#ExerciseCapacity

A Machine Learning Approach to Non-Exercise Prediction of Peak VO 2 in Advanced Heart Failure ML models using non-exercise clinical data can estimate peak VO₂ in heart transplant candidates, aiding evaluation when CPET is not feasible.

This study introduces a #MachineLearning framework for #NonExercise estimation of #PeakVO2 in advanced #HeartFailure, enabling accurate assessment of #ExerciseCapacity without #CPET and supporting timely, evidence-based transplant decisions.

#OpenAccess: tinyurl.com/2647d64b

Characteristics of Daily Walking Bouts as Valid and Reliable Indicators of Exercise Capacity in Pulmonary Arterial Hypertension: Insights From the Randomized Controlled Study With Selexipag (TRACE) There is a need for objective, continuous and remote assessment of exercise capacity in patients with pulmonary arterial hypertension (PAH). Using data from the TRACE study, in which 108 adult patien...

TRACE study found wrist-worn #actigraphy measured walking bouts in patients w/ #Pulmonary Arterial Hypertension correlate with 6MWD & physical impacts of #PAH, speaking to the utility of #digitalmeasures to monitor #exercisecapacity
@pvrinstitute.bsky.social onlinelibrary.wiley.com/doi/10.1002/...