Improving Reporting of Exercise Capacity Across Age Ranges Using Novel Workload Reference Equations - 01/03/24

Doi : 10.1016/j.amjcard.2024.01.022

Everton J. Santana, MSc ^a,^b,^c,^⁎ , Jeffrey W. Christle, PhD ^a,^b,^d, Nicholas Cauwenberghs, PhD ^c, James E. Peterman, PhD ^e, Vincent Busque ^a, Bruna Gomes, MD ^a,^b,^f, Shadi P. Bagherzadeh, MD ^a, Kegan Moneghetti, PhD ^g, Tatiana Kuznetsova, MD, PhD ^c, Matthew Wheeler, MD, PhD ^a, Euan Ashley, MD, PhD ^a,^h,ⁱ, Matthew P. Harber, PhD ^j, Ross Arena, PhD ^k,^l, Leonard A. Kaminsky, PhD ^e,^j,^l, Jonathan Myers, PhD ^l,^m,^⁎ , Francois Haddad, MD ^a,^b,^n,^o,^⁎
^a Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California
^b Stanford Cardiovascular Institute, Stanford University, Stanford, California
^c Research Unit Hypertension and Cardiovascular Epidemiology, Department of Cardiovascular Sciences, University of Leuven, Leuven, Belgium
^d Stanford Sports Cardiology, Department of Medicine, Stanford University, Stanford, California
^e Fisher Institute of Health and Well-Being, Ball State University, Muncie, Indiana
^f Department of Cardiology, Pneumology and Angiology, Heidelberg University Hospital, Heidelberg, Germany
^g Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
^h Department of Genetics, Stanford University School of Medicine, Stanford, California
ⁱ Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California
^j Clinical Exercise Physiology Laboratory, College of Health, Ball State University, Muncie, Indiana
^k Department of Physical Therapy, College of Applied Sciences, University of Illinois at Chicago, Chicago, Illinois
^l Healthy Living for Pandemic Event Protection (HL – PIVOT) Network, Chicago, Illinios
^m Division of Cardiology, Veterans Affairs Palo Alto Healthcare System and Stanford University, Palo Alto, California
ⁿ Stanford Diabetes Research Center, Stanford University, Stanford, California
^o Wu Tsai Performance Alliance, Stanford University, Stanford, California

^⁎Corresponding authors.

Highlights

•	Commonly used workload equations can lead to inaccurate exercise capacity reporting based on percent-predicted workload.
•	We propose novel workload reference equations for treadmill exercise testing.
•	The sex-specific equations consider the nonlinear effects of age.
•	These equations have the potential to improve and simplify reporting of exercise capacity.

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Résumé

Exercise capacity (EC) is an important predictor of survival in the general population and in subjects with cardiopulmonary disease. Despite its relevance, considering the percent-predicted workload (%pWL) given by current equations may overestimate EC in older adults. Therefore, to improve the reporting of EC in clinical practice, our main objective was to develop workload reference equations (pWL) that better reflect the relation between workload and age. Using the Fitness Registry and the Importance of Exercise National Database (FRIEND), we analyzed a reference group of 6,966 apparently healthy participants and 1,060 participants with heart failure who underwent graded treadmill cardiopulmonary exercise testing. For the first group, the mean age was 44 years (18 to 79); 56.5% of participants were males and 15.4% had obesity. Peak oxygen consumption was 11.6 ± 3.0 METs in males and 8.5 ± 2.4 METs in females. After partition analysis, we first developed sex-specific pWL equations to allow comparisons to a healthy weight reference. For males, pWL (METs) = 14.1−0.9×10⁻³×age² and 11.5−0.87×10⁻³×age² for females. We used those equations as denominators of %pWL, and based on their distribution, we determined thresholds for EC classification, with average EC defined by the range corresponding to 85% to 115%pWL. Compared with %pWL using current equations, the new equations yielded better-calibrated %pWL across different age ranges. We also derived body mass index-adjusted pWL equations that better assessed EC in subjects with heart failure. In conclusion, the novel pWL equations have the potential to impact the report of EC in practice.

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Keywords : cardiorespiratory fitness, exercise testing, nonlinear statistical models, reference limits

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CRediT authorship contribution statement

	Drs. Myers and Haddad contributed equally to this work as senior authors.
	Funding: This study was funded by the Stanford Cardiovascular Institute (Stanford, California) and Stanford Biomarker and Phenotypic Core Laboratory (Stanford, California).

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Vol 215

P. 32-41 - mars 2024 Retour au numéro

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Improving Reporting of Exercise Capacity Across Age Ranges Using Novel Workload Reference Equations - 01/03/24

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