Multimorbidity-the co-occurrence of multiple diseases-is associated to poor prognosis, but the scarce knowledge of its development over time hampers the effectiveness of clinical interventions. Here we identify multimorbidity clusters, trace their evolution in older adults, and detect the clinical trajectories and mortality of single individuals as they move among clusters over 12 years. By means of a fuzzy c-means cluster algorithm, we group 2931 people ≥60 years in five clinically meaningful multimorbidity clusters (52%). The remaining 48% are part of an unspecific cluster (i.e. none of the diseases are overrepresented), which greatly fuels other clusters at follow-ups. Clusters contribute differentially to the longitudinal development of other clusters and to mortality. We report that multimorbidity clusters and their trajectories may help identifying homogeneous groups of people with similar needs and prognosis, and assisting clinicians and health care systems in the personalization of clinical interventions and preventive strategies.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320143 | PMC |
| http://dx.doi.org/10.1038/s41467-020-16780-x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Prognostic signature of multimorbidity, geriatric syndromes and resources cluster in older in- and outpatients: a pooled secondary analysis with a 6-month follow-up.
BMJ Open
December 2024
Department II of Internal Medicine and Center for Molecular Medicine Cologne, University of Cologne, Faculty of Medicine and University Hospital Cologne, University Hospital Cologne, Cologne, Nordrhein-Westfalen, Germany
Objective: The prognosis of older adults is strongly influenced by the relation of multifactorial geriatric syndromes (GS) and their health-maintaining counterparts, geriatric resources (GR). The present analysis aimed to identify clusters of comorbidities, GS and GR, and to measure their multidimensional prognostic signature in older patients admitted to different healthcare settings.
Design: Pooled secondary analysis of three longitudinal interventional studies with the 3- and 6-month follow-up data collection on mortality and rehospitalisation.
Research Status and Direction of Chronic Obstructive Pulmonary Disease Complicated with Coronary Heart Disease: A Bibliometric Analysis from 2005 to 2024.
Int J Chron Obstruct Pulmon Dis
January 2025
Department of Radiology, The First Affiliated Hospital of Huzhou University, Huzhou, Zhejiang, People's Republic of China.
Objective: There is increasing evidence that chronic obstructive pulmonary disease (COPD) is associated with coronary heart disease (CHD). In this study, we provide valuable insights in the field by examining the evolution of the relationship between COPD and CHD over the past 20 years.
Methods: A comprehensive computer search was conducted in the Web of Science (WOS) core dataset, covering literature on COPD combined with CHD from January 1, 2005, to August 20, 2024.
Cohort profile: creation of the SAIL MELD-B e-cohort (SMC) and SAIL MELD-B children and young adult e-cohort (SMYC) to investigate the lived experience of the 'burdensomeness' of multimorbidity.
BMJ Open
January 2025
Population Data Science, Faculty of Medicine, Swansea University Medical School, Swansea, UK.
Purpose: We have established the SAIL MELD-B electronic cohort (e-cohort SMC) and the SAIL MELD-B children and Young adults e-cohort (SMYC) as a part of the Multidisciplinary Ecosystem to study Lifecourse Determinants and Prevention of Early-onset Burdensome Multimorbidity (MELD-B) project. Each cohort has been created to investigate and develop a deeper understanding of the lived experience of the 'burdensomeness' of multimorbidity by identifying new clusters of burdensomeness concepts, exploring early life risk factors of multimorbidity and modelling hypothetical prevention scenarios.
Participants: The SMC and SMYC are longitudinal e-cohorts created from routinely collected individual-level population-scale anonymised data sources available within the Secure Anonymised Information Linkage (SAIL) Databank.
Multimorbidity clusters and their associations with health-related quality of life in two UK cohorts.
BMC Med
January 2025
General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, Glasgow, UK.
Background: Identifying clusters of multiple long-term conditions (MLTCs), also known as multimorbidity, and their associated burden may facilitate the development of effective and cost-effective targeted healthcare strategies. This study aimed to identify clusters of MLTCs and their associations with long-term health-related quality of life (HRQoL) in two UK population-based cohorts.
Methods: Age-stratified clusters of MLTCs were identified at baseline in UK Biobank (n = 502,363, 54.
Multimorbidity latent classes in relation to 11-year mortality, risk factors and health-related quality of life in Malaysia: a prospective health and demographic surveillance system study.
BMC Med
January 2025
Global Public Health, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Subang Jaya, Sunway City, Selangor, Malaysia.
Background: We aimed to identify specific multimorbidity latent classes among multi-ethnic community-dwelling adults aged ≥ 18 years in Malaysia. We further explored the risk factors associated with these patterns and examined the relationships between the multimorbidity patterns and 11-year all-cause mortality risk, as well as health-related quality of life (HRQoL).
Methods: Using data from 18,101 individuals (aged 18-97 years) from the baseline Census 2012, Health Round 2013, and Verbal Autopsies 2012-2023 of the South East Asia Community Observatory (SEACO) health and demographic surveillance system, latent class analysis was performed on 13 chronic health conditions to identify statistically and clinically meaningful groups.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!