Frailty SyndromeCOHORFESNCT06965972
The CohorFES: a Prospective Study of Frailty and Dependence
An observational study of Frailty Syndrome, run by Parc de Salut Mar at 1 site in Spain.
Trial 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. Read more about this study
- Who is it for?
- Ages 65 to 120 yearsHealthy volunteers can take part
- Conditions the study is for
- Frailty Syndrome
- How many people
- 1,500 participants
- Where
- 1 siteSpain
- Study dates
- 1 Dec 2022to 31 Dec 2035
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 65 to 120 years
- All sexes
- Healthy volunteers accepted
- Older adult
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
Who may be able to join
- women and men 65 years old or above visited in the outpatient clinics of participant centers
- Signed informed consent
Who cannot join
- Patients in a critical situation of end of live or Barthel scale <60.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Spain1 site, 1 recruiting
- Recruiting
Hospital del Mar Research Institute
Barcelona, Catalonia, 08003
Natalia Garcia-Giralt, PhD, 0034933160497, ngarcia@researchmar.net
Diana Ovejero, PhD, dovejero@researchmar.net
About this study
Official title: 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.
Read more
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.
Read the detailed description
- 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).
- 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.
- 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.
- Conditions
- Frailty Syndrome
- Keywords
- COHORFES, Frailty, FTS5
- Medical subject headings
- Frailty
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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 being measured
The primary outcome is the main question the study is designed to answer.
Fried phenotype
Frailty measure
Measured: 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
Frailty measure
Measured: Through study completion, an average of 5 years
Electronic Frailty index
Frailty measure
Measured: Through study completion, an average of 5 years
Secondary outcomes (19)
Bone Mineral Density
Bone Mineral Density measured using a Dual-Energy X-Ray Analysis (DXA) device (Hologic Horizon Wi, Hologic®).
Measured: Through study completion, an average of 5 years
Abnormal peripheral blood biochemistry
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)
Measured: Through study completion, an average of 5 years
Age
Age in years
Measured: baseline
Date of Birth
Date (dd/mm/yyyy)
Measured: baseline
Sex
sex (Male or Female)
Measured: baseline
Living situation
Living situation: Alone or accompanied
Measured: baseline
Educational level
Educational level: number of years in the school and college
Measured: baseline
All-cause mortality.
mortality during study follow-up (y/n)
Measured: From baseline until the date of death from any cause, an average of 5 years
Condition diagnosis
New condition diagnosis during follow-up (for ex. diagnosis of cancer, fracture, dementia, etc)
Measured: Through study completion, an average of 5 years
Usual treatments
treatments being taken by the patient
Measured: Through study completion, an average of 5 years
Pharmacy use
number of different drugs being taken by the patient
Measured: Through study completion, an average of 5 years
Loss of weight
Loss of weight in the last year in grams
Measured: Through study completion, an average of 5 years
Geriatric Depression Scale
Geriatric Depression Scale: 15 items (y/n) were combined to report GDS
Measured: Through study completion, an average of 5 years
Barthel Index
Barthel Index: measure of functional disability
Measured: Through study completion, an average of 5 years
Lawton-Brody Instrumental Activities of Daily Living Scale
to assess independent living skills. It contains 8 items that are rated with a summary score from 0 (low functioning) to 8 (high functioning).
Measured: Through study completion, an average of 5 years
Pfeiffer test
test of 10 questions used to assess a person's cognitive status
Measured: Through study completion, an average of 5 years
Predimed questionnaire
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
Measured: Through study completion, an average of 5 years
Healthcare resource use
number of medical care consultations
Measured: Through study completion, an average of 5 years
Non-elective hospital admissions
Number of admissions in a Hospital
Measured: Through study completion, an average of 5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 May 2025
- Study start1 Dec 2022
- Primary completionDec 2030 (estimated)
- Study completion31 Dec 2035 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (16)Papers the sponsor has linked to this study.
- Other trials for Frailty SyndromeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Parc de Salut Mar
- Sponsor type
- University, hospital or other
- Collaborators
- Consorcio Centro de Investigación Biomédica en Red (CIBER), CIBER on frailty and healthy ageing
- Responsible party
- Sponsor
- Investigators
- Xavier Nogues, PhD, Principal investigator, Hospital del Mar
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06965972
- Sponsor's protocol ID
- PI19/00033
- Acronym
- COHORFES
- Status last verified
- Dec 2024
- First submitted
- 7 Apr 2025
- Last updated
- 11 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: 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.
Publications
Stow D, Matthews FE, Barclay S, Iliffe S, Clegg A, De Biase S, Robinson L, Hanratty B. Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study. Age Ageing. 2018 Jul 1;47(4):564-569. doi: 10.1093/ageing/afy022.
PubMed 29546362Gilbert T, Neuburger J, Kraindler J, Keeble E, Smith P, Ariti C, Arora S, Street A, Parker S, Roberts HC, Bardsley M, Conroy S. Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study. Lancet. 2018 May 5;391(10132):1775-1782. doi: 10.1016/S0140-6736(18)30668-8. Epub 2018 Apr 26.
PubMed 29706364Clegg A, Bates C, Young J, Ryan R, Nichols L, Teale EA, Mohammed MA, Parry J, Marshall T. Development and validation of an electronic frailty index using routine primary care electronic health record data. Age Ageing. 2018 Mar 1;47(2):319. doi: 10.1093/ageing/afx001. No abstract available.
PubMed 28100452Garcia-Garcia FJ, Carnicero JA, Losa-Reyna J, Alfaro-Acha A, Castillo-Gallego C, Rosado-Artalejo C, Gutierrrez-Avila G, Rodriguez-Manas L. Frailty Trait Scale-Short Form: A Frailty Instrument for Clinical Practice. J Am Med Dir Assoc. 2020 Sep;21(9):1260-1266.e2. doi: 10.1016/j.jamda.2019.12.008. Epub 2020 Jan 29.
PubMed 32005416Checa-Lopez M, Oviedo-Briones M, Pardo-Gomez A, Gonzales-Turin J, Guevara-Guevara T, Carnicero JA, Alamo-Ascencio S, Landi F, Cesari M, Grodzicki T, Rodriguez-Manas L; FRAILTOOLS consortium. FRAILTOOLS study protocol: a comprehensive validation of frailty assessment tools to screen and diagnose frailty in different clinical and social settings and to provide instruments for integrated care in older adults. BMC Geriatr. 2019 Mar 18;19(1):86. doi: 10.1186/s12877-019-1042-1.
PubMed 30885132Garcia-Garcia FJ, Carcaillon L, Fernandez-Tresguerres J, Alfaro A, Larrion JL, Castillo C, Rodriguez-Manas L. A new operational definition of frailty: the Frailty Trait Scale. J Am Med Dir Assoc. 2014 May;15(5):371.e7-371.e13. doi: 10.1016/j.jamda.2014.01.004. Epub 2014 Mar 2.
PubMed 24598478Gill TM, Gahbauer EA, Han L, Allore HG. The relationship between intervening hospitalizations and transitions between frailty states. J Gerontol A Biol Sci Med Sci. 2011 Nov;66(11):1238-43. doi: 10.1093/gerona/glr142. Epub 2011 Aug 17.
PubMed 21852286Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007 Jul;62(7):722-7. doi: 10.1093/gerona/62.7.722.
PubMed 17634318Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-56. doi: 10.1093/gerona/56.3.m146.
PubMed 11253156Rodriguez-Manas L, Rodriguez-Artalejo F, Sinclair AJ. The Third Transition: The Clinical Evolution Oriented to the Contemporary Older Patient. J Am Med Dir Assoc. 2017 Jan;18(1):8-9. doi: 10.1016/j.jamda.2016.10.005. Epub 2016 Nov 22. No abstract available.
PubMed 27887892Rodriguez-Manas L, Fried LP. Frailty in the clinical scenario. Lancet. 2015 Feb 14;385(9968):e7-e9. doi: 10.1016/S0140-6736(14)61595-6. Epub 2014 Nov 6. No abstract available.
PubMed 25468154Sirven N, Rapp T. The cost of frailty in France. Eur J Health Econ. 2017 Mar;18(2):243-253. doi: 10.1007/s10198-016-0772-7. Epub 2016 Feb 25.
PubMed 26914932Trombetti A, Hars M, Hsu FC, Reid KF, Church TS, Gill TM, King AC, Liu CK, Manini TM, McDermott MM, Newman AB, Rejeski WJ, Guralnik JM, Pahor M, Fielding RA; LIFE Study Investigators. Effect of Physical Activity on Frailty: Secondary Analysis of a Randomized Controlled Trial. Ann Intern Med. 2018 Mar 6;168(5):309-316. doi: 10.7326/M16-2011. Epub 2018 Jan 9.
PubMed 29310138Rodriguez-Manas L, Feart C, Mann G, Vina J, Chatterji S, Chodzko-Zajko W, Gonzalez-Colaco Harmand M, Bergman H, Carcaillon L, Nicholson C, Scuteri A, Sinclair A, Pelaez M, Van der Cammen T, Beland F, Bickenbach J, Delamarche P, Ferrucci L, Fried LP, Gutierrez-Robledo LM, Rockwood K, Rodriguez Artalejo F, Serviddio G, Vega E; FOD-CC group (Appendix 1). Searching for an operational definition of frailty: a Delphi method based consensus statement: the frailty operative definition-consensus conference project. J Gerontol A Biol Sci Med Sci. 2013 Jan;68(1):62-7. doi: 10.1093/gerona/gls119. Epub 2012 Apr 16.
PubMed 22511289Morley JE, Vellas B, van Kan GA, Anker SD, Bauer JM, Bernabei R, Cesari M, Chumlea WC, Doehner W, Evans J, Fried LP, Guralnik JM, Katz PR, Malmstrom TK, McCarter RJ, Gutierrez Robledo LM, Rockwood K, von Haehling S, Vandewoude MF, Walston J. Frailty consensus: a call to action. J Am Med Dir Assoc. 2013 Jun;14(6):392-7. doi: 10.1016/j.jamda.2013.03.022.
PubMed 23764209
Study at a glance
From the registry record, last updated by the sponsor on 11 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Cohort for the Study of Phenotypic Clusters, Progression Paths and Outcomes of Frailty and Dependence: The Spanish CohorFES
- ClinicalTrials.gov ID
- NCT06965972
- Acronym / sponsor ID
- COHORFES / PI19/00033
- Conditions
- Frailty Syndrome
- Keywords
- COHORFES, Frailty, FTS5
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- Parc de Salut MarUniversity, hospital or other
- Collaborators
- Consorcio Centro de Investigación Biomédica en Red (CIBER), CIBER on frailty and healthy ageing
- Study start
- 1 Dec 2022 (actual)
- Primary completion
- Dec 2030 (estimated)
- Study completion
- 31 Dec 2035 (estimated)
- First posted
- 11 May 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
- 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).
- 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.
- 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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 65 to 120 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Older adult
- 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
Key inclusion criteria (2 listed)
- women and men 65 years old or above visited in the outpatient clinics of participant centers
- Signed informed consent
Key exclusion criteria (1 listed)
- Patients in a critical situation of end of live or Barthel scale <60.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Fried phenotype
Time frame: Through study completion, an average of 5 years
Frailty measure
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
Electronic Frailty index
Time frame: Through study completion, an average of 5 years
Frailty measure
19 secondary outcomes
Bone Mineral Density
Time frame: Through study completion, an average of 5 years
Abnormal peripheral blood biochemistry
Time frame: Through study completion, an average of 5 years
Age
Time frame: baseline
Date of Birth
Time frame: baseline
Sex
Time frame: baseline
Living situation
Time frame: baseline
Educational level
Time frame: baseline
All-cause mortality.
Time frame: 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
Usual treatments
Time frame: Through study completion, an average of 5 years
Pharmacy use
Time frame: Through study completion, an average of 5 years
Loss of weight
Time frame: Through study completion, an average of 5 years
Geriatric Depression Scale
Time frame: Through study completion, an average of 5 years
Barthel Index
Time frame: 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
Pfeiffer test
Time frame: Through study completion, an average of 5 years
Predimed questionnaire
Time frame: Through study completion, an average of 5 years
Healthcare resource use
Time frame: Through study completion, an average of 5 years
Non-elective hospital admissions
Time frame: Through study completion, an average of 5 years
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 May 2025.
- Results publication: PubMed 29546362Stow D, Matthews FE, Barclay S, Iliffe S, Clegg A, De Biase S, Robinson L, Hanratty B. Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study. Age Ageing. 2018 Jul 1;47(4):564-569. doi: 10.1093/ageing/afy022.
- Results publication: PubMed 29706364Gilbert T, Neuburger J, Kraindler J, Keeble E, Smith P, Ariti C, Arora S, Street A, Parker S, Roberts HC, Bardsley M, Conroy S. Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study. Lancet. 2018 May 5;391(10132):1775-1782. doi: 10.1016/S0140-6736(18)30668-8. Epub 2018 Apr 26.
- Results publication: PubMed 28100452Clegg A, Bates C, Young J, Ryan R, Nichols L, Teale EA, Mohammed MA, Parry J, Marshall T. Development and validation of an electronic frailty index using routine primary care electronic health record data. Age Ageing. 2018 Mar 1;47(2):319. doi: 10.1093/ageing/afx001. No abstract available.
- Results publication: PubMed 32005416Garcia-Garcia FJ, Carnicero JA, Losa-Reyna J, Alfaro-Acha A, Castillo-Gallego C, Rosado-Artalejo C, Gutierrrez-Avila G, Rodriguez-Manas L. Frailty Trait Scale-Short Form: A Frailty Instrument for Clinical Practice. J Am Med Dir Assoc. 2020 Sep;21(9):1260-1266.e2. doi: 10.1016/j.jamda.2019.12.008. Epub 2020 Jan 29.
- Results publication: PubMed 30885132Checa-Lopez M, Oviedo-Briones M, Pardo-Gomez A, Gonzales-Turin J, Guevara-Guevara T, Carnicero JA, Alamo-Ascencio S, Landi F, Cesari M, Grodzicki T, Rodriguez-Manas L; FRAILTOOLS consortium. FRAILTOOLS study protocol: a comprehensive validation of frailty assessment tools to screen and diagnose frailty in different clinical and social settings and to provide instruments for integrated care in older adults. BMC Geriatr. 2019 Mar 18;19(1):86. doi: 10.1186/s12877-019-1042-1.
- Results publication: PubMed 24598478Garcia-Garcia FJ, Carcaillon L, Fernandez-Tresguerres J, Alfaro A, Larrion JL, Castillo C, Rodriguez-Manas L. A new operational definition of frailty: the Frailty Trait Scale. J Am Med Dir Assoc. 2014 May;15(5):371.e7-371.e13. doi: 10.1016/j.jamda.2014.01.004. Epub 2014 Mar 2.
- Results publication: PubMed 21852286Gill TM, Gahbauer EA, Han L, Allore HG. The relationship between intervening hospitalizations and transitions between frailty states. J Gerontol A Biol Sci Med Sci. 2011 Nov;66(11):1238-43. doi: 10.1093/gerona/glr142. Epub 2011 Aug 17.
- Results publication: PubMed 17634318Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci. 2007 Jul;62(7):722-7. doi: 10.1093/gerona/62.7.722.
- Results publication: PubMed 11253156Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-56. doi: 10.1093/gerona/56.3.m146.
- Results publication: PubMed 27887892Rodriguez-Manas L, Rodriguez-Artalejo F, Sinclair AJ. The Third Transition: The Clinical Evolution Oriented to the Contemporary Older Patient. J Am Med Dir Assoc. 2017 Jan;18(1):8-9. doi: 10.1016/j.jamda.2016.10.005. Epub 2016 Nov 22. No abstract available.
- Results publication: PubMed 25468154Rodriguez-Manas L, Fried LP. Frailty in the clinical scenario. Lancet. 2015 Feb 14;385(9968):e7-e9. doi: 10.1016/S0140-6736(14)61595-6. Epub 2014 Nov 6. No abstract available.
- Results publication: PubMed 26914932Sirven N, Rapp T. The cost of frailty in France. Eur J Health Econ. 2017 Mar;18(2):243-253. doi: 10.1007/s10198-016-0772-7. Epub 2016 Feb 25.
- Individual participant dataSharing planned: Yes. 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Xavier Nogues, PhD principal investigator
Hospital del Mar
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Frailty Syndrome, run by Parc de Salut Mar at 1 site in Spain.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 11 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Spain. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Natalia Garcia-Giralt, PhD (00346160497, ngarcia@researchmar.net), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Fried phenotype (time frame: Through study completion, an average of 5 years). The study lists 3 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06965972, which also lists 16 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 May 2025.