Data Analysis to Evaluate Which Specific Gait Measures Are Associated with Risk of Injurious Falls Evaluating Gait Measures Associated with the Risk of Injurious Falls Through Data Analysis

What this trial studies

The goal of this study is to understand if specific gait and activity measures can help predict injurious falls in older women. The main questions it aims to answer are: Can combining daily gait (DLG) and daily physical activity (DLPA) measures more accurately predict the risk of injurious falls? How effective is wearable technology and machine learning in analyzing these activity measures for fall prediction? Researchers will analyze data from the Women's Health Study (WHS), using wearable technology to track daily walking patterns and physical activity, and apply machine learning to assess the likelihood of harmful falls.

Conditions in scope

• Women
• Age ≥45
• After Menopause or Without Intention of Pregnancy

Interventions

• Daily Activity Patterns Using Wearable Tri-Axial Sensors (Device) — This intervention uniquely focuses on the prediction of injurious falls by combining daily life gait (DLG) measures (e.g., gait speed, cadence, variability) with daily life physical activity (DLPA) measures (e.g., activity levels, activity fragmentation). Unlike other studies, this analysis leverages…

Who can join

Women only · Ages 45 Years and up

Inclusion criteria

• after menopause or without intention of pregnancy

Exclusion criteria

• history of CHD, cerebrovascular disease, cancer (except non-melanoma skin cancer), or other serious illness;
• history of serious side effects to study treatments;
• taking aspirin, drugs containing aspirin, or non-steroidal anti-inflammatory drugs \> once a week, or ready to give up the use of these drugs;
• taking anticoagulants or corticosteroids;
• Taking vitamin A, E or ß-carotene supplements \> once a week.

Eligibility wording paraphrased from the public record. View the full criteria on ClinicalTrials.gov before contacting a site.

Where it’s happening

Status & timeline

• Overall status: Active, not recruiting
• Study type: Observational
• Phase: N/A
• Start date: 2024-08-06
• Primary completion: 2030-08-01
• Last update posted: 2024-10-16
• First posted: 2024-10-16

Sponsor & contact

Lead sponsor: Tel-Aviv Sourasky Medical Center (Other Gov)

For trial site contact information, use the official record at ClinicalTrials.gov. Contact details change frequently and the public record is the source of truth.

Outcome measures

Primary outcomes

• Association of Gait Speed with Risk of Injurious Falls (AIM1) (njurious falls within 1 year after baseline assessment using time-to-event analyses.)
  The study will evaluate the association between gait speed (measured in meters per second) and the risk of injurious falls within one year following the accelerometer assessment.
• Association of Cadence with Risk of Injurious Falls (AIM1) (Injurious falls within 1 year after baseline assessment using time-to-event analyses.)
  The study will assess the association between cadence (measured in steps per minute) and the risk of injurious falls within one year following the accelerometer assessment.
• Association of Gait Variability with Risk of Injurious Falls (AIM1) (Time Frame: Injurious falls within 1 year after baseline assessment using time-to-event analyses.)
  The study will assess the association between gait variability (measured as the standard deviation of step times) and the risk of injurious falls within one year following the accelerometer assessment.
• Association of Overall Activity Levels with Risk of Injurious Falls (AIM2) (Injurious falls within 1 year after baseline assessment using time-to-event analyses)
  The study will evaluate the association between overall activity levels (measured in average accelerometer counts per minute) and the risk of injurious falls within one year following the baseline assessment.
• Association of Activity Fragmentation with Risk of Injurious Falls (AIM2) (Injurious falls within 1 year after baseline assessment using time-to-event analyses.)
  The study will assess the association between activity fragmentation (measured by the fragmentation index) and the risk of injurious falls within one year following the baseline assessment.

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