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These cross-sectional results suggest that low CRF is associated with an increased clustering of the metabolic abnormalities associated with the MS in both adult men and women and support the need for future prospective analyses.

Background: The relationship between cardiorespiratory fitness (CRF) and mortality risk has typically been assessed using a single measurement, though some evidence suggests the change in CRF over time influences risk. This evidence is predominantly based on studies using estimated CRF (CRF e). The strength of this relationship using change in directly measured CRF over time in apparently healthy men and women is not well understood. Purpose: To examine the association of change in CRF over time, measured using cardiopulmonary exercise testing (CPX), with all-cause and disease-specific mortality and to compare baseline and subsequent CRF measurements as predictors of all-cause mortality. Methods: Participants included 833 apparently healthy men and women (42.9 ± 10.8 years) who underwent two maximal CPXs, the second CPX being ≥ 1 year following the baseline assessment (mean 8.6 years, range 1.0 to 40.3 years). Participants were followed for up to 17.7 (SD 11.8) years for all-cause-, cardiovascular disease-(CVD), and cancer mortality. Cox-proportional hazard models were performed to determine the association between the change in CRF, computed as visit 1 (CPX1) peak oxygen consumption (VO 2peak [mL•kg-1• min-1 ])visit 2 (CPX2) VO 2peak , and mortality outcomes. A Wald-Chi square test of equality was used to compare the strength of CPX1 to CPX2 VO 2peak in predicting mortality. Results: During follow-up, 172 participants died. Overall, the change in CPX-CRF was inversely related to all-cause, CVD, and cancer mortality (p<0.05). Each 1 mL•kg-1• min-1 increase was associated with a ~ 11, 15, and 16% (all p<0.001) reduction in allcause, CVD, and cancer mortality, respectively. The inverse relationship between CRF and allcause mortality was significant (p<0.05) when men and women were examined independently, after adjusting for years since first CPX, baseline VO 2peak , and age. Further, the Wald Chi-square test of equality found CPX2 VO 2peak to be a significantly stronger predictor of all-cause mortality than CPX1 VO 2peak (p<0.05). Conclusion: The change in CRF over time was inversely related to

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Peak oxygen uptake values can be predicted with reasonable accuracy from the BSU/Bruce Ramp protocol. The BSU/Bruce Ramp would be an excellent choice for laboratories desiring to use a ramp treadmill protocol because of the design of the protocol with identical workloads at equivalent time periods (3, 6, 9, 12, 15, 18, 21 minutes) as the commonly used Bruce protocol.

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Aims A recent scientific statement suggests clinicians should routinely assess cardiorespiratory fitness using at least non-exercise prediction equations. However, no study has comprehensively compared the many non-exercise cardiorespiratory fitness prediction equations to directly-measured cardiorespiratory fitness using data from a single cohort. Our purpose was to compare the accuracy of non-exercise prediction equations to directly-measured cardiorespiratory fitness and evaluate their ability to classify an individual's cardiorespiratory fitness. Methods The sample included 2529 tests from apparently healthy adults (42% female, aged 45.4 ± 13.1 years (mean±standard deviation). Estimated cardiorespiratory fitness from 28 distinct non-exercise prediction equations was compared with directly-measured cardiorespiratory fitness, determined from a cardiopulmonary exercise test. Analysis included the Benjamini–Hochberg procedure to compare estimated cardiorespiratory fitness with directly-measured cardiorespiratory fitness, Pearson product moment correlations, standard error of estimate values, and the percentage of participants correctly placed into three fitness categories. Results All of the estimated cardiorespiratory fitness values from the equations were correlated to directly measured cardiorespiratory fitness ( p < 0.001) although the R2 values ranged from 0.25–0.70 and the estimated cardiorespiratory fitness values from 27 out of 28 equations were statistically different compared with directly-measured cardiorespiratory fitness. The range of standard error of estimate values was 4.1–6.2 ml·kg−1·min−1. On average, only 52% of participants were correctly classified into the three fitness categories when using estimated cardiorespiratory fitness. Conclusion Differences exist between non-exercise prediction equations, which influences the accuracy of estimated cardiorespiratory fitness. The present analysis can assist researchers and clinicians with choosing a non-exercise prediction equation appropriate for epidemiological or population research. However, the error and misclassification associated with estimated cardiorespiratory fitness suggests future research is needed on the clinical utility of estimated cardiorespiratory fitness.

These results challenge the applicability of the generalized RPE recommendations described in recent exercise guidelines under typical clinical exercise testing conditions. The basis for the generalized RPE recommendations warrant further investigation. Those who desire to use RPE as a marker of relative exercise intensity during SSLMGXT should take into consideration the large interindividual variability in these measures.