A Nonexercise Prediction of Peak Oxygen Uptake for Patients With Cardiovascular Disease: DATA FROM THE FITNESS REGISTRY AND THE IMPORTANCE OF EXERCISE INTERNATIONAL DATABASE (FRIEND)

Evaluating current assessment techniques of cardiorespiratory fitness

INTRODUCTION

Considerable and convincing global data from cohorts across the health spectrum (i.e. apparently healthy to known disease) indicate that cardiorespiratory fitness (CRF) is a major predictor of overall and cardiovascular disease (CVD)-survival, seemingly with greater prognostic resolution compared to other traditional CVD risk factors. Therefore, the assessment of CRF in research and clinical settings is of major importance.

AREAS COVERED

In this manuscript, we review the technology of measuring CRF assessed by the 'gold standard,' cardiopulmonary exercise testing (CPET), as well as with various other methods (e.g. estimated metabolic equivalents, 6-minute walk tests, shuttle tests, and non-exercise equations that estimate CRF), all of which provide significant prognostic information for CVD- and all-cause survival. The literature through May 2024 has been cited.

EXPERT OPINION

The promotion of physical activity in efforts to improve levels of CRF is needed throughout the world to improve lifespan and, more importantly, healthspan. The routine assessment of CRF should be considered a vital sign that is routinely assessed in clinical practice.

Assessing cardiorespiratory fitness in clinical and community settings: Lessons and advancements in the 100th year anniversary of VO2max

Cardiorespiratory fitness (CRF) is a well-established biomarker that has applications to all adults across the health and disease spectrum. Despite overwhelming evidence supporting the prognostic utility of CRF, it remains vastly underutilized. CRF is optimally measured via cardiopulmonary exercise testing which may not be feasible to implement on a large scale. Therefore, it is prudent to develop ways to accurately estimate CRF that can be applied in clinical and community settings. As such, several prediction equations incorporating non-exercise information that is readily available from routine clinical encounters have been developed that provide an adequate reflection of CRF that could be implemented to raise awareness of the importance of CRF. Further, technological advances in smartphone apps and consumer-grade wearables have demonstrated promise to provide reasonable estimates of CRF that are widely available, which could enhance the utilization of CRF in both clinical and community settings.

2023 update: The importance of cardiorespiratory fitness in the United States

The American Heart Association issued a Policy Statement in 2013 that characterized the importance of cardiorespiratory fitness (CRF) as an essential marker of health outcomes and specifically the need for increased assessment of CRF. This statement summarized the evidence demonstrating that CRF is "one of the most important correlates of overall health status and a potent predictor of an individual's future risk of cardiovascular disease." Subsequently, this Policy Statement led to the development of a National Registry for CRF (Fitness Registry and the Importance of Exercise: A National Data Base [FRIEND]) which established normative reference values for CRF for adults in the United States (US). This review provides an overview of the progress made in the past decade to further our understanding of the importance of CRF, specifically related to prevention and for clinical populations. Additionally, this review overviews the evolvement and additional uses of FRIEND and summarizes a hierarchy of assessment methods for CRF. In summary, continued efforts are needed to expand the representation of data from across the US, and to include data from pediatric populations, to further develop the CRF Reference Standards for the US as well as further develop Global CRF Reference Standards.

Cardiorespiratory fitness as a vital sign of CVD risk in the COVID-19 era

The severe health consequences of the corona virus disease 2019 (COVID-19) pandemic have been exacerbated by the prevalence of cardiovascular disease (CVD) risk factors, such as physical inactivity, obesity, hypertension, and diabetes. Further, policy decisions during the pandemic augmented unhealthy lifestyle behaviors and health inequalities, likely increasing the global disease burden. Cardiorespiratory fitness (CRF) is a well-established biomarker associated with CVD risk. Emerging data demonstrate that high CRF offers some protection against severe outcomes from COVID-19 infection, highlighting the importance of CRF for population health and the potential for limiting the severity of future pandemics. CRF is best assessed by cardiopulmonary exercise testing (CPET), which will be an important tool for understanding the prolonged pathophysiology of COVID-19, the emergence of long-COVID, and the lasting effects of COVID-19 on CVD risk. Utilization of CRF and CPET within clinical settings should become commonplace because of lessons learned from the COVID-19 pandemic.

Cardiorespiratory fitness estimations and their ability to predict all-cause mortality in patients with cardiovascular disease

Background

In cardiac rehabilitation programs, cardiorespiratory fitness is commonly estimated (eCRF) from the maximum workload achieved on a graded exercise test. This study compared four well-established eCRF equations in their ability to predict mortality in patients with cardiovascular disease (CVD).

Methods

A total of 7269 individuals with CVD were studied (81% male; age 59.4 ± 10.3yr). eCRF was calculated using equations from the American College of Sports Medicine, Bruce et al., the Fitness Registry and the Importance of Exercise International Database, and McConnell and Clark. The eCRF from each equation was compared with a RMANOVA. Cox proportional hazard models assessed the relationship between the eCRF equations and mortality risk. The predictive ability of the models was compared using the concordance index.

Results

There were 284 deaths (85% male) over a follow-up period of 5.8 ± 2.8yr. Although differences in eCRF were observed between each equation (P < 0.05), the eCRF from each of the four equations was predictive of mortality (P < 0.05). The concordance index values for each of the models were the same (0.77) indicating similar predictive performance.

Conclusions

The four well-established eCRF equations did not differ in their ability to predict mortality in patients with CVD, indicating any could be used for this purpose. However, the differences in eCRF from each of the equations suggest potential differences in their ability to guide clinical care and should be the focus of future research.