Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal

Detalhes bibliográficos
Autor(a) principal: Horta, Alexandra Bayão
Data de Publicação: 2020
Outros Autores: Geraldes, Carlos, Salgado, Cátia, Vieira, Susana, Xavier, Miguel, Papoila, Ana Luísa
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/109428
Resumo: Funding: The work of A.L. Papoila and C. Geraldes is partially sponsored by national funds through Fundação Nacional para a Ciência e Tecnologia, Portugal—FCT under the project PEst-OE/MAT/UI0006/2014. The work of Cátia Salgado was supported by the PhD Scholarship SFRH/BD/121875/2016 from Portuguese Foundation for Science & Technology. S. M. Vieira acknowledges the support by Program Investigador FCT (IF/00833/2014) from FCT, co-funded by the European Social Fund (ESF) through the Operational Program Human Potential (POPH).
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spelling Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectalA multivariable prediction model to select colorectal surgical patients for co-managementClinicalColorectal surgery/methodsCooperative behaviorDecision support systemsFailure to rescueHealth carePatient selectionMedicine(all)SDG 3 - Good Health and Well-beingFunding: The work of A.L. Papoila and C. Geraldes is partially sponsored by national funds through Fundação Nacional para a Ciência e Tecnologia, Portugal—FCT under the project PEst-OE/MAT/UI0006/2014. The work of Cátia Salgado was supported by the PhD Scholarship SFRH/BD/121875/2016 from Portuguese Foundation for Science & Technology. S. M. Vieira acknowledges the support by Program Investigador FCT (IF/00833/2014) from FCT, co-funded by the European Social Fund (ESF) through the Operational Program Human Potential (POPH).Introduction: Increased life expectancy leads to older and frailer surgical patients. Co-management between medical and surgical specialities has proven favourable in complex situations. Selection of patients for co-management is full of difficulties. The aim of this study was to develop a clinical decision support tool to select surgical patients for co-management. Material and Methods: Clinical data was collected from patient electronic health records with an ICD-9 code for colorectal surgery from January 2012 to December 2015 at a hospital in Lisbon. The outcome variable consists in co-management signalling. A dataset from 344 patients was used to develop the prediction model and a second data set from 168 patients was used for external validation. Results: Using logistic regression modelling the authors built a five variable (age, burden of comorbidities, ASA-PS status, surgical risk and recovery time) predictive referral model for co-management. This model has an area under the curve (AUC) of 0.86 (95% CI: 0.81 - 0.90), a predictive Brier score of 0.11, a sensitivity of 0.80, a specificity of 0.82 and an accuracy of 81.3%. Discussion: Early referral of high-risk patients may be valuable to guide the decision on the best level of post-operative clinical care. We developed a simple bedside decision tool with a good discriminatory and predictive performance in order to select patients for comanagement. Conclusion: A simple bed-side clinical decision support tool of patients for co-management is viable, leading to potential improvement in early recognition and management of postoperative complications and reducing the ‘failure to rescue’. Generalizability to other clinical settings requires adequate customization and validation.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)RUNHorta, Alexandra BayãoGeraldes, CarlosSalgado, CátiaVieira, SusanaXavier, MiguelPapoila, Ana Luísa2020-12-29T00:03:39Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/109428por0870-399XPURE: 27073907https://doi.org/10.20344/AMP.12996info: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:RCAAP2024-03-11T04:53:46Zoai:run.unl.pt:10362/109428Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:41:27.005478Repositório 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 Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
A multivariable prediction model to select colorectal surgical patients for co-management
title Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
spellingShingle Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
Horta, Alexandra Bayão
Clinical
Colorectal surgery/methods
Cooperative behavior
Decision support systems
Failure to rescue
Health care
Patient selection
Medicine(all)
SDG 3 - Good Health and Well-being
title_short Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
title_full Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
title_fullStr Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
title_full_unstemmed Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
title_sort Um modelo de predição para seleccionar para co-gestão doentes de cirurgia colo-rectal
author Horta, Alexandra Bayão
author_facet Horta, Alexandra Bayão
Geraldes, Carlos
Salgado, Cátia
Vieira, Susana
Xavier, Miguel
Papoila, Ana Luísa
author_role author
author2 Geraldes, Carlos
Salgado, Cátia
Vieira, Susana
Xavier, Miguel
Papoila, Ana Luísa
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
RUN
dc.contributor.author.fl_str_mv Horta, Alexandra Bayão
Geraldes, Carlos
Salgado, Cátia
Vieira, Susana
Xavier, Miguel
Papoila, Ana Luísa
dc.subject.por.fl_str_mv Clinical
Colorectal surgery/methods
Cooperative behavior
Decision support systems
Failure to rescue
Health care
Patient selection
Medicine(all)
SDG 3 - Good Health and Well-being
topic Clinical
Colorectal surgery/methods
Cooperative behavior
Decision support systems
Failure to rescue
Health care
Patient selection
Medicine(all)
SDG 3 - Good Health and Well-being
description Funding: The work of A.L. Papoila and C. Geraldes is partially sponsored by national funds through Fundação Nacional para a Ciência e Tecnologia, Portugal—FCT under the project PEst-OE/MAT/UI0006/2014. The work of Cátia Salgado was supported by the PhD Scholarship SFRH/BD/121875/2016 from Portuguese Foundation for Science & Technology. S. M. Vieira acknowledges the support by Program Investigador FCT (IF/00833/2014) from FCT, co-funded by the European Social Fund (ESF) through the Operational Program Human Potential (POPH).
publishDate 2020
dc.date.none.fl_str_mv 2020-12-29T00:03:39Z
2020
2020-01-01T00:00:00Z
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 http://hdl.handle.net/10362/109428
url http://hdl.handle.net/10362/109428
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv 0870-399X
PURE: 27073907
https://doi.org/10.20344/AMP.12996
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.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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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