Why the study?
Cardiovascular diseases cause significant morbidity and mortality in older adults in China, and an ageing population underscores the need for innovative cardiometabolic management strategies.
Does the integration of digital biomarkers from wearable devices and clinical indicators predict cardiovascular events, dementia, and mortality in older adults with cardiometabolic diseases?
Does the integration of digital biomarkers from wearable devices and clinical indicators predict cardiovascular events, dementia, and mortality in older adults with cardiometabolic diseases?
This protocol outlines a prospective cohort study aiming to integrate digital biomarkers from wearable devices with clinical data to predict cardiovascular events and establish a digital twin platform for precision medicine in older adults with cardiometabolic diseases.
BACKGROUND: Cardiovascular diseases (CVDs) represent a significant cause of morbidity and mortality among older adults in China, exerting a substantial influence on their quality of life and life expectancy. The country’s ageing population is predicted to intensify this burden, underscoring the need for the development of innovative and effective management strategies. METHODS: The prospective cohort study will recruit older patients with cardiometabolic diseases from multiple community health service centres in Shanghai. Participants will be comprehensively assessed for CVD risk factors, medications, functional status, and multi-omics data, along with continuous sign monitoring data from wearable bracelets and their electronic health records. The primary objective of the study is twofold: firstly, to explore the independent and joint predictive power of digital biomarkers and clinical indicators for cardiovascular events (new incident/recurrent), dementia, death and other adverse outcomes in older adults; and secondly, to establish a digital twin platform for precision medicine. DISCUSSION: The study proposes a novel integration of digital intelligence into cardiometabolic health management for older adults. The utilisation of comprehensive data collection and advanced analytical methods is anticipated to generate valuable insights into the intricate interplay of risk factors and outcomes. The development of personalised risk assessment models and intelligent alert systems has the potential to enhance the prevention and treatment of CVDs, thereby improving health outcomes and quality of life for older adults. TRIAL REGISTRATION: ChiCTR2500096478 (Chinese Clinical Trial Registry). Registered 24 January 2025 - Prospectively registered.
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Yang et al. (2025) studied this question.
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