Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/151675 |
Resumo: | Currently available urinalysis methods are often applied for screening and monitoring of several pathologies. However, traditionally analyzed biomarkers in urinalysis still lack sensitivity and specificity to accurately diagnose some diseases. Several studies have proposed the use of electronic noses (eNoses) for the analysis of volatile organic compounds in urine samples that may, directly or indirectly, correlate with certain pathologies. Hence, the aim of this study was to perform a systematic review and meta-analysis of studies concerning the use of portable electronic noses for diagnosis or monitoring of pathologies through analysis of urine samples. A systematic review of the literature was held according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Twenty-four articles met the inclusion criteria and were included in the analysis. The results of the revised studies showed that there are various volatile organic compound profiles, identified through eNose analysis, that may be applied for diagnosis or monitoring of several diseases, such as diabetes, urinary tract infection, inflammatory bowel disease, and kidney disease. A meta-analysis was conducted taking into consideration the data of 10 of the initial 24 articles. The pooled sensitivity, specificity, and diagnostic odds ratio were 84% (95% CI, 0.72–0.92), 85% (95% CI, 0.75–0.91), and 24.17 (95% CI: 7.85–74.41), respectively. The area under the receiver operating characteristic curve was 0.897. These results suggest that eNose technology has adequate diagnostic accuracy for several pathologies and could be a promising screening tool for clinical settings. However, more studies are needed to reduce heterogeneity between results. |
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Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysisCurrently available urinalysis methods are often applied for screening and monitoring of several pathologies. However, traditionally analyzed biomarkers in urinalysis still lack sensitivity and specificity to accurately diagnose some diseases. Several studies have proposed the use of electronic noses (eNoses) for the analysis of volatile organic compounds in urine samples that may, directly or indirectly, correlate with certain pathologies. Hence, the aim of this study was to perform a systematic review and meta-analysis of studies concerning the use of portable electronic noses for diagnosis or monitoring of pathologies through analysis of urine samples. A systematic review of the literature was held according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Twenty-four articles met the inclusion criteria and were included in the analysis. The results of the revised studies showed that there are various volatile organic compound profiles, identified through eNose analysis, that may be applied for diagnosis or monitoring of several diseases, such as diabetes, urinary tract infection, inflammatory bowel disease, and kidney disease. A meta-analysis was conducted taking into consideration the data of 10 of the initial 24 articles. The pooled sensitivity, specificity, and diagnostic odds ratio were 84% (95% CI, 0.72–0.92), 85% (95% CI, 0.75–0.91), and 24.17 (95% CI: 7.85–74.41), respectively. The area under the receiver operating characteristic curve was 0.897. These results suggest that eNose technology has adequate diagnostic accuracy for several pathologies and could be a promising screening tool for clinical settings. However, more studies are needed to reduce heterogeneity between results.Wolters Kluwer Health20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/151675eng2444-866410.1097/j.pbj.0000000000000188Afonso, HASFarraia, MVVieira, MACavaleiro Rufo, Jinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:14:14Zoai:repositorio-aberto.up.pt:10216/151675Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:57:33.555952Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis |
title |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis |
spellingShingle |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis Afonso, HAS |
title_short |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis |
title_full |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis |
title_fullStr |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis |
title_full_unstemmed |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis |
title_sort |
Diagnosis of pathological conditions through electronic nose analysis of urine samples: a systematic review and meta-analysis |
author |
Afonso, HAS |
author_facet |
Afonso, HAS Farraia, MV Vieira, MA Cavaleiro Rufo, J |
author_role |
author |
author2 |
Farraia, MV Vieira, MA Cavaleiro Rufo, J |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Afonso, HAS Farraia, MV Vieira, MA Cavaleiro Rufo, J |
description |
Currently available urinalysis methods are often applied for screening and monitoring of several pathologies. However, traditionally analyzed biomarkers in urinalysis still lack sensitivity and specificity to accurately diagnose some diseases. Several studies have proposed the use of electronic noses (eNoses) for the analysis of volatile organic compounds in urine samples that may, directly or indirectly, correlate with certain pathologies. Hence, the aim of this study was to perform a systematic review and meta-analysis of studies concerning the use of portable electronic noses for diagnosis or monitoring of pathologies through analysis of urine samples. A systematic review of the literature was held according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Twenty-four articles met the inclusion criteria and were included in the analysis. The results of the revised studies showed that there are various volatile organic compound profiles, identified through eNose analysis, that may be applied for diagnosis or monitoring of several diseases, such as diabetes, urinary tract infection, inflammatory bowel disease, and kidney disease. A meta-analysis was conducted taking into consideration the data of 10 of the initial 24 articles. The pooled sensitivity, specificity, and diagnostic odds ratio were 84% (95% CI, 0.72–0.92), 85% (95% CI, 0.75–0.91), and 24.17 (95% CI: 7.85–74.41), respectively. The area under the receiver operating characteristic curve was 0.897. These results suggest that eNose technology has adequate diagnostic accuracy for several pathologies and could be a promising screening tool for clinical settings. However, more studies are needed to reduce heterogeneity between results. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/151675 |
url |
https://hdl.handle.net/10216/151675 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2444-8664 10.1097/j.pbj.0000000000000188 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Wolters Kluwer Health |
publisher.none.fl_str_mv |
Wolters Kluwer Health |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799135896906235904 |