Heart Failure (HF) is a complex disease associated with the highest burden of cost to the healthcare system. The cardiopulmonary exercise test (CPET) is instrumental in determining the prognosis of patients with HF. This multicentre study will validate whether aggregate biometric data from the Apple Watch combined with demographic, cardiac, and biomarker testing can improve our ability to predict heart failure outcomes among a diverse outpatient HF population.
broad age range (> 18 years of age)
NT-proBNP > 400 or 1000 if in AF
Within 3 months post discharge from HF hospitalization/ HF ED visit/ HF rapid clinic visit with intensification of diuretic therapy
NYHA functional class I-IV, heart failure with reduced and preserved ejection fraction
Unable to perform a CPET based on the standard protocol
End stage renal disease requiring dialysis
Living with LVAD
MRP deems patient unfit for the study
Adult (\>18 years of age), ambulatory heart failure patients currently followed by the University Health Network and hospitals in multi-site validation study.
Cohort
Prospective
Not listed
Prediction of CPET parameters
Measure predictive power of cardiorespiratory fitness estimated from data obtained from Apple Watch in combination with clinical and/or demographical data against reductions in measures of cardiorespiratory fitness in heart failure patients such as peak VO2
Prediction of worsening heart failure
Measure predictive power of cardiorespiratory fitness estimated from data obtained from Apple Watch in combination with clinical and/or demographical data against worsening heart failure
Prediction of CPET parameters
Measure predictive power of biometric data obtained from Apple Watch in combination with clinical and/or demographical data against cardiorespiratory fitness measurements as assessed by CPET
Prediction of worsening HF as a combined and stratified outcome
Measure predictive power of biometric data obtained from Apple Watch in combination with clinical and/or demographical data against worsening heart failure
Prediction of existing markers of poor prognosis
Measure predictive power of biometric data obtained from Apple Watch in combination with clinical and/or demographical data from the Apple Watch be against existing markers of poor prognosis specifically as defined by the SHFM, BNP, Quality of life (QOL) indicators, and CPET parameters?
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University Health Network, Toronto
Lead sponsor
Canadian Institutes of Health Research (CIHR)
Collaborator
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