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Authordc.contributor.authorBarroilhet Diez, Sergio 
Authordc.contributor.authorBieling, Alexandra E. 
Authordc.contributor.authorMcCoy, Thomas H. 
Authordc.contributor.authorPerlis, Roy H. 
Admission datedc.date.accessioned2020-06-02T19:19:58Z
Available datedc.date.available2020-06-02T19:19:58Z
Publication datedc.date.issued2020
Cita de ítemdc.identifier.citationGeneral Hospital Psychiatry 64 (2020) 63–67es_ES
Identifierdc.identifier.other10.1016/j.genhosppsych.2020.01.003
Identifierdc.identifier.urihttps://repositorio.uchile.cl/handle/2250/175140
Abstractdc.description.abstractBackground: Personality has long been studied as a factor associated with health outcomes. Investigations of large, generalizable clinical cohorts are limited by variations in personality diagnostic methodologies and difficulties with long-term follow-up. Methods: Electronic health records of a cohort of patients admitted to a general hospital were characterized using a previously developed natural language processing tool for extracting DSM-5 and ICD-11 personality domains. We used Cox regression and Fine-Gray competing risk survival to analyze the relationships between these personality estimates, sociodemographic features, and risk of readmission and mortality. Results: Among 12,274 patients, 2379 deaths occurred in the course of 61,761 patient-years at risk, with 19,985 admissions during follow-up. Detachment was the most common personality feature. Presence of disinhibition was independently associated with a higher mortality risk, while anankastic traits were associated with a lower mortality risk. Increased likelihood of readmission was predicted by detachment, while decreased likelihood of readmission was associated with disinhibition and psychoticism traits. Conclusions: Personality features can be identified from electronic health records and are associated with readmission and mortality risk. Developing treatment strategies that target patients with higher personality symptom burden in specific dimensions could enable more efficient and focused interventions.es_ES
Patrocinadordc.description.sponsorshipUnited States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Mental Health (NIMH) 1R01MH106577es_ES
Lenguagedc.language.isoenes_ES
Publisherdc.publisherElsevieres_ES
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 Chile*
Link to Licensedc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/cl/*
Sourcedc.sourceGeneral Hospital Psychiatryes_ES
Keywordsdc.subjectPersonality disorderes_ES
Keywordsdc.subjectPersonality domainses_ES
Keywordsdc.subjectNatural language processinges_ES
Keywordsdc.subjectMachine learninges_ES
Keywordsdc.subjectElectronic health recordes_ES
Keywordsdc.subjectMortalityes_ES
Keywordsdc.subjectReadmissiones_ES
Títulodc.titleAssociation between DSM-5 and ICD-11 personality dimensional traits in a general medical cohort and readmission and mortalityes_ES
Document typedc.typeArtículo de revistaes_ES
dcterms.accessRightsdcterms.accessRightsAcceso Abierto
Catalogueruchile.catalogadorctces_ES
Indexationuchile.indexArtículo de publicación ISI
Indexationuchile.indexArtículo de publicación SCOPUS


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Attribution-NonCommercial-NoDerivs 3.0 Chile
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Chile