• 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

2019冠状病毒病(COVID-19)患者与流感患者胸部影像的差异:一项系统评价与荟萃分析

Differences of the Chest Images Between Coronavirus Disease 2019 (COVID-19) Patients and Influenza Patients: A Systematic Review and Meta-analysis.

作者信息

Han Yingying, Wang Zhijia, Li Xingzhao, Zhong Zhuan

机构信息

Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China, 130000, ORCID: 0000-0002-3583-0448.

Department of Radiology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China, 130000.

出版信息

Int J Med Sci. 2025 Jan 13;22(3):641-650. doi: 10.7150/ijms.98194. eCollection 2025.

DOI:10.7150/ijms.98194
PMID:39898255
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11783069/
Abstract

Coronavirus disease 2019 (COVID-19) and influenza are two infectious diseases that can pose a great threat to human health. We aimed to compare the differences in chest images between patients with COVID-19 and influenza to deepen the understanding of these two diseases. We searched PubMed, Embase and Web of Science for articles published before December 25, 2023, and performed a meta-analysis using Stata 14.0 with a random-effects model. The study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Twenty-six articles with 2,159 COVID-19 patients and 1,568 influenza patients were included in the meta-analysis. By comparing chest computed tomography (CT) and chest X-ray, we found that COVID-19 patients had more peripheral lung lesions (OR=3.66, 95% CI: 1.84-7.31). Although COVID-19 patients had more bilateral lung involvement (OR=1.74, 95% CI: 0.90-3.38) and less unilateral lung involvement (OR=0.67, 95% CI: 0.44-1.02), these two results were not statistically significant. Patients with COVID-19 showed more ground-glass opacities (OR=2.83, 95% CI: 1.85-4.32), reverse halo signs (OR=3.47, 95% CI: 2.37-5.08), interlobular septal thickening (OR=2.16, 95% CI: 1.55-3.01), vascular enlargement (OR=5.00, 95% CI: 1.80-13.85) and crazy-paving patterns (OR=2.63, 95% CI: 1.57-4.41) on chest images than patients with influenza. We also found that compared with influenza patients, pleural effusion was rare in COVID-19 patients (OR=0.15, 95% CI: 0.07-0.31). There are some differences in the manifestations and distributions of lesions between patients with COVID-19 and influenza on chest images, which is helpful to distinguish these two infectious diseases.

摘要

2019冠状病毒病(COVID-19)和流感是两种可能对人类健康构成重大威胁的传染病。我们旨在比较COVID-19患者和流感患者胸部影像的差异,以加深对这两种疾病的理解。我们在PubMed、Embase和Web of Science上检索了2023年12月25日前发表的文章,并使用Stata 14.0采用随机效应模型进行荟萃分析。该研究按照系统评价和荟萃分析的首选报告项目(PRISMA)指南进行。荟萃分析纳入了26篇文章,共2159例COVID-19患者和1568例流感患者。通过比较胸部计算机断层扫描(CT)和胸部X线,我们发现COVID-19患者的外周肺病变更多(OR=3.66,95%CI:1.84-7.31)。虽然COVID-19患者双侧肺受累更多(OR=1.74,95%CI:0.90-3.38),单侧肺受累更少(OR=0.67,95%CI:0.44-1.02),但这两个结果均无统计学意义。COVID-19患者胸部影像上的磨玻璃影(OR=2.83,95%CI:1.85-4.32)、反晕征(OR=3.47,95%CI:2.37-5.08)、小叶间隔增厚(OR=2.16,95%CI:1.55-3.01)、血管增粗(OR=5.00,95%CI:1.80-13.85)和铺路石样表现(OR=2.63,95%CI:1.57-4.41)比流感患者更多。我们还发现,与流感患者相比,COVID-19患者胸腔积液较少见(OR=0.15,95%CI:0.07-0.31)。COVID-19患者和流感患者胸部影像上病变的表现和分布存在一些差异,这有助于区分这两种传染病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/868be520fce9/ijmsv22p0641g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/0a3fb94c686f/ijmsv22p0641g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/7be8fc886678/ijmsv22p0641g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/0af2c33c6540/ijmsv22p0641g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/1dc88225f494/ijmsv22p0641g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/868be520fce9/ijmsv22p0641g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/0a3fb94c686f/ijmsv22p0641g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/7be8fc886678/ijmsv22p0641g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/0af2c33c6540/ijmsv22p0641g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/1dc88225f494/ijmsv22p0641g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f165/11783069/868be520fce9/ijmsv22p0641g005.jpg

相似文献

1
Differences of the Chest Images Between Coronavirus Disease 2019 (COVID-19) Patients and Influenza Patients: A Systematic Review and Meta-analysis.2019冠状病毒病(COVID-19)患者与流感患者胸部影像的差异:一项系统评价与荟萃分析
Int J Med Sci. 2025 Jan 13;22(3):641-650. doi: 10.7150/ijms.98194. eCollection 2025.
2
Thoracic imaging tests for the diagnosis of COVID-19.用于 COVID-19 诊断的胸部影像学检查。
Cochrane Database Syst Rev. 2022 May 16;5(5):CD013639. doi: 10.1002/14651858.CD013639.pub5.
3
Physical interventions to interrupt or reduce the spread of respiratory viruses.物理干预措施以阻断或减少呼吸道病毒的传播。
Cochrane Database Syst Rev. 2023 Jan 30;1(1):CD006207. doi: 10.1002/14651858.CD006207.pub6.
4
Differences in clinical characteristics between coronavirus disease 2019 (COVID-19) and influenza: a systematic review and meta-analysis.2019冠状病毒病(COVID-19)与流感临床特征的差异:一项系统综述和荟萃分析
NPJ Prim Care Respir Med. 2025 Jan 28;35(1):8. doi: 10.1038/s41533-025-00414-0.
5
Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.在基层医疗机构或医院门诊环境中,如果患者出现以下症状和体征,可判断其是否患有 COVID-19。
Cochrane Database Syst Rev. 2022 May 20;5(5):CD013665. doi: 10.1002/14651858.CD013665.pub3.
6
The effect of sample site and collection procedure on identification of SARS-CoV-2 infection.样本采集部位和采集程序对严重急性呼吸综合征冠状病毒2(SARS-CoV-2)感染鉴定的影响。
Cochrane Database Syst Rev. 2024 Dec 16;12(12):CD014780. doi: 10.1002/14651858.CD014780.
7
Publication timeline of chest imaging reporting in children with coronavirus disease 2019 (COVID-19): a systematic review spanning 2020.2019年冠状病毒病(COVID-19)患儿胸部影像报告的发表时间线:一项涵盖2020年的系统评价
Pediatr Radiol. 2022 Sep;52(10):1998-2008. doi: 10.1007/s00247-022-05466-9. Epub 2022 Aug 12.
8
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.系统性药理学治疗慢性斑块状银屑病:网络荟萃分析。
Cochrane Database Syst Rev. 2021 Apr 19;4(4):CD011535. doi: 10.1002/14651858.CD011535.pub4.
9
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.慢性斑块状银屑病的全身药理学治疗:一项网状荟萃分析。
Cochrane Database Syst Rev. 2017 Dec 22;12(12):CD011535. doi: 10.1002/14651858.CD011535.pub2.
10
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.慢性斑块状银屑病的全身药理学治疗:一项网状Meta分析。
Cochrane Database Syst Rev. 2020 Jan 9;1(1):CD011535. doi: 10.1002/14651858.CD011535.pub3.

引用本文的文献

1
Influenza A vs. COVID-19: A Retrospective Comparison of Hospitalized Patients in a Post-Pandemic Setting.甲型流感与新冠病毒:大流行后环境下住院患者的回顾性比较
Microorganisms. 2025 Aug 6;13(8):1836. doi: 10.3390/microorganisms13081836.

本文引用的文献

1
Quality of Life 6 Months after COVID-19 Hospitalisation: A Single-Centre Polish Registry.新冠病毒感染住院治疗6个月后的生活质量:一项波兰单中心登记研究
J Clin Med. 2023 Aug 16;12(16):5327. doi: 10.3390/jcm12165327.
2
What Is Machine Learning, Artificial Neural Networks and Deep Learning?-Examples of Practical Applications in Medicine.什么是机器学习、人工神经网络和深度学习?——医学中的实际应用示例
Diagnostics (Basel). 2023 Aug 3;13(15):2582. doi: 10.3390/diagnostics13152582.
3
Artificial neural network based prediction of the lung tissue involvement as an independent in-hospital mortality and mechanical ventilation risk factor in COVID-19.
基于人工神经网络的 COVID-19 肺部组织受累预测及其作为院内独立死亡和机械通气风险因素。
J Med Virol. 2023 May;95(5):e28787. doi: 10.1002/jmv.28787.
4
Chest computed tomography analysis of lung sparing morphology: differentiation of COVID-19 pneumonia from influenza pneumonia and bacterial pneumonia using the arched bridge and vacuole signs.肺保留形态的胸部计算机断层扫描分析:利用拱桥征和空泡征鉴别新型冠状病毒肺炎与流感肺炎及细菌性肺炎
Hong Kong Med J. 2023 Feb;29(1):39-48. doi: 10.12809/hkmj219291.
5
Comparison of hospitalized patients with severe pneumonia caused by COVID-19 and influenza A (H7N9 and H1N1): A retrospective study from a designated hospital.新型冠状病毒肺炎(COVID-19)与甲型流感(H7N9和H1N1)所致重症肺炎住院患者的比较:来自一家定点医院的回顾性研究
Open Med (Wars). 2022 Dec 9;17(1):1965-1972. doi: 10.1515/med-2022-0610. eCollection 2022.
6
Comparative analysis of elderly hospitalized patients with COVID-19 or influenza A H1N1 virus infections.老年住院患者 COVID-19 或甲型 H1N1 流感病毒感染的对比分析。
Int J Infect Dis. 2022 Dec;125:278-284. doi: 10.1016/j.ijid.2022.11.008. Epub 2022 Nov 9.
7
Application of artificial intelligence in diagnosing COVID-19 disease symptoms on chest X-rays: A systematic review.人工智能在诊断胸部 X 光 COVID-19 疾病症状中的应用:系统评价。
Int J Med Sci. 2022 Sep 28;19(12):1743-1752. doi: 10.7150/ijms.76515. eCollection 2022.
8
SARS-CoV-2 and seasonal influenza: similarities and disparities.SARS-CoV-2 与季节性流感:相似与差异。
Arch Virol. 2022 Dec;167(12):2761-2765. doi: 10.1007/s00705-022-05615-3. Epub 2022 Oct 21.
9
Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study.一项多中心队列研究中COVID-19与流感感染的计算机断层扫描成像特征的时间演变比较。
Eur J Radiol Open. 2022;9:100431. doi: 10.1016/j.ejro.2022.100431. Epub 2022 Jun 24.
10
A Retrospective, Monocentric Study Comparing Co and Secondary Infections in Critically Ill COVID-19 and Influenza Patients.一项比较重症 COVID-19 患者和流感患者合并感染与继发感染的回顾性单中心研究。
Antibiotics (Basel). 2022 May 24;11(6):704. doi: 10.3390/antibiotics11060704.