Key result
TRUE-HF evaluates whether Apple Watch data can estimate peak oxygen uptake in ambulatory heart failure.
Why the study?
Current methods to assess exercise capacity in heart failure are often limited to tertiary centers and lack scalability or accessibility, whereas wearable devices enable near-continuous dynamic biometrics.
Can HealthKit data from Apple Watch accurately estimate cardiorespiratory fitness compared to gold standard CPET in ambulatory patients with heart failure?
Can HealthKit data from Apple Watch accurately estimate cardiorespiratory fitness compared to gold standard CPET in ambulatory patients with heart failure?
The TRUE-HF study aims to determine if wearable technology (Apple Watch) can accurately estimate peak oxygen uptake in ambulatory heart failure patients, potentially providing a scalable alternative to traditional CPET.
Wearable VO2 estimation in ambulatory HF awaits validation; TRUE-HF leaves open whether Apple Watch HealthKit data can match CPET.
BACKGROUND: Heart failure (HF) is a highly prevalent condition characterized by exercise intolerance, an important metric for ambulatory prognostication. However, current methods to assess exercise capacity are often limited to tertiary HF centers, lacking scalability or accessibility. Wearable devices can enable near-continuous dynamic biometrics including exercise tolerance. METHODS: Leveraging the capabilities of Apple Watch and a custom application, the TRUE-HF (Ted Rogers Understanding of Exacerbations in Heart Failure) Apple cardiopulmonary exercise testing study aims to investigate whether HealthKit data from Apple Watch can estimate cardiorespiratory fitness, as compared with the gold standard peak oxygen uptake from cardiopulmonary exercise testing. The TRUE-HF study will evaluate the potential impact of wearable technology in the functional assessment of ambulatory patients with HF. The primary end point is to use HealthKit variables to estimate a TRUE-HF peak oxygen uptake. We outline key features of this trial designed to reduce the burden of wearable technology. In addition, we highlight the benefits of various machine learning analyses, with a particular focus on transformer models for the wearable space. CONCLUSIONS: Using cutting-edge wearable technology and machine learning analytics, TRUE-HF may provide state-of-the-art assessment of functional capacity by measuring participant-generated free-world data. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05008692.
No takes yet. Share an insight, caveat, or question.
Moayedi et al. (2025) studied Heart failure. Apple Watch and custom application vs. Cardiopulmonary exercise testing (CPET) was evaluated on Estimate a TRUE-HF peak oxygen uptake using HealthKit variables. The TRUE-HF study is designed to evaluate whether Apple Watch HealthKit data can estimate peak oxygen uptake compared with cardiopulmonary exercise testing in ambulatory heart failure.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: