• 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

电子鼻呼吸测试在临床应用中的准确性:系统评价和荟萃分析。

Accuracy of the Electronic Nose Breath Tests in Clinical Application: A Systematic Review and Meta-Analysis.

机构信息

Institute of Environmental and Occupational Health Sciences, National Taiwan University, Taipei 10055, Taiwan.

Department of Public Health, National Taiwan University College of Public Health, Taipei 10055, Taiwan.

出版信息

Biosensors (Basel). 2021 Nov 22;11(11):469. doi: 10.3390/bios11110469.

DOI:10.3390/bios11110469
PMID:34821685
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8615633/
Abstract

(1) Background: An electronic nose applies a sensor array to detect volatile biomarkers in exhaled breath to diagnose diseases. The overall diagnostic accuracy remains unknown. The objective of this review was to provide an estimate of the diagnostic accuracy of sensor-based breath tests for the diagnosis of diseases. (2) Methods: We searched the PubMed and Web of Science databases for studies published between 1 January 2010 and 14 October 2021. The search was limited to human studies published in the English language. Clinical trials were not included in this review. (3) Results: Of the 2418 records identified, 44 publications were eligible, and 5728 patients were included in the final analyses. The pooled sensitivity was 90.0% (95% CI, 86.3-92.8%, I = 47.7%), the specificity was 88.4% (95% CI, 87.1-89.5%, I = 81.4%), and the pooled area under the curve was 0.93 (95% CI 0.91-0.95). (4) Conclusion: The findings of our review suggest that a standardized report of diagnostic accuracy and a report of the accuracy in a test set are needed. Sensor array systems of electronic noses have the potential for noninvasiveness at the point-of-care in hospitals. Nevertheless, the procedure for reporting the accuracy of a diagnostic test must be standardized.

摘要

(1) 背景:电子鼻应用传感器阵列来检测呼气中的挥发性生物标志物,以诊断疾病。整体诊断准确性尚不清楚。本综述的目的是提供基于传感器的呼吸测试在疾病诊断中的诊断准确性的估计。(2) 方法:我们在 PubMed 和 Web of Science 数据库中搜索了 2010 年 1 月 1 日至 2021 年 10 月 14 日期间发表的研究。搜索仅限于以英语发表的人类研究。本综述未包括临床试验。(3) 结果:在 2418 条记录中,有 44 篇符合纳入标准,最终分析纳入了 5728 名患者。汇总敏感性为 90.0%(95%CI,86.3-92.8%,I = 47.7%),特异性为 88.4%(95%CI,87.1-89.5%,I = 81.4%),曲线下面积为 0.93(95%CI 0.91-0.95)。(4) 结论:我们的综述结果表明,需要标准化诊断准确性报告和测试集准确性报告。电子鼻的传感器阵列系统具有在医院现场进行非侵入性检测的潜力。然而,诊断测试准确性的报告程序必须标准化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/86621e88950c/biosensors-11-00469-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/bd7ed0195295/biosensors-11-00469-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/c2bab160d0d0/biosensors-11-00469-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/deb422316edf/biosensors-11-00469-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/266f98d5da5f/biosensors-11-00469-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/1681bbcbea6d/biosensors-11-00469-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/86621e88950c/biosensors-11-00469-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/bd7ed0195295/biosensors-11-00469-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/c2bab160d0d0/biosensors-11-00469-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/deb422316edf/biosensors-11-00469-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/266f98d5da5f/biosensors-11-00469-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/1681bbcbea6d/biosensors-11-00469-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8ab/8615633/86621e88950c/biosensors-11-00469-g006.jpg

相似文献

1
Accuracy of the Electronic Nose Breath Tests in Clinical Application: A Systematic Review and Meta-Analysis.电子鼻呼吸测试在临床应用中的准确性:系统评价和荟萃分析。
Biosensors (Basel). 2021 Nov 22;11(11):469. doi: 10.3390/bios11110469.
2
Accuracy and Methodologic Challenges of Volatile Organic Compound-Based Exhaled Breath Tests for Cancer Diagnosis: A Systematic Review and Meta-analysis.基于挥发性有机化合物的呼气测试用于癌症诊断的准确性和方法学挑战:系统评价和荟萃分析。
JAMA Oncol. 2019 Jan 1;5(1):e182815. doi: 10.1001/jamaoncol.2018.2815. Epub 2019 Jan 10.
3
Diagnostic Performance of Electronic Noses in Cancer Diagnoses Using Exhaled Breath: A Systematic Review and Meta-analysis.电子鼻在基于呼气检测的癌症诊断中的诊断性能:一项系统评价和荟萃分析。
JAMA Netw Open. 2022 Jun 1;5(6):e2219372. doi: 10.1001/jamanetworkopen.2022.19372.
4
Exhaled-breath Testing for Prostate Cancer Based on Volatile Organic Compound Profiling Using an Electronic Nose Device (Aeonose™): A Preliminary Report.基于电子鼻设备(Aeonose™)对挥发性有机化合物分析的呼气检测前列腺癌:初步报告。
Eur Urol Focus. 2020 Nov 15;6(6):1220-1225. doi: 10.1016/j.euf.2018.11.006. Epub 2018 Nov 24.
5
Electronic nose analysis of exhaled breath to diagnose ventilator-associated pneumonia.呼出气的电子鼻分析用于诊断呼吸机相关性肺炎。
Respir Med. 2015 Nov;109(11):1454-9. doi: 10.1016/j.rmed.2015.09.014. Epub 2015 Sep 30.
6
Diagnosis of tuberculosis through breath test: A systematic review.通过呼吸测试诊断结核病:系统评价。
EBioMedicine. 2019 Aug;46:202-214. doi: 10.1016/j.ebiom.2019.07.056. Epub 2019 Aug 8.
7
Accuracy of breath test for diabetes mellitus diagnosis: a systematic review and meta-analysis.用于糖尿病诊断的呼气试验准确性:系统评价与荟萃分析
BMJ Open Diabetes Res Care. 2021 May;9(1). doi: 10.1136/bmjdrc-2021-002174.
8
Comparative analysis of volatile organic compounds of breath and urine for distinguishing patients with liver cirrhosis from healthy controls by using electronic nose and voltammetric electronic tongue.运用电子鼻和伏安型电子舌对呼出气体和尿液中的挥发性有机化合物进行比较分析,以区分肝硬化患者与健康对照者。
Anal Chim Acta. 2021 Nov 1;1184:339028. doi: 10.1016/j.aca.2021.339028. Epub 2021 Sep 3.
9
Advancing accuracy in breath testing for lung cancer: strategies for improving diagnostic precision in imbalanced data.提高肺癌呼吸测试的准确性:改善不平衡数据中诊断精度的策略。
Respir Res. 2024 Jan 16;25(1):32. doi: 10.1186/s12931-024-02668-7.
10
Evening and morning exhaled volatile compound patterns are different in obstructive sleep apnoea assessed with electronic nose.使用电子鼻评估时,阻塞性睡眠呼吸暂停患者早晚呼出的挥发性化合物模式不同。
Sleep Breath. 2015 Mar;19(1):247-53. doi: 10.1007/s11325-014-1003-z. Epub 2014 May 20.

引用本文的文献

1
Design of an Electronic Nose System with Automatic End-Tidal Breath Gas Collection for Enhanced Breath Detection Performance.用于增强呼气检测性能的具有自动潮气末呼吸气体收集功能的电子鼻系统设计
Micromachines (Basel). 2025 Apr 14;16(4):463. doi: 10.3390/mi16040463.
2
Residential Proximity Land Use Characteristics and Exhaled Volatile Organic Compounds' Impact on Pulmonary Function in Asthmatic Children.居住附近土地利用特征及呼出挥发性有机化合物对哮喘儿童肺功能的影响
J Xenobiot. 2025 Feb 5;15(1):27. doi: 10.3390/jox15010027.
3
Development of Electronic Nose as a Complementary Screening Tool for Breath Testing in Colorectal Cancer.

本文引用的文献

1
Chemometric analysis of the global pattern of volatile organic compounds in the exhaled breath of patients with COVID-19, post-COVID and healthy subjects. Proof of concept for post-COVID assessment.新冠病毒、新冠后和健康受试者呼气中挥发性有机化合物的全球模式的化学计量分析。新冠后评估的概念验证。
Talanta. 2022 Jan 1;236:122832. doi: 10.1016/j.talanta.2021.122832. Epub 2021 Sep 2.
2
Comparative analysis of volatile organic compounds of breath and urine for distinguishing patients with liver cirrhosis from healthy controls by using electronic nose and voltammetric electronic tongue.运用电子鼻和伏安型电子舌对呼出气体和尿液中的挥发性有机化合物进行比较分析,以区分肝硬化患者与健康对照者。
Anal Chim Acta. 2021 Nov 1;1184:339028. doi: 10.1016/j.aca.2021.339028. Epub 2021 Sep 3.
3
电子鼻作为结直肠癌呼气检测辅助筛查工具的开发
Biosensors (Basel). 2025 Feb 1;15(2):82. doi: 10.3390/bios15020082.
4
A Review on Long COVID Screening: Challenges and Perspectives Focusing on Exhaled Breath Gas Sensing.长新冠筛查综述:聚焦呼出气气体传感的挑战与展望
ACS Sens. 2025 Mar 28;10(3):1564-1578. doi: 10.1021/acssensors.4c02280. Epub 2024 Dec 16.
5
Application of electronic nose technology in the diagnosis of gastrointestinal diseases: a review.电子鼻技术在胃肠道疾病诊断中的应用:综述
J Cancer Res Clin Oncol. 2024 Aug 27;150(8):401. doi: 10.1007/s00432-024-05925-w.
6
Exhaled Biomarkers for Point-of-Care Diagnosis: Recent Advances and New Challenges in Breathomics.用于即时诊断的呼出生物标志物:呼吸组学的最新进展与新挑战
Micromachines (Basel). 2023 Feb 4;14(2):391. doi: 10.3390/mi14020391.
7
Forecasting the Post-Pandemic Effects of the SARS-CoV-2 Virus Using the Bullwhip Phenomenon Alongside Use of Nanosensors for Disease Containment and Cure.利用牛鞭效应预测严重急性呼吸综合征冠状病毒2(SARS-CoV-2)病毒的大流行后影响,并结合使用纳米传感器进行疾病控制和治疗。
Materials (Basel). 2022 Jul 21;15(14):5078. doi: 10.3390/ma15145078.
8
Mask assistance to colorimetric sniffers for detection of Covid-19 disease using exhaled breath metabolites.使用呼出气体代谢物,通过口罩辅助比色嗅探器检测新冠病毒疾病
Sens Actuators B Chem. 2022 Oct 15;369:132379. doi: 10.1016/j.snb.2022.132379. Epub 2022 Jul 14.
9
Modular Point-of-Care Breath Analyzer and Shape Taxonomy-Based Machine Learning for Gastric Cancer Detection.用于胃癌检测的模块化即时呼吸分析仪及基于形状分类法的机器学习
Diagnostics (Basel). 2022 Feb 14;12(2):491. doi: 10.3390/diagnostics12020491.
The smell of lung disease: a review of the current status of electronic nose technology.肺部疾病的气味:电子鼻技术现状综述。
Respir Res. 2021 Sep 17;22(1):246. doi: 10.1186/s12931-021-01835-4.
4
Discrimination of COPD and lung cancer from controls through breath analysis using a self-developed e-nose.利用自主研发的电子鼻通过呼吸分析对 COPD 和肺癌与对照进行区分。
J Breath Res. 2021 Aug 3;15(4). doi: 10.1088/1752-7163/ac1326.
5
The PRISMA 2020 statement: an updated guideline for reporting systematic reviews.PRISMA 2020 声明:系统评价报告的更新指南。
BMJ. 2021 Mar 29;372:n71. doi: 10.1136/bmj.n71.
6
Sensing gastric cancer via point-of-care sensor breath analyzer.通过即时传感器呼气分析仪检测胃癌。
Cancer. 2021 Apr 15;127(8):1286-1292. doi: 10.1002/cncr.33437. Epub 2021 Mar 19.
7
Breath biopsy of breast cancer using sensor array signals and machine learning analysis.使用传感器阵列信号和机器学习分析进行乳腺癌呼吸活检。
Sci Rep. 2021 Jan 8;11(1):103. doi: 10.1038/s41598-020-80570-0.
8
Applying the electronic nose for pre-operative SARS-CoV-2 screening.应用电子鼻进行术前 SARS-CoV-2 筛查。
Surg Endosc. 2021 Dec;35(12):6671-6678. doi: 10.1007/s00464-020-08169-0. Epub 2020 Dec 2.
9
Volatile organic compound breath testing detects in-situ squamous cell carcinoma of bronchial and laryngeal regions and shows distinct profiles of each tumour.挥发性有机化合物呼气检测可检测支气管和喉部的原位鳞状细胞癌,并显示出每种肿瘤的不同特征。
J Breath Res. 2020 Oct 6;14(4):046013. doi: 10.1088/1752-7163/abb18a.
10
Detection of Ovarian Cancer through Exhaled Breath by Electronic Nose: A Prospective Study.通过电子鼻检测呼出气体诊断卵巢癌:一项前瞻性研究。
Cancers (Basel). 2020 Aug 25;12(9):2408. doi: 10.3390/cancers12092408.