Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models

Abstract 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 Rese...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Concepción Violán, Sergio Fernández-Bertolín, Marina Guisado-Clavero, Quintí Foguet-Boreu, Jose M. Valderas, Josep Vidal Manzano, Albert Roso-Llorach, Margarita Cabrera-Bean
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/91c806cf229d4492b37f95a83ae880cb
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:91c806cf229d4492b37f95a83ae880cb
record_format	dspace
spelling	oai:doaj.org-article:91c806cf229d4492b37f95a83ae880cb2021-12-02T18:37:07ZFive-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models10.1038/s41598-020-73231-92045-2322https://doaj.org/article/91c806cf229d4492b37f95a83ae880cb2020-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-73231-9https://doaj.org/toc/2045-2322Abstract 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.Concepción ViolánSergio Fernández-BertolínMarina Guisado-ClaveroQuintí Foguet-BoreuJose M. ValderasJosep Vidal ManzanoAlbert Roso-LlorachMargarita Cabrera-BeanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 10, Iss 1, Pp 1-11 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Concepción Violán Sergio Fernández-Bertolín Marina Guisado-Clavero Quintí Foguet-Boreu Jose M. Valderas Josep Vidal Manzano Albert Roso-Llorach Margarita Cabrera-Bean Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models
description	Abstract 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.
format	article
author	Concepción Violán Sergio Fernández-Bertolín Marina Guisado-Clavero Quintí Foguet-Boreu Jose M. Valderas Josep Vidal Manzano Albert Roso-Llorach Margarita Cabrera-Bean
author_facet	Concepción Violán Sergio Fernández-Bertolín Marina Guisado-Clavero Quintí Foguet-Boreu Jose M. Valderas Josep Vidal Manzano Albert Roso-Llorach Margarita Cabrera-Bean
author_sort	Concepción Violán
title	Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models
title_short	Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models
title_full	Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models
title_fullStr	Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models
title_full_unstemmed	Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models
title_sort	five-year trajectories of multimorbidity patterns in an elderly mediterranean population using hidden markov models
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/91c806cf229d4492b37f95a83ae880cb
work_keys_str_mv	AT concepcionviolan fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels AT sergiofernandezbertolin fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels AT marinaguisadoclavero fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels AT quintifoguetboreu fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels AT josemvalderas fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels AT josepvidalmanzano fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels AT albertrosollorach fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels AT margaritacabrerabean fiveyeartrajectoriesofmultimorbiditypatternsinanelderlymediterraneanpopulationusinghiddenmarkovmodels
_version_	1718377811851345920

Five-year trajectories of multimorbidity patterns in an elderly Mediterranean population using Hidden Markov Models

Ejemplares similares