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Performance of blink reflex in patients during anesthesia induction with propofol and remifentanil: prediction probabilities and multinomial logistic analysis

2020-11-14Journal article Open access
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dc.contributor.authorFerreira, Ana Leitão
dc.contributor.authorNunes, Catarina S
dc.contributor.authorVide, Sérgio
dc.contributor.authorFelgueiras, João
dc.contributor.authorCardoso, Márcio
dc.contributor.authorAmorim, Pedro
dc.contributor.authorMendes, Joaquim
dc.date.accessioned2021-07-06T18:10:11Z
dc.date.available2021-07-06T18:10:11Z
dc.date.issued2020-11-14
dc.description.abstractBackground: The amount of propofol needed to induce loss of responsiveness varied widely among patients, and they usually required less than the initial dose recommended by the drug package inserts. Identifying precisely the moment of loss of responsiveness will determine the amount of propofol each patient needs. Currently, methods to decide the exact moment of loss of responsiveness are based on subjective analysis, and the monitors that use objective methods fail in precision. Based on previous studies, we believe that the blink reflex can be useful to characterize, more objectively, the transition from responsiveness to unresponsiveness. The purpose of this study is to investigate the relation between the electrically evoked blink reflex and the level of sedation/anesthesia measured with an adapted version of the Richmond Agitation-Sedation Scale, during the induction phase of general anesthesia with propofol and remifentanil. Adding the blink reflex to other variables may allow a more objective assessment of the exact moment of loss of responsiveness and a more personalized approach to anesthesia induction. Results: The electromyographic-derived features proved to be good predictors to estimate the different levels of sedation/anesthesia. The results of the multinomial analysis showed a reasonable performance of the model, explaining almost 70% of the adapted Richmond Agitation-Sedation Scale variance. The overall predictive accuracy for the model was 73.6%, suggesting that it is useful to predict loss of responsiveness. Conclusions: Our developed model was based on the information of the electromyographic-derived features from the blink reflex responses. It was able to predict the drug effect in patients undergoing general anesthesia, which can be helpful for the anesthesiologists to reduce the overwhelming variability observed between patients and avoid many cases of overdosing and associated risks. Despite this, future research is needed to account for variabilities in the clinical response of the patients and with the interactions between propofol and remifentanil. Nevertheless, a method that could allow for an automatic prediction/detection of loss of responsiveness is a step forward for personalized medicine.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationFerreira AL, Nunes CS, Vide S, Felgueiras J, Cardoso M, Amorim P, Mendes J. Performance of blink reflex in patients during anesthesia induction with propofol and remifentanil: prediction probabilities and multinomial logistic analysis. Biomed Eng Online. 2020 Nov 14;19(1):84. doi: 10.1186/s12938-020-00828-6. PMID: 33189149; PMCID: PMC7666522.pt_PT
dc.identifier.doi10.1186/s12938-020-00828-6pt_PT
dc.identifier.issn1475-925X
dc.identifier.urihttp://hdl.handle.net/10400.16/2489
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherBioMed Centralpt_PT
dc.relationAdvanced Consciousness Assessment for Anaesthesia
dc.relation.publisherversionhttps://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-020-00828-6pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAnesthesia monitoringpt_PT
dc.subjectBlink reflexpt_PT
dc.subjectLoss of responsivenesspt_PT
dc.subjectPredictionpt_PT
dc.subjectPropofolpt_PT
dc.subjectSedationpt_PT
dc.titlePerformance of blink reflex in patients during anesthesia induction with propofol and remifentanil: prediction probabilities and multinomial logistic analysispt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleAdvanced Consciousness Assessment for Anaesthesia
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F98915%2F2013/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEMS%2F50022%2F2013/PT
oaire.citation.conferencePlaceEnglandpt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage84pt_PT
oaire.citation.titleBiomedical engineering onlinept_PT
oaire.citation.volume19pt_PT
oaire.fundingStream5876
person.familyNameNunes
person.familyNameAmorim
person.givenNameCatarina
person.givenNamePedro
person.identifier.ciencia-id691F-CDC2-E26A
person.identifier.orcid0000-0002-8357-0994
person.identifier.orcid0000-0001-7466-4174
person.identifier.ridK-5110-2012
person.identifier.scopus-author-id7006695219
person.identifier.scopus-author-id55429654100
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublicationaad38f74-e8d1-431c-a230-8ca77db9f190
relation.isAuthorOfPublication.latestForDiscoveryaad38f74-e8d1-431c-a230-8ca77db9f190
relation.isProjectOfPublication3241d100-64cf-4e35-84ec-9dedf893c179
relation.isProjectOfPublication083cd235-fcfe-4010-bff5-56a9f4e4f8d6
relation.isProjectOfPublication.latestForDiscovery083cd235-fcfe-4010-bff5-56a9f4e4f8d6

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