Polymodal Fall Prediction in Healthy Older Adults: Clinical, Laboratory, and Blood-Based Biomarkers

Trial statusNot yet recruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age65+
SponsorSlb Pharma

About this trial

The goal of this observational study is to identify clinical, laboratory, and biological markers associated with past (and future falls) in healthy older adults aged 65 years and over.

The main question it aims to answer is: Which clinical, functional, laboratory, and blood-based markers distinguish older adults who have fallen at least once during the previous 12 months from those who have not?

Researchers will compare older adults with a history of falls with similar older adults without a history of falls. One hundred healthy older adults aged 65 and over, including both fallers and non-fallers, will be recruited for the study.

Participants will complete questionnaires and undergo cognitive and physical tests, physical activity and sleep monitoring, gait, balance, muscle, sensory and vestibular assessments, brain and muscle imaging, and blood sampling. Blood samples will be used to study proteins and genetic variants that may be associated with falls. Participants will then be followed for one year using a smartphone-based application to report falls.

The study is based on the hypothesis that a history of falling in an otherwise healthy older adult may be associated with subtle clinical, functional, and biological differences compared with a similar older adult without a history of falls. The findings may support the future development of more accurate and scalable tools for early fall-risk detection and targeted fall-prevention strategies. No direct therapeutic benefit is expected from participation.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

being aged ≥65 years,

having independent ambulation,

having an Mini Mental State Examination (MMSE) score ≥24,

being fluent in French,

Disqualifiers

neurological or psychiatric disorders affecting motor or cognitive function (e.g., Parkinson's disease, stroke sequelae, major depression) or other severe comorbidities that could affect participant safety and study outcomes,

recent lower-limb surgery (<12 months),

polypharmacy (use of more than four medications) or fall-risk increasing drugs,

significant sensory impairments limiting assessment,

Trial population

Community-dwelling adults aged 65 years who meet the study eligibility criteria. The study will recruit 100 participants: 50 who experienced at least one fall during the 12 months before enrollment and 50 who experienced no falls during that period. All participants will undergo the same baseline assessments and prospective 12-month fall monitoring.

Trial design

Design model

Cohort

Time perspective

Prospective

Treatments tested in this trial

Not listed

Trial groups

100 Participants
are grouped into 2 trial groups
Group A: Prior Fall History
Group B: No Prior Fall History

Trial outcomes

Primary outcomes

1

Stable Candidate Multimodal Biomarkers Discriminating Participants With and Without Prior Falls

The outcome will be the number and identity of stable candidate biomarkers that discriminate participants who experienced at least one fall during the previous 12 months from participants who experienced no falls during that period.

Time frame
Baseline assessment

Secondary outcomes

1

Predictive Performance of Baseline Biomarkers for Incident Falls

The ability of baseline biomarkers retained by the stability-selection procedure to predict at least one incident fall during prospective follow-up will be evaluated. Predictive performance will be reported using the area under the receiver operating characteristic curve, sensitivity, and specificity, each with 95% confidence intervals.

Time frame
From completion of baseline assessments through 12 months of prospective follow-up

Other outcomes

Locations

This trial has no locations.

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Slb Pharma

Lead sponsor

Université de Caen Normandie

Collaborator

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