A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996 |
Resumo: | 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. |
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A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-ManagementUm Modelo de Predição para Seleccionar para Co-Gestão Doentes de Cirurgia Colo-rectalColorectal Surgery/methodsCooperative BehaviorDecision Support SystemsClinicalFailure to RescueHealth CarePatient SelectionCirurgia ColorrectalComportamento CooperativoFalha da Terapia de ResgateSelecção de DoentesSistemas de Apoio à Decisão ClínicaIntroduction: 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.Introdução: O aumento da esperança média de vida leva a que a população cirúrgica seja cada vez mais velha e frágil. Os modelos colaborativos de co-gestão entre especialidades médicas e cirúrgicas têm demonstrado ser favoráveis em situações complexas. A selecção de doentes para co-gestão está repleta de dificuldades. O objectivo deste estudo foi construir uma ferramenta de apoio à decisão para selecionar doentes de submetidos a cirurgia colo-rectal para co-gestão.Material e Métodos: A informação clínica foi colhida dos processos clínicos electrónicos de doentes que tiveram um código ICD-9 de cirurgia colo-rectal no período de janeiro 2012 a dezembro 2015, num hospital em Lisboa. A variável resposta consiste na sinalização para co-gestão. Um conjunto de dados de 344 doentes foi usado para o desenvolvimento do modelo predictivo e, um segundo conjunto de dados de 168 doentes foi usado para a validação externa do modelo.Resultados: Os autores construíram um modelo predictivo, de regressão logística, com cinco variáveis clínicas (idade, carga de co-morbilidades, ASA-PS status, risco cirúrgico e tempo de recobro) para predizer a selecção de doentes para co-gestão. O modelo tem uma área sob a curva (AUC) de 0,86 (95% IC: 0,81 - 0,90), um score predictivo de Brier de 0,11, uma sensibilidade de 0,80, uma especificidade de 0,82 e uma precisão de classificação de 81,3%.Discussão: A sinalização precoce dos doentes de alto risco ajuda a definir o melhor nível de cuidados ao doente operado. Desenvolvemos uma ferramenta de apoio à decisão, simples, aplicável à cabeceira do doente com uma boa capacidade discriminativa e preditiva para seleccionar os doentes para co-gestão.Conclusão: A selecção de doentes para co-gestão entre a cirurgia e a medicina interna permite o reconhecimento e a correcção precoce de complicações pós-operatórias reduzindo o ‘failure to rescue’. A ferramenta, uma vez customizada e validada, poderá ser aplicada em outros cenários clínicos.Ordem dos Médicos2021-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfimage/jpegimage/jpegimage/jpegapplication/pdfapplication/pdfapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/mswordapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentapplication/pdfhttps://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996oai:ojs.www.actamedicaportuguesa.com:article/12996Acta Médica Portuguesa; Vol. 34 No. 2 (2021): February; 118-127Acta Médica Portuguesa; Vol. 34 N.º 2 (2021): Fevereiro; 118-1271646-07580870-399Xreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAPenghttps://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/6188https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11943https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11944https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11945https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11981https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11982https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12204https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12215https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12470https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12603Direitos de Autor (c) 2020 Acta Médica Portuguesainfo:eu-repo/semantics/openAccessHorta, Alexandra BayãoGeraldes, CarlosSalgado, CátiaVieira, SusanaXavier, MiguelPapoila, Ana Luísa2022-12-20T11:06:45Zoai:ojs.www.actamedicaportuguesa.com:article/12996Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:20:15.752593Repositório 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 |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management Um Modelo de Predição para Seleccionar para Co-Gestão Doentes de Cirurgia Colo-rectal |
title |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management |
spellingShingle |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management Horta, Alexandra Bayão Colorectal Surgery/methods Cooperative Behavior Decision Support Systems Clinical Failure to Rescue Health Care Patient Selection Cirurgia Colorrectal Comportamento Cooperativo Falha da Terapia de Resgate Selecção de Doentes Sistemas de Apoio à Decisão Clínica |
title_short |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management |
title_full |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management |
title_fullStr |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management |
title_full_unstemmed |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management |
title_sort |
A Multivariable Prediction Model to Select Colorectal Surgical Patients for Co-Management |
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.author.fl_str_mv |
Horta, Alexandra Bayão Geraldes, Carlos Salgado, Cátia Vieira, Susana Xavier, Miguel Papoila, Ana Luísa |
dc.subject.por.fl_str_mv |
Colorectal Surgery/methods Cooperative Behavior Decision Support Systems Clinical Failure to Rescue Health Care Patient Selection Cirurgia Colorrectal Comportamento Cooperativo Falha da Terapia de Resgate Selecção de Doentes Sistemas de Apoio à Decisão Clínica |
topic |
Colorectal Surgery/methods Cooperative Behavior Decision Support Systems Clinical Failure to Rescue Health Care Patient Selection Cirurgia Colorrectal Comportamento Cooperativo Falha da Terapia de Resgate Selecção de Doentes Sistemas de Apoio à Decisão Clínica |
description |
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. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-02-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
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article |
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publishedVersion |
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https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996 oai:ojs.www.actamedicaportuguesa.com:article/12996 |
url |
https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996 |
identifier_str_mv |
oai:ojs.www.actamedicaportuguesa.com:article/12996 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/6188 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11943 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11944 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11945 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11981 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/11982 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12204 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12215 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12470 https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/12996/12603 |
dc.rights.driver.fl_str_mv |
Direitos de Autor (c) 2020 Acta Médica Portuguesa info:eu-repo/semantics/openAccess |
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Direitos de Autor (c) 2020 Acta Médica Portuguesa |
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openAccess |
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Ordem dos Médicos |
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Ordem dos Médicos |
dc.source.none.fl_str_mv |
Acta Médica Portuguesa; Vol. 34 No. 2 (2021): February; 118-127 Acta Médica Portuguesa; Vol. 34 N.º 2 (2021): Fevereiro; 118-127 1646-0758 0870-399X 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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