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SHIP-AGE: Frailty, Renal Function, and Multi-component Primary Care in Rural Mecklenburg-Western Pomerania (MV-FIT)

U

University Medicine Greifswald

Status

Not yet enrolling

Conditions

Frailty Syndrome

Treatments

Diagnostic Test: Multi-factorial geriatric assessment, monitoring & management systems

Study type

Interventional

Funder types

Other

Identifiers

NCT05962203
BB 161/22

Details and patient eligibility

About

Chronic kidney disease (CKD) is a leading risk factor for cardiovascular and all-cause mortality among the elderly. Mecklenburg-Western Pomerania has the largest prevalence of CKD in Germany and Europe. The CKD impact in primary care strategies to reduce frailty syndrome in the elderly is unknown. For this purpose, about 820 elderly participants will be included in an observational study (MV-FIT), who will undergo an multi-factorial geriatric assessment, monitoring & management program, specifically designed to avoid frailty. The goal of the full-scale study is to evaluate the impact of CKD in multi-component primary care strategies to reduce frailty among elderly persons in rural Mecklenburg-Western Pomerania. MV-FIT will be conducted on individuals in rural Mecklenburg-Western Pomerania, who will be observed over a period of 3 years. The Study of Health in Pomerania (SHIP) is a population-based epidemiological, two independent-cohort, study (SHIP and SHIP-TREND). SHIP cohorts have been followed for >24 years. SHIP/SHIP TEND participants >60 years or older will studied by a follow-up survey. The aim is to gain new insights into the development of frailty and to develop strategies for keeping those affected healthy.

Full description

Our study is a longitudinal population-based epidemiological SHIP-cohort study combined with a prospective, multi-centered, observational/interventional investigation. MV-FIT is an observational study of individuals aged 65 years or older with mGFR >30 mL/min (n=~820). All participants in the observational/interventional study will receive guideline-based, multi-factorial geriatric assessment, monitoring & managements (multi-component healthcare). Subjects will be stratified by mGFR. Objectives are 1) to implement multi-component healthcare specifically comprised of components to reduce frailty and incident falls, 2) to improve compliance and adherence to the multi-component healthcare for frailty and improvement of patient welfare, ability to live independently, quality-of-life, number of falls, referrals to nursing homes, all-cause mortality in primary care of the elderly, 3) to seek the elderly individuals' experience during the course of multi-factorial primary care intervention through In-depth interviews, 4) to clarify the burden of CKD on frailty and health status, and 5) to identify novel risk factors and mechanisms for frailty and pre-frailty. MV-FIT data will be corroborated by SHIP/SHIP-TREND data.

Enrollment

820 estimated patients

Sex

All

Ages

65 to 100 years old

Volunteers

Accepts Healthy Volunteers

Inclusion criteria

  • age 65 years or older
  • mGFR > 30 mL/min per 1.73 m2
  • being able to understand and give written informed consent.

Exclusion criteria

  • bedridden
  • palliative
  • inability to consent
  • severe dementia
  • inability to speak
  • lack of compliance (paracusis, inability to fulfill at least 60% of the assessments)

Trial design

Primary purpose

Prevention

Allocation

N/A

Interventional model

Single Group Assignment

Masking

None (Open label)

820 participants in 1 patient group

Multi-factorial geriatric assessment, monitoring & management systems
Experimental group
Description:
All participants in the observational/interventional study (MV-FIT) will receive guideline-based, multi-factorial geriatric assessment, monitoring \& managements (multi-component healthcare). Other: GFR Measuremments, Blood sampling, Urine sampling
Treatment:
Diagnostic Test: Multi-factorial geriatric assessment, monitoring & management systems

Trial contacts and locations

0

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Central trial contact

Maik Gollasch, MD, PhD; Julia Rüdebusch, PhD

Data sourced from clinicaltrials.gov

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