Cardiopulmonary Exercise Testing in Health and Heart Failure – Improving Established Methods and Exploring New Frontiers to Evaluate Physical Fitness Status for Risk Stratification

Background
Aging and the changing age demographics potentially represent one of the most critical problems of our time. The shift of the major causes of morbidity towards chronic disease, coupled with changing age demographics, is likely to lead to an epidemic of age-driven chronic disease. Cardiovascular diseases (CVD), which include heart failure (HF), are the leading cause of death worldwide. The prevalence of HF continues to rise over time in sync with the aging population. HF has been defined as a global pandemic, based on the large number of people affected by the syndrome worldwide. Physiological functions decline with age, and these declines often end in a systemic process that contributes to numerous physiological impairments and disease. The ability to perform physical tasks is critical for maintaining overall functional capacity, and physical fitness parameters are biomarkers of health among older adults, predicting quality of life, disability, and mortality. Links between CVD risk factors and limitations in physical fitness have been widely described. Physical fitness markers include measurements of endurance capacity, muscle strength, and neuromuscular coordination. Cardiorespiratory fitness (CRF) and other markers measured by cardiopulmonary exercise testing (CPET) have been described to be highly useful health markers, and VO2peak is even suggested for use as a vital sign in clinical evaluation. Some limitations, however, likely hinder a wider application of CPET including: 1) the evaluation of whether the true individual physiological limit is reached and VO2peak can be determined, 2) the lack of accurate and suitable normative reference values of healthy individuals across the lifespan, 3) submaximal CPET parameters as an alternative in the case VO2peak was not reached. Further, additional physical fitness measurements and their combination to a composite outcome could provide a useful tool for the management of age-related chronic disease such as HF. To date, however, no attempts to combine biomarkers of several physical fitness domains have been performed.
Aims
The aims of this Ph.D. project were: (1) To review the current evidence of CPET variables for the purpose of risk stratification and management of heart failure with reduced ejection fraction (HFrEF); (2) To design and conduct a study involving a comprehensive assessment of physical fitness components and cardiovascular (CV) function to identify which markers are most highly associated with CV risk with increasing age and which markers are most impaired in HF; (3) To determine data-based and age-dependent cutoffs for maximal exercise criteria for a general population which is free of exercise-limiting chronic conditions; (4) To provide reference values for maximal and submaximal CPET parameters across the adult age spectrum of a healthy European cohort and to analyze the associations between physical activity (PA) levels and CPET parameters; (5) To determine whether VO2-kinetics is a useful marker for risk stratification of HF; and finally (6) to analyze whether a composite measure (health distance, HD) of physical fitness biomarkers can increase discriminative performance between healthy individuals and patients with HF compared to standard clinical biomarkers.
Methods
In this Ph.D. project, a literature review (publication 1) and one large project including two cross-sectional studies (publication 2-6) were conducted. In the literature review, five widely studied gas exchange variables from CPET (VO2peak, VE/VCO2 slope, exercise oscillatory ventilation (EOV), oxygen uptake efficiency slope (OUES) and PETCO2) were evaluated regarding risk stratification and management of HFrEF based on nine different criteria (proof of concept, prospective validation, incremental value, clinical utility, clinical outcomes, cost-effectiveness, ease of use, methodological consensus and reference values). The literature search was performed for each of the five variables and the nine criteria separately, beginning with a search for systematic reviews using the Cochrane Library. Subsequently, simple search strings were used for electronic literature searches in the Medline and Embase databases.
The COmPLETE Project, the project of this Ph.D. Thesis, consists of two parts: COmPLETE-Health and COmPLETE-Heart (study protocol, publication 2). COmPLETE-Health examined physical fitness and CV markers in a healthy population aged between 20 and 90 years. A total number of approximately 490 participants with a valid cardiorespiratory fitness measurement (the primary outcome) were included. Participants were equally distributed over the 7 age decades from 20–30 to 80–90 and by sex (50% female). COmPLETE-Heart examined the same physical fitness and CV markers as COmPLETE-Health in 80 patients at different stages of chronic HF. CRF was assessed by CPET. Secondary outcomes included walking speed, balance, isometric strength, peak power, and handgrip strength. PA as a behavioral component was assessed objectively via accelerometry, and several CV assessments were performed.
For publication 3, CPET data from the COmPLETE-Health Study were analyzed involving 274 men and 252 women. All participants underwent a CPET until maximal voluntary exertion using a cycle ergometer. To determine new exhaustion criteria, based on maximal respiratory exchange ratio (RERmax) and age-predicted maximal heart rate (APMHR), one-sided lower tolerance intervals for the tests confirming VO2 plateau status were calculated using a confidence level of 95% and a coverage of 90%.
In publication 4, CPET data of the COmPLETE-Health Study were further analyzed. Participant included in the final analysis, had to have reached secondary exhaustion criteria based on age-dependent RER cut-offs during the CPET. PA was objectively and continuously measured over 14 days using a triaxial accelerometer. Quantile curves were calculated for CPET parameters to provide reference data. To investigate the associations between CPET parameters and PA levels, linear regression analysis was performed.
In publication 5, the CPET data of both the healthy participants of the COmPLETE-Health Study and the patients with HF of the COmPLETE-Heart Study were analyzed. To achieve comparability, we first created a matched dataset where we matched two healthy participants to every patient with HF according to age and sex (2:1 matching). The CPET was preceded by a 3-minute low-intensity warm-up and followed by a 3-minute recovery bout. VO2-kinetics was calculated from the rest-to-exercise transition of the warm-up bout (on-kinetics), from the exercise-to-recovery transition following ramp test termination (off-kinetics), and from the initial delay of VO2 during the warm-up to ramp-test transition (ramp-kinetics).
As in publication 5, both groups—COmPLETE-Health and COmPLETE-Heart—were analyzed in publication 6. Fifty-nine biomarkers in the categories fitness (cardiovascular endurance, muscle strength, and neuromuscular coordination) and general health (anthropometry, vascular and respiratory health and blood testing) were used for the analysis. HDs were computed for all relevant biomarkers and domain-specific subsets as the Mahalanobis distance defined for vectors of biomarker measurements that quantified the deviations of individuals’ biomarker profiles from “optimal” values in the “reference population” (healthy study participants aged less than 40 years). Linear regressions were fitted with HD outcomes and disease status (HF/Healthy) and relevant covariates as predictors. Also were logistic regressions fitted for the disease status as the outcome and sex, age, and age2 as covariates in the base model and the same covariates plus combinations of one or two HDs to compare different models’ performance in predicting HF cases.
Results
Publication 1: The Role of Gas Exchange Variables in Cardiopulmonary Exercise Testing for Risk Stratification and Management of Heart Failure with Reduced Ejection Fraction (1).
This review demonstrated that the evidence supporting the clinical assessment of variables beyond peak VO2 for HF patients with reduced ejection fraction is well established. The five variables: peak VO2 or predicted peak VO2, VE/VCO2 slope, EOV, OUES, and PETCO2 provide evidence for the criteria “proof of concept”, “prospective validation”, and “incremental value”. Based on the results of this review, the combined assessment of peak VO2 or predicted peak VO2, VE/VCO2 slope, and EOV is recommended as part of the clinical examination. Further, because no additional costs are incurred in investigating the OUES and PETCO2, these parameters should also be considered as part of routine analysis. Each of those five variables reflects in part a different pathophysiologic feature of HFrEF, and combining these variables delivers a broader three-dimensional picture of the pathophysiologic process and severity of HFrEF. A multi-variable approach is, therefore, appropriate.
Publication 2: Functional Aging in Health and Heart Failure: the COmPLETE Study (2).
The COmPLETE study will allow for the investigation and characterization of the physical fitness components of endurance capacity, muscle strength, and neuromuscular coordination in individuals aged 20 to 90 years without chronic diseases and in patients with HF. The age-matched comparison with patients at different stages of HF may provide an estimate of the health distance of different fitness parameters to healthy individuals. Health distance provides a new complex measure of aging-related decline in the adaptive capacity of the organism by comparing the values of the physiological “norms” (COmPLETE-Health) with those with prevalent HF (our example). The study’s results shall provide a better understanding of which functional characteristics should specifically be targeted in primary and secondary prevention to achieve optimal healthspan.
Publication 3: New Data-based Cutoffs for Maximal Exercise Criteria Across the Lifespan (3).
The analysis of 526 participants aged 20–90 years revealed data-based optimal secondary exhaustion criteria according to tolerance intervals optimizing the evaluation of VO2max. These criteria are for the age group of 20 to 39 years: RERmax ≥ 1.13, APMHR210 ≥ 96%, and APMHR208 93%; for the age group of 40 to 59 years: RERmax ≥ 1.10, APMHR210 ≥ 99%, and APMHR208 92%; and, for the age group of 60 to 69 years: RERmax ≥ 1.06, APMHR210 ≥ 99%, and APMHR208 89%. The proposed cut-off values for secondary criteria reduce the risk of underestimating VO2max. The criteria differ clearly from previously used lower cut-offs and our results show that higher criteria need to be applied. Lower criteria than the ones we suggest would increase false-positive results, assuming participants are exhausted although, in fact, they are not.
Publication 4: Novel CPET Reference Values in Healthy Adults: Associations with Physical Activity (4).
VO2peak values observed in the group aged 20–29 years were 46.6 ± 7.9 and 39.3 ± 6.5 (mL/kg/min) for males and females, respectively. On average, each age category (10-year increments) showed a 10% lower VO2peak relative to the next younger age category. VO2peak values of previous studies were, on average 7.5 (mL/kg/min) (20%) lower for males and 6.5 (mL/kg/min) (21%) lower for females. There was strong evidence supporting a positive association between VO2peak (mL/kg/min) and the level of habitual PA performed at vigorous PA (estimate 0.26; p < 0.001].
Publication 5: VO2 Kinetics: An Alternative to Peak VO2 for Risk Stratification and Diagnosis in Heart Failure (5).
VO2 off-kinetics demonstrated the highest z-score differences between healthy participants and patients with HF. Furthermore, off-kinetics were strongly associated with VO2peak. In contrast, ramp-kinetics and on-kinetics showed only minimal z-score differences between healthy participants and patients with HF. The best on- and off-kinetic parameters significantly improved a model to predict disease severity. However, there was no significant additional value of VO2-kinetics when VO2peak was part of the model.
Publication 6: Composite Measures of Physical Fitness to Discriminate between Healthy Aging and Heart Failure: the COmPLETE Study (6).
Nine out of ten calculated HDs showed evidence of group differences between the Healthy and the HF group (p ≤ 0.002), and most models presented a negative estimate of the interaction term age by group (p < 0.05 for eight out of ten HDs). The predictive performance of HF cases of the base model significantly increased by adding HD General health or HD Fitness with an increase in the AUC estimate from 0.63 to 0.89 and 0.84, respectively. HD Cardiovascular endurance alone reached an AUC of 0.88. Further, there is evidence that the combination of HD Cardiovascular endurance and HD General health shows superior predictive power compared to when using HDs alone.
Conclusions
The results of this thesis provide further knowledge and advances in the assessment of physical fitness, particularly CPET markers for risk stratification and management of chronic diseases such as HF. According to our literature review: a multi-parameter approach including VO2peak, VE/VCO2 slope, and EOV is recommended when assessing HF patients with reduced ejection fraction by CPET. The application of the provided age-dependent exhaustion criteria reduces the risk of underestimating VO2peak and provides a simple, yet effective tool. Further, reference values for maximal and several submaximal CPET parameters over a large age range are novel and differences to other studies are clinically highly relevant. Vigorous-intensity PA showed a strong positive association with higher VO2peak and other performance-related CPET parameters within the healthy cohort. Further, VO2-kinetics can provide an acceptable substitute if VO2peak cannot be determined. VO2 off-kinetics appears to be superior for distinguishing patients with HF and healthy participants compared to VO2 on-kinetics and ramp-kinetics. Finally, when combining several physical fitness biomarkers, a significant difference in HD between healthy individuals and patients with HF can be observed. The application of HD could strengthen a comprehensive assessment of physical fitness and may present an optimal target for interventions to slow the decline of physical fitness with aging and, therefore, to increase healthspan.