The CohorFES: a Prospective Study of Frailty and Dependence (COHORFES)

May 2, 2025 updated by: Parc de Salut Mar

Prospective Cohort for the Study of Phenotypic Clusters, Progression Paths and Outcomes of Frailty and Dependence: The Spanish CohorFES

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.

Study Overview

Status

Recruiting

Conditions

Detailed Description

  1. Background of the study:

    Frailty is one of the major challenges of the 21st Century, and a top priority for national and international organisms like the WHO (World Health Organization) or the European Parliament. This has put frailty as one of the top priorities in the biomedical research agenda of the European Commission. Frailty is constituted by a physiological state of increased vulnerability and impaired resilience to stressors (i.e. diseases, external agents, drugs tolerability and toxicity) due to the combined effect of the aging process and some chronic diseases which drives to a final stage of dependency and disability with a sharp impact in quality of life, health and social resources consumption, hospitalization and death.

    It is well-known the relevance of frailty, its detection, and management since we are aware about their reversibility, the costs on the health systems, and its potential impact in clinical settings. In a clear contrast with the abundancy of data in non-clinical settings, there is a lack of strong data in the clinical setting where the prevalence of frailty is higher and where the risks for developing its most serious adverse consequences is more likely. There is hence an urgent need for a better screening and diagnosis of frailty, its trajectories and the determinants of these separate trajectories depending upon both the characteristics of frailty in each patient (associated or not with sarcopenia, or cognitive impairment or different clusters of chronic diseases).

  2. Review of prior research:

    While the different categories of the syndrome based on the severity of the observed deficits (robust, frail, pre-frail) are quite well defined and characterized from an epidemiological point of view, there is a scarcity of data on the functional pathways between these diagnostic categories (and, among them, disability), and this is especially true in clinical cohorts. This is really shocking considering that one of the most relevant factors, if not the first one, associated with a poor evolution of frailty is to experience an episode of hospitalization.

    The overarching goal of this study is therefore, to identify the critical subgroups of subjects at risk of progression from robustness to prefrailty and frailty and from there to their late stages, and the pathways that mediate this trajectory amongst community-dwelling Spanish subjects.

    Another important issue in this field would be to find an easy tool to identify frailty and factors which could be implemented in our full outpatients list. In addition to the more classical instruments to assess frailty, several groups currently members of CIBER on Frailty and Healthy Ageing (CIBERFES) developed an instrument that overcomes some of the problems raised by the more classical ones. The Frailty Trait Scale-FTS has shown a good predictive capacity for some outcomes in very old patients living in the community. More recently, and as part of an EU-funded project (FRAILTOOLS) we have found that the full version of FTS is able to detect frailty in some clinical settings (Acute Care Geriatric Unit, Geriatric Service outpatient office and Primary Care), with a good predictive capacity for adverse outcomes (death, incident disability, deterioration in SPPB, falls and hospitalization) at 6-12-18 months. However, the full version of FTS, composed of 12 items, takes around 15 minutes, making it unpractical in usual clinical conditions, where the time available by the physician or the nurse is lower. With this fact in mind, a shorter version of only 5 items (the so-called FTS 5) was developed.

    This shorter version takes less time, but more interestingly, FTS 5 offers promising results based upon the sensitivity to detect small changes shown by the full FTS. Finally, the variables that compose the FTS5 (gait velocity, grip strength, BMI, PASE, and balance) can be incorporated into electronic instruments. This has been the case for the electronic frailty index (eFI), developed and validated in the British electronic records based on the Rockwood's frailty model that would allow to assess the frailty profile after to consider 36 items or deficits at the same moment of visit by primary care o hospital physician or the more recent Hospital Frailty Risk Score based on clinical diagnoses that is able to predict death but showing only a fair concordance with the Frailty Phenotype and the Frailty Index.

    The use of easy electronic tools has been useful not only in hospital care but also in routine primary care practice. Moreover, it would be easier to measure the adverse outcomes, including falls, delirium, disability, care home admission, hospitalization and mortality as it has been recently shown.

  3. Rationale of study:

Inside this conceptual framework and considering the scarce data available in clinical settings about frailty diagnosis, trajectories and prognosis, the main goal of this project is to stablish a clinical, real-life and prospective cohort (COHORFES) to identify clinical and biological phenotypic clusters that drive through the different stages of frailty and to identify the underlying mechanisms that finally will trigger the disability.

Study Type

Observational

Enrollment (Estimated)

1500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • Spain
    • Catalonia
      • Barcelona, Catalonia, Spain, 08003
        • Recruiting
        • Hospital del Mar Research Institute
        • Principal Investigator:
          • José Antonio Serra Rexach
        • Contact:
        • Contact:
        • Principal Investigator:
          • Xavier Nogues
        • Principal Investigator:
          • Pedro Abizanda Soler
        • Principal Investigator:
          • Leocadio Rodriguez Mañas
        • Principal Investigator:
          • Francisco José García García
        • Sub-Investigator:
          • Diana Ovejero
        • Sub-Investigator:
          • Natalia Garcia-Giralt
        • Sub-Investigator:
          • Anna Ribes
        • Sub-Investigator:
          • Montserrat Rabassa
        • Sub-Investigator:
          • Jose Antonio Carnicero Carreño
        • Sub-Investigator:
          • Mariam El Assar de la Fuente
        • Sub-Investigator:
          • Carmen Maria Osuna Del pozo
        • Sub-Investigator:
          • Inmaculada Carmona
        • Sub-Investigator:
          • M Ángeles Caballero Mora
        • Sub-Investigator:
          • Elisa Belen Cortes Zamora
        • Sub-Investigator:
          • Almudena Avendaño Céspedes
        • Sub-Investigator:
          • Bárbara Agud Andreu
        • Sub-Investigator:
          • Fernando Gómez Galera
        • Principal Investigator:
          • Maria Cristina Andrés Lacueva

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

Participants are women and men 65 years old or above visited in the outpatient clinics of participant centers:

Hospital General Universitario Gregorio Marañón, Madrid Hospital Universitario de Getafe, Madrid Hospital General Universitario de Ciudad Real, Ciudad real Hospital del Mar, Consorci Mar Parc Salut de Barcelona, Barcelona Complejo Hospitalario Universitario de Albacete, Albacete Fundación del Hospital Nacional de Parapléjicos, Toledo

These participants are included in the COHORFES

Description

Inclusion Criteria:

  • women and men 65 years old or above visited in the outpatient clinics of participant centers
  • Signed informed consent

Exclusion Criteria:

  • Patients in a critical situation of end of live or Barthel scale <60.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
women and men 65 years old or above visited in the outpatient clinics of participant centers

To stablish the CohorFES, a prospective and observational study based on real population. Patients are recruited from the beginning of the project and followed year on year during all the study time.

Individuals visited in participant centers and meet inclusion criteria are asked to participate into the study. These individuals are consecutively included to the study after signed the informed consent.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Fried phenotype
Time Frame: Through study completion, an average of 5 years
Frailty measure
Through study completion, an average of 5 years
Frailty Trait Scale 5 ítems: 1.- walking speed test, 2.- grip strength, 3.- Physical Activity, 4- Body Mass Index (BMI), 5.- progressive Romberg test. Point 1 to 5 are combined to report the frailty trait scale
Time Frame: Through study completion, an average of 5 years
Frailty measure
Through study completion, an average of 5 years
Electronic Frailty index
Time Frame: Through study completion, an average of 5 years
Frailty measure
Through study completion, an average of 5 years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Bone Mineral Density
Time Frame: Through study completion, an average of 5 years
Bone Mineral Density measured using a Dual-Energy X-Ray Analysis (DXA) device (Hologic Horizon Wi, Hologic®).
Through study completion, an average of 5 years
Abnormal peripheral blood biochemistry
Time Frame: Through study completion, an average of 5 years

Detection of anormal values of the following parameters (y/n):

  • Leukocytes ml/mmc
  • Red blood cells ml/mmc
  • Hemoglobin g/dl
  • Hematocrit %
  • Red blood cell distribution width %
  • Platelets ml/mmc
  • Vitamin D ng/ml
  • TSH nmol/l
  • Glucose mg/dl
  • Glycated hemoglobin (diabetics only) %
  • Creatinine mg/dl
  • Sodium meq/dl
  • Potassium meq/dl
  • Calcium mg/dl
  • Phosphorus mg/dl
  • GPT u/l
  • GOT u/l
  • Phosphatase alkaline u/l
  • Total proteins g/dl
  • Albumin g/dl
  • Prealbumin mg/dl
  • Cholesterol mg/dl
  • Triglycerides mg/dl
  • HDL mg/dl
  • LDL mg/dl
  • C-reactive protein mg/ml

These parameters are combined with the final outcome: abnormal biochemistry (y/n)
Through study completion, an average of 5 years
Age
Time Frame: baseline
Age in years
baseline
Date of Birth
Time Frame: baseline
Date (dd/mm/yyyy)
baseline
Sex
Time Frame: baseline
sex (Male or Female)
baseline
Living situation
Time Frame: baseline
Living situation: Alone or accompanied
baseline
Educational level
Time Frame: baseline
Educational level: number of years in the school and college
baseline
All-cause mortality.
Time Frame: From baseline until the date of death from any cause, an average of 5 years
mortality during study follow-up (y/n)
From baseline until the date of death from any cause, an average of 5 years
Condition diagnosis
Time Frame: Through study completion, an average of 5 years
New condition diagnosis during follow-up (for ex. diagnosis of cancer, fracture, dementia, etc)
Through study completion, an average of 5 years
Usual treatments
Time Frame: Through study completion, an average of 5 years
treatments being taken by the patient
Through study completion, an average of 5 years
Pharmacy use
Time Frame: Through study completion, an average of 5 years
number of different drugs being taken by the patient
Through study completion, an average of 5 years
Loss of weight
Time Frame: Through study completion, an average of 5 years
Loss of weight in the last year in grams
Through study completion, an average of 5 years
Geriatric Depression Scale
Time Frame: Through study completion, an average of 5 years
Geriatric Depression Scale: 15 items (y/n) were combined to report GDS
Through study completion, an average of 5 years
Barthel Index
Time Frame: Through study completion, an average of 5 years
Barthel Index: measure of functional disability
Through study completion, an average of 5 years
Lawton-Brody Instrumental Activities of Daily Living Scale
Time Frame: Through study completion, an average of 5 years
to assess independent living skills. It contains 8 items that are rated with a summary score from 0 (low functioning) to 8 (high functioning).
Through study completion, an average of 5 years
Pfeiffer test
Time Frame: Through study completion, an average of 5 years
test of 10 questions used to assess a person's cognitive status
Through study completion, an average of 5 years
Predimed questionnaire
Time Frame: Through study completion, an average of 5 years
The adherence of participants to the Mediterranean diet will be assessed through the 14-item Mediterranean diet adherence screener (MEDAS) validated for the Spanish population in a phone interview with the participant
Through study completion, an average of 5 years
Healthcare resource use
Time Frame: Through study completion, an average of 5 years
number of medical care consultations
Through study completion, an average of 5 years
Non-elective hospital admissions
Time Frame: Through study completion, an average of 5 years
Number of admissions in a Hospital
Through study completion, an average of 5 years

Other Outcome Measures

Outcome Measure
Measure Description
Time Frame
Metabolomics
Time Frame: Through study completion, an average of 5 years
Quantitative metabolomics approach applied to analyze plasma samples using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). It is defined as altered metaboloma (y/n)
Through study completion, an average of 5 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Parc de Salut Mar

Collaborators

Consorcio Centro de Investigación Biomédica en Red (CIBER)
CIBER on frailty and healthy ageing

Investigators

  • Principal Investigator: Xavier Nogues, PhD, Hospital del Mar

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 1, 2022

Primary Completion (Estimated)

December 1, 2030

Study Completion (Estimated)

December 31, 2035

Study Registration Dates

First Submitted

April 7, 2025

First Submitted That Met QC Criteria

May 2, 2025

First Posted (Actual)

May 11, 2025

Study Record Updates

Last Update Posted (Actual)

May 11, 2025

Last Update Submitted That Met QC Criteria

May 2, 2025

Last Verified

December 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • PI19/00033

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

YES

IPD Plan Description

Once the project is completed and after the necessary embargo periods, de-identified data will be shared with the research community upon request to the PI of the study. Intellectual property rights or sensitive data will be handled in accordance with the EU General Data Protection Regulation (GDPR). As this is a prospective observational cohort with long-term clinical data collection, the data will be deposited in the IMIM repository and shared upon request to the research group responsible for the data.

Data dissemination will take place through academic journals and conference presentations.

IPD Sharing Time Frame

from 1/1/2035 to 31/12/2050

IPD Sharing Access Criteria

All researcher can request to the Hospital del Mar Research Institute the anomyzed IPD from 1/1/2035

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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