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Study protocol to stablish a prospective cohort for the study of phenotypic clusters, progression paths and outcomes of frailty and dependence: The CohorFES

Garcia-Giralt, N.; Ovejero, D.; Carnicero Carreno, J. A.; Ribes, A.; Abizanda Soler, P.; Serra Rexach, J. A.; Garcia Garcia, F. J.; Rabassa, M.; Rodriguez Manas, L.; Sanchez Pla, A.; El Assar de la Fuente, M.; Osuna Del pozo, C. M.; Carmona, I.; Caballero-Mora, M. A.; Mazoteras Munoz, V.; Cortes Zamora, E. B.; Avendano Cespedes, A.; Agud Andreu, B.; Gomez Galera, F.; Soldado-Folgado, J.; Andres Lacueva, M. C.; Nogues, X.

2025-05-31 geriatric medicine
10.1101/2025.05.29.25328600 medRxiv
Show abstract

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. 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, we 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. 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. Protocol RegistrationNCT06965972 (date 05/02/2025)

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