Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects

Detalhes bibliográficos
Autor(a) principal: Albuquerque, João
Data de Publicação: 2022
Outros Autores: Medeiros, Ana Margarida, Alves, Ana Catarina, Bourbon, Mafalda, Antunes, Marília
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.18/8288
Resumo: Observational Study
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spelling Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjectsFamilial HypercholesterolemiaCholesterolDoenças Cardio e Cérebro-vascularesColesterolHipercolesterolemia FamiliarObservational StudyFamilial Hypercholesterolemia (FH) is an inherited disorder of lipid metabolism, characterized by increased low density lipoprotein cholesterol (LDLc) levels. The main purpose of the current work was to explore alternative classification methods to traditional clinical criteria for FH diagnosis, based on several biochemical and biological indicators. Logistic regression (LR), decision tree (DT), random forest (RF) and naive Bayes (NB) algorithms were developed for this purpose, and thresholds were optimized by maximization of Youden index (YI). All models presented similar accuracy (Acc), specificity (Spec) and positive predictive values (PPV). Sensitivity (Sens) and G-mean values were significantly higher in LR and RF models, compared to the DT. When compared to Simon Broome (SB) biochemical criteria for FH diagnosis, all models presented significantly higher Acc, Spec and G-mean values (p < 0.01), and lower negative predictive value (NPV, p < 0.05). Moreover, LR and RF models presented comparable Sens values. Adjustment of the cut-off point by maximizing YI significantly increased Sens values, with no significant loss in Acc. The obtained results suggest such classification algorithms can be a viable alternative to be used as a widespread screening method. An online application has been developed to assess the performance of the LR model in a wider population.NORTE-08-5369-FSE-000018/Horizon 2020 Framework Programme UID/MAT/00006/2019/Fundação para a Ciência e a Tecnologia PTDC/SAU-SER/29180/2017/Fundação para a Ciência e a TecnologiaNature ResearchRepositório Científico do Instituto Nacional de SaúdeAlbuquerque, JoãoMedeiros, Ana MargaridaAlves, Ana CatarinaBourbon, MafaldaAntunes, Marília2022-10-31T14:47:46Z2022-01-212022-01-21T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.18/8288engSci Rep. 2022 Jan 21;12(1):1164. doi: 10.1038/s41598-022-05063-82045-232210.1038/s41598-022-05063-8info: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:RCAAP2023-07-20T15:42:27Zoai:repositorio.insa.pt:10400.18/8288Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:42:53.314735Repositório 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 Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
title Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
spellingShingle Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
Albuquerque, João
Familial Hypercholesterolemia
Cholesterol
Doenças Cardio e Cérebro-vasculares
Colesterol
Hipercolesterolemia Familiar
title_short Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
title_full Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
title_fullStr Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
title_full_unstemmed Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
title_sort Performance comparison of different classification algorithms applied to the diagnosis of familial hypercholesterolemia in paediatric subjects
author Albuquerque, João
author_facet Albuquerque, João
Medeiros, Ana Margarida
Alves, Ana Catarina
Bourbon, Mafalda
Antunes, Marília
author_role author
author2 Medeiros, Ana Margarida
Alves, Ana Catarina
Bourbon, Mafalda
Antunes, Marília
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Nacional de Saúde
dc.contributor.author.fl_str_mv Albuquerque, João
Medeiros, Ana Margarida
Alves, Ana Catarina
Bourbon, Mafalda
Antunes, Marília
dc.subject.por.fl_str_mv Familial Hypercholesterolemia
Cholesterol
Doenças Cardio e Cérebro-vasculares
Colesterol
Hipercolesterolemia Familiar
topic Familial Hypercholesterolemia
Cholesterol
Doenças Cardio e Cérebro-vasculares
Colesterol
Hipercolesterolemia Familiar
description Observational Study
publishDate 2022
dc.date.none.fl_str_mv 2022-10-31T14:47:46Z
2022-01-21
2022-01-21T00:00:00Z
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/10400.18/8288
url http://hdl.handle.net/10400.18/8288
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Sci Rep. 2022 Jan 21;12(1):1164. doi: 10.1038/s41598-022-05063-8
2045-2322
10.1038/s41598-022-05063-8
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.publisher.none.fl_str_mv Nature Research
publisher.none.fl_str_mv Nature Research
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
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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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