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dc.contributor.authorGrunde Wibetoe
dc.contributor.authorJoseph Sexton
dc.contributor.authorEirik Ikdahl
dc.contributor.authorSilvia Rollefstad
dc.contributor.authorGeorge D. Kitas
dc.contributor.authorPiet van Riel
dc.contributor.authorSherine Gabriel
dc.contributor.authorTore K. Kvien
dc.contributor.authorKaren Douglas
dc.contributor.authorAamer Sandoo
dc.contributor.authorElke E. Arts
dc.contributor.authorSolveig Wållberg-Jonsson
dc.contributor.authorSolbritt Rantapää Dahlqvist
dc.contributor.authorGeorge Karpouzas
dc.contributor.authorPatrick H. Dessein
dc.contributor.authorLinda Tsang
dc.contributor.authorHani El-Gabalawy
dc.contributor.authorCarol A. Hitchon
dc.contributor.authorVirginia Pascual-Ramos
dc.contributor.authorGonzález-Gay Mantecón, Miguel Ángel 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2021-04-16T08:58:34Z
dc.date.available2021-04-16T08:58:34Z
dc.date.issued2020
dc.identifier.issn1478-6354
dc.identifier.urihttp://hdl.handle.net/10902/21281
dc.description.abstractBackground: In younger individuals, low absolute risk of cardiovascular disease (CVD) may conceal an increased risk age and relative risk of CVD. Calculation of risk age is proposed as an adjuvant to absolute CVD risk estimation in European guidelines. We aimed to compare the discriminative ability of available risk age models in prediction of CVD in rheumatoid arthritis (RA). Secondly, we also evaluated the performance of risk age models in subgroups based on RA disease characteristics. Methods: RA patients aged 30?70 years were included from an international consortium named A Trans-Atlantic Cardiovascular Consortium for Rheumatoid Arthritis (ATACC-RA). Prior CVD and diabetes mellitus were exclusión criteria. The discriminatory ability of specific risk age models was evaluated using c-statistics and their standard errors after calculating time until fatal or non-fatal CVD or last follow-up. Results: A total of 1974 patients were included in the main analyses, and 144 events were observed during followup, the median follow-up being 5.0 years. The risk age models gave highly correlated results, demonstrating R2 values ranging from 0.87 to 0.97. However, risk age estimations differed > 5 years in 15?32% of patients. C-statistics ranged 0.68?0.72 with standard errors of approximately 0.03. Despite certain RA characteristics being associated with low c-indices, standard errors were high. Restricting analysis to European RA patients yielded similar results. Conclusions: The cardiovascular risk age and vascular age models have comparable performance in predicting CVD in RA patients. The influence of RA disease characteristics on the predictive ability of these prediction models remains inconclusive.es_ES
dc.format.extent10 p.es_ES
dc.language.isoenges_ES
dc.publisherBioMed Centrales_ES
dc.rightsAttribution 4.0 International. © The Author(s)es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceArthritis Research & Therapy (2020) (2020) 22:90es_ES
dc.subject.otherCardiovascular risk agees_ES
dc.subject.otherVascular agees_ES
dc.subject.otherCardiovascular diseasees_ES
dc.subject.otherRisk factorses_ES
dc.subject.otherRheumatoid arthritises_ES
dc.titlePrediction of cardiovascular events in rheumatoid arthritis using risk age calculations: evaluation of concordance across risk age modelses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1186/s13075-020-02178-zes_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1186/s13075-020-02178-z
dc.type.versionpublishedVersiones_ES


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Attribution 4.0 International. © The Author(s)Excepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International. © The Author(s)