Polypharmacy Patterns in Multimorbid Older People with Cardiovascular Disease: Longitudinal Study

Author:

Villén Noemí,Roso-Llorach Albert,Gallego-Moll CarlosORCID,Danes-Castells MarcORCID,Fernández-Bertolin Sergio,Troncoso-Mariño Amelia,Monteagudo Monica,Amado Ester,Violán ConcepciónORCID

Abstract

(1) Introduction: Cardiovascular disease is associated with high mortality, especially in older people. This study aimed to characterize the evolution of combined multimorbidity and polypharmacy patterns in older people with different cardiovascular disease profiles. (2) Material and methods: This longitudinal study drew data from the Information System for Research in Primary Care in people aged 65 to 99 years with profiles of cardiovascular multimorbidity. Combined patterns of multimorbidity and polypharmacy were analysed using fuzzy c-means clustering techniques and hidden Markov models. The prevalence, observed/expected ratio, and exclusivity of chronic diseases and/or groups of these with the corresponding medication were described. (3) Results: The study included 114,516 people, mostly men (59.6%) with a mean age of 78.8 years and a high prevalence of polypharmacy (83.5%). The following patterns were identified: Mental, behavioural, digestive and cerebrovascular; Neuropathy, autoimmune and musculoskeletal; Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological; Non-specific; Multisystemic; Respiratory, cardiovascular, behavioural and genitourinary; Diabetes and ischemic cardiopathy; and Cardiac. The prevalence of overrepresented health problems and drugs remained stable over the years, although by study end, cohort survivors had more polypharmacy and multimorbidity. Most people followed the same pattern over time; the most frequent transitions were from Non-specific to Mental, behavioural, digestive and cerebrovascular and from Musculoskeletal, mental, behavioural, genitourinary, digestive and dermatological to Non-specific. (4) Conclusions: Eight combined multimorbidity and polypharmacy patterns, differentiated by sex, remained stable over follow-up. Understanding the behaviour of different diseases and drugs can help design individualised interventions in populations with clinical complexity.

Publisher

MDPI AG

Subject

Geriatrics and Gerontology,Gerontology,Aging,Health (social science)

Reference59 articles.

1. World Health Organization (2022, September 15). Ageing and Health. Available online: https://www.who.int/news-room/fact-sheets/detail/ageing-and-health.

2. Khan, T. WHO Health Topics: Cardiovascular Diseases, World Health Organization. Available online: https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1.

3. World Health Organization (2022). The Global Health Observatory: Global Health Estimates: Leading Causes of Death, World Health Organization.

4. Sex differences in coronary heart disease and stroke mortality: A global assessment of the effect of ageing between 1980 and 2010;Bots;BMJ Glob. Health,2017

5. 2021 ESC guidelines on cardiovascular disease prevention in clinical practice;Visseren;Eur. Heart J.,2021

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