“…Briefly, Kaminky et al indicate the level of training, the method of testing (cycle ergometry, treadmill, rowing machine, etc. ), co-existing CVDs, and respiratory exchange ratio (RER) as factors influencing VO 2 [ 17 ]. Other contributors perhaps include the psychological attitude of the athlete to the effort (i.e.…”
In recent years, numerous prognostic models have been developed to predict VO2max. Nevertheless, their accuracy in endurance athletes (EA) stays mostly unvalidated. This study aimed to compare predicted VO2max (pVO2max) with directly measured VO2max by assessing the transferability of the currently available prediction models based on their R2, calibration-in-the-large, and calibration slope. 5,260 healthy adult EA underwent a maximal exertion cardiopulmonary exercise test (CPET) (84.76% male; age 34.6±9.5 yrs.; VO2max 52.97±7.39 mL·min-1·kg-1, BMI 23.59±2.73 kg·m-2). 13 models have been selected to establish pVO2max. Participants were classified into four endurance subgroups (high-, recreational-, low- trained, and “transition”) and four age subgroups (18–30, 31–45, 46–60, and ≥61 yrs.). Validation was performed according to TRIPOD guidelines. pVO2max was low-to-moderately associated with direct CPET measurements (p>0.05). Models with the highest accuracy were for males on a cycle ergometer (CE) (Kokkinos R2 = 0.64), females on CE (Kokkinos R2 = 0.65), males on a treadmill (TE) (Wasserman R2 = 0.26), females on TE (Wasserman R2 = 0.30). However, selected models underestimated pVO2max for younger and higher trained EA and overestimated for older and lower trained EA. All equations demonstrated merely moderate accuracy and should only be used as a supplemental method for physicians to estimate CRF in EA. It is necessary to derive new models on EA populations to include routinely in clinical practice and sports diagnostic.
“…Briefly, Kaminky et al indicate the level of training, the method of testing (cycle ergometry, treadmill, rowing machine, etc. ), co-existing CVDs, and respiratory exchange ratio (RER) as factors influencing VO 2 [ 17 ]. Other contributors perhaps include the psychological attitude of the athlete to the effort (i.e.…”
In recent years, numerous prognostic models have been developed to predict VO2max. Nevertheless, their accuracy in endurance athletes (EA) stays mostly unvalidated. This study aimed to compare predicted VO2max (pVO2max) with directly measured VO2max by assessing the transferability of the currently available prediction models based on their R2, calibration-in-the-large, and calibration slope. 5,260 healthy adult EA underwent a maximal exertion cardiopulmonary exercise test (CPET) (84.76% male; age 34.6±9.5 yrs.; VO2max 52.97±7.39 mL·min-1·kg-1, BMI 23.59±2.73 kg·m-2). 13 models have been selected to establish pVO2max. Participants were classified into four endurance subgroups (high-, recreational-, low- trained, and “transition”) and four age subgroups (18–30, 31–45, 46–60, and ≥61 yrs.). Validation was performed according to TRIPOD guidelines. pVO2max was low-to-moderately associated with direct CPET measurements (p>0.05). Models with the highest accuracy were for males on a cycle ergometer (CE) (Kokkinos R2 = 0.64), females on CE (Kokkinos R2 = 0.65), males on a treadmill (TE) (Wasserman R2 = 0.26), females on TE (Wasserman R2 = 0.30). However, selected models underestimated pVO2max for younger and higher trained EA and overestimated for older and lower trained EA. All equations demonstrated merely moderate accuracy and should only be used as a supplemental method for physicians to estimate CRF in EA. It is necessary to derive new models on EA populations to include routinely in clinical practice and sports diagnostic.
“…In humans, the basic metabolic cost of life measured as the resting metabolic rate (MR) is ∼1,500 kcal/day, which is generated from oxygen consumption at a rate of 3.5-3.8 mlO 2 /min/kg of body weight, equivalent to 1.34 watts/kg (Taivassalo et al 2003; Jeppesen et al 2009; Davies 1961). During maximal exercise (VO 2max ), humans on average achieve an MR of 43 mL O 2 /min/kg or 13.67 watts/kg (Kaminsky et al 2021), representing a ∼10-fold dynamic range at the whole-body level. The highest ever recorded VO 2max is 96 mL O 2 /min/kg or 32.50 watts/kg (Haugen et al 2018), corresponding to a dynamic range of >25-fold from rest.…”
Section: Resultsmentioning
confidence: 99%
“…Baseline whole body metabolic rates were obtained from indirect calorimetry in three small human cohorts reporting values consistent with literature norms (Taivassalo et al 2003; Jeppesen et al 2009; Rising et al 2003). Max whole body MR (i.e., VO 2 peak) estimates were obtained from Kaminsky et al (Kaminsky et al 2021). An estimation of skin-specific MR was calculated using Q O2 values for human in vivo tissues (see Table 4 in (Davies 1961).…”
The allometric theory of metabolism predicts that the rate of biological aging is proportional to an organism’s size and metabolic rate (MR). Here we test this hypothesis in humans by generating longitudinal, multi-modal signatures of aging in primary human fibroblasts. Relative to metabolic rates in the human body, isolated cells exhibit markedly elevated MR and operate closer to their maximal energy production capacity. Accordingly, per-cell division, isolated cells display accelerated telomere shortening and increased rate of DNA methylation aging. Moreover, despite a marked reduction in division rate towards the end of life, mass-specific MR increases exponentially, reflecting hypermetabolism. We develop a theoretical-mathematical model that accounts for a partitioning of energetic costs related to both growth or maintenance, quantifying the potential origins of hypermetabolism in vitro, and with advancing age. Moreover, we define genome-wide molecular rescaling factors that confirm and quantify the systematic acceleration of molecular aging kinetics in cultured fibroblasts, and use this approach to show how metabolic and pharmacological manipulations that increase or decrease MR predictably accelerate or decelerate the rates of biological aging. The interconnected speedup of energetic and molecular dynamics across the lifespan of human cells has important theoretical and clinical implications for aging biology.
“…Notable studies from several countries reporting directly measured VO 2peak by gas-analysis during maximal exercise is shown in Fig. 1 and Table 1 [ 8 , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] , [32] , [33] , [34] ], indicating more or less constant (linear) declines. The age-related declines are similar across both cycle ergometry and treadmill exercise, although values from treadmill exercise are generally higher [ 34 ].…”
Section: Age-related Declines In Cross-sectional Studiesmentioning
confidence: 99%
“…The age-related declines are similar across both cycle ergometry and treadmill exercise, although values from treadmill exercise are generally higher [ 34 ]. Although the baseline fitness level decreases with higher age, meaning that percentage decline increases, most studies still have reported declines of 10–15% in older age-groups as well [ 8 , 15 , 16 , 21 , [23] , [24] , [25] , 32 , 33 ]. Fig.…”
Section: Age-related Declines In Cross-sectional Studiesmentioning
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