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Predicting critically ill patients outcome in the ICU using UHPLC-HRMS data

2024-03Conference paper Open access
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authorProfile.emailbiblioteca@isel.pt
datacite.subject.fosEngenharia e Tecnologia::Engenharia Química
dc.contributor.authorFonseca, Tiago AH
dc.contributor.authorHenrique Fonseca, Tiago Alexandre
dc.contributor.authorVon Rekowski, Cristiana P.
dc.contributor.authorVon Rekowski, Cristiana
dc.contributor.authorAraújo, Rúben
dc.contributor.authorAraújo, Rúben Alexandre Dinis
dc.contributor.authorOliveira, M. Conceição
dc.contributor.authorOliveira, Maria Conceição
dc.contributor.authorBento, Luís
dc.contributor.authorJustino, Gonçalo C.
dc.contributor.authorJustino, Gonçalo
dc.contributor.authorCalado, Cecília
dc.contributor.authorCalado, Cecília
dc.contributor.editorDomingues, Nuno A. S.
dc.contributor.editorGomes, Vítor
dc.contributor.editorTopcuoglu, Bulent
dc.date.accessioned2025-04-04T12:07:54Z
dc.date.available2025-04-04T12:07:54Z
dc.date.issued2024-03
dc.description.abstractThe available scores to predict patients’ outcomes in specific settings generally present low sensitivities and specificities when applied to intensive care units’ (ICUs) populations. Advancements in analytical techniques, notably Ultra-High Performance Liquid Chromatography- Mass Spectrometry (UHPLCHRMS) transformed biomarker identification, enabling a comprehensive profiling of biofluids, including serum. In the current work, untargeted metabolomics, utilizing UHPLC-HRMS serum analysis, was performed on 16 ICU patients, categorized as either discharged (n=8), or deceased (n=8) in average seven days post sample collection. Linear discriminant analysis (LDA) or principal component analysis (PCA)-LDA models involving different metabolite sets were developed, enabling to predict patients’ outcomes in the ICU with 92% accuracy and 83% sensitivity on validation datasets. These results highlight the advantages of UHPLC-HRMS as a platform capable of providing a set of clinically significant biomarkers to predict patients’ outcome. The available scores to predict patients’ outcomes in specific settings generally present low sensitivities and specificities when applied to intensive care units’ (ICUs) populations. Advancements in analytical techniques, notably Ultra-High Performance Liquid Chromatography- Mass Spectrometry (UHPLCHRMS) transformed biomarker identification, enabling a comprehensive profiling of biofluids, including serum. In the current work, untargeted metabolomics, utilizing UHPLC-HRMS serum analysis, was performed on 16 ICU patients, categorized as either discharged (n=8), or deceased (n=8) in average seven days post sample collection. Linear discriminant analysis (LDA) or principal component analysis (PCA)-LDA models involving different metabolite sets were developed, enabling to predict patients’ outcomes in the ICU with 92% accuracy and 83% sensitivity on validation datasets. These results highlight the advantages of UHPLC-HRMS as a platform capable of providing a set of clinically significant biomarkers to predict patients’ outcome.eng
dc.identifier.citationFonseca, T. A. H. et al. Predicting critically ill patients outcome in the ICU using UHPLC-HRMS data. In 3rd International Conference on Challenges in Engineering, Medical, Economics and Education: Research & Solutions (CEMEERS-24a), Porto, Portugal, 2024, pp. 16-21, doi: 10.17758/EIRAI20
dc.identifier.doihttps://doi.org/10.17758/EIRAI20
dc.identifier.isbn978-989-9121-36-2
dc.identifier.urihttp://hdl.handle.net/10400.21/21753
dc.language.isoeng
dc.peerreviewedyes
dc.publisherPilares D`Elegância
dc.relation.hasversionhttps://fenp.org/procceeding.php/40
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBiomarkers
dc.subjectIntensive care unit
dc.subjectPredictive models
dc.subjectMetabolomics
dc.subjectMass spectrometry
dc.titlePredicting critically ill patients outcome in the ICU using UHPLC-HRMS dataeng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2024-03-07
oaire.citation.conferencePlacePorto, Portugal
oaire.citation.endPage21
oaire.citation.startPage16
oaire.citation.title3rd International Conference on Challenges in Engineering, Medical, Economics and Education: Research & Solutions (CEMEERS-24a)
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameHenrique Fonseca
person.familyNameVon Rekowski
person.familyNameAraújo
person.familyNameOliveira
person.familyNameJustino
person.familyNameCalado
person.givenNameTiago Alexandre
person.givenNameCristiana
person.givenNameRúben Alexandre Dinis
person.givenNameMaria Conceição
person.givenNameGonçalo
person.givenNameCecília
person.identifier1960990
person.identifier734387
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person.identifier.ciencia-id9A18-BFDC-ED95
person.identifier.ciencia-idAB11-548D-A6A9
person.identifier.ciencia-id781D-3A77-5A3B
person.identifier.ciencia-id9418-E320-3177
person.identifier.orcid0000-0003-0741-2211
person.identifier.orcid0009-0009-6843-1935
person.identifier.orcid0000-0002-9369-6486
person.identifier.orcid0000-0002-3068-4920
person.identifier.orcid0000-0003-4828-4738
person.identifier.orcid0000-0002-5264-9755
person.identifier.ridH-8263-2012
person.identifier.ridB-3190-2011
person.identifier.ridE-2102-2014
person.identifier.scopus-author-id35611565300
person.identifier.scopus-author-id6507263334
person.identifier.scopus-author-id6603163260
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