Refining the Risk Prediction of Cardiorespiratory Fitness With Network Analysis: A Welcome and Needed Line of Inquiry

The value of ascertaining an individual’s cardiorespiratory fitness (CRF) is clear; a convincing body of evidence spanning several decades supports the importance of determining CRF in apparently healthy individuals, as well as those at risk for or diagnosed with ≥1 chronic diseases. In fact, CRF is now viewed as a vital sign, recognized as one of the most powerful prognostic markers for mortality and providing a window into one’s future health trajectory.1 CRF has traditionally been considered to be synonymous with peak aerobic capacity or oxygen consumption (Vo2), either estimated from treadmill speed/grade or ergometer Watts (ie, metabolic equivalents) or directly measured through ventilatory expired gas analysis. We have now come to appreciate the fact that CRF, from the perspective of an aerobic exercise stimulus, is ideally represented by a collection of measures that synergistically provide a multidimensional view of CRF. These exercise measures may be grouped into the following categories: (1) aerobic capacity or peak Vo2; (2) ventilatory efficiency, commonly assessed as the minute ventilation/carbon dioxide production (VE/Vco2) slope; (3) hemodynamics (ie, blood pressure); (4) electrocardiography, capturing both heart rate and rhythm; (5) pulmonary function and inspiratory muscle strength and endurance; and (6) symptomatology, including exertional dyspnea, leg fatigue, and angina. Traditional exercise testing on a treadmill or cycle ergometer, which entails hemodynamics, electrocardiography, and symptomatology monitoring, combined with ventilatory expired gas analysis, defines cardiopulmonary exercise testing (CPET) and provides an optimal multidimensional assessment of CRF. CPET consistently demonstrates diagnostic and prognostic utility, as well as the ability to gauge therapeutic efficacy. Scientific statements from the United States and Europe support the use of CPET in apparently healthy …