New approaches for improving cardiovascular risk assessment
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/102548 https://doi.org/10.1016/j.repc.2015.10.006 |
Resumo: | Introduction and Objectives: Clinical guidelines recommend the use of cardiovascular risk assessment tools (risk scores) to predict the risk of events such as cardiovascular death, since these scores can aid clinical decision-making and thereby reduce the social and economic costs of cardiovascular disease (CVD). However, despite their importance, risk scores present important weaknesses that can diminish their reliability in clinical contexts. This study presents a new framework, based on current risk assessment tools, that aims to minimize these limitations. Methods: Appropriate application and combination of existing knowledge is the main focus of this work. Two different methodologies are applied: (i) a combination scheme that enables data to be extracted and processed from various sources of information, including current risk assessment tools and the contributions of the physician; and (ii) a personalization scheme based on the creation of patient groups with the purpose of identifying the most suitable risk assessment tool to assess the risk of a specific patient. Results: Validation was performed based on a real patient dataset of 460 patients at Santa Cruz Hospital, Lisbon, Portugal, diagnosed with non-ST-segment elevation acute coronary syndrome. Promising results were obtained with both approaches, which achieved sensitivity, specificity and geometric mean of 78.79%, 73.07% and 75.87%, and 75.69%, 69.79% and 72.71%, respectively. Conclusions: The proposed approaches present better performances than current CVD risk scores; however, additional datasets are required to back up these findings. |
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7160 |
spelling |
New approaches for improving cardiovascular risk assessmentNovas abordagens para a melhoria da avaliação do risco cardiovascularCardiovascular risk assessmentModel combinationPersonalizationClinical decision support systemsRisk scoresAvaliação de riscocardiovascularCombinaçãode modelosPersonalizaçãoSistemas de apoio à decisão clínicaClassificadores de riscoCardiovascular DiseasesHumansPortugalReproducibility of ResultsRisk FactorsRisk AssessmentIntroduction and Objectives: Clinical guidelines recommend the use of cardiovascular risk assessment tools (risk scores) to predict the risk of events such as cardiovascular death, since these scores can aid clinical decision-making and thereby reduce the social and economic costs of cardiovascular disease (CVD). However, despite their importance, risk scores present important weaknesses that can diminish their reliability in clinical contexts. This study presents a new framework, based on current risk assessment tools, that aims to minimize these limitations. Methods: Appropriate application and combination of existing knowledge is the main focus of this work. Two different methodologies are applied: (i) a combination scheme that enables data to be extracted and processed from various sources of information, including current risk assessment tools and the contributions of the physician; and (ii) a personalization scheme based on the creation of patient groups with the purpose of identifying the most suitable risk assessment tool to assess the risk of a specific patient. Results: Validation was performed based on a real patient dataset of 460 patients at Santa Cruz Hospital, Lisbon, Portugal, diagnosed with non-ST-segment elevation acute coronary syndrome. Promising results were obtained with both approaches, which achieved sensitivity, specificity and geometric mean of 78.79%, 73.07% and 75.87%, and 75.69%, 69.79% and 72.71%, respectively. Conclusions: The proposed approaches present better performances than current CVD risk scores; however, additional datasets are required to back up these findings.2016-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/102548http://hdl.handle.net/10316/102548https://doi.org/10.1016/j.repc.2015.10.006eng08702551Paredes, SimãoRocha, TeresaMendes, DianaCarvalho, PauloHenriques, JorgeMorais, JoãoFerreira, JorgeMendes, Miguelinfo: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:RCAAP2022-09-30T20:32:43Zoai:estudogeral.uc.pt:10316/102548Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:19:30.924472Repositório 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 |
New approaches for improving cardiovascular risk assessment Novas abordagens para a melhoria da avaliação do risco cardiovascular |
title |
New approaches for improving cardiovascular risk assessment |
spellingShingle |
New approaches for improving cardiovascular risk assessment Paredes, Simão Cardiovascular risk assessment Model combination Personalization Clinical decision support systems Risk scores Avaliação de riscocardiovascular Combinaçãode modelos Personalização Sistemas de apoio à decisão clínica Classificadores de risco Cardiovascular Diseases Humans Portugal Reproducibility of Results Risk Factors Risk Assessment |
title_short |
New approaches for improving cardiovascular risk assessment |
title_full |
New approaches for improving cardiovascular risk assessment |
title_fullStr |
New approaches for improving cardiovascular risk assessment |
title_full_unstemmed |
New approaches for improving cardiovascular risk assessment |
title_sort |
New approaches for improving cardiovascular risk assessment |
author |
Paredes, Simão |
author_facet |
Paredes, Simão Rocha, Teresa Mendes, Diana Carvalho, Paulo Henriques, Jorge Morais, João Ferreira, Jorge Mendes, Miguel |
author_role |
author |
author2 |
Rocha, Teresa Mendes, Diana Carvalho, Paulo Henriques, Jorge Morais, João Ferreira, Jorge Mendes, Miguel |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Paredes, Simão Rocha, Teresa Mendes, Diana Carvalho, Paulo Henriques, Jorge Morais, João Ferreira, Jorge Mendes, Miguel |
dc.subject.por.fl_str_mv |
Cardiovascular risk assessment Model combination Personalization Clinical decision support systems Risk scores Avaliação de riscocardiovascular Combinaçãode modelos Personalização Sistemas de apoio à decisão clínica Classificadores de risco Cardiovascular Diseases Humans Portugal Reproducibility of Results Risk Factors Risk Assessment |
topic |
Cardiovascular risk assessment Model combination Personalization Clinical decision support systems Risk scores Avaliação de riscocardiovascular Combinaçãode modelos Personalização Sistemas de apoio à decisão clínica Classificadores de risco Cardiovascular Diseases Humans Portugal Reproducibility of Results Risk Factors Risk Assessment |
description |
Introduction and Objectives: Clinical guidelines recommend the use of cardiovascular risk assessment tools (risk scores) to predict the risk of events such as cardiovascular death, since these scores can aid clinical decision-making and thereby reduce the social and economic costs of cardiovascular disease (CVD). However, despite their importance, risk scores present important weaknesses that can diminish their reliability in clinical contexts. This study presents a new framework, based on current risk assessment tools, that aims to minimize these limitations. Methods: Appropriate application and combination of existing knowledge is the main focus of this work. Two different methodologies are applied: (i) a combination scheme that enables data to be extracted and processed from various sources of information, including current risk assessment tools and the contributions of the physician; and (ii) a personalization scheme based on the creation of patient groups with the purpose of identifying the most suitable risk assessment tool to assess the risk of a specific patient. Results: Validation was performed based on a real patient dataset of 460 patients at Santa Cruz Hospital, Lisbon, Portugal, diagnosed with non-ST-segment elevation acute coronary syndrome. Promising results were obtained with both approaches, which achieved sensitivity, specificity and geometric mean of 78.79%, 73.07% and 75.87%, and 75.69%, 69.79% and 72.71%, respectively. Conclusions: The proposed approaches present better performances than current CVD risk scores; however, additional datasets are required to back up these findings. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01 |
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/10316/102548 http://hdl.handle.net/10316/102548 https://doi.org/10.1016/j.repc.2015.10.006 |
url |
http://hdl.handle.net/10316/102548 https://doi.org/10.1016/j.repc.2015.10.006 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
08702551 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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 |
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 |
repository.mail.fl_str_mv |
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1799134089325838336 |