Suppr超能文献

绝对嗜酸性粒细胞计数可预测老年新冠患者从普通隔离病房转入重症监护病房的情况。

Absolute Eosinophil Count Predicts Intensive Care Unit Transfer Among Elderly COVID-19 Patients From General Isolation Wards.

作者信息

Huang Jinjin, Zhang Zhicheng, Liu Shunfang, Gong Chen, Chen Liping, Ai Guo, Zhu Xiaodong, Zhang Chunli, Li Dengju

机构信息

Department of Hematology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Department of Gastroenterology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

出版信息

Front Med (Lausanne). 2020 Nov 4;7:585222. doi: 10.3389/fmed.2020.585222. eCollection 2020.

Abstract

As of June 1, 2020, coronavirus disease 2019 (COVID-19) has caused a global pandemic and resulted in over 370,000 deaths worldwide. Early identification of COVID-19 patients who need to be admitted to the intensive care unit (ICU) helps to improve the outcomes. We aim to investigate whether absolute eosinophil count (AEC) can predict ICU transfer among elderly COVID-19 patients from general isolation wards. A retrospective study of 94 elderly patients older than 60 years old with COVID-19 was conducted. We compared the basic clinical characteristics and levels of inflammation markers on admission to general isolation wards and the needs for ICU transfer between the eosinopenia (AEC on admission <20 cells/μl) and non-eosinopenia (AEC ≥20 cells/μl) groups. There was a significantly higher ICU transfer rate in the eosinopenia group than in the non-eosinopenia group (51 vs. 9%, < 0.001). Multivariate analysis revealed that eosinopenia was associated with an increased risk of ICU transfer in elderly COVID-19 patients [adjusted odds ratio (OR) 6.12 (95% CI, 1.23-30.33), = 0.027] after adjustment of age, lymphocyte count, neutrophil count, C-reactive protein (CRP), and ferritin levels. The eosinopenia group had higher levels of CRP, ferritin, and cytokines [interleukin-2 receptor (IL-2R), interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α)] than the non-eosinophil group ( < 0.001). The area under the curve of AEC on admission for predicting ICU transfer among elderly COVID-19 patients was 0.828 (95% CI, 0.732-0.923). The best cut-off value of AEC was 25 cells/μl with a sensitivity of 91% and a specificity of 71%, respectively. Absolute eosinophil count on admission is a valid predictive marker for ICU transfer among elderly COVID-19 patients from general isolation wards and, therefore, can help case triage and optimize ICU utilization, especially for health care facilities with limited ICU capacity.

摘要

截至2020年6月1日,2019冠状病毒病(COVID-19)已引发全球大流行,导致全球超过37万人死亡。尽早识别需要入住重症监护病房(ICU)的COVID-19患者有助于改善治疗结果。我们旨在调查绝对嗜酸性粒细胞计数(AEC)能否预测老年COVID-19患者从普通隔离病房转入ICU的情况。对94例年龄大于60岁的COVID-19老年患者进行了一项回顾性研究。我们比较了普通隔离病房入院时的基本临床特征、炎症标志物水平,以及嗜酸性粒细胞减少组(入院时AEC<20个/μl)和非嗜酸性粒细胞减少组(AEC≥20个/μl)之间转入ICU的需求。嗜酸性粒细胞减少组的ICU转入率显著高于非嗜酸性粒细胞减少组(51%对9%,P<0.001)。多因素分析显示,在调整年龄、淋巴细胞计数、中性粒细胞计数、C反应蛋白(CRP)和铁蛋白水平后,嗜酸性粒细胞减少与老年COVID-19患者转入ICU的风险增加相关[调整后的优势比(OR)为6.12(95%CI,1.23 - 30.33),P = 0.027]。嗜酸性粒细胞减少组的CRP、铁蛋白和细胞因子[白细胞介素-2受体(IL-2R)、白细胞介素-6(IL-6)、白细胞介素-8(IL-8)、白细胞介素-10(IL-10)和肿瘤坏死因子-α(TNF-α)]水平高于非嗜酸性粒细胞组(P<0.001)。入院时AEC预测老年COVID-19患者转入ICU的曲线下面积为0.828(95%CI,0.732 - 0.923)。AEC的最佳截断值为25个/μl,敏感性和特异性分别为91%和71%。入院时的绝对嗜酸性粒细胞计数是老年COVID-19患者从普通隔离病房转入ICU的有效预测指标,因此有助于病例分诊并优化ICU的使用,特别是对于ICU容量有限的医疗机构。

相似文献

1
Absolute Eosinophil Count Predicts Intensive Care Unit Transfer Among Elderly COVID-19 Patients From General Isolation Wards.
Front Med (Lausanne). 2020 Nov 4;7:585222. doi: 10.3389/fmed.2020.585222. eCollection 2020.
2
Eosinopenia and post-hospital outcomes in critically ill non-cardiac vascular surgery patients.
Nutr Metab Cardiovasc Dis. 2019 Aug;29(8):847-855. doi: 10.1016/j.numecd.2019.05.061. Epub 2019 May 22.
3
Eosinopenia as a predictor of unexpected re-admission and mortality after intensive care unit discharge.
Anaesth Intensive Care. 2013 Mar;41(2):231-41. doi: 10.1177/0310057X1304100130.
4
Eosinopenia, an early marker of increased mortality in critically ill medical patients.
Intensive Care Med. 2011 Jul;37(7):1136-42. doi: 10.1007/s00134-011-2170-z. Epub 2011 Mar 3.
5
[Risk factors for death in elderly patients admitted to intensive care unit after elective abdominal surgery: a consecutive 5-year retrospective study].
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2021 Dec;33(12):1453-1458. doi: 10.3760/cma.j.cn121430-20210804-00118.
7
Eosinophil count at intensive care unit admission was not predictor of hospital mortality: results of a case control study.
J Intensive Care. 2015 Jun 6;3(1):27. doi: 10.1186/s40560-015-0093-4. eCollection 2015.
8
Eosinopenia <100/μL as a marker of active COVID-19: An observational prospective study.
J Microbiol Immunol Infect. 2021 Feb;54(1):61-68. doi: 10.1016/j.jmii.2020.12.005. Epub 2021 Jan 8.
9
Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients.
SN Compr Clin Med. 2022;4(1):39. doi: 10.1007/s42399-021-01115-8. Epub 2022 Jan 17.

引用本文的文献

1
Evaluation of Hematological Parameters in Predicting Intensive Care Unit Admission in COVID-19 Patients.
SN Compr Clin Med. 2022;4(1):39. doi: 10.1007/s42399-021-01115-8. Epub 2022 Jan 17.
2
Impact of Anti-Type 2 Inflammation Biologic Therapy on COVID-19 Clinical Course and Outcome.
J Inflamm Res. 2021 Dec 14;14:6845-6853. doi: 10.2147/JIR.S345665. eCollection 2021.
3
Eosinophil: A Nonnegligible Predictor in COVID-19 Re-Positive Patients.
Front Immunol. 2021 Jul 29;12:690653. doi: 10.3389/fimmu.2021.690653. eCollection 2021.
4
Emerging Evidence for Pleiotropism of Eosinophils.
Int J Mol Sci. 2021 Jun 30;22(13):7075. doi: 10.3390/ijms22137075.
6
Anti-IL5 Drugs in COVID-19 Patients: Role of Eosinophils in SARS-CoV-2-Induced Immunopathology.
Front Pharmacol. 2021 Mar 9;12:622554. doi: 10.3389/fphar.2021.622554. eCollection 2021.

本文引用的文献

3
Characteristics and prognostic factors of disease severity in patients with COVID-19: The Beijing experience.
J Autoimmun. 2020 Aug;112:102473. doi: 10.1016/j.jaut.2020.102473. Epub 2020 Apr 24.
4
Using IL-2R/lymphocytes for predicting the clinical progression of patients with COVID-19.
Clin Exp Immunol. 2020 Jul;201(1):76-84. doi: 10.1111/cei.13450. Epub 2020 May 15.
5
Abnormalities of peripheral blood system in patients with COVID-19 in Wenzhou, China.
Clin Chim Acta. 2020 Aug;507:174-180. doi: 10.1016/j.cca.2020.04.024. Epub 2020 Apr 24.
7
Laboratory data analysis of novel coronavirus (COVID-19) screening in 2510 patients.
Clin Chim Acta. 2020 Aug;507:94-97. doi: 10.1016/j.cca.2020.04.018. Epub 2020 Apr 18.
9
C-reactive protein correlates with computed tomographic findings and predicts severe COVID-19 early.
J Med Virol. 2020 Jul;92(7):856-862. doi: 10.1002/jmv.25871. Epub 2020 Apr 25.
10
Clinical Features of 85 Fatal Cases of COVID-19 from Wuhan. A Retrospective Observational Study.
Am J Respir Crit Care Med. 2020 Jun 1;201(11):1372-1379. doi: 10.1164/rccm.202003-0543OC.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验