What this means
Researchers plan to follow people over time and group them by health signs linked to frailty. This is a plan, and it does not yet show what will be found.
Plain-English summary written by an AI model from the registry listing.
- Status
- Recruiting
- Who can join
- Ages 65–120
- Where
- 1 site
The science
- Registered title
- The CohorFES: a Prospective Study of Frailty and Dependence
- Trial ID
- NCT06965972 ↗
- Phase
- Not applicable
- Study type
- observational
- Conditions
- Frailty Syndrome
- Sponsor
- Parc de Salut Mar
- Ages
- 65 Years to 120 Years
- Dates
- First posted May 11, 2025 · updated May 11, 2025
Registry summary
Background Frailty has become a major problem for the health system, but also a window of opportunity to fight against disability through preventive strategies focused on the detection and treatment of frailty in all settings. However, no systematic strategies of screening and early detection are available in clinical settings. This project aims to identify clinical and biological phenotypic clusters that drive through the different stages of frailty and to describe the underlying mechanisms of the trajectories leading to disability and the potential for treatment. Moreover, validation of Frailty Trait Scale 5 (FTS5) will be performed as an easy model to be implemented in primary care and hospital scope.
Methods/design A prospective population-based cohort will be stablished for frailty phenotyping (CohorFES). Creation of a CIBERFES Biobank where blood and urine samples from participants of CohortFES are stored for future researches. Demographic and clinical history data, anthropometric measurements, predimed questionnaire, peripheral blood biochemical variables and metabolomics were collected for each participant at baseline and every year until become frailty.
Using cluster partition models (k-means and hierarchical clustering) will group together individuals with similar deficits and characteristics (frailty phenotypes). Then, by using pre-established criteria (gap and silhouette), the proposed clustering solution (belonging to given clusters) will be evaluated. Further, investigators will assess, in a longitudinal fashion, the appearance and accumulation of deficits during the study period and identifying the clusters subgroups with more rapid progression. Results will be applied to establish and compare clusters and trajectories. Finally, frailty phenotypes and patient clusters will be correlated with health outcomes such as the use of health services (both primary and secondary care), hospital admissions, and mortality.
Discussion Information about clinical and biological phenotypic clusters that drive through the different stages of frailty can lead to identify potential targets that could improve the therapeutic management of these patients.
In summary, from a research perspective the project aims to better understanding of the interindividual variability in clinical events that lead to frailty, dependence and finally, to death.
Sites (1)
- Hospital del Mar Research Institute, Barcelona, Catalonia, Spain
