dc.rights.license | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.contributor.author | Soto-Gordoa, Myriam | |
dc.contributor.other | Arrospide Elgarresta, Mikel | |
dc.contributor.other | Gerovska, Daniela | |
dc.contributor.other | Jauregui García, María L. | |
dc.contributor.other | Merino Hernández, Marisa L. | |
dc.contributor.other | Araúzo Bravo, Marcos J. | |
dc.date.accessioned | 2024-10-16T13:44:59Z | |
dc.date.available | 2024-10-16T13:44:59Z | |
dc.date.issued | 2024 | |
dc.identifier.issn | 2589-0042 | en |
dc.identifier.other | https://katalogoa.mondragon.edu/janium-bin/janium_login_opac.pl?find&ficha_no=178127 | en |
dc.identifier.uri | https://hdl.handle.net/20.500.11984/6664 | |
dc.description.abstract | Multimorbidity (MM) is the co-occurrence of two or more chronic diseases. We provided a dynamic approach revealing the MM complexity constructing a multistep incidence-age model for all patients with MM between 2014 and 2021 in the Basque Health System, Spain. The multistep model, with eight steps for males and nine for females, is a very well-fitting representation of MM. To gain insight into the MM components, we modeled the 19 diseases used to calculate the Charlson Comorbidity Index (CCI). We observed that the CCI diseases formed a complex interaction network. Hierarchical clustering of the incidence-age profiles clustered the CCI diseases into low- and high-risk of dying pathologies. Diseases with a higher number of steps are better represented by a multistep model. Anatomically, diseases associated with the central nervous system have the highest number of steps, followed by those associated with the kidney, heart, peripheral vasulature, pancreas, joints, cerebral vasculature, lung, stomach, and liver. | en |
dc.language.iso | eng | en |
dc.publisher | Elsevier | en |
dc.rights | © 2024 The Authors | en |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Pathophysiology | en |
dc.subject | bioinformatics | en |
dc.title | Chronic disease incidence explained by stepwise models and co-occurrence among them | en |
dcterms.accessRights | http://purl.org/coar/access_right/c_abf2 | en |
dcterms.source | iScience | en |
local.contributor.group | Dirección de operaciones logístico productivas | es |
local.description.peerreviewed | true | en |
local.identifier.doi | https://doi.org/10.1016/j.isci.2024.110816 | en |
local.source.details | Vol. 27. N. 9. N. art. 110816, 2024 | |
oaire.format.mimetype | application/pdf | en |
oaire.file | $DSPACE\assetstore | en |
oaire.resourceType | http://purl.org/coar/resource_type/c_6501 | en |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | en |
dc.unesco.tesauro | http://vocabularies.unesco.org/thesaurus/concept251 | en |
dc.unesco.tesauro | http://vocabularies.unesco.org/thesaurus/concept10264 | en |
oaire.funderName | Comisión Europea | en |
oaire.funderIdentifier | https://ror.org/00k4n6c32 / http://data.crossref.org/fundingdata/funder/10.13039/501100000780 | en |
oaire.fundingStream | Horizon 2020 | en |
oaire.awardNumber | 899417 | en |
oaire.awardTitle | Circular DNA in diagnosis and disease models (CIRCULAR VISION) | en |
oaire.awardURI | https://doi.org/10.3030/899417 | en |
dc.unesco.clasificacion | http://skos.um.es/unesco6/3202 | en |
dc.unesco.clasificacion | http://skos.um.es/unesco6/3212 | en |