• 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

入院时 COVID-19 的生化严重程度风险评分:Covichem。

Covichem: A biochemical severity risk score of COVID-19 upon hospital admission.

机构信息

Department of Biochemistry, Pellegrin Hospital, University Hospital of Bordeaux, Bordeaux, France.

Inserm U1034, Biology of Cardiovascular Diseases, Pessac, France.

出版信息

PLoS One. 2021 May 6;16(5):e0250956. doi: 10.1371/journal.pone.0250956. eCollection 2021.

DOI:10.1371/journal.pone.0250956
PMID:33956870
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8101934/
Abstract

Clinical and laboratory predictors of COVID-19 severity are now well described and combined to propose mortality or severity scores. However, they all necessitate saturable equipment such as scanners, or procedures difficult to implement such as blood gas measures. To provide an easy and fast COVID-19 severity risk score upon hospital admission, and keeping in mind the above limits, we sought for a scoring system needing limited invasive data such as a simple blood test and co-morbidity assessment by anamnesis. A retrospective study of 303 patients (203 from Bordeaux University hospital and an external independent cohort of 100 patients from Paris Pitié-Salpêtrière hospital) collected clinical and biochemical parameters at admission. Using stepwise model selection by Akaike Information Criterion (AIC), we built the severity score Covichem. Among 26 tested variables, 7: obesity, cardiovascular conditions, plasma sodium, albumin, ferritin, LDH and CK were the independent predictors of severity used in Covichem (accuracy 0.87, AUROC 0.91). Accuracy was 0.92 in the external validation cohort (89% sensitivity and 95% specificity). Covichem score could be useful as a rapid, costless and easy to implement severity assessment tool during acute COVID-19 pandemic waves.

摘要

目前已经很好地描述了 COVID-19 严重程度的临床和实验室预测因素,并将其组合起来提出了死亡率或严重程度评分。然而,它们都需要饱和的设备,如扫描仪,或者难以实施的程序,如血气测量。为了在入院时提供一个简单快捷的 COVID-19 严重程度风险评分,并牢记上述限制,我们寻求一种评分系统,需要有限的侵入性数据,如简单的血液测试和病史评估的合并症。对 303 名患者(203 名来自波尔多大学医院,100 名来自巴黎皮提-萨尔佩特里埃医院的外部独立队列)进行了回顾性研究,收集了入院时的临床和生化参数。使用 Akaike 信息准则(AIC)逐步模型选择,我们构建了严重程度评分 Covichem。在 26 个测试变量中,肥胖、心血管疾病、血浆钠、白蛋白、铁蛋白、乳酸脱氢酶和肌酸激酶是 Covichem 中严重程度的独立预测因素(准确性为 0.87,AUROC 为 0.91)。在外部验证队列中的准确性为 0.92(敏感性为 89%,特异性为 95%)。在急性 COVID-19 大流行期间,Covichem 评分可能是一种快速、免费且易于实施的严重程度评估工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9a8/8101934/d20d2fe9da82/pone.0250956.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9a8/8101934/f33db3b80d9a/pone.0250956.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9a8/8101934/d20d2fe9da82/pone.0250956.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9a8/8101934/f33db3b80d9a/pone.0250956.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b9a8/8101934/d20d2fe9da82/pone.0250956.g002.jpg

相似文献

1
Covichem: A biochemical severity risk score of COVID-19 upon hospital admission.入院时 COVID-19 的生化严重程度风险评分:Covichem。
PLoS One. 2021 May 6;16(5):e0250956. doi: 10.1371/journal.pone.0250956. eCollection 2021.
2
Diagnostic utility of the Covichem score in predicting COVID-19 disease.Covichem 评分预测 COVID-19 疾病的诊断效用。
Am J Emerg Med. 2022 Oct;60:50-56. doi: 10.1016/j.ajem.2022.07.025. Epub 2022 Jul 16.
3
Development and validation of a prognostic nomogram for predicting in-hospital mortality of COVID-19: a multicenter retrospective cohort study of 4086 cases in China.开发和验证一种预测 COVID-19 住院患者死亡率的预后列线图:一项中国多中心回顾性队列研究 4086 例。
Aging (Albany NY). 2021 Feb 9;13(3):3176-3189. doi: 10.18632/aging.202605.
4
Predictors of clinical deterioration in non-severe patients with COVID-19: a retrospective cohort study.新型冠状病毒肺炎非重症患者临床恶化的预测因素:一项回顾性队列研究。
Curr Med Res Opin. 2021 Mar;37(3):385-391. doi: 10.1080/03007995.2021.1876005. Epub 2021 Feb 4.
5
Identification of risk factors for in-hospital death of COVID - 19 pneumonia -- lessions from the early outbreak.鉴定 COVID-19 肺炎院内死亡的风险因素——来自早期爆发的教训。
BMC Infect Dis. 2021 Jan 25;21(1):113. doi: 10.1186/s12879-021-05814-4.
6
Analysis of Risk Factors for Thromboembolic Events in 88 Patients with COVID-19 Pneumonia in Wuhan, China: A Retrospective Descriptive Report.中国武汉 88 例新冠肺炎肺炎患者血栓栓塞事件危险因素分析:回顾性描述性报告。
Med Sci Monit. 2021 Apr 11;27:e929708. doi: 10.12659/MSM.929708.
7
National Early Warning Score 2 (NEWS2) on admission predicts severe disease and in-hospital mortality from Covid-19 - a prospective cohort study.入院时的国家早期预警评分 2 (NEWS2)可预测新冠病毒疾病的严重程度和住院死亡率-一项前瞻性队列研究。
Scand J Trauma Resusc Emerg Med. 2020 Jul 13;28(1):66. doi: 10.1186/s13049-020-00764-3.
8
Development and validation of a simple risk score for diagnosing COVID-19 in the emergency room.开发和验证一种用于急诊科诊断 COVID-19 的简单风险评分。
Epidemiol Infect. 2020 Nov 13;148:e273. doi: 10.1017/S0950268820002769.
9
Development of a multivariate prediction model of intensive care unit transfer or death: A French prospective cohort study of hospitalized COVID-19 patients.建立 ICU 转科或死亡的多变量预测模型:一项法国前瞻性队列研究COVID-19 住院患者。
PLoS One. 2020 Oct 19;15(10):e0240711. doi: 10.1371/journal.pone.0240711. eCollection 2020.
10
Development and validation of a prognostic COVID-19 severity assessment (COSA) score and machine learning models for patient triage at a tertiary hospital.开发和验证一种用于三级医院患者分诊的 COVID-19 严重程度预后评估 (COSA) 评分和机器学习模型。
J Transl Med. 2021 Feb 5;19(1):56. doi: 10.1186/s12967-021-02720-w.

引用本文的文献

1
The 123 COVID SCORE: A simple and reliable diagnostic tool to predict in-hospital death in COVID-19 patients on hospital admission.123 COVID 评分:一种简单可靠的诊断工具,用于预测入院时 COVID-19 患者的住院死亡。
PLoS One. 2024 Oct 22;19(10):e0309922. doi: 10.1371/journal.pone.0309922. eCollection 2024.
2
An Observational Study on the Utility of Lab Parameters in Evaluating the Severity of Patients in South India with Covid-19.一项关于实验室参数在评估印度南部新冠病毒病患者严重程度中的效用的观察性研究
J Pharm Bioallied Sci. 2023 Jul;15(Suppl 1):S414-S418. doi: 10.4103/jpbs.jpbs_549_22. Epub 2023 Jul 5.
3
Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19.

本文引用的文献

1
Multi-dimensional COVID-19 short- and long-term outcome prediction algorithm.多维新冠肺炎短期和长期预后预测算法
Expert Rev Precis Med Drug Dev. 2020;5(4):239-242. doi: 10.1080/23808993.2020.1785286. Epub 2020 Jun 24.
2
Insights into disparities observed with COVID-19.对观察到的 COVID-19 差异的深入了解。
J Intern Med. 2021 Apr;289(4):463-473. doi: 10.1111/joim.13199. Epub 2020 Dec 6.
3
Risk factors for Covid-19 severity and fatality: a structured literature review.Covid-19 严重程度和死亡率的风险因素:系统文献回顾。
学习临床概念以预测 COVID-19 进展为重症的风险。
AMIA Annu Symp Proc. 2023 Apr 29;2022:1257-1266. eCollection 2022.
4
Development of lab score system for predicting COVID-19 patient severity: A retrospective analysis.实验室评分系统预测 COVID-19 患者严重程度的开发:一项回顾性分析。
PLoS One. 2022 Sep 9;17(9):e0273006. doi: 10.1371/journal.pone.0273006. eCollection 2022.
5
The Associations of Iron Related Biomarkers with Risk, Clinical Severity and Mortality in SARS-CoV-2 Patients: A Meta-Analysis.铁相关生物标志物与 SARS-CoV-2 患者风险、临床严重程度和死亡率的关联:一项荟萃分析。
Nutrients. 2022 Aug 19;14(16):3406. doi: 10.3390/nu14163406.
6
Diagnostic utility of the Covichem score in predicting COVID-19 disease.Covichem 评分预测 COVID-19 疾病的诊断效用。
Am J Emerg Med. 2022 Oct;60:50-56. doi: 10.1016/j.ajem.2022.07.025. Epub 2022 Jul 16.
7
Risk of Death in Comorbidity Subgroups of Hospitalized COVID-19 Patients Inferred by Routine Laboratory Markers of Systemic Inflammation on Admission: A Retrospective Study.入院时常规全身炎症标志物推断的住院 COVID-19 患者合并症亚组的死亡风险:一项回顾性研究。
Viruses. 2022 May 31;14(6):1201. doi: 10.3390/v14061201.
8
A Comparison of XGBoost, Random Forest, and Nomograph for the Prediction of Disease Severity in Patients With COVID-19 Pneumonia: Implications of Cytokine and Immune Cell Profile.XGBoost、随机森林和列线图在预测 COVID-19 肺炎患者疾病严重程度方面的比较:细胞因子和免疫细胞特征的意义。
Front Cell Infect Microbiol. 2022 Apr 12;12:819267. doi: 10.3389/fcimb.2022.819267. eCollection 2022.
9
CT-based severity assessment for COVID-19 using weakly supervised non-local CNN.基于CT的COVID-19严重程度评估:使用弱监督非局部卷积神经网络
Appl Soft Comput. 2022 May;121:108765. doi: 10.1016/j.asoc.2022.108765. Epub 2022 Mar 29.
10
Mesenchymal stem cells and COVID-19: What they do and what they can do.间充质干细胞与新型冠状病毒肺炎:它们的作用及潜在能力
World J Stem Cells. 2021 Sep 26;13(9):1318-1337. doi: 10.4252/wjsc.v13.i9.1318.
Infection. 2021 Feb;49(1):15-28. doi: 10.1007/s15010-020-01509-1. Epub 2020 Aug 28.
4
Predicting Disease Severity and Outcome in COVID-19 Patients: A Review of Multiple Biomarkers.预测 COVID-19 患者的疾病严重程度和结局:多种生物标志物的综述。
Arch Pathol Lab Med. 2020 Dec 1;144(12):1465-1474. doi: 10.5858/arpa.2020-0471-SA.
5
Characterization of acute kidney injury in critically ill patients with severe coronavirus disease 2019.2019年重症冠状病毒病危重症患者急性肾损伤的特征
Clin Kidney J. 2020 Jun 6;13(3):354-361. doi: 10.1093/ckj/sfaa099. eCollection 2020 Jun.
6
A Comprehensive Appraisal of Laboratory Biochemistry Tests as Major Predictors of COVID-19 Severity.实验室生物化学检测对 COVID-19 严重程度的主要预测因素的综合评估。
Arch Pathol Lab Med. 2020 Dec 1;144(12):1457-1464. doi: 10.5858/arpa.2020-0389-SA.
7
Is Hypertension a Real Risk Factor for Poor Prognosis in the COVID-19 Pandemic?高血压是否是 COVID-19 大流行中预后不良的真正危险因素?
Curr Hypertens Rep. 2020 Jun 13;22(6):43. doi: 10.1007/s11906-020-01057-x.
8
Assessment of risk, severity, mortality, glycemic control and antidiabetic agents in patients with diabetes and COVID-19: A narrative review.评估糖尿病合并 COVID-19 患者的风险、严重程度、死亡率、血糖控制和抗糖尿病药物:叙述性综述。
Diabetes Res Clin Pract. 2020 Jul;165:108266. doi: 10.1016/j.diabres.2020.108266. Epub 2020 Jun 11.
9
A brief-review of the risk factors for covid-19 severity.Covid-19 严重程度的危险因素简述。
Rev Saude Publica. 2020;54:60. doi: 10.11606/s1518-8787.2020054002481. Epub 2020 Jun 1.
10
Impact of sex and gender on COVID-19 outcomes in Europe.欧洲 COVID-19 结局的性别差异。
Biol Sex Differ. 2020 May 25;11(1):29. doi: 10.1186/s13293-020-00304-9.