Multimorbidity patterns with K-means nonhierarchical cluster analysis
Violán, Concepció (Universitat Autònoma de Barcelona)
Roso-Llorach, Albert (Universitat Autònoma de Barcelona)
Foguet-Boreu, Quintí (Universitat Autònoma de Barcelona)
Guisado-Clavero, Marina (Universitat Autònoma de Barcelona)
Pons-Vigués, Mariona (Universitat Autònoma de Barcelona)
Pujol Ribera, Enriqueta (Universitat Autònoma de Barcelona)
Valderas, Jose M. (University of Exeter Medical School)

Fecha:	2018
Resumen:	The purpose of this study was to ascertain multimorbidity patterns using a non-hierarchical cluster analysis in adult primary patients with multimorbidity attended in primary care centers in Catalonia. Cross-sectional study using electronic health records from 523,656 patients, aged 45-64 years in 274 primary health care teams in 2010 in Catalonia, Spain. Data were provided by the Information System for the Development of Research in Primary Care (SIDIAP), a population database. Diagnoses were extracted using 241 blocks of diseases (International Classification of Diseases, version 10). Multimorbidity patterns were identified using two steps: 1) multiple correspondence analysis and 2) k-means clustering. Analysis was stratified by sex. The 408,994 patients who met multimorbidity criteria were included in the analysis (mean age, 54. 2 years [Standard deviation, SD: 5. 8], 53. 3% women). Six multimorbidity patterns were obtained for each sex; the three most prevalent included 68% of the women and 66% of the men, respectively. The top cluster included coincident diseases in both men and women: Metabolic disorders, Hypertensive diseases, Mental and behavioural disorders due to psychoactive substance use, Other dorsopathies, and Other soft tissue disorders. Non-hierarchical cluster analysis identified multimorbidity patterns consistent with clinical practice, identifying phenotypic subgroups of patients. The online version of this article (10. 1186/s12875-018-0790-x) contains supplementary material, which is available to authorized users.
Ayudas:	Ministerio de Economía y Competitividad PI12/00427 Ministerio de Economía y Competitividad RD12/0005
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:	Multimorbidity ; Cluster analysis ; Multiple correspondence analysis ; K-means clustering ; Primary health care ; Electronic health records ; Diseases
Publicado en:	BMC family practice, Vol. 19 (july 2018) , ISSN 1471-2296

DOI: 10.1186/s12875-018-0790-x
PMID: 29969997

11 p, 1.3 MB

El registro aparece en las colecciones:
Documentos de investigación > Documentos de los grupos de investigación de la UAB > Centros y grupos de investigación (producción científica) > Ciencias de la salud y biociencias > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
Artículos > Artículos de investigación
Artículos > Artículos publicados