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dc.contributor.authorMelero-Alegria, Jose Ignacio
dc.contributor.authorCascón Barbero, José Manuel 
dc.contributor.authorRomero, Alfonso
dc.contributor.authorVara, Pedro Pablo
dc.contributor.authorBarreiro-Pérez, Manuel
dc.contributor.authorVicente-Palacios, Víctor
dc.contributor.authorPerez-Escanilla, Fernando
dc.contributor.authorHernandez-Hernandez, Jesus
dc.contributor.authorGarde, Beatriz
dc.contributor.authorCascon, Sara
dc.contributor.authorMartín García, Ana 
dc.contributor.authorDiaz-Pelaez, Elena
dc.contributor.authorde Dios, Jose Maria
dc.contributor.authorUribarri González, Aitor
dc.contributor.authorJiménez Candil, Francisco Javier 
dc.contributor.authorCruz González, Ignacio 
dc.contributor.authorBlazquez, Baltasara
dc.contributor.authorHernandez, Jose Manuel
dc.contributor.authorSanchez-Pablo, Clara
dc.contributor.authorSantolino, Inmaculada
dc.contributor.authorLedesma, Maria Concepcion
dc.contributor.authorMuriel, Paz
dc.contributor.authorDorado Díaz, Pedro Ignacio 
dc.contributor.authorSánchez Fernández, Pedro Luis 
dc.date.accessioned2021-05-20T11:42:18Z
dc.date.available2021-05-20T11:42:18Z
dc.date.issued2019
dc.identifier.citationMelero-Alegria JI, Cascon M, Romero A, et al. (2019).SALMANTICOR study. Rationale and design of a populationbased study to identify structural heart disease abnormalities: a spatial and machine learning analysis. BMJ Open ;9:e024605. doi:10.1136/ bmjopen-2018-024605es_ES
dc.identifier.issn2044-6055
dc.identifier.urihttp://hdl.handle.net/10366/146076
dc.description.abstract[EN]Introduction: This study aims to obtain data on the prevalence and incidence of structural heart disease in a population setting and, to analyse and present those data on the application of spatial and machine learning methods that, although known to geography and statistics, need to become used for healthcare research and for political commitment to obtain resources and support effective public health programme implementation. Methods and analysis: We will perform a cross-sectional survey of randomly selected residents of Salamanca (Spain). 2400 individuals stratified by age and sex and by place of residence (rural and urban) will be studied. The variables to analyse will be obtained from the clinical history, different surveys including social status, Mediterranean diet, functional capacity, ECG, echocardiogram, VASERA and biochemical as well as genetic analysis. Ethics and dissemination: The study has been approved by the ethical committee of the healthcare community. All study participants will sign an informed consent for participation in the study. The results of this study will allow the understanding of the relationship between the different influencing factors and their relative importance weights in the development of structural heart disease.es_ES
dc.language.isoenges_ES
dc.publisherBMJ Openes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMachine learninges_ES
dc.subjectUrbanes_ES
dc.subjectStructural heart diseases_ES
dc.subjectSpatial analysises_ES
dc.subjectRurales_ES
dc.subjectPopulationes_ES
dc.subjectInstituto de Investigación Biomédica de Salamanca (IBSAL)es_ES
dc.subject.meshHeart Diseases*
dc.titleSALMANTICOR study. Rationale and design of a population-based study to identify structural heart disease abnormalities: a spatial and machine learning analysises_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversion10.1136/bmjopen-2018-024605
dc.subject.unesco3205.01 Cardiologíaes_ES
dc.identifier.doi10.1136/bmjopen-2018-024605
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.essn2044-6055
dc.journal.titleBMJ Openes_ES
dc.volume.number9es_ES
dc.issue.number2es_ES
dc.page.initiale024605es_ES
dc.type.hasVersioninfo:eu-repo/semantics/draftes_ES
dc.subject.decsenfermedades cardíacas*


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