Auxiliary Data as Surrogates for Systematic Coronary Risk Evaluation Model Version 2 Risk Calculator Inputs
Elena Pavicic, Miriam Strasser, Patric Wyss, Serena Lozza-Fiacco, Manuela Moraru, Danielle V Bower, Rowan Iskandar, Petra Stute
Organization
University Hospital of Bern, Inselspital, Switzerland.
Team
Elena Pavicic, Miriam Strasser, Patric Wyss, Serena Lozza-Fiacco, Manuela Moraru, Danielle V Bower, Rowan Iskandar, Petra Stute.
Project Description & Objectives
The aim of the study was to investigate whether data collected from wearable devices, such as heart rate, step count, and sleep-related parameters, can reduce uncertainty in cardiovascular disease (CVD) risk prediction among apparently healthy women aged 40–69 years when blood pressure and blood lipid values required for the SCORE2 risk calculator are unavailable. A secondary objective was to identify wearable-derived features that contribute most to reducing uncertainty in CVD risk prediction.
Read the full article at Auxiliary Data as Surrogates for Systematic Coronary Risk Evaluation Model Version 2 Risk Calculator InputsAuxiliary Data as Surrogates for Systematic Coronary Risk Evaluation Model Version 2 Risk Calculator Inputs.
Data Collection Process
Participants attended two study visits scheduled 7 to 10 days apart. At baseline, anthropometric measures, blood pressure, pulse, waist circumference, blood samples for lipid profile and HbA1c, and questionnaire data on medical history, nutrition, menopausal symptoms, psychosocial health, anxiety, depression, stress, sleep, and quality of life were collected. Participants wore a Garmin® wearable device for 7 days, generating data on heart rate, physical activity, sleep, and related digital biomarkers. Statistical analyses will explore probabilistic approaches to impute systematically missing SCORE2 input parameters, particularly blood pressure and blood lipids, using auxiliary variables such as age, BMI, and wearable-derived features. Model performance will be evaluated by comparing probabilistic CVD risk predictions with SCORE2 estimates based on complete clinical input data.
Fitrockr Utilization
Fitrockr was the platform used to register device users, assign devices, collect synchronized wearable data, and export detailed health logs.
Wearable Used
Garmin vivosmart 5
Number of Participants
250
Duration
16 months
Metrics Collected
Heart Rate
Sleep
Physical Activity
Fitrockr Sync Type
Fitrockr Sync on Smartphone