Refining Maximal Heart Rate Estimation to Enhance Exercise Recommendations for Persons with Parkinson's disease.

Objective: To derive and evaluate an alternative equation to estimate maximal HR in PwPD in the absence of structured exercise testing using observed maximal HR data from a maximal cardiopulmonary exercise test (CPET) and basic demographic and clinical data.

Design: Baseline data from a randomized clinical trial SETTING: Academic medical center PARTICIPANTS: Eighty-two persons with mild-moderate PD who completed a CPET INTERVENTION: Not applicable MAIN OUTCOME MEASURES: A linear regression model was fit to maximal HR from CPET using the relaxed least absolute shrinkage and selection operator (lasso) and seven readily clinically accessible candidate covariables. Model fit was assessed by leave-one-out cross-validation. Maximal HRs from the CPET were compared with estimates from the regression model and from two traditional age-based maximal HR estimators, (220-age) and [208 - (0.7*age)].

Results: The regression-based HR estimator was [166 - (1.15 * age) + (0.60 * resting HR)] and most closely fit the observed maximal HR from the CPET. The (220-age) and [208 - (0.7*age)] equations overestimated maximal HR for 88% and 94% of the participants, respectively. The mean square error of the regression-based estimator was 63% and 75% lower than those of the two traditional age-based estimators, respectively.

Conclusion: Overestimating maximal HR generates prescribed target HR zones that are likely unachievable during aerobic exercise. The proposed regression-based maximal HR estimator most closely fit observed maximal HRs from the CPET. Adoption of this estimator, based upon both age and resting HR, may improve estimated maximal HR accuracy and thus provide more appropriate and achievable exercise HR zones for PwPD in the absence of a CPET.