Cardiovascular Diseases, Menopause
Conditions
Keywords
Menopause, Cardiovascular disease risk, Wearables, SCORE2, Health monitoring
Brief summary
The goal of the clinical trial is to assess whether the data collected from wearable devices can reduce the uncertainty in predicting the cardiovascular disease (CVD) risk in women aged 40-69 years in a situation where information about the blood pressure and blood lipids are unavailable. Participants will: * Complete a screening and baseline assessment, including blood sample collection and vital parameter measurement. * Wear a wearable device for one week. * Fill in a work and sleep journal. * Complete a last visit assessment.
Interventions
None listed
Sponsors
Insel Gruppe AG, University Hospital Bern
Study design
Observational model
COHORT
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
FEMALE
Age
40 Years to 69 Years
Healthy volunteers
Yes
Inclusion criteria
* Fluency in German (written and oral). * Ownership of a smartphone. * Signing the informed consent form.
Exclusion criteria
* Diagnosis of cardiovascular disease. * Diagnosis of diabetes mellitus. * Diagnosis of chronic kidney disease. * Diagnosis of familial hypercholesterolemia. * Incapable of providing informed consent. * Current employment at the Section Gynecological Endocrinology and Reproductive Medicine of the Department for Obstetrics and Gynecology at the Inselspital Bern or any other professional relation to one of the study project leaders / investigators. * Concurrent participation in a clinical intervention study. * Inability to comply with the study procedures for any reason, including language comprehension, psychiatric illness, general inability to get to the study site. * Participant's smartphone not compatible with Fitrockr. * Technical inability of participant's smartphone to connect to the smartwatch.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Reduction in CVD Risk Prediction Uncertainty Using Wearable Data | After 7-day wearable data collection period. | Assessment of the reduction in prediction uncertainty of cardiovascular disease (CVD) risk in women aged 40-69 years when wearable-derived data (e.g., heart rate, daily step count) is used to replace missing physician-recorded inputs (e.g., blood pressure and lipid levels). The reduction will be quantified using the Continuous Ranked Probability Score (CRPS), whereby smaller CRPS values indicate improved performance. An improvement is considered substantial if introducing wearable data reduces CRPS by at least 5%. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Identification of wearable data that improve cardiovascular disease risk prediction without clinical key inputs | After 7-day wearable data collection period. | Identifying specific data from wearable devices that most effectively reduce uncertainty in predicting CVD risk in the absence of information on blood pressure, blood lipids, and the presence or absence of metabolic syndrome. To achieve this, statistical and machine learning methods capable of handling irregularly samples time series of bio-signals recorded by the wearable devices will be applied. |
Countries
Switzerland
Contacts
Primary ContactPetra Stute, Prof.
Outcome results
None listed