Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models
Violán, Concepció (Universitat Autònoma de Barcelona)
Fernández-Bertolín, Sergio (Universitat Autònoma de Barcelona)
Guisado-Clavero, Marina (Universitat Autònoma de Barcelona)
Foguet-Boreu, Quintí (Hospital Universitari de Vic. Departament de Psiquiatria)
Valderas, Jose M. (University of Exeter Medical School)
Vidal Manzano, Josep (Universitat Politècnica de Catalunya)
Roso-Llorach, Albert (Universitat Autònoma de Barcelona)
Cabrera-Bean, Margarita (Universitat Politècnica de Catalunya)

Fecha:	2020
Resumen:	This study aimed to analyse the trajectories and mortality of multimorbidity patterns in patients aged 65 to 99 years in Catalonia (Spain). Five year (2012-2016) data of 916,619 participants from a primary care, population-based electronic health record database (Information System for Research in Primary Care, SIDIAP) were included in this retrospective cohort study. Individual longitudinal trajectories were modelled with a Hidden Markov Model across multimorbidity patterns. We computed the mortality hazard using Cox regression models to estimate survival in multimorbidity patterns. Ten multimorbidity patterns were originally identified and two more states (death and drop-outs) were subsequently added. At baseline, the most frequent cluster was the Non-Specific Pattern (42%), and the least frequent the Multisystem Pattern (1. 6%). Most participants stayed in the same cluster over the 5 year follow-up period, from 92. 1% in the Nervous, Musculoskeletal pattern to 59. 2% in the Cardio-Circulatory and Renal pattern. The highest mortality rates were observed for patterns that included cardio-circulatory diseases: Cardio-Circulatory and Renal (37. 1%); Nervous, Digestive and Circulatory (31. 8%); and Cardio-Circulatory, Mental, Respiratory and Genitourinary (28. 8%). This study demonstrates the feasibility of characterizing multimorbidity patterns along time. Multimorbidity trajectories were generally stable, although changes in specific multimorbidity patterns were observed. The Hidden Markov Model is useful for modelling transitions across multimorbidity patterns and mortality risk. Our findings suggest that health interventions targeting specific multimorbidity patterns may reduce mortality in patients with multimorbidity.
Ayudas:	Instituto de Salud Carlos III PI16/00639 Generalitat de Catalunya 2017SGR578
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Diseases ; Medical research
Publicado en:	Scientific reports, Vol. 10 (october 2020) , ISSN 2045-2322

DOI: 10.1038/s41598-020-73231-9
PMID: 33037233

11 p, 3.1 MB

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