Refining Maximal Heart Rate Estimation to Enhance Exercise Recommendations for Persons With Parkinson Disease

Area of Science:

• Cardiology
• Neurology
• Exercise Physiology

Background:

• Accurate maximal heart rate (MHR) estimation is crucial for prescribing safe and effective aerobic exercise.
• Traditional age-based MHR formulas often overestimate MHR in individuals with Parkinson disease (PD).
• Overestimated MHR can lead to unachievable target heart rate zones during exercise for PD patients.

Purpose of the Study:

• To derive and validate a novel equation for estimating MHR in individuals with PD.
• To compare the accuracy of the new equation against traditional MHR estimators.
• To improve the precision of exercise heart rate prescriptions for PD patients without formal testing.

Main Methods:

• A randomized controlled trial dataset from 82 participants with mild-to-moderate PD was analyzed.
• A linear regression model, utilizing the least absolute shrinkage and selection operator (LASSO), was employed.
• The model incorporated age and resting heart rate to predict MHR, with validation through leave-one-out cross-validation.

Main Results:

• The derived regression-based MHR equation is [166 - (1.15 × age) + (0.60 × resting heart rate)].
• Traditional formulas (220 - age) and [208 - (0.7 × age)] overestimated MHR in 88% and 94% of participants, respectively.
• The new estimator demonstrated significantly lower mean square error compared to traditional methods, indicating superior accuracy.

Conclusions:

• The proposed regression-based MHR estimator provides a more accurate prediction of MHR in individuals with PD compared to standard formulas.
• This novel equation, incorporating age and resting heart rate, offers a practical tool for establishing appropriate and attainable exercise heart rate zones.
• Implementing this estimator can enhance exercise prescription, promoting better adherence and outcomes for individuals with PD undergoing aerobic training.