3309. doi: 10.1007/s00330-020-06731-x. Epub 2020 Feb 13.
9
Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.《武汉 2019 年新型冠状病毒感染的肺炎 138 例住院患者临床特征分析》
JAMA. 2020 Mar 17;323(11):1061-1069. doi: 10.1001/jama.2020.1585.
10
Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study.中国武汉 99 例 2019 年新型冠状病毒肺炎患者的流行病学和临床特征:描述性研究。
Lancet. 2020 Feb 15;395(10223):507-513. doi: 10.1016/S0140-6736(20)30211-7. Epub 2020 Jan 30.