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01.12.2018 | Research article | Ausgabe 1/2018 Open Access

BMC Geriatrics 1/2018

Multimorbidity patterns in the elderly: a prospective cohort study with cluster analysis

Zeitschrift:
BMC Geriatrics > Ausgabe 1/2018
Autoren:
Marina Guisado-Clavero, Albert Roso-Llorach, Tomàs López-Jimenez, Mariona Pons-Vigués, Quintí Foguet-Boreu, Miguel Angel Muñoz, Concepción Violán
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s12877-018-0705-7) contains supplementary material, which is available to authorized users.

Abstract

Background

Multimorbidity is the coexistence of more than two chronic diseases in the same individual; however, there is no consensus about the best definition. In addition, few studies have described the variability of multimorbidity patterns over time. The aim of this study was to identify multimorbidity patterns and their variability over a 6-year period in patients older than 65 years attended in primary health care.

Methods

A cohort study with yearly cross-sectional analysis of electronic health records from 50 primary health care centres in Barcelona. Selected patients had multimorbidity and were 65 years of age or older in 2009. Diagnoses (International Classification of Primary Care, second edition) were extracted using O’Halloran criteria for chronic diseases. Multimorbidity patterns were identified using two steps: 1) multiple correspondence analysis and 2) k-means clustering. Analysis was stratified by sex and age group (65–79 and ≥80 years) at the beginning of the study period.

Results

Analysis of 2009 electronic health records from 190,108 patients with multimorbidity (59.8% women) found a mean age of 71.8 for the 65–79 age group and 84.16 years for those over 80 (Standard Deviation [SD] 4.35 and 3.46, respectively); the median number of chronic diseases was seven (Interquartil range [IQR] 5–10). We obtained 6 clusters of multimorbidity patterns (1 nonspecific and 5 specifics) in each group, being the specific ones: Musculoskeletal, Endocrine-metabolic, Digestive/Digestive-respiratory, Neurological, and Cardiovascular patterns. A minimum of 42.5% of the sample remained in the same pattern at the end of the study, reflecting the stability of these patterns.

Conclusions

This study identified six multimorbidity patterns per each group, one nonnspecific pattern and five of them with a specific pattern related to an organic system. The multimorbidity patterns obtained had similar characteristics throughout the study period. These data are useful to improve clinical management of each specific subgroup of patients showing a particular multimorbidity pattern.
Zusatzmaterial
Additional file 1: Multimorbidity patterns in women 65–79 years across the period analysed. Patterns defined by prevalence >20% and ratio O/E > 2. (XLSX 26 kb)
12877_2018_705_MOESM1_ESM.xlsx
Additional file 2: Multimorbidity patterns in men 65–79 years across the period analysed. Patterns defined by prevalence >20% and ratio O/E > 2. (XLSX 32 kb)
12877_2018_705_MOESM2_ESM.xlsx
Additional file 3: Multimorbidity patterns in women aged >80 years across the period analysed. Patterns defined by prevalence >20% and ratio O/E > 2. (XLSX 29 kb)
12877_2018_705_MOESM3_ESM.xlsx
Additional file 4: Multimorbidity patterns in men >80 years across the period analysed. Patterns defined by prevalence >20% and ratio O/E > 2. (XLSX 37 kb)
12877_2018_705_MOESM4_ESM.xlsx
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