GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome

Detalhes bibliográficos
Autor(a) principal: Neto, Afonso B.L.
Data de Publicação: 2023
Outros Autores: Sousa, José P., Gil, Paulo, Henriques, Jorge
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/105083
https://doi.org/10.1016/j.inffus.2022.10.019
Resumo: Cardiovascular Diseases (CVDs) are the world’s leading cause of morbidity and mortality, being responsible for almost 17 million deaths each year. In Europe, let alone it is estimated that 20% of all citizens suffer from one form of CVD, namely cerebrovascular disease or heart failure and Coronary Artery Disease (CAD). Among the latter, Acute Coronary Syndrome (ACS) is of particular importance since it is deadly and, hence, requires a prompt diagnosis and immediate medical attention. Aiming to deal with prognostication and promote consistency in managing patients with ACS, the Global Registry of Acute Coronary Events (GRACE) risk score has been proposed. This tool is based on eight independent risk factors roughly accounting for 89.9% of prognostic information. Nevertheless, as some other risk factors, not included in GRACE, are also known to be important vectors in the stratification of patients, namely haemoglobin at admission, it is expected that by embedding additional risk factors information into GRACE it will lead to a better characterisation of a patient’s risk. Making use of data-fusion techniques, the present work proposes a generalisable framework to improve the classification performance of GRACE in predicting the risk of death in the course of six months after an ACS event, while preserving its interpretability and applicability. Considering haemoglobin concentration at admission, as an additional risk factor, it is shown that the discrimination performance of new GRACE Plus score outperformed that of GRACE in a database of cohorts comprising 1506 patients admitted with ACS, showing a F-1 score of 0.6033 for GRACE Plus against 0.5828 for GRACE, which is corroborated by one-tailed t-test in terms of correct stratification of death and survival endpoints, namely, = −9.1876 and < 0.001.
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spelling GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary SyndromeAcute Coronary SyndromeGRACE risk scoreData fusionMachine learningCorrection factorCardiovascular Diseases (CVDs) are the world’s leading cause of morbidity and mortality, being responsible for almost 17 million deaths each year. In Europe, let alone it is estimated that 20% of all citizens suffer from one form of CVD, namely cerebrovascular disease or heart failure and Coronary Artery Disease (CAD). Among the latter, Acute Coronary Syndrome (ACS) is of particular importance since it is deadly and, hence, requires a prompt diagnosis and immediate medical attention. Aiming to deal with prognostication and promote consistency in managing patients with ACS, the Global Registry of Acute Coronary Events (GRACE) risk score has been proposed. This tool is based on eight independent risk factors roughly accounting for 89.9% of prognostic information. Nevertheless, as some other risk factors, not included in GRACE, are also known to be important vectors in the stratification of patients, namely haemoglobin at admission, it is expected that by embedding additional risk factors information into GRACE it will lead to a better characterisation of a patient’s risk. Making use of data-fusion techniques, the present work proposes a generalisable framework to improve the classification performance of GRACE in predicting the risk of death in the course of six months after an ACS event, while preserving its interpretability and applicability. Considering haemoglobin concentration at admission, as an additional risk factor, it is shown that the discrimination performance of new GRACE Plus score outperformed that of GRACE in a database of cohorts comprising 1506 patients admitted with ACS, showing a F-1 score of 0.6033 for GRACE Plus against 0.5828 for GRACE, which is corroborated by one-tailed t-test in terms of correct stratification of death and survival endpoints, namely, = −9.1876 and < 0.001.This work has been partially supported by Fundação para a Ciência e Tecnologia (FCT), Portugal, I.P./MCTES through national funds (PIDDAC), within the scope of CISUC R&D Unit - UIDB/00326/2020, CTS - Centro de Tecnologia e Sistemas - UIDB/00066/2020, and grant SFRH/BSAB/150268/2019.Elsevier20232024-06-29T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/105083http://hdl.handle.net/10316/105083https://doi.org/10.1016/j.inffus.2022.10.019eng15662535https://doi.org/10.1016/j.inffus.2022.10.019Neto, Afonso B.L.Sousa, José P.Gil, PauloHenriques, Jorgeinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-10-27T11:12:02Zoai:estudogeral.uc.pt:10316/105083Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:21:40.110255Repositório 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 GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
title GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
spellingShingle GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
Neto, Afonso B.L.
Acute Coronary Syndrome
GRACE risk score
Data fusion
Machine learning
Correction factor
title_short GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
title_full GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
title_fullStr GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
title_full_unstemmed GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
title_sort GRACE PLUS: A data fusion-based approach to improve GRACE score in the risk assessment of Acute Coronary Syndrome
author Neto, Afonso B.L.
author_facet Neto, Afonso B.L.
Sousa, José P.
Gil, Paulo
Henriques, Jorge
author_role author
author2 Sousa, José P.
Gil, Paulo
Henriques, Jorge
author2_role author
author
author
dc.contributor.author.fl_str_mv Neto, Afonso B.L.
Sousa, José P.
Gil, Paulo
Henriques, Jorge
dc.subject.por.fl_str_mv Acute Coronary Syndrome
GRACE risk score
Data fusion
Machine learning
Correction factor
topic Acute Coronary Syndrome
GRACE risk score
Data fusion
Machine learning
Correction factor
description Cardiovascular Diseases (CVDs) are the world’s leading cause of morbidity and mortality, being responsible for almost 17 million deaths each year. In Europe, let alone it is estimated that 20% of all citizens suffer from one form of CVD, namely cerebrovascular disease or heart failure and Coronary Artery Disease (CAD). Among the latter, Acute Coronary Syndrome (ACS) is of particular importance since it is deadly and, hence, requires a prompt diagnosis and immediate medical attention. Aiming to deal with prognostication and promote consistency in managing patients with ACS, the Global Registry of Acute Coronary Events (GRACE) risk score has been proposed. This tool is based on eight independent risk factors roughly accounting for 89.9% of prognostic information. Nevertheless, as some other risk factors, not included in GRACE, are also known to be important vectors in the stratification of patients, namely haemoglobin at admission, it is expected that by embedding additional risk factors information into GRACE it will lead to a better characterisation of a patient’s risk. Making use of data-fusion techniques, the present work proposes a generalisable framework to improve the classification performance of GRACE in predicting the risk of death in the course of six months after an ACS event, while preserving its interpretability and applicability. Considering haemoglobin concentration at admission, as an additional risk factor, it is shown that the discrimination performance of new GRACE Plus score outperformed that of GRACE in a database of cohorts comprising 1506 patients admitted with ACS, showing a F-1 score of 0.6033 for GRACE Plus against 0.5828 for GRACE, which is corroborated by one-tailed t-test in terms of correct stratification of death and survival endpoints, namely, = −9.1876 and < 0.001.
publishDate 2023
dc.date.none.fl_str_mv 2023
2024-06-29T00:00:00Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/105083
http://hdl.handle.net/10316/105083
https://doi.org/10.1016/j.inffus.2022.10.019
url http://hdl.handle.net/10316/105083
https://doi.org/10.1016/j.inffus.2022.10.019
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language eng
dc.relation.none.fl_str_mv 15662535
https://doi.org/10.1016/j.inffus.2022.10.019
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dc.publisher.none.fl_str_mv Elsevier
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