Cyranose 320呼吸分析中的线性和非线性模型综述。

IF 3.7 4区 医学 Q1 BIOCHEMICAL RESEARCH METHODS
Maryan Arrieta, Barbara Swanson, Louis Fogg, Abhinav Bhushan
{"title":"Cyranose 320呼吸分析中的线性和非线性模型综述。","authors":"Maryan Arrieta,&nbsp;Barbara Swanson,&nbsp;Louis Fogg,&nbsp;Abhinav Bhushan","doi":"10.1088/1752-7163/accf31","DOIUrl":null,"url":null,"abstract":"<p><p>Analysis of volatile organic compounds (VOCs) in breath specimens has potential for point of care (POC) screening due to ease of sample collection. While the electronic nose (e-nose) is a standard VOC measure across a wide range of industries, it has not been adopted for POC screening in healthcare. One limitation of the e-nose is the absence of mathematical models of data analysis that yield easily interpreted findings at POC. The purposes of this review were to (1) examine the sensitivity/specificity results from studies that analyzed breath smellprints using the Cyranose 320, a widely used commercial e-nose, and (2) determine whether linear or nonlinear mathematical models are superior for analyzing Cyranose 320 breath smellprints. This systematic review was conducted according to the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analyses using keywords related to e-nose and breath. Twenty-two articles met the eligibility criteria. Two studies used a linear model while the rest used nonlinear models. The two studies that used a linear model had a smaller range for mean of sensitivity and higher mean (71.0%-96.0%;<i>M</i>= 83.5%) compared to the studies that used nonlinear models (46.9%-100%;<i>M</i>= 77.0%). Additionally, studies that used linear models had a smaller range for mean of specificity and higher mean (83.0%-91.5%;<i>M</i>= 87.2%) compared to studies that used nonlinear models (56.9%-94.0%;<i>M</i>= 76.9%). Linear models achieved smaller ranges for means of sensitivity and specificity compared to nonlinear models supporting additional investigations of their use for POC testing. Because our findings were derived from studies of heterogenous medical conditions, it is not known if they generalize to specific diagnoses.</p>","PeriodicalId":15306,"journal":{"name":"Journal of breath research","volume":"17 3","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Review of linear and nonlinear models in breath analysis by Cyranose 320.\",\"authors\":\"Maryan Arrieta,&nbsp;Barbara Swanson,&nbsp;Louis Fogg,&nbsp;Abhinav Bhushan\",\"doi\":\"10.1088/1752-7163/accf31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Analysis of volatile organic compounds (VOCs) in breath specimens has potential for point of care (POC) screening due to ease of sample collection. While the electronic nose (e-nose) is a standard VOC measure across a wide range of industries, it has not been adopted for POC screening in healthcare. One limitation of the e-nose is the absence of mathematical models of data analysis that yield easily interpreted findings at POC. The purposes of this review were to (1) examine the sensitivity/specificity results from studies that analyzed breath smellprints using the Cyranose 320, a widely used commercial e-nose, and (2) determine whether linear or nonlinear mathematical models are superior for analyzing Cyranose 320 breath smellprints. This systematic review was conducted according to the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analyses using keywords related to e-nose and breath. Twenty-two articles met the eligibility criteria. Two studies used a linear model while the rest used nonlinear models. The two studies that used a linear model had a smaller range for mean of sensitivity and higher mean (71.0%-96.0%;<i>M</i>= 83.5%) compared to the studies that used nonlinear models (46.9%-100%;<i>M</i>= 77.0%). Additionally, studies that used linear models had a smaller range for mean of specificity and higher mean (83.0%-91.5%;<i>M</i>= 87.2%) compared to studies that used nonlinear models (56.9%-94.0%;<i>M</i>= 76.9%). Linear models achieved smaller ranges for means of sensitivity and specificity compared to nonlinear models supporting additional investigations of their use for POC testing. Because our findings were derived from studies of heterogenous medical conditions, it is not known if they generalize to specific diagnoses.</p>\",\"PeriodicalId\":15306,\"journal\":{\"name\":\"Journal of breath research\",\"volume\":\"17 3\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2023-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of breath research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1088/1752-7163/accf31\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of breath research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1088/1752-7163/accf31","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 2

摘要

呼气样本中挥发性有机化合物(VOCs)的分析由于易于样本采集,有可能用于护理点(POC)筛查。虽然电子鼻(e-nose)是广泛行业的标准VOC测量方法,但它尚未被用于医疗保健中的POC筛查。电子鼻的一个限制是缺乏数据分析的数学模型,无法在POC上产生容易解释的发现。本综述的目的是:(1)检查使用Cyranose 320(一种广泛使用的商用电子鼻)分析呼吸指纹的研究的敏感性/特异性结果,以及(2)确定线性或非线性数学模型是否更适合分析Cyranose 320呼吸指纹。本系统评价根据系统评价和荟萃分析首选报告项目的指南进行,使用与电子鼻和呼吸相关的关键词。22篇文章符合入选标准。两项研究使用线性模型,其余研究使用非线性模型。与使用非线性模型的研究(46.9%-100%,M= 77.0%)相比,使用线性模型的两项研究灵敏度均值范围较小,均值较高(71.0%-96.0%,M= 83.5%)。此外,与使用非线性模型的研究(56.9%-94.0%,M= 76.9%)相比,使用线性模型的研究具有更小的特异性平均值范围和更高的平均值(83.0%-91.5%,M= 87.2%)。与非线性模型相比,线性模型的灵敏度和特异性范围较小,支持对其用于POC测试的额外调查。由于我们的研究结果来自于异质性医疗条件的研究,因此尚不清楚它们是否适用于特定的诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review of linear and nonlinear models in breath analysis by Cyranose 320.

Analysis of volatile organic compounds (VOCs) in breath specimens has potential for point of care (POC) screening due to ease of sample collection. While the electronic nose (e-nose) is a standard VOC measure across a wide range of industries, it has not been adopted for POC screening in healthcare. One limitation of the e-nose is the absence of mathematical models of data analysis that yield easily interpreted findings at POC. The purposes of this review were to (1) examine the sensitivity/specificity results from studies that analyzed breath smellprints using the Cyranose 320, a widely used commercial e-nose, and (2) determine whether linear or nonlinear mathematical models are superior for analyzing Cyranose 320 breath smellprints. This systematic review was conducted according to the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analyses using keywords related to e-nose and breath. Twenty-two articles met the eligibility criteria. Two studies used a linear model while the rest used nonlinear models. The two studies that used a linear model had a smaller range for mean of sensitivity and higher mean (71.0%-96.0%;M= 83.5%) compared to the studies that used nonlinear models (46.9%-100%;M= 77.0%). Additionally, studies that used linear models had a smaller range for mean of specificity and higher mean (83.0%-91.5%;M= 87.2%) compared to studies that used nonlinear models (56.9%-94.0%;M= 76.9%). Linear models achieved smaller ranges for means of sensitivity and specificity compared to nonlinear models supporting additional investigations of their use for POC testing. Because our findings were derived from studies of heterogenous medical conditions, it is not known if they generalize to specific diagnoses.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of breath research
Journal of breath research BIOCHEMICAL RESEARCH METHODS-RESPIRATORY SYSTEM
CiteScore
7.60
自引率
21.10%
发文量
49
审稿时长
>12 weeks
期刊介绍: Journal of Breath Research is dedicated to all aspects of scientific breath research. The traditional focus is on analysis of volatile compounds and aerosols in exhaled breath for the investigation of exogenous exposures, metabolism, toxicology, health status and the diagnosis of disease and breath odours. The journal also welcomes other breath-related topics. Typical areas of interest include: Big laboratory instrumentation: describing new state-of-the-art analytical instrumentation capable of performing high-resolution discovery and targeted breath research; exploiting complex technologies drawn from other areas of biochemistry and genetics for breath research. Engineering solutions: developing new breath sampling technologies for condensate and aerosols, for chemical and optical sensors, for extraction and sample preparation methods, for automation and standardization, and for multiplex analyses to preserve the breath matrix and facilitating analytical throughput. Measure exhaled constituents (e.g. CO2, acetone, isoprene) as markers of human presence or mitigate such contaminants in enclosed environments. Human and animal in vivo studies: decoding the ''breath exposome'', implementing exposure and intervention studies, performing cross-sectional and case-control research, assaying immune and inflammatory response, and testing mammalian host response to infections and exogenous exposures to develop information directly applicable to systems biology. Studying inhalation toxicology; inhaled breath as a source of internal dose; resultant blood, breath and urinary biomarkers linked to inhalation pathway. Cellular and molecular level in vitro studies. Clinical, pharmacological and forensic applications. Mathematical, statistical and graphical data interpretation.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信