Temporal patterns of multiple long-term conditions in individuals with intellectual disability living in Wales: an unsupervised clustering approach to disease trajectories
This study reveals complex multimorbidity patterns in individuals with ID, highlighting age and sex differences. The identified clusters provide new insights into disease progression and co-occurrence in this population. These findings can inform the development of targeted interventions and risk stratification strategies, potentially improving personalised healthcare for individuals with ID and MLTCs with the aim of improving health outcome for this vulnerable group of patients i.e. reducing frequency and length of hospital admissions and premature mortality.
Authors
- Gyuchan Thomas Jun (ORCID: https://orcid.org/0000-0002-0958-0107)
- Emeka Abakasanga (ORCID: https://orcid.org/0000-0002-4742-3102)
- Georgina Cosma (ORCID: https://orcid.org/0000-0002-4663-6907)
- Ashley Akbari (ORCID: https://orcid.org/0000-0003-0814-0801)
- Reza Kiani (ORCID: https://orcid.org/0000-0002-2765-7155)
- Satheesh Gangadharan (ORCID: https://orcid.org/0000-0001-7034-4173)
- Francesco Zaccardi (ORCID: https://orcid.org/0000-0002-2636-6487)
- Rania Kousovista
Institutions
- Loughborough University (GB)
- University of Leicester (GB)
- Swansea University (GB)
- Leicestershire Partnership NHS Trust (GB)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2025-03-27
- DOI
- https://doi.org/10.3389/fdgth.2025.1528882
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 0.00