UNIVERSITY OF CALGARY. Determining the Maximal Physiological Steady State in Cycling with Precision: Critical Power

Transcription

1 UNIVERSITY OF CALGARY Determining the Maximal Physiological Steady State in Cycling with Precision: Critical Power Estimations or Self-selected Exercise Intensity? by Felipe Mattioni Maturana A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE GRADUATE PROGRAM IN KINESIOLOGY CALGARY, ALBERTA AUGUST, 2016 Felipe Mattioni Maturana 2016

2 Abstract Giving the inherent limitations of critical power (CP) testing and the demanding maximal lactate steady state (MLSS) protocol, this thesis aimed: i) to compare the power outputs (POs) derived from two methods of estimating CP (i.e., the power-time relationship (CPHYP) and the 3-minute all-out test (CP3MIN)) and the determined MLSS; and ii) to test cyclists ability to predict their highest sustainable PO (CPSELF). Thirteen healthy young participants (26±3 yr; 69.0±9.2 kg; 174±10 cm; 60.4±5.9 ml kg -1 min-1 ) were tested. PO at MLSS was lower than CPHYP and CP3MIN (p<0.05). PO at CPSELF was similar (p>0.05) to MLSS. The mean difference between the measures of MLSS and CPSELF was zero, and both methods presented similar (p>0.05) metabolic responses. The disagreement between CPHYP and CP3MIN with the PO at MLSS questions the ability of CP to estimate the maximal steady state, while CPSELF may offer an alternative approach to predict it with more precision. ii

3 Preface The present thesis is based on a collection of two scientific manuscripts, as follows: Chapter 2: Mattioni Maturana F, Keir DA, McLay KM, Murias JM. Can measures of critical power precisely estimate the maximal metabolic steady state? Accepted Applied Physiology, Nutrition and Metabolism. Chapter 3: Mattioni Maturana F, Keir DA, McLay KM, Murias JM. Critical power testing or self-selected cycling: Which one is the best predictor of maximal metabolic steady-state? Under review Journal of Science and Medicine in Sport. iii

4 Acknowledgements I would like to express my deep gratitude to the following individuals: Dr. Juan Murias and Dr. Guillaume Millet for believing in my potential and giving me the opportunity to pursue my dream as a MSc student; for the open doors policy, which did not matter how busy their schedule was, they always had time for both a professional and personal talk; and for all the guidance and knowledge provided throughout these two years. Dr. Brian MacIntosh, Dr. Donald Paterson, and Dr. Louis Passfield for being in my Examining Committee. Kaitlin McLay, John Temesi, and Jessica O Connell for their technical help with the laboratory equipment. Daniel Keir for all the support with project design, data analysis and manuscript writing. Dr. Cleiton Bona, Dr. Cesar Martins, and Dr. Heiliane Fontana for all their help and motivation to pursue the dream of coming to Canada when I was still an undergraduate student. All the visiting students in the Human Performance Laboratory for making this period the most amazing time of my life so far. Rafael Fortuna for being such a good friend and making me go through all the difficulties that come along with this process. Thanks for helping me when I first started teaching in KNES 373 and for taking me to the Rocky Mountains on every single weekend in the summer. All my brave subjects, especially the Master of Kinesiology (MKin) students that kindly agreed to participate in this project. My family who was always there for me. My mother Sonia, my father Osorio, my brother Diego, and my angel Elaine. Thank you for everything. iv

5 Dedication I dedicate this thesis to my parents. This dream would not have become true without their support. I love you. v

6 Table of Contents Abstract... ii Preface... iii Acknowledgements... iv Dedication...v Table of Contents... vi List of Figures and Illustrations... viii List of Symbols, Abbreviations and Nomenclature... ix Epigraph...x CHAPTER Exercise Intensity Thresholds...1 Exercise Intensity Domains...3 Practical Application of Exercise Intensity Thresholds...6 Maximal Lactate Steady State...8 Critical Power minute all-out test for estimation of CP...14 Self-selected exercise intensity...17 Purpose...19 Author and co-authors contributions...19 CHAPTER Can measures of critical power precisely estimate the maximal metabolic steady state?20 Abstract...21 Introduction...22 Methods...24 Exercise Protocols...25 Equipment and Measurements...27 Data Analyses...27 Statistical Analyses...28 Results...29 Discussion...30 References...35 CHAPTER Critical power testing or self-selected cycling: Which one is the best predictor of maximal metabolic steady-state?...46 Abstract...47 Introduction...48 Methods...50 Exercise Protocols...51 Equipment and Measurements...53 Data Analyses...53 Statistical Analyses...54 Results...55 Discussion...56 vi

7 References...60 CHAPTER Conclusions...67 Limitations...68 Future directions...69 BIBLIOGRAPHY...71 APPENDICES...81 Appendix A: Letter of Consent...81 Appendix B: Recruitment Poster...91 vii

8 List of Figures and Illustrations Figure 1. V O2 response following the onset of moderate (below the gas exchange threshold), heavy (between gas exchange threshold and critical power), and severe (above critical power) (from Poole and Jones (2012)) Figure 2. Relationship between [La] and exercise intensity (as a percentage of V O2max), and the respective exercise intensity domain markers (from Binder et al. (2008)) Figure 3. Schematic of the step increase (left) and the ramp incremental (right) protocols (adapted from Keir et al. (2016)) Figure 4. The effect of endurance training on the [La] curve. The arrows are representing the demarcation of the aerobic threshold before (white circles) and after training (black circles) (adapted from Jones and Carter (2000a)) Figure 5. [La] measures over the course of a 30-minute ride for three different POs relative to MLSS: below MLSS (diamonds), at MLSS (squares), and above MLSS (triangles) (from Svedahl and MacIntosh (2003)) Figure 6. Representation of the CP measurement for three different muscle groups at four different intensities. The upper panel shows the three tests performed to exhaustion (A, B, and C) for one muscle group. The left lower panel, displays the relationship between A, B, and C defined by the linear equation of CP. On the lower right, the representation of the CP for the three muscle groups is presented (from Monod and Scherrer (1965)) Figure 7. Relationship between the imposed PO and tlim (hyperbolic equation; upper panel), and between the Wlim and tlim (linear equation; lower panel) from the same experimental data (from Moritani et al. (1981)) Figure 8. The PO profile throughout a 3-minute all-out test in a representative participant (from Vanhatalo et al. (2007)) viii

9 List of Symbols, Abbreviations and Nomenclature Symbol Definition V O2max Maximal oxygen uptake PO Power output [La] Blood lactate concentration O2 Oxygen V E Ventilation CO2 Carbon dioxide H + Hydrogen ions V CO2 Carbon dioxide production MLSS Maximal lactate steady state CP Critical power W Anaerobic work capacity [La] Difference in blood lactate concentration Wlim Work limit tlim Time limit GET RPE PCr RCP TTE CPHYP CP3MIN CPSELF 50 V E/V CO2 WEP ANOVA LOA CoV SEE RI Gas exchange threshold Rating of perceived exertion Phosphocreatine Respiratory compensation point Time-to-exhaustion CP 2-parameter hyperbolic model CP 3-minute all-out test CP self-selected exercise intensity 50% of difference between V O2max and GET Ventilatory equivalent for V CO2 Integral of the area under the curve Analysis of variance Limits of agreement Coefficient of variation Standard error of the estimation Ramp incremental ix

10 Epigraph Love all, trust a few, do wrong to none. -William Shakespeare x

11 CHAPTER 1 After the seminal work of Hill and Lupton (1923), the concept of maximal oxygen uptake (V O2max) has been widely used as a tool for evaluation of maximal aerobic capacity, as well as a determinant of performance in endurance events. However, how can the final outcome be predicted in a competition among elite athletes with similar V O2max values? Under these circumstances, the concept of V O2max becomes less relevant to differentiate the final result of a competition as, even though a high V O2max is a prerequisite for success in aerobic events, other factors will ultimately determine the winner of an endurance contest. Importantly, this concept would apply not only to elite endurance athletes, but also to any group in which individuals have a relatively similar V O2max. Therefore, when evaluating homogeneous groups, it is crucial to consider other factors such as the energy cost of exercise and the highest percentage of V O2max that an athlete can sustain for a prolonged period of time (Di Prampero et al. 1986; Di Prampero et al. 1993). The latter, is commonly defined as endurance performance (Léger et al. 1986; Péronnet et al. 1987; Tokmakidis et al. 1987). Throughout the years, the so-called anaerobic threshold (defined as the respiratory compensation point) has become the most acceptable method for assessing endurance performance (Costill et al. 1972; Sjodin and Svedenhag 1985; Joyner 1991); however, there are numerous concepts associated to exercise intensity thresholds in the literature, and their nomenclature and methods of measurement often generate disagreements and confusion among researchers and coaches. Exercise Intensity Thresholds Gradually, the concept of exercise intensity thresholds has become an important component of endurance performance, and correct determination of these thresholds plays an 1

12 important role in the outcome of exercise training interventions (Ribeiro et al. 1986; Svedahl and MacIntosh 2003; Binder et al. 2008; Faude et al. 2009). The phenomenon of thresholds is defined and identified by physiological alterations within the body, such as metabolic and ventilatory responses to the exercise intensity exerted (e.g., speed or power output (PO)). In general terms, despite the different terminology often found in the literature, two main exercise intensity thresholds are commonly described: i) the aerobic; and ii) the anaerobic threshold. Although different approaches have been used to determine these thresholds, blood as well as ventilatory/gas exchange responses to exercise are most commonly used to identify their boundaries. When using blood markers, the aerobic threshold is characterized by a systemic increase in blood lactate concentration ([La]) above resting levels. When estimations are made based on gas exchange and ventilatory parameters, the aerobic threshold is associated to a systemic increase in end tidal O2 in relation to V O2. The first breakpoint in minute ventilation (V E) in relation to V O2 is often used as a confirmatory response to the aerobic threshold (i.e., the V O2 associated to the first breakpoint in V E should match to the V O2 associated to the systemic increase in end tidal O2). The anaerobic threshold is characterized by the exercise intensity at which [La] production rate exceeds elimination rate, thus resulting in an exponential increase in [La]. When using gas exchange and ventilatory indicators, this threshold is identified as a systemic decrease in end tidal CO2 caused by the hyperventilatory response due to the increase in H +. The second breakpoint in the V E-to- V O2 relation is used here as a confirmatory response to the anaerobic threshold (i.e., the V O2 associated to the second breakpoint in V E should match to the V O2 associated to the systemic decrease in end tidal CO2) (Wasserman et al. 1973; Beaver et al. 1986). 2

13 Exercise Intensity Domains From a physiological perspective, exercise intensity thresholds demarcate the boundaries between different exercise intensity domains. Similar to the concepts of exercise intensity thresholds, the nomenclature for these exercise intensities domains is also somewhat confusing as the terminological differences exist within the literature, as noted in Figure 1 and 2. For the purpose of this thesis, the exercise intensity domains and their associations with exercise intensity thresholds will be based on the denomination of moderate, heavy, and very heavy intensity of exercise, as previously described (Whipp et al. 2005). Figure 1. V O2 response following the onset of moderate (below the gas exchange threshold), heavy (between gas exchange threshold and critical power), and severe (above critical power) (from Poole and Jones (2012)). 3

14 Continuous exercise performed within the moderate intensity domain is characterized by a stable [La] that is similar to that of resting levels, as well as stable V O2 response. Its upper boundary is defined as the aerobic threshold (Wasserman et al. 1973). When continuous exercise is performed within the heavy intensity domain, the [La] and V O2 increase beyond what they would be expected to be in the moderate intensity domain, but they eventually stabilize. At this point, an accumulation of H + related to the greater metabolic demand from the higher intensity of exercise leads to an increase in the carbon dioxide production (V CO2), which results in a steeper increase in V E, while the end tidal pressure of CO2 remains stable (isocapnic buffering). Figure 2. Relationship between [La] and exercise intensity (as a percentage of V O2max), and the respective exercise intensity domain markers (from Binder et al. (2008)). The upper boundary of the heavy intensity domain, defined as the anaerobic threshold, is the highest exercise intensity at which [La] production and removal are in equilibrium. This intensity 4

15 of exercise is linked to the concept of maximal lactate steady state (MLSS), considered by some authors as the gold standard for the anaerobic threshold determination (Brooks 1985; Aunola and Rusko 1992; Wonisch et al. 2002). The intensity of exercise within the very heavy intensity domain is, therefore, theoretically characterized by a systemic increase in [La] and V O2 until volitional fatigue ensues and/or its upper boundary is reached, (i.e., the V O2max). The determination of exercise intensity thresholds (i.e. the upper boundaries of exercise intensity domains) as well as of V O2max is commonly estimated performing an incremental exercise test to exhaustion, which can be generally divided into two categories: ramp incremental (RI) and step increase test (Figure 3). Figure 3. Schematic of the step increase (left) and the ramp incremental (right) protocols (adapted from Keir et al. (2016)). During cycling exercise, for example, a RI test consists of an initial exercise intensity (i.e., PO), followed by a continuous and linear increase in PO (e.g., 1 W every 2 seconds for a 30 W min -1 increase in PO) until volitional fatigue ensues. The step increase protocol consists of cycling at an 5

16 exercise intensity for a predetermined period of time that, at lower POs, allows V O2 and [La] to be stabilized to a new steady state (preceded by a mono-exponential increase). This is followed by subsequent step increases (which at high enough POs will result in V O2 and [La] not being able to stabilize anymore) until volitional fatigue occurs (Freund et al. 1986). Practical Application of Exercise Intensity Thresholds Once determined, exercise intensity thresholds are often expressed as a percentage of V O2max (%V O2max), especially when the goal is to give an indicator of endurance, instead of an absolute PO, for example. (Kumagai et al. 1982; Palgi et al. 1984). From a practical perspective, exercise training interventions should be prescribed based on anaerobic threshold rather than V O2max, assuring more effectiveness on the outcome. This will induce a right-shift in the [La] curve (i.e., the [La] curve represents the threshold demarcation during incremental/endurance exercise (Figure 4)) that leads to a higher anaerobic threshold and/or higher V O2max (Sady et al. 1980; Ready and Quinney 1981; Yoshida et al. 1982). For example, training at the same %V O2max (e.g., 80% of V O2max) for two different individuals might result in one training within the heavy intensity domain (e.g., trained athlete with an anaerobic threshold of 90% of V O2max) whereas for another individual might result in training within the very heavy intensity domain (e.g., college student with an anaerobic threshold of 75% of V O2max) (Poole and Gaesser 1985; Acevedo and Goldfarb 1989). Additionally, another factor to consider for prescribing exercise training intensities based on the anaerobic threshold is the training status of the individual. For example, whereas for sedentary individuals wishing to improve their overall aerobic performance for improving fitness and health, training at an exercise intensity near the anaerobic threshold might suffice, but this might not be the case for trained athletes, who might require training stimuli that more precisely target a 6

17 combination of near and above anaerobic threshold exercise intensities in order to improve their performance (Londeree 1997). Under such circumstances, precise determination of the intensity of exercise that demarcates the boundary between the heavy and the very heavy domains is relevant. Figure 4. The effect of endurance training on the [La] curve. The arrows are representing the demarcation of the aerobic threshold before (white circles) and after training (black circles) (adapted from Jones and Carter (2000a)). Based on the above mentioned information, identifying the exercise intensity that corresponds to the upper boundary of the heavy intensity domain (i.e., anaerobic threshold) plays an important role in the outcome of training interventions in competitive sports. As described by Svedahl and MacIntosh (2003), the determination of the anaerobic threshold is a topic that has generated ample debate. Among the methods that exist for determination of a PO that represents the upper boundary of the heavy intensity domain, the maximal lactate steady state 7

18 (MLSS) (Tegtbur et al. 1993) and critical power (CP) (Moritani et al. 1981) have gained notoriety in the past 50 years. Maximal Lactate Steady State As described by Skinner and McLellan (1980), the anaerobic threshold represents an exercise intensity (e.g., PO) or V O2 at which changes in ventilatory/gas exchange responses are observed due to metabolic acidosis within the active muscles. Beyond this PO, physiological parameters, such as [La] and V O2, cannot longer be stabilized. The determination of this PO is well described by the MLSS, which represents the highest exercise intensity of stable [La]. In other words, it is the upper boundary of the equilibrium between production and removal of blood lactate. Thus, the limit of tolerance (i.e., time-to-exhaustion) of exercise intensities at and below MLSS is relatively long (i.e., between ~ 30 and 60 minutes for intensities at MLSS (Fontana et al. 2009; Grossl et al. 2012)). On the contrary, the time-to-exhaustion above MLSS is going to be dependent on the individual ability to perform work within the very heavy intensity domain (i.e., anaerobic work capacity (W ). Although a [La] threshold of 4.0 mmol L -1 has been proposed as a fixed value that corresponds to the anaerobic threshold for every individual (Heck et al. 1985), it has been described that [La] can have a great variability among athletes, independently of training status (ranging from 2.0 to 8.0 mmol L -1 ) (Beneke et al. 2000). As early described by Margaria et al. (1964) and Saiki et al. (1967), the MLSS is determined by a series of 5-8 constant-load rides, of up to 30 minutes of duration, on separate days (Londeree and Ames 1975; Scheen et al. 1981; Hurley et al. 1984; Urhausen et al. 1993). The [La] is measured every 5 minutes, and the difference in [La] ( [La]) during the last 20 minutes is considered for determination of MLSS (Figure 5). 8

19 Figure 5. [La] measures over the course of a 30-minute ride for three different POs relative to MLSS: below MLSS (diamonds), at MLSS (squares), and above MLSS (triangles) (from Svedahl and MacIntosh (2003)). The criterion for the determination of MLSS still remains a topic of debate, with the [La] ranging from 0.2 to 1.0 mmol L -1 often accepted as the upper limit for acceptance of an stabilized (steadystate) [La] response (Heck et al. 1985; Haverty et al. 1988; Beneke 2003). Despite the different views on this topic, the most commonly used criterion is the [La] of 1.0 mmol L -1 (Heck et al. 1985; Snyder et al. 1994; Harnish et al. 1999; Dekerle et al. 2003; Fontana et al. 2009; Keir et al. 2015). Since the MLSS is determined through a series of 30-minute constant-load rides, the [La] response is known over the course of this period; however, little is known about the limit of tolerance (i.e., time-to-exhaustion) along with other physiological measures (e.g., V O2) at this exercise intensity. In a study including fourteen male cyclists, Grossl et al. (2012) showed that the time-to-exhaustion at MLSS was 54.7 ± 10.9 min, with a mean [La] at the time that volitional fatigue of 4.1 ± 0.9 mmol L -1 and no significant changes in V O2 over the course of the ride. In 9

20 contrast, in a study with moderately trained men, the time-to-exhaustion at MLSS was 37.7 ± 8.9 min (Fontana et al. 2009). These data indicate a certain level of uncertainty in relation to the limit of tolerance during rides at an exercise intensity corresponding to the upper boundary of the heavy intensity domain. Critical Power The concept of CP was first introduced by Monod and Scherrer (1965) as the maximal intensity of a muscle, or muscle group, to perform work for prolonged periods without fatigue (although it is now known that fatigue is present in sub-maximal exercise intensities, especially the one corresponding to CP, this was the concept description presented by the authors). As described by the authors, the CP of a muscle is measured by doing a series of muscular work tests at different intensities, so that the intensity remains constant for each test, and it is high enough to lead to muscular exhaustion. From these series of tests, the linear relationship of the work (in joules) against the time-to-exhaustion performed in each test was plotted and defined by the authors as work limit (Wlim) and time limit (tlim), respectively. The linear equation for determination of CP, is defined as follows: Wlim = a + b tlim where Wlim, in joules, represents the work limit; a is the y-intercept, also a measure of the anaerobic work capacity (i.e., W ); b is the slope, representing the CP; and tlim, in seconds, represents the time limit (abscissa). This linear relationship is represented on Figure 6 for three different muscle groups. Moreover, Monod and Scherrer (1965) described that when the intensity applied is less than or equal to CP, exhaustion cannot occur, which leads to the traditional definition of CP: the maximal exercise intensity that can be performed indefinitely. 10

21 Figure 6. Representation of the CP measurement for three different muscle groups at four different intensities. The upper panel shows the three tests performed to exhaustion (A, B, and C) for one muscle group. The left lower panel, displays the relationship between A, B, and C defined by the linear equation of CP. On the lower right, the representation of the CP for the three muscle groups is presented (from Monod and Scherrer (1965)). Followed by the concept of CP of a single muscle, Moritani et al. (1981) introduced CP into cycling, an exercise modality involving a large body mass. The authors successfully attempted to correlate the PO and the V O2 associated to the anaerobic threshold obtained from a RI test, to the PO and V O2 associated to the estimated CP. A high positive correlation was found for both PO (r = 0.907, p < 0.01) and V O2 (r = 0.927, p < 0.01). Despite the exciting results, some limitations of this approach should be highlighted. First, although the nomenclature anaerobic threshold was used, the method applied in the analysis identified what is typically defined as the gas exchange threshold, which represents the aerobic threshold instead, as early described in the present thesis. Second, no constant-load rides at the estimated CP were performed, and the authors estimated a 11

22 V O2 value associated with CP from the linear regression equation of V O2 and PO from the RI test. In relation to this, an important limitation of this approach should be highlighted when discussing the possibility of deriving a PO that corresponds to that of the V O2 associated with the anaerobic threshold, when obtaining this information from a ramp or step incremental test. As described by Scheuermann and Kowalchuk (1998), and later by Keir et al. (2016), the PO linked to the anaerobic threshold derived from an incremental test is sensitive to the characteristics of the protocol (i.e., the steepness of the ramp); Thus, although the V O2 associated to the exercise intensity threshold remains constant independently of the increase in the ramp, obtaining a PO value from an incremental exercise test that yields the metabolic response (e.g., V O2) that represents the anaerobic threshold (i.e., upper boundary of the heavy intensity domain) still remains a challenge. Such obstacle is due to heterogeneous V O2 kinetics and V O2 gain responses, especially within the heavy and very heavy intensity domains (responses within the moderate intensity domain are relatively constant), among individuals (Keir et al. 2016). Independently of this limitation, an important aspect of this work by Moritani et al. (1981) is that this was the first study to describe CP as the limit of exercise tolerance within the very heavy intensity domain through the two-parameter hyperbolic equation, as follows: t = W / (PO CP) where t represents the time-to-exhaustion, in seconds; W represents the anaerobic work capacity, in Joules; PO represents the PO that the individual is cycling at, in watts; and CP represents the CP, watts. The curvilinear (hyperbolic) nature of CP when plotting the time-to-exhaustion against the PO of each one of the trials commonly shows a tapered fall in time-to-exhaustion at higher POs compared to lower. Therefore, when cycling at an exercise intensity above CP, time-to- 12

23 exhaustion may be predictable with the use of the hyperbolic equation. Figure 7 displays the interrelationship between the linear and the hyperbolic equation on CP estimations. Figure 7. Relationship between the imposed PO and tlim (hyperbolic equation; upper panel), and between the Wlim and tlim (linear equation; lower panel) from the same experimental data (from Moritani et al. (1981)). In the work of Poole and colleagues (1988), the authors measured physiological responses of cycling at an exercise intensity at CP and above CP (CP + 5% of the PO related to V O2max), which, on average, corresponded to ~20 W, over the course of 24 minutes. When cycling at CP, the participants reached a steady state V O2 and [La] responses. On the contrary, cycling above CP induced the same physiological variables to drift towards their maximum values. Also, all the participants, but one, failed before reaching 24 minutes. Thus, it was suggested that CP represents 13

24 the highest exercise intensity of physiological steady state, which may be also an index of the upper boundary of the heavy exercise intensity domain. Since CP is an estimation, it is important that the model used for its estimation is robust and that the final outcome does not change independently of the protocol design. The measurement of CP can be done through a wide range of time-to-exhaustion trials, ranging from 2 to 7, on separate days, depending on the criteria adopted to reduce the error of the parameter estimates (Hill 1993). Bishop et al. (1998a) investigated the influence of a variety of POs that resulted in performance of five trials ranging from 1 to 10 minutes in duration, in the power-time relationship (i.e., shorter and longer time-to-exhaustion trials were used to estimate CP). The CP was estimated through the linear and hyperbolic equations using three trials in different order from the five that were performed. Estimations of CP were completed using the three shortest trials (CP1,2,3), the three longest trials (CP3,4,5), as well as the first, the third, and the fifth trials (CP1,3,5). A significant difference between all the three methods was found, both using linear and hyperbolic equations, with CP1,2,3 being the highest and CP3,4,5 the lowest estimate. Thus, the authors suggested that if CP is to be a representative PO of the maximal physiological steady state, the time-to-exhaustion trials should be performed over a variety range of time in order to minimize the influence of shorter trials on the parameter estimates, and then achieving a more accurate value. 3-minute all-out test for estimation of CP Based on the fact that CP measurements (as well as MLSS) require performing several tests on separate days, studies have been conducted with the aim to develop a protocol that accurately estimates the maximal physiological steady state (i.e., CP) within a single session in the laboratory. An approach that has gained attention over recent years is the use of all-out exercise to estimate 14

25 CP. Some studies have attempted to use a 90-second all-out exercise (Davies and Sandstrom 1989; Gastin and Lawson 1994; Williams et al. 2005); however, estimations of CP were significantly higher than those derived from the power-time relationship (Dekerle et al. 2006). Therefore, Vanhatalo and colleagues (Burnley et al. 2006; Vanhatalo et al. 2007) proposed a 3-minute all-out test for estimation of CP and the MLSS in a single session in the laboratory. The hypothesis behind this protocol design was that, since all-out exercise induce the depletion of the anaerobic sources (i.e., W ), with a test longer than 90 seconds the W would be reduced to zero and the exercise intensity (i.e., PO) at the end would be supported by oxidative sources and then correspond to CP, according to the hyperbolic equation of CP, as follows: t = W / (PO CP) so that if the PO was to be isolated, the equation would be then: PO = (W /t) + CP Thus, when the W is fully depleted, the PO would be equal to CP. The authors further suggested that within the first 10 seconds of the test the generated PO reaches its peak, followed by a consistent decrease up to 2.5 minutes caused by the depletion of W, and then a plateau in the PO is achieved for the last 30 seconds, with ATP being resynthesized only by oxidative sources (Figure 8). Such method was later described as an ideal model since it attains V O2max, generates a large amplitude in the V O2 slow component, and, as mentioned, results in a complete depletion of W (Poole et al. 2016). 15

26 Figure 8. The PO profile throughout a 3-minute all-out test in a representative participant (from Vanhatalo et al. (2007)). The 3-minute all-out test is performed using the linear mode (i.e., fixed resistance) of the cycle ergometer, with the equation as follows: Linear factor = 50 / cadence 2 where the linear factor represents the percentage of body weight (kg) to be applied on the flywheel during the test; 50 represents the V O2 associated to 50% of the difference between the gas exchange threshold (GET) and the V O2max; and cadence represents the preferred cadence of the participants during the RI test. Despite the good theoretical background and the promising results from these investigations, some limitations need to be highlighted. For example, the authors did not perform prolonged rides at the estimated CP derived from the 3-minute all-out test to confirm that a physiological steady state had been achieved. Instead, the results from the 3-minute all-out test were either compared to CP 16

27 estimations from the power-time relationship (Vanhatalo et al. 2007) or to prolonged rides that were performed at a PO that was within a 30-watt range from the estimated value of CP (i.e., 15 W above and below) (Burnley et al. 2006). The comparison of the 3-minute all-out estimates with the power-time relationship parameters showed narrow limits of agreement, with the mean difference between the measures being close to zero. However, it should be noted that whether or not those CP estimations from the traditional method (i.e., power-time relationship) represented an accurate exercise intensity related to the maximal physiological steady state (i.e., stable V O2 and [La]) was not investigated. When evaluating rides at 15 W below the CP value derived from the 3-min all-out test, the V O2 and [La] concentrations were stable. In contrast, rides performed at a PO 15 W above the estimated CP resulted in V O2 and [La] projecting to their peak values. Although the authors concluded that the 3-min all-out test was a promising tool to evaluate CP, the lack of validation as to whether or not metabolic steady-state was actually achieved during these experiments questions the usefulness of this methods. If measures of CP are aimed for accurate prescription of exercise intensity or performance, it seems evident that any prediction that underestimates CP will result in lower than expected training effects, and that any prediction that overestimates CP will elicit exercise intensities that are unsustainable. Self-selected exercise intensity Accurate estimations of CP seem challenging as well as it is a physically and mentally demanding protocol. Given the certainty as to whether or not the estimated CP value is a valid measure of the upper boundary of the heavy exercise intensity domain, an approach in which individuals predict their highest sustainable exercise intensity based on their own perception of effort would reduce the need for multiple tests (e.g., CP and MLSS). 17

28 It has been previously suggested that time trial tests of a self-selected exercise intensity (selfpacing) may be more reliable than CP testing as well as more reflective of high performance in sports (Jeukendrup et al. 1996; Hopkins et al. 2001). Moreover, in exercise training prescription, especially in elite athletes, the correct determination of this critical metabolic rate becomes crucial. It is defined as the maximal exercise intensity at which a steady state can be achieved and sustained (Gaesser and Poole 1996; Jones and Carter 2000b). Previous studies evidenced that triathletes presented a steady state [La] during 30-minute rides at self-selected intensity at which the participants could either increase or decrease the exercise intensity throughout the ride, based on their own perception of effort, with the aim of cycling at their highest sustainable intensity (Perrey et al. 2003; Groslambert et al. 2004). Thus, the authors concluded that the self-pacing approach may be a useful way of determining an individual s highest sustainable exercise intensity, and therefore, it might abolish the need for more traditional testing methods (i.e., CP and MLSS). Scherr et al. (2013) indicated in a large sample study (i.e. 2,560 participants) that, independently of age, sex, or training status, individuals were able to relate similar RPE to [La] thresholds during a RI test. High correlations between RPE and heart rate (r = 0.74, p < 0.001) as well as RPE and [La] (r = 0.83, p < 0.001) were found. These findings suggest that, indeed, individuals are capable of identifying physiological alterations within the body during exercise that closely correspond to different exercise intensity thresholds, without the need for external measurements. Importantly, it should be noted that in this study fixed [La] values were used for determination of exercise intensity thresholds for the data analysis (i.e., 3.0 and 4.0 mmol L -1 ). Therefore, whether or not individuals would be able to identify their MLSS, only based on perception of effort, needs yet to be determined. 18

29 Purpose The present thesis was divided into two different manuscripts. The manuscript entitled Can measures of critical power precisely estimate the metabolic steady state? aimed to test the accuracy of two methods of estimating CP (i.e., power-time relationship and 3-minute all-out test) compared to the MLSS. A second aim of this manuscript was to test whether or not the MLSS also elicits the maximal V O2 steady-state, confirming, then, a physiological steady state. The manuscript entitled Critical power testing or self-selected cycling: Which one is the best predictor of maximal metabolic steady-state? aimed to test the ability of individuals in predicting their critical metabolic rate (defined as MLSS) based on their perception of effort during two 30- minute rides. A second aim of this manuscript was to test the agreement between the self-selected exercise intensities and estimations of CP. Author and co-authors contributions The authors listed below contributed to the manuscripts as follows: Felipe Mattioni Maturana (author): protocol design, data collection, data analysis, statistical analysis, and manuscript writing. Daniel A. Keir (co-author): project design, data analysis, and manuscript revisions. Kaitlin M. McLay (co-author): data collection, and manuscript revisions. Juan M. Murias (corresponding author): project design, data analysis, statistical analysis, and manuscript revisions. 19

30 CHAPTER 2 Can measures of critical power precisely estimate the maximal metabolic steady state? Felipe Mattioni Maturana 1, Daniel A. Keir 2, Kaitlin M. McLay 2, Juan M. Murias 1 1 Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada; 2 School of Kinesiology, The University of Western Ontario, London, ON, Canada Corresponding author: Juan M. Murias Faculty of Kinesiology, University of Calgary KNB 434, 2500 University Dr NW Calgary, AB, Canada, T2N 1N4 jmmurias@ucalgary.ca tel , fax

31 Abstract Critical power (CP) conceptually represents the highest power output (PO) at physiological steadystate. In cycling exercise, CP is traditionally derived from the hyperbolic relationship of ~5 timeto-exhaustion trials (TTE) (CPHYP). Recently, a 3-min all-out test (CP3MIN) has been proposed for estimation of CP as well the maximal lactate steady state (MLSS). Purpose: To compare the POs derived from CPHYP, CP3MIN and MLSS, and the oxygen uptake (V O2) and blood lactate concentrations ([La]) at MLSS. Methods: Thirteen healthy young subjects (26±3yr; 69.0±9.2kg; 174±10cm; 60.4±5.9mL kg -1 min-1 ) were tested. CPHYP was estimated from 5 TTE. CP3MIN was calculated as the mean PO during the last 30 s of a 3-min all-out test. MLSS was the highest PO during a 30-min ride where the variation in [La] was 1.0 mmol L -1 during the last 20 min. Results: PO at MLSS (233±41W; coefficient of variation (CoV) 18%) was lower than CPHYP (253±44W; CoV, 17%) and CP3MIN (250±51W; CoV, 20%) (p<0.05). Limits of agreement (LOA) from Bland-Altman plots between CPHYP and CP3MIN (-39 to 31W), and CP3MIN and MLSS (-29 to 62W) were wide, whereas CPHYP and MLSS presented the narrowest LOA (-7 to 48W). MLSS yielded not only the maximum PO of stable [La], but also stable V O2. Conclusions: POs associated to CPHYP and CP3MIN were larger than those observed during MLSS rides. Although CPHYP and CP3MIN were not different, the wide LOA between these two tests and the discrepancy with PO at MLSS questions the ability of CP measures to determine the maximal physiological steady-state. Key Words: POWER-TIME RELATIONSHIP; 3-MINUTE ALL-OUT; MAXIMAL LACTATE STEADY STATE; EXERCISE INTENSITY THRESHOLDS. 21

32 Introduction In endurance type exercises such as running, cycling or swimming, numerous physiological thresholds may be observed. These thresholds are identified in terms of exercise intensity (e.g., speed, power output) and represent specific levels beyond which physiological/metabolic conditions within the body and perception of effort are altered. Identification of these intensitydependent thresholds is often used for aerobic fitness assessment, exercise prescription, and to assure training effectiveness (Yeh et al. 1983; Binder et al. 2008). Therefore, correct determination of physiological thresholds can play an important role in the outcome of exercise training interventions. As described by Skinner and McLellan (1980), there is a threshold intensity separating endurance exercise that is sustainable purely by oxidative phosphorylation from those intensities requiring additional energy via substrate-level phosphorylation a consequence of which is an inability to maintain physiological homeostasis. This important boundary represents the upper limit of sustainable exercise tolerance (i.e. dividing heavy from very heavy or severe intensity exercise domains) and is characterized as the highest metabolic rate associated with the attainment of steady-state oxygen uptake (V O2), phosphocreatine degradation (PCr), blood lactate ([La]) and hydrogen ion concentration and muscle acidosis (Jones et al. 2008). Although this threshold has been proposed to best be determined using several different concepts, such as critical power (CP) (Moritani et al. 1981; Poole et al. 2016), maximal lactate steady state (MLSS) (Svedahl and MacIntosh 2003), and respiratory compensation point (RCP) (Beaver et al. 1986), it has been argued that each share similar physiological attributes (Keir et al. 2015). Given its theoretical applicability for training and performance, the CP concept has become one of the most widely used tests by researchers and coaches to evaluate the threshold intensity associated to the highest intensity of exercise associated to metabolic stability (Jenkins and 22

33 Quigley 1990; Jenkins and Quigley 1992; Overend et al. 1992; Smith and Hill 1993; Bishop and Jenkins 1995; Bishop et al. 1998b; Bull et al. 2000; Neder et al. 2000). Measures of CP are typically derived from the relationship between power output (PO) and time-to-exhaustion (TTE) as determined from 4-6 constant-power output exercise tests of variable intensity (Morton 2006). Although different modelling strategies have been proposed, the CP parameter is commonly determined as the power asymptote of a 2-parameter hyperbolic fit to the power-time relationship (CPHYP). Having estimated CP with this method, Poole et al. (1988) showed that cycling at CP engenders a plateau in both V O2 and [La]. However, when constant-power output was performed above CP (CP + 5% of peak PO (POpeak)) a continuous increase in both V O2 and [La] were observed. In the constant-power output paradigm, the profiles of both V O2 and [La] are strongly related (Barstow et al. 1993) and are used to stratify exercise intensity into domains or clusters of PO that elicit predictable V O2 and [La] response profiles within an individual (Whipp et al. 2002). Based on the seminal work of Poole et al. (1988), CP has been considered as the demarcation point separating heavy and very heavy (severe) intensity exercise domains. Therefore, in addition to CP estimation from the asymptote of the power-time curve, CP also has a clear physiological classification: the highest PO resulting in the eventual stabilization of both V O2 and [La]. Despite the potential practical applications of CP testing, repeated high levels of effort may be difficult and/or inconvenient to obtain. For this reason, a 3-minute all-out test (CP3MIN) has been proposed as an alternative, time-effective, and valid approach to determine CP from one single session (Vanhatalo et al. 2007). It has been concluded that estimating CP with this method does not differ from estimations based on the traditional power-time relationship determined from multiple constant-power output tests (Burnley et al. 2006). Further, these authors demonstrated that performing a 30-min ride at 15 W below CP3MIN resulted in stable [La] in most of the 23

34 participants, whereas performing at 15 W above CP3MIN resulted in [La] projecting to maximal values and rapid onset of exhaustion. While these patterns were characteristic of the responses expected for exercise above versus below CP, no measurement of the physiological variables (i.e. [La] and V O2) were (or have been) performed at the estimated CP3MIN. This is relevant as a margin of ±15 W is large for a test that is intended to predict the highest level of sustainable performance. Therefore, the degree of accuracy associated with estimation of CP as it relates to its ability to determine the maximal PO associated with physiological steady-state remains unknown. The purpose of this study was to compare the PO values associated with i) CPHYP; ii) CP3MIN; and iii) MLSS and to assess the blood [La] and V O2 responses during 30-min rides at these power outputs. It was hypothesized that the PO associate to CPHYP and CP3MIN would reflect that of MLSS. Methods Thirteen healthy young participants (9 men and 4 women; mean ± SD values: age, 26 ± 3 yr; body mass, 69.0 ± 9.2 kg; height, 174 ± 10 cm) volunteered and gave written informed consent to participate in the study. All participants had previous recreational or competitive cycling experience. Participants were nonsmokers, with no musculoskeletal and cardiorespiratory conditions. The full testing protocol was completed in 6 ± 1 weeks and consisted of: i) a preliminary maximal ramp incremental test for determination of peak oxygen consumption (V O2peak), POpeak, the V O2 associated to RCP and gas exchange threshold (GET), ii) five TTE tests for estimation of CPHYP, iii) a 3-min all-out test for estimation of CP3MIN, iv) two to four 30-min constant-power output rides for determination of MLSS, and v) a final ramp incremental test to examine if the testing procedure produced any training effects. All procedures were conducted in an environmentally controlled laboratory (i.e. temperature ~21 C, relative humidity ~36%), at a 24

35 similar time of the day for each subject. Participants performed each test on separate days, with a minimum interval of 24 h and a maximum interval of 72 h between tests. Participants were instructed to keep their water and carbohydrate intake consistent throughout the protocol, and they were requested not to practice vigorous physical activity for 24 h prior to each test, and not to consume caffeine during the 12 h prior to the test. This study was approved by the Conjoint Health Research Ethics Board of the University of Calgary. Exercise Protocols For all exercise tests, participants cycled at their preferred pedal cadence (range, rpm), which was determined during the preliminary ramp incremental test. Failure to maintain the cadence within 5 rpm for longer than 5 s despite strong verbal encouragement was considered the moment of exhaustion. Participants were blinded to the elapsed time, but they received visual feedback for the pedal cadence. Ramp incremental test. The ramp incremental tests consisted of a 50-W baseline for 4 minutes, as suggested by Boone and Bourgois (2012), followed by either 30 W min -1 (1 W every 2 s) (men) or 25 W min -1 (1 W every 2.4 s) (women) increase in PO. CPHYP. For the estimation of CPHYP, each participant performed five constant-power output trials to exhaustion which ranged from approximately 1-20 min, as recommended by Morton (2006). The first three TTE trials were performed at 80, 95 and 110% of POpeak (as previously determined in the preliminary ramp incremental test). Ten min after one of these TTE trials, a familiarization of the 3-minute all-out test was performed. The order of the tests was randomly assigned. Subsequently, the other two power outputs were determined to generate an even distribution of TTE between the five trials. Each test was preceded by a 4-min baseline at 20 W, followed by a square-wave transition to the predetermined PO, until the participants were unable to continue 25

36 despite strong verbal encouragement. Blood [La] was measured at 2 min of baseline and at the moment of exhaustion. CP3MIN. Participants performed a 4-min baseline at 20 W, immediately followed by 3 minutes of all-out exercise for estimation of CP3MIN. The resistance during the 3-min all-out effort corresponded to a cadence-specific PO associated to 50% of the difference between the GET and VO2peak ( 50) as determined during the preliminary ramp incremental test (Vanhatalo et al. 2007). The resistance was determined using the linear mode of the cycle ergometer, calculated as follows: Linear factor = 50 / cadence 2 Participants were instructed to speed up their cadence to approximately 110 rpm during the last 5 s of the baseline, as recommended by Vanhatalo et al. (2007). After that, participants were instructed to pedal as fast as possible for the entire duration of the protocol. Strong verbal encouragement was provided throughout the entire test. No visual feedback was provided to the participants. Blood [La] was measured at 2 min of baseline and at the end of the test. MLSS. Participants performed two to four, 30-min constant-power output rides for determination of MLSS. Each test started with a 4-min baseline at 20 W, followed by a step transition to the predetermined PO derived from a self-selected intensity in order to minimize the number of tests needed (ref. Chapter 3). Blood [La] was measured at 2 min of baseline and at a 5-min intervals after the load was increased, throughout the 30 minutes of exercise (i.e. 5 th, 10 th, 15 th, 20 th, 25 th, and 30 th min). The first test was performed at CPHYP, and the following rides were dependent on the [La] response of the previous test, as follows: if the [La] increased by > 1.0 mmol L -1 between the 10 th and 30 th min during exercise, the successive test was performed at 10 W below; if the [La] response increased by < 1.0 mmol L -1, the successive test was performed at 10 W above. Thus, the 26

37 PO was either increased or reduced by 10 W until the highest PO that elicited the MLSS (i.e. increase of 1.0 mmol L -1 between the 10 th and 30 th min) was determined. Equipment and Measurements All exercise tests were performed on an electromagnetically braked cycle ergometer (Velotron Dynafit Pro, Racer Mate, Seattle, WA, USA). Breath-by-breath pulmonary gas exchange, ventilation and heart rate (HR) were continuously measured using a metabolic cart (Quark CPET, COSMED, Rome, Italy), as previously described (De Roia et al. 2012). Calibration was done before each test as recommended by the manufacturer. Breath-by-breath V O2 data were edited as follows: data points that were 3 SD from the local mean were considered outliers and then removed (Lamarra et al. 1987); trials were interpolated on a second-by-second basis, time-aligned to the onset of exercise (i.e. time zero representing the onset of the constant-power output or RI exercise), and averaged into 30-s time bins. Blood [La] was measured with a portable lactate analyzer (Lactate Scout, SensLab Gmb, Lepzig, Germany) through a 2-µl capillary sample of whole blood taken from a finger prick. Data Analyses GET and RCP were determined by two expert reviewers blinded to the identity of the participants. The average of the two values was used for analysis as long as all estimates were within 100 ml min -1. GET was determined by visual inspection as the V O2 at which CO2 output (V CO2) began to increase out of proportion in relation to V O2, with a systemic rise in minute ventilation (V E) in relation to V O2 and end-tidal PO2 whereas the ventilatory equivalent of V CO2 (V E/ V CO2) and end-tidal PCO2 were stable (Beaver et al. 1986). RCP was determined as the point in V O2 where end-tidal PCO2 began to decrease after a period of isocapnic buffering (Whipp et al. 1989), 27

38 as well as the second breakpoint in the V E-to- V O2 relation and confirmed examining V E/ V CO2 plotted against V O2. V O2peak was considered as the highest 30-s V O2 average throughout the ramp incremental test. POpeak was established as the highest PO achieved prior to exhaustion. CPHYP was determined by fitting a two-parameter hyperbolic model (Hill 1993) to each subject s power-time relationship using nonlinear least squares regression analysis, as follows: t = W / (PO CP) where t is time to exhaustion (s), W is the anaerobic work capacity (J), CP is the critical power (W), and PO is the predetermined PO (W). The goodness of fit for the hyperbolic model was determined as the 95% confidence interval (CI) for CP. CP3MIN was defined as the average PO of the last 30s of the 3-min all-out test (Vanhatalo et al. 2007). The anaerobic work capacity was defined as the integral of the work performed under the curve and above CP3MIN (WEP). V O2 and HR responses from the constant-power output tests were averaged into 30-s time bins for data display. All data editing, processing, and modeling were performed using OriginLab version 9.2 (OriginLab, Northampton, MA). Statistical Analyses Data are presented as mean ± SD. One-way repeated-measures ANOVA was used to determine statistical significance for the dependent variables. Bland-Altman plots were used to assess the limits of agreement (LOA) between the POs at CPHYP, CP3MIN, and MLSS, and one-sample Z-tests were used to determine whether the average difference between values (i.e. bias) was significantly different from zero. Two-tailed pairwise t-tests were used to compare differences between the values (i.e. absolute V O2peak, RCP, and POpeak) obtained from the preliminary and final ramp 28

39 incremental test, as well as to determine whether there was a steady-state in the V O2 response between the 10 th and the 30 th min of exercise during the ride at MLSS. To assess the variability of the estimations of CP and MLSS, the coefficient of variation (CoV) was calculated. All statistical analyses were performed using SigmaPlot version 13.0 (Systat Software Inc., San Jose, CA). Statistical significance was set as an alpha level less than Results CPHYP, CP3MIN, and MLSS. Figure 1 shows the CPHYP and CP3MIN estimations for a representative subject. There were no differences (p > 0.05) between the PO values obtained from CPHYP (95% CI: W) and CP3MIN (95% CI: W). However, the PO associated with MLSS was lower (p < 0.05; Table 1). W and WEP values are also displayed in Table 1. [La]PRE was similar in CPHYP and CP3MIN (1.2 ± 0.3 mmol L -1 and 1.3 ± 0.5 mmol L -1 ; p > 0.05). CPHYP [La]POST (12.5 ± 3.0 mmol L -1 ) was lower (p < 0.05) than that observed at CP3MIN [La]POST (15.4 ± 2.6 mmol L -1 ). Group mean PO values during TTE trials as well as mean duration of each trial are displayed on Table 2. Group mean [La] during the rides at MLSS was 3.7 ± 1.3 mmol L -1 and 4.4 ± 1.5 mmol L -1 at the 10 th and the 30 th minute, respectively (group mean difference was 0.8 ± 0.2 mmol L -1 ). The V O2 response during the MLSS rides was stable (p > 0.05) between the 10 th (3.50 ± 0.62 L min -1 ) and 30 th minute (3.54 ± 0.63 L min -1 ) (Figure 2), and similar to that observed at RCP (p>0.05; Table 2). For the eight participants who managed to complete 30 min of exercise at 10 W above the PO associated to MLSS, the V O2 was larger (p < 0.05) at minute 30 (3.73 ± 0.47 L min -1 ) compared to minute 10 (3.63 ± 0.49 L min -1 ). For the participants who completed the 30 min trials at both MLSS and above MLSS (i.e. ~ 10 W), the V O2 at the 30 th minute of exercise 29

40 was lower (p < 0.05) when riding at the PO associated to MLSS (3.54 ± 0.63 L min -1 ) compared to 10 W above this PO (3.73 ± 0.47 L min -1 ) (Figure 2). Figure 3 shows Bland-Altman plots representing the agreement between individual PO (W) values derived from CP3MIN and CPHYP (panel A), CPHYP and MLSS (panel B), and CP3MIN and MLSS (panel C). The mean difference (i.e. bias) between CP3MIN and CPHYP (LOA: - 39 to + 31 W), CP3MIN and MLSS (LOA: - 29 to + 62 W), and CPHYP and MLSS (LOA: - 7 to + 48 W) were not different (p > 0.05) from zero. The narrowest LOA was observed between POs associated to CPHYP and MLSS. CoV was 17%, 20%, and 18% for CPHYP, CP3MIN, and MLSS, respectively. Ramp Incremental test. V O2peak, and RCP were similar during the preliminary compared to the final ramp incremental test (p > 0.05; Table 3). However, a small albeit significant change in POpeak was observed from these tests (p < 0.05; Table 3). Discussion The present study evaluated and compared the PO values associated with CPHYP, CP3MIN and MLSS, and examined the blood [La] and V O2 responses during 30-min rides at these power outputs. The main findings were that: a) although CPHYP and CP3MIN provided a similar mean PO, there was a large dispersion in the individual CP estimations as indicated by the wide LOA (Figure 3A); b) MLSS rides yielded the maximum PO at which not only [La], but also V O2 were stable, whereas rides at 10 W above MLSS presented, in addition to the non-steady [La] response, a greater V O2 (i.e. significant difference in V O2 between the 10 th and 30 th min mark across the 30- min ride); and c) despite both CPHYP and CP3MIN eliciting a PO larger than that observed at MLSS, CPHYP presented narrower LOA with respect to MLSS than CP3MIN compared to MLSS. 30

41 Throughout the years, the CP concept has been recognized as the maximal PO that an individual can sustain for a prolonged period of time (Monod and Scherrer 1965; Moritani et al. 1981). For this reason CP has been considered as the boundary between heavy and very heavy intensity domains (Poole et al. 1988). Although CP is a measure derived from the power-time asymptote as originally proposed by Monod and Scherrer (1965), it is interpreted by some as a power output value without any physiological correlates. However, many argue that CP should be associated to specific physiological events (Poole et al. 1988; Jenkins and Quigley 1990; Keir et al. 2015). In theory, precise determination of CP should yield the maximal exercise intensity at which a metabolic steady-state can be achieved. When exercising at intensities above CP, the V O2 profile, theoretically, projects towards V O2max, with exhaustion occurring thereafter (Poole et al. 1988). Therefore, the identification of this metabolic boundary becomes important for determination of sustainable from unsustainable exercise intensities. In practice, CP estimation (regardless of method, i.e., CPHYP and CP3MIN) is performed to identify a PO that corresponds to the highest intensity that an individual can sustain indefinitely while maintaining a metabolic steady-state. Given the magnitude of variability amongst the investigated methods used to determine CP, it is logical that a validation trial be performed to ensure that: a) the exercise is tolerable for a prolonged duration; and b) that a physiological steady-state is achieved. In this context, precise estimation of CP should yield a physiological response expected at MLSS. Previous studies suggested that the CP3MIN may be an alternative method to identify the MLSS in a single test (Burnley et al. 2006; Vanhatalo et al. 2007). However, other investigations (Sperlich et al. 2011; Bergstrom et al. 2013) have shown that CP3MIN consistently overestimates MLSS and that cycling at CP3MIN is unsustainable (Bergstrom et al. 2013), inducing V O2 and [La] responses indicative of very heavy intensity exercise. Given the overestimation of CP concerns when using 31

42 the 3-min all-out test, other studies have used the isokinetic mode of the cycle ergometer (note the original CP3MIN is determined with the linear mode) to determine whether or not this approach would elicit a CP value that was in agreement with estimations from multiple TTE trials. Using this approach, the authors reported a large intra-subject variability as well as a discrepancy between these measures and CP estimations, (Dekerle et al. 2014; Karsten et al. 2014) which further questions the validity of the 3-min all-out test as a measure of CP. In the present study, individual comparisons between MLSS and CP3MIN (Figure 3C) resulted in the largest variability in LOA amongst tests (LOA: -29 to +62 W), with CP3MIN tending to overestimate MLSS (bias: 17 W) and a sustainable PO. Therefore, while CP3MIN provides a more time-effective method by which to estimate CP (i.e. a ramp incremental test and a 3-min all-out test), the POs derived from this test were generally inconsistent with what they were expected to determine. With this in mind, it is still important to highlight that CP3MIN provides a useful approach to estimate a PO that will approximate the highest rate of metabolic steady-state; however, based on the present data, further physiological validation should be conducted before adopting this PO as a true intensity associated with physiological homeostasis, as there is no clear evidence that there is a physiological link between these two measures. Even though CPHYP is the traditional method for estimating the boundary between heavy and very heavy intensity domains and been widely used in this context (Jenkins and Quigley 1990; Jenkins and Quigley 1992; Overend et al. 1992; Neder et al. 2000), in the present study only one subject achieved a stable [La] when cycling at the PO derived from CPHYP. For the rest of the participants, CPHYP overestimated MLSS and, as a consequence, physiological steady-state was not achieved. It has to be acknowledged, however, that the PO derived from the power-time relationship might be influenced by the strategy used to model the data as well as by the range of TTE trials chosen. 32

43 For example, data ranges based on shorter trial durations yield greater hyperbolic asymptotes, and thus greater CP values whereas the opposite occurs for TTE ranges incorporating longer trial durations (Bishop et al. 1998b; Jenkins et al. 1998). Indeed, the method/protocol selected to identify CP can largely affect CP estimation; even within the same participant (Housh et al. 1989; Jenkins and Quigley 1990; Jenkins and Quigley 1992; McLellan and Cheung 1992; Bishop et al. 1998b; Bull et al. 2000). Thus, TTE trials should include a wide range of durations to minimize the potential bias introduced by TTE trial duration on the estimation of CP and its proximity to the maximal metabolic steady-state (Morton 1996; Bishop et al. 1998b). The present study utilized the 2-parameter hyperbolic model for modelling as proposed by other investigations (Moritani et al. 1981; Poole et al. 1988). However, it should be noticed that other fitting strategies that were explored (i.e., linear fitting and 3-parameter model hyperbolic model - data not presented) did not change the final outcome of the current results. Nevertheless, the narrower LOA between CPHYP and MLSS suggest that, although CPHYP consistently overestimated the PO associated to the highest stable metabolic rate (mean bias = 20 W), this method of CP estimation appears to offer a more accurate estimation of metabolic steady-state when compared to CP3MIN. However, additional validation for a precise identification of the PO associated to the maximal physiological steady-state is recommended. The concept of MLSS becomes important for establishing the accuracy of methods for estimating CP. An obvious disadvantage of the MLSS measurement is that it requires multiple visits to the laboratory and somewhat invasive measures. However, it could be argued that even the POs derived from CPHYP and CP3MIN would require further evaluation to determine whether or not the PO associated to metabolic steady-state was determined. Some would argue that the concepts of CP and MLSS do not reflect the same physiological responses (Brickley et al. 2002; Pringle and 33

44 Jones 2002). In this regard, a recent study has shown that the V O2 associated to CP and MLSS were similar suggesting that they may share common underlying mechanisms (Keir et al. 2015). Although this is a tenable idea, debate still exists on the topic. What is important here is measurements of CP become practically irrelevant if they do not measure what they are supposed to measure. For example, even if the concept of MLSS was not to be discussed, PO determined from CPHYP and CP3MIN often demonstrated 30 W of separation which is highly variable for a test that is supposed to determine the border between sustainable and unsustainable exercise. In this situation, the question becomes, which one of those tests reflects CP? That the mean values are similar for CPHYP and CP3MIN tends to conceal the fact that the individual differences in the estimation of CP were often quite large. In other words, if CP testing is adopted for its practical utility in exercise training prescription, which testing method should be relied upon and how can it be ensured that the estimated PO is not too easy or too hard? With these inherent testing limitations, it could be suggested that researchers and coaches should conduct CP measurements by testing the individual s capability of self-predicting the highest sustainable PO that can be maintained for 30-min (or longer) as previously proposed (Perrey et al. 2003; Groslambert et al. 2004). A self-selected intensity may offer a more efficient strategy to optimize time in an athlete s periodization and a more cost-effective alternative to laboratory testing. Further investigation is necessary to explore the validity of this approach. In conclusion, this study showed that the POs associated to CPHYP and CP3MIN are different from those derived from MLSS measurements. Importantly, although CPHYP and CP3MIN where similar, the dispersion of these data between the two tests reduces the probability of precise determination of CP, independent of whether or not agreement is reached in terms of the mechanistic basis linking CP to MLSS. 34

45 References Barstow, T.J., Casaburi, R., and Wasserman, K O2 uptake kinetics and the O2 deficit as related to exercise intensity and blood lactate. J Appl Physiol 75: Beaver, W.L., Wasserman, K., and Whipp, B.J A new method for detecting anaerobic threshold by gas exchange. J Appl Physiol (1985) 60: Bergstrom, H.C., Housh, T.J., Zuniga, J.M., Traylor, D.A., Lewis, R.W., Camic, C.L., Schmidt, R.J., and Johnson, G.O Responses during exhaustive exercise at critical power determined from the 3-min all-out test. J Sports Sci 31: Binder, R.K., Wonisch, M., Corra, U., Cohen-Solal, A., Vanhees, L., Saner, H., and Schmid, J.P Methodological approach to the first and second lactate threshold in incremental cardiopulmonary exercise testing. Eur J Cardiovasc Prev Rehabil 15: Bishop, D. and Jenkins, D.G The influence of recovery duration between periods of exercise on the critical power function. Eur J Appl Physiol Occup Physiol 72: Bishop, D., Jenkins, D.G., and Howard, A The critical power function is dependent on the duration of the predictive exercise tests chosen. Int J Sports Med 19: Boone, J. and Bourgois, J The oxygen uptake response to incremental ramp exercise: methodogical and physiological issues. Sports Med 42: Brickley, G., Doust, J., and Williams, C.A Physiological responses during exercise to exhaustion at critical power. Eur J Appl Physiol 88:

46 Bull, A.J., Housh, T.J., Johnson, G.O., and Perry, S.R Effect of mathematical modeling on the estimation of critical power. Med Sci Sports Exerc 32: Burnley, M., Doust, J.H., and Vanhatalo, A A 3-min all-out test to determine peak oxygen uptake and the maximal steady state. Med Sci Sports Exerc 38: De Roia, G., Pogliaghi, S., Adami, A., Papadopoulou, C., and Capelli, C Effects of priming exercise on the speed of adjustment of muscle oxidative metabolism at the onset of moderateintensity step transitions in older adults. Am J Physiol Regul Integr Comp Physiol 302: R Dekerle, J., Barstow, T.J., Regan, L., and Carter, H The critical power concept in all-out isokinetic exercise. J Sci Med Sport 17: Groslambert, A., Grappe, F., Bertucci, W., Perrey, S., Girard, A.J., and Rouillon, J.D A perceptive individual time trial performed by triathletes to estimate the anaerobic threshold. A preliminary study. J Sports Med Phys Fitness 44: Hill, D.W The critical power concept. A review. Sports Med 16: Housh, D.J., Housh, T.J., and Bauge, S.M The accuracy of the critical power test for predicting time to exhaustion during cycle ergometry. Ergonomics 32: Jenkins, D., Kretek, K., and Bishop, D The duration of predicting trials influences time to fatigue at critical power. J Sci Med Sport 1: Jenkins, D.G. and Quigley, B.M Blood lactate in trained cyclists during cycle ergometry at critical power. Eur J Appl Physiol Occup Physiol 61: Jenkins, D.G. and Quigley, B.M Endurance training enhances critical power. Med Sci Sports Exerc 24: Jones, A.M., Wilkerson, D.P., Vanhatalo, A., and Burnley, M Influence of pacing strategy on O2 uptake and exercise tolerance. Scand J Med Sci Sports 18:

47 Karsten, B., Jobson, S.A., Hopker, J., Passfield, L., and Beedie, C The 3-min test does not provide a valid measure of critical power using the SRM isokinetic mode. Int J Sports Med 35: Keir, D.A., Fontana, F.Y., Robertson, T.C., Murias, J.M., Paterson, D.H., Kowalchuk, J.M., and Pogliaghi, S Exercise Intensity Thresholds: Identifying the Boundaries of Sustainable Performance. Med Sci Sports Exerc 47: Lamarra, N., Whipp, B.J., Ward, S.A., and Wasserman, K Effect of interbreath fluctuations on characterizing exercise gas exchange kinetics. J Appl Physiol 62: McLellan, T.M. and Cheung, K.S A comparative evaluation of the individual anaerobic threshold and the critical power. Med Sci Sports Exerc 24: Monod, H. and Scherrer, J The Work Capacity of a Synergic Muscular Group. Ergonomics 8: Moritani, T., Nagata, A., devries, H.A., and Muro, M Critical power as a measure of physical work capacity and anaerobic threshold. Ergonomics 24: Morton, R.H A 3-parameter critical power model. Ergonomics 39: Morton, R.H The critical power and related whole-body bioenergetic models. Eur J Appl Physiol 96: Neder, J.A., Jones, P.W., Nery, L.E., and Whipp, B.J The effect of age on the power/duration relationship and the intensity-domain limits in sedentary men. Eur J Appl Physiol 82: Overend, T.J., Cunningham, D.A., Paterson, D.H., and Smith, W.D Physiological responses of young and elderly men to prolonged exercise at critical power. Eur J Appl Physiol Occup Physiol 64:

48 Perrey, S., Grappe, F., Girard, A., Bringard, A., Groslambert, A., Bertucci, W., and Rouillon, J.D Physiological and metabolic responses of triathletes to a simulated 30-min time-trial in cycling at self-selected intensity. Int J Sports Med 24: Poole, D.C., Burnley, M., Vanhatalo, A., Rossiter, H.B., and Jones, A.M Critical Power: An Important Fatigue Threshold in Exercise Physiology. Med Sci Sports Exerc. Poole, D.C., Ward, S.A., Gardner, G.W., and Whipp, B.J Metabolic and respiratory profile of the upper limit for prolonged exercise in man. Ergonomics 31: Pringle, J.S. and Jones, A.M Maximal lactate steady state, critical power and EMG during cycling. Eur J Appl Physiol 88: Skinner, J.S. and McLellan, T.M The transition from aerobic to anaerobic metabolism. Res Q Exerc Sport 51: Smith, J.C. and Hill, D.W Stability of parameter estimates derived from the power/time relationship. Can J Appl Physiol 18: Sperlich, B., Haegele, M., Thissen, A., Mester, J., and Holmberg, H.C Are peak oxygen uptake and power output at maximal lactate steady state obtained from a 3-min all-out cycle test? Int J Sports Med 32: Svedahl, K. and MacIntosh, B.R Anaerobic threshold: the concept and methods of measurement. Can J Appl Physiol 28: Vanhatalo, A., Doust, J.H., and Burnley, M Determination of critical power using a 3-min all-out cycling test. Med Sci Sports Exerc 39: Whipp, B.J., Davis, J.A., and Wasserman, K Ventilatory control of the 'isocapnic buffering' region in rapidly-incremental exercise. Respir Physiol 76:

49 Whipp, B.J., Rossiter, H.B., and Ward, S.A Exertional oxygen uptake kinetics: a stamen of stamina? Biochem Soc Trans 30: Yeh, M.P., Gardner, R.M., Adams, T.D., Yanowitz, F.G., and Crapo, R.O "Anaerobic threshold": problems of determination and validation. J Appl Physiol 55:

50 Table 1. PO values derived from CPHYP (with standard error of the estimation (SEE)), CP3MIN, and MLSS, as well as W and WEP values derived from CPHYP and CP3MIN, respectively. Participant CPHYP (W) SEE W (kj) CP3MIN (W) WEP (kj) MLSS (W) Mean 253* * SD *Denotes significant difference from MLSS (p < 0.05). Denotes significant difference from W 40

51 Table 2. Mean PO and TTE values during trials for estimation of CPHYP. % POpeak PO (W) 413 ± ± ± ± ± 46 TTE (s) 102 ± ± ± ± ± 203 Average % POpeak values for the two longest trials for estimation of CPHYP according to the methods. 41

52 Table 3. V O2peak (L min -1 ), RCP (L min -1 ), and POpeak (W) group mean values from the preliminary and the final ramp incremental test. V O2peak (L min -1 ) RCP (L min -1 ) POpeak (W) Pre Ramp Incremental 4.17 ± ± ± 54 Post Ramp Incremental 4.31 ± ± ± 56 * *Denotes significant difference from the preliminary ramp incremental (p < 0.05). 42

53 Figure 1. The CPHYP (left panel) and CP3MIN (right panel) fits are displayed in a representative subject. The dashed lines represent the PO derived from the two-parameter hyperbolic model (left panel), and the PO average in the last 30 s in the 3-min all-out test (right panel). 43

54 Figure 2. Group mean (with SD bars: +SD represents > MLSS and SD represents MLSS) data displaying the V O2 response (L min -1 ) during 30-min constant-power output rides performed at MLSS as well as 10 W above MLSS, plotted as a function of time (min). The dashed vertical line represent the onset of constant-power exercise following baseline. *Denotes significant difference from the 10 th min mark (p < 0.05). 44

55 Figure 3. Bland-Altman plots displaying agreement between individual measures of CPHYP and CP3MIN (panel A), MLSS and CPHYP (panel B), and MLSS and CP3MIN (panel C). The differences between measures (y-axis) are plotted as a function of the mean of the two measures (x-axis) in absolute values (W). The mean difference (i.e. bias) is represented by the horizontal dashed line, whereas the limits of agreement (mean ± 2 SD) are represented by the paired horizontal dotted lines. 45

56 CHAPTER 3 Critical power testing or self-selected cycling: Which one is the best predictor of maximal metabolic steady-state? Felipe Mattioni Maturana 1, Daniel A. Keir 2, Kaitlin M. McLay 2, Juan M. Murias 1 1 Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada; 2 School of Kinesiology, The University of Western Ontario, London, ON, Canada Corresponding author: Juan M. Murias Faculty of Kinesiology, University of Calgary KNB 434, 2500 University Dr NW Calgary, AB, Canada, T2N 1N4 jmmurias@ucalgary.ca tel , fax

57 Abstract Critical power (CP) demarcates the boundary between heavy and very heavy exercise intensity domains, and therefore, the power output (PO) that can be sustained at the maximal metabolic steady-state during constant-po exercise (i.e., maximal lactate steady-state (MLSS)). However, the estimated CP does not always reflect a sustainable intensity of exercise, and blood lactate concentration ([La]) and oxygen uptake (V O2) cannot be stabilized. Purpose: To test cyclists ability to predict their highest PO associated with metabolic steady-state based on their own perception of effort. Methods: Thirteen healthy young cyclists (26±3 yrs; 69.0±9.2 kg; 174±10 cm) were tested. CP from 5 time-to-exhaustion trials was derived from a 2-parameter hyperbolic model (CPHYP). Participants performed two 30-min rides at a self-selected PO that they considered the highest sustainable exercise intensity (CPSELF). Additionally, MLSS was determined as the highest PO at which variation in [La] 1.0 mmol L -1 between the 10 th and 30 th min was observed during a 30-min ride. Results: Mean PO at CPSELF (233±42 W) was similar (p>0.05) to MLSS (233±41 W), whereas CPHYP (253±44 W) consistently overestimated (p<0.05) the PO associated to metabolic steady-state. The limits of agreement (LOA) between MLSS and CPSELF were -20 to +20 W (bias= 0 W, p>0.05), whereas the LOA between CPHYP and CPSELF were -40 to 0 W (bias= -20 W, p<0.05). CPSELF and MLSS presented similar (p>0.05) metabolic response (i.e., V O2, [La], and HR). Conclusion: CPSELF may offer an approach to predict the maximal physiological steadystate during constant-po exercise with more precision than CPHYP. Key Words: POWER-TIME RELATIONSHIP; MAXIMAL LACTATE STEADY-STATE; EXERCISE INTENSITY THRESHOLDS; PERCEIVED EXERTION. 47

58 Introduction During incremental exercise, two metabolic thresholds can be identified. The first threshold is consequent to a systemic increase in arterial lactate concentration ([La]) above resting levels and the second threshold, which occurs at a higher intensity, marks the intensity exceeding the capacity of bicarbonate to buffer the acidosis associated with continued [La] accumulation (Beaver et al. 1986). This second threshold, is considered to be a key marker of the upper limits of exercise tolerance (Skinner and McLellan 1980) representing the highest metabolic rate at which oxidative metabolism alone can satisfy the energetic requirements of the exercise and thus oxygen uptake (V O2) and [La] may be stabilized. Throughout the years, various methods have been proposed for identification of the specific intensity associated with this important physiological threshold. For example, critical power (CP) (Moritani et al. 1981; Poole et al. 2016), maximal lactate steady state (MLSS) (Svedahl and MacIntosh 2003), and respiratory compensation point (RCP) (Beaver et al. 1986) have been indicated to characterize this physiological boundary. Indeed, despite ongoing controversy related to the mechanistic underpinnings surrounding these paradigms, Keir et al. (2015) recently indicated that CP, MLSS, and RCP occurred at the same metabolic rate (as inferred by V O2) suggesting that these indexes arise from similar physiological phenomena. Although measures of CP, MLSS and RCP may represent the highest sustainable intensity of exercise, each one of these models has some inherent testing limitations. For example, it has been shown that, independently of the testing protocol, CP estimations may either over- or underestimate the maximal metabolic steady-state power output (PO), necessitating further physiological validation before the highest PO of sustainable exercise can be identified (Mattioni Maturana et al. 2016). Alternatively, the MLSS approach may be a more appropriate method for establishing the highest sustainable intensity of exercise in that it is determined during constant- 48

59 PO of prolonged duration (i.e., 30 min); however, this procedure may be considered timeconsuming as it requires multiple [La] measures to be established (Heck et al. 1985). Finally, although estimation of the V O2 associated with RCP following a ramp incremental (RI) (or step) test is relatively straightforward, determining a precise PO corresponding to the V O2 is challenging as the V O2-PO relationship can be disassociated in protocols of varying ramp increment due to the action of the V O2 slow component and individual differences in V O2 kinetics (Scheuermann and Kowalchuk 1998; Keir et al. 2016). In order to minimize the time and equipment needed for the identification of the maximal metabolic steady-state PO, previous studies (Perrey et al. 2003; Groslambert et al. 2004) suggested performing a 30-min time trial at a self-selected intensity as an alternative method for estimation of the highest sustainable intensity of exercise with triathletes. During these trials participants were able to freely adjust their PO during the 30 min of cycling exercise. Although this approach allowed subjects to cycle at their highest perceived sustainable intensity at any given point during the 30-min ride, the maximal metabolic steady-state would not necessarily be achieved (i.e. the participants would periodically decrease PO throughout the ride facilitating recovery during unstable metabolic conditions). Although Groslambert et al. (2004) reported that the PO and HR, associated to RCP were not different compared to the mean PO and HR from the self-selected trial, the lack of metabolic measures of [La] and V O2 limits the ability to interpret the results in the context of metabolic steady-state. On the contrary, even though Perrey et al. (2003) showed that participants achieved a metabolic steady-state (i.e., stable [La] and V O2 responses) during the same protocol (i.e., self-selected time trials), verification of maximal metabolic steady-state was not performed. Therefore, it is tenable that individuals are capable of predicting an intensity that yields their maximal physiological steady-state. In this regard, Scherr et al. (2013) demonstrated, in a 49

60 sample of 2,560 participants, that individuals were capable of accurately perceiving and identifying exercise intensity domains based on their own predetermined exercise intensity thresholds during an incremental test, independently of sex, age and training status. These authors reported a strong relationship between rate of perceived exertion (RPE) and [La], with RPE increasing curvilinearly along with [La] during the RI test. These findings indicate that individuals have the ability to identify correctly exercise intensity through perception of effort. Therefore, it is possible that individuals may also be able to identify a PO associated with their highest sustainable intensity of exercise. Were this to be true, successful assessment of physiological thresholds could be performed without the use of time-consuming protocols and monitoring tools. Thus, the aim of the present study was to determine whether individual s self-predicted highest sustainable PO (CPSELF) coincides with the highest physiological steady-state intensity. Additionally, this intensity was compared to the POs associated with: i) CP estimated using a 2- parameter hyperbolic fit to the power-time relationship established from a series of exhaustive trials (CPHYP), and ii) MLSS. It was hypothesized that there would not be any differences in the mean PO as well as mean physiological responses between CPSELF and MLSS. Methods This study was part of a larger project that included the comparison of two different protocols to determine CP (Mattioni Maturana et al. 2016). Although the overall project was designed to answer these separate research questions, the absolute values for CP and MLSS have been reported elsewhere (Mattioni Maturana et al. 2016). In relation to the present data set, thirteen healthy young participants (9 men and 4 women; mean ± SD values: age, 26 ± 3 yr; body mass, 69.0 ± 9.2 kg; height, 174 ± 10 cm) volunteered and gave written informed consent to participate in the study. 50

61 All participants had previous recreational or competitive cycling experience. Participants were nonsmokers, with no musculoskeletal and cardiorespiratory conditions. The full testing protocol was completed in four to six weeks and consisted of: i) a preliminary maximal RI test to the limit of tolerance for determination of peak V O2 (V O2peak), the V O2 associated to RCP, and POpeak; ii) five time to exhaustion (TTE) tests for estimation of CPHYP; iii) two, 30-min constant-po rides at a self-selected exercise intensity for determination of CPSELF; and iv) one or two additional 30-min constant-po rides for determination of MLSS. All procedures were conducted in an environmentally controlled laboratory (i.e. temperature ~21 C, relative humidity ~36%), at a similar time of the day for each subject. Participants were instructed to keep their water consumption and diet consistent throughout the protocol, and they were requested not to practice vigorous physical activity in the 24 h prior to the test. This study was approved by the Conjoint Health Research Ethics Board of the University of Calgary. Exercise Protocols For all exercise tests, participants cycled at their preferred pedal cadence (range, rpm), which was determined during the RI test. Failure to maintain the cadence within 5 rpm, for longer than 5 s despite strong verbal encouragement was considered the criterion for test termination and an exhaustive effort Participants were blinded to the elapsed time, but they received visual feedback for the pedal cadence. Measures of breath-by-breath V O2 and beat-by-beat HR were obtained during each test. Ramp incremental test. The RI test consisted of a 50-W baseline for 4 minutes, followed by either 30-W min -1 (1 W every 2 s) (men) or 25-W min -1 (1 W every 2.4 s) (women) increase in PO. CPHYP. Each participant performed five constant-po TTE trials which ranged from approximately 1-20 min. The order of the TTE tests was randomly assigned. The first three TTE trials were 51

62 performed at 80, 95 and 110% of POpeak. Subsequently, the other two POs were determined to generate an even distribution of TTE amongst the five trials. Each test was preceded by a 4-min baseline at 20 W, followed by a step transition to the predetermined PO. This intensity was maintained until the participants were unable to continue despite strong verbal encouragement. Blood [La] was measured at 2 min of baseline and at the moment of exhaustion. CPSELF. Two 30-min rides were performed for determination of CPSELF. During the first test, participants were given up to 10 min to freely cycle at different POs using the cadence-independent mode of the cycle ergometer, so that they could choose the PO that they felt would be the highest sustainable PO for a prolonged time, the starting intensity was set at 50 W, and participants could either increase or decrease the PO by as little as 1 W. After the exercise intensity was chosen, participants rested on the bike for 10 min before starting the protocol, which consisted of a 20-W baseline for 4 min followed by a step-increase to the self-selected PO. Participants were blinded to the actual PO value in the ergometer. For the second test, participants were asked whether they wished to increase or decrease the PO from the previous test and the PO was adjusted accordingly. Participants did not receive any feedback related to their V O2, [La], HR, or PO from the previous 30-min ride. Thereafter, participants performed a second 30 min ride at their self-adjusted PO. CPSELF was determined as the PO that participants perceived to be their highest sustainable intensity of exercise. During both self-selected trials, blood [La] was measured at 2 min of baseline and at a 5-min intervals throughout the 30 minutes of exercise (i.e. 5 th, 10 th, 15 th, 20 th, 25 th, and 30 th min). MLSS. In addition to the 30-min rides at a self-selected PO, participants performed one to two 30- min constant-po rides for determination of the MLSS. In order to minimize the number of tests required for determination of MLSS, the PO was chosen based on the [La] responses of the CPSELF 52

63 measures. Each test started with a 4-min baseline at 20 W, followed by a step transition to a predetermined PO. Blood [La] was measured at 2 min of baseline and at a 5-min intervals throughout the 30 min of exercise (i.e. 5 th, 10 th, 15 th, 20 th, 25 th, and 30 th min). Subsequent rides were dependent on the [La] responses from the previous test as follows: if the [La] increased by > 1.0 mmol L -1 between the 10 th and 30 th min of exercise, the successive test was performed at 10 W below; if the [La] response increased by < 1.0 mmol L -1, the successive test was performed at 10 W above. Thus, the PO was either increased or decreased by 10 W until the highest PO eliciting a stable lactate (i.e., MLSS, < 1.0 mmol L -1 increase between the 10 th and 30 th min) was determined. Equipment and Measurements All exercise tests were performed on an electromagnetically braked cycle ergometer (Velotron Dynafit Pro, Racer Mate, Seattle, WA, USA). Breath-by-breath pulmonary gas exchange, ventilation and HR were continuously measured using a metabolic cart (Quark CPET, COSMED, Rome, Italy). Calibration was done before each test in accordance with manufacturer guidelines. Blood [La] was measured using a portable lactate analyzer (Lactate Scout, SensLab Gmb, Lepzig, Germany) through a 2-µl capillary sample of whole blood taken from a finger prick. Data Analyses Breath-by-breath V O2 data were edited as follows: data points that were 3 SD from the local mean were considered outliers and then removed (Lamarra et al. 1987); trials were interpolated on a second-by-second basis, time-aligned to the onset of exercise (i.e., time zero representing the onset of the constant-po or RI exercise), and averaged into 30-s time bins. V O2peak was considered as the highest 30-s V O2 average throughout the RI test. POpeak was established as the PO achieved at the moment of exhaustion. RCP was determined as the V O2 53

64 where end-tidal PCO2 began to decrease after a period of isocapnia (Whipp et al. 1989). This point was corroborated with the second breakpoint in the minute ventilation (V E)-to-V O2 relationship and examining systematic increase in the ventilatory equivalent of V CO2 (V E/V CO2). RCP was determined by two blinded expert reviewers. The average of the two values was used for analysis as long as all estimates were within 100 ml min -1. CPHYP was determined by fitting a two-parameter hyperbolic model (Hill 1993) to each subject s power-tte relationship (i.e., POs and correspondents times to exhaustion) using nonlinear least squares regression analysis, as follows: t = W / (PO CP) where t is time to exhaustion (s), W is the anaerobic work capacity (J), CP is the critical power (W), and PO is the predetermined PO (W). The goodness of fit for the hyperbolic model was determined as the 95% confidence interval for CP. All data editing, processing, and modeling were performed using OriginLab version 9.2 (OriginLab, Northampton, MA). Statistical Analyses Data are presented as mean ± SD. A one-way repeated-measures ANOVA was used to determine statistical significance for the POs associated to CPHYP, CPSELF and MLSS, as well as the V O2 associated to RCP, CPSELF, and MLSS. Bland-Altman plots were used to assess the limits of agreement (LOA) between the POs at CPHYP, CPSELF, and MLSS, and one-sample Z-tests were used to determine whether the average difference between values (i.e., bias) was significantly different from zero. Two-way repeated-measures ANOVA was used to determine whether there was a steady-state in the V O2 response between the 10 th and the 30 th min of exercise during the ride at MLSS and CPSELF, as well as to determine statistical significance for the HR and [La] 54

65 responses. All statistical analyses were performed using SPSS version 23.0 (SPSS, Inc., Chicago, IL). Statistical significance was set as an alpha level less than Results RI test. Group mean V O2peak and POpeak were 4.17 ± 0.68 L min -1 and 376 ± 54 W, respectively. The group mean V O2 associated to RCP (3.59 ± 0.55 L min -1 ), CPSELF (3.43 ± 0.62 L min -1 ), and MLSS (3.48 ± 0.60 L min -1 ) were not significantly different (p>0.05). CPHYP, CPSELF, and MLSS. Table 1 displays individual and mean PO values estimated from CPHYP as well as determined from CPSELF and MLSS. There were no differences between the POs determined from CPSELF and MLSS (p>0.05); however, the PO associated with CPHYP was greater than both CPSELF and MLSS (p<0.05). Figure 1 displays Bland-Altman plots with the agreement between the participants PO values derived from MLSS and CPSELF (left panel), and CPHYP and CPSELF (right panel). The comparison between measures presented the same range of LOA (MLSS vs CPSELF: - 20 to 20 W; CPHYP vs CPSELF: -40 to 0 W). However, as previously stated, CPHYP estimations were consistently greater than CPSELF. Compared to MLSS, PO values associated to CPSELF presented the smallest difference between measures within the participants (i.e., mean bias = 0 W, p>0.05). A significant bias (- 20 W, p<0.05) between measures of CPHYP and CPSELF was observed. Figure 2 displays the mean V O2 as well as HR responses for rides at MLSS and CPSELF. Group mean [La] at the 10 th and 30 th min mark during the 30-min rides at CPSELF were 4.2 ± 1.5 mmol L - 1 and 6.4 ± 2.0 mmol L -1, respectively. Whereas group mean [La] at the 10 th and 30 th min mark at the MLSS were 3.7 ± 1.3 mmol L -1 and 4.4 ± 1.5 mmol L -1. The group mean difference in [La] between the 30 th and 10 th min was 1.1 ± 0.7 mmol L -1 and 0.8 ± 0.2 mmol L -1 for CPSELF and 55

66 MLSS, respectively. The mean V O2 response was similar (p>0.05) for CPSELF and MLSS at both the 10 th and the 30 th min of exercise. Moreover, the mean V O2 responses between the 10 th and the 30 th min was not different in both conditions (i.e., CPSELF and MLSS) (p>0.05; Table 2). Group mean HR response during the last 20 minutes of rides at CPSELF and MLSS were also not different (p>0.05). Discussion The present study compared the PO values derived from CPHYP, CPSELF, and MLSS, as well as the V O2, [La], and HR responses during 30-min rides at CPSELF and MLSS. The main results were: i) CPSELF and MLSS provided the same mean PO (Table 1), as well as a mean difference between measures (i.e., bias) equal to zero (Figure 1); ii) both CPSELF and MLSS yielded steady-state responses in V O2 and HR that were not different over the last 20 min of the 30-min rides (p>0.05; Figure 2 and Table 2); iii) CPHYP estimations were greater than both CPSELF and MLSS; and iv) CPHYP consistently overestimated the PO at which V O2 and [La] were stable (i.e., MLSS) (Table 1). Scherr and colleagues (2013) reported that individuals were capable of perceiving metabolic changes during incremental exercise and identifying specific intensities associated with the traditional exercise intensity domain schema. The present study shed light on this hypothesis by examining whether individuals self-predicted highest sustainable PO (i.e., CPSELF) would be associated with their highest metabolic steady-state. Furthermore, this intensity was also compared to other intensity markers that are thought to reflect this important boundary (i.e., CPHYP and MLSS). Relative to CPHYP, CPSELF was significantly lower (p<0.05, bias = -20 W), however, CPSELF and MLSS presented similar mean PO (with no significant bias between the measures). 56

67 Additionally, the V O2, [La], and HR responses between CPSELF and MLSS were not different (p>0.05), confirming that individuals are capable of perceiving and identifying their highest PO associated with metabolic steady-state. In accordance with Scherr et al. (2013), these data support the contention that, at least in a group of moderately trained individuals, CPSELF is an effective strategy for exercise intensity stratification. To our knowledge, no study has compared the PO as well as physiological responses from a selfselected prediction trial to those of MLSS. Previous work attempted to link the PO obtained from a self-selected 30-min time trial to the PO associated with RCP derived from a ramp incremental test (Perrey et al. 2003; Groslambert et al. 2004). However, the authors compared the average PO during the 30-min time trials to the PO associated to RCP during the RI test. Such analysis would be affected by the characteristics of the increase in PO and not transferrable to the highest sustainable PO during constant load trial. Nevertheless, the present data support the hypothesis that individuals are capable of predicting the highest point at which [La] production and elimination are in equilibrium, representing the exercise intensity that yields the maximal metabolic steady state (i.e. boundary between heavy and very heavy intensity domains). In the present study, all participants had previous cycling experience. It could be argued that this previous experience improved their ability to self-select a PO reflective of the maximal metabolic steady-state. However, it should be noted that although the participants were experienced cyclists, many of them were not familiar with the concept of how a PO value on a cycle ergometer translates to the road (e.g., bike gear). Additionally, participants were blinded to PO values to constrain PO selection to perceived effort. Interestingly, even under these conditions, the participants CPSELF was closely associated with their maximal metabolic steady-state (as corroborated by MLSS). This finding has important implications from both a training and research testing perspective. For 57

68 example, it is known that measures of CP and MLSS require multiple tests to be determined, and both have been used to estimate the highest sustainable PO, and to characterize aerobic fitness (Moritani et al. 1981; devries et al. 1982; Poole et al. 1988; Poole et al. 1990; Housh et al. 1991; Jenkins and Quigley 1992). However, if participants are capable of self-selecting a PO that is very close to the expected MLSS, then the number of repetitions needed for its determination could be reduced. This testing strategy may provide a useful tool for researchers to minimize the amount of time needed during some testing protocols (i.e., MLSS), as well as for coaches prescribing exercise intensities when access to the adequate equipment to assess metabolic variables is not available. Collectively, the present findings indicate that participants perception of effort accurately represents physiological events associated to exercise intensity thresholds, and questions the usefulness of measuring CP from a practical perspective. As described in a previous report (Mattioni Maturana et al. 2016), CPHYP estimations accurately measured the maximal physiological steady-state in only one participant. Since exercise was terminated if [La] exceeded this maximum criterion, few individuals completed the full 30-min rides at CPHYP. On the contrary, although the group mean [La] for CPSELF between the 10 th and 30 th min was not different (p>0.05), the mean [La] was slightly above the criterion to be considered stable (i.e., 1.1 ± 0.7 mmol L -1 ). This occurred because two individuals determined their CPSELF at 19 and 20 W above MLSS. However, even with the inclusion of these two individuals, CPSELF estimations were still below CPHYP. In conclusion, CPSELF not only provided the same mean PO as MLSS, but also was characterized by similar metabolic responses (i.e. V O2, [La], and HR). While CPHYP requires multiple tests to be estimated, the present study showed that it is possible to predict the PO that represents the boundary between the heavy and the very heavy exercise intensity domains within two self- 58

69 selected 30-min rides (i.e. CPSELF). Thus, CPSELF may be used as an alternative approach for determination of the highest exercise intensity that yields physiological steady state. 59

70 References Beaver, W.L., Wasserman, K., and Whipp, B.J A new method for detecting anaerobic threshold by gas exchange. J Appl Physiol (1985) 60: devries, H.A., Moritani, T., Nagata, A., and Magnussen, K The relation between critical power and neuromuscular fatigue as estimated from electromyographic data. Ergonomics 25: Groslambert, A., Grappe, F., Bertucci, W., Perrey, S., Girard, A.J., and Rouillon, J.D A perceptive individual time trial performed by triathletes to estimate the anaerobic threshold. A preliminary study. J Sports Med Phys Fitness 44: Heck, H., Mader, A., Hess, G., Mucke, S., Muller, R., and Hollmann, W Justification of the 4-mmol/l lactate threshold. Int J Sports Med 6: Hill, D.W The critical power concept. A review. Sports Med 16: Housh, T.J., Devries, H.A., Housh, D.J., Tichy, M.W., Smyth, K.D., and Tichy, A.M The relationship between critical power and the onset of blood lactate accumulation. J Sports Med Phys Fitness 31: Jenkins, D.G. and Quigley, B.M Endurance training enhances critical power. Med Sci Sports Exerc 24: Keir, D.A., Benson, A.P., Love, L.K., Robertson, T.C., Rossiter, H.B., and Kowalchuk, J.M Influence of muscle metabolic heterogeneity in determining the Vo2p kinetic response to rampincremental exercise. J Appl Physiol 120: Keir, D.A., Fontana, F.Y., Robertson, T.C., Murias, J.M., Paterson, D.H., Kowalchuk, J.M., and Pogliaghi, S Exercise Intensity Thresholds: Identifying the Boundaries of Sustainable Performance. Med Sci Sports Exerc 47:

71 Lamarra, N., Whipp, B.J., Ward, S.A., and Wasserman, K Effect of interbreath fluctuations on characterizing exercise gas exchange kinetics. J Appl Physiol 62: Mattioni Maturana, F., Keir, D.A., McLay, K.M., and Murias, J.M Can measures of critical power precisely estimate the maximal metabolic steady state? Appl Physiol Nutr Metab. Moritani, T., Nagata, A., devries, H.A., and Muro, M Critical power as a measure of physical work capacity and anaerobic threshold. Ergonomics 24: Perrey, S., Grappe, F., Girard, A., Bringard, A., Groslambert, A., Bertucci, W., and Rouillon, J.D Physiological and metabolic responses of triathletes to a simulated 30-min time-trial in cycling at self-selected intensity. Int J Sports Med 24: Poole, D.C., Burnley, M., Vanhatalo, A., Rossiter, H.B., and Jones, A.M Critical Power: An Important Fatigue Threshold in Exercise Physiology. Med Sci Sports Exerc. Poole, D.C., Ward, S.A., Gardner, G.W., and Whipp, B.J Metabolic and respiratory profile of the upper limit for prolonged exercise in man. Ergonomics 31: Poole, D.C., Ward, S.A., and Whipp, B.J The effects of training on the metabolic and respiratory profile of high-intensity cycle ergometer exercise. Eur J Appl Physiol Occup Physiol 59: Scherr, J., Wolfarth, B., Christle, J.W., Pressler, A., Wagenpfeil, S., and Halle, M Associations between Borg's rating of perceived exertion and physiological measures of exercise intensity. Eur J Appl Physiol 113: Scheuermann, B.W. and Kowalchuk, J.M Attenuated respiratory compensation during rapidly incremented ramp exercise. Respir Physiol 114: Skinner, J.S. and McLellan, T.M The transition from aerobic to anaerobic metabolism. Res Q Exerc Sport 51:

72 Svedahl, K. and MacIntosh, B.R Anaerobic threshold: the concept and methods of measurement. Can J Appl Physiol 28: Whipp, B.J., Davis, J.A., and Wasserman, K Ventilatory control of the 'isocapnic buffering' region in rapidly-incremental exercise. Respir Physiol 76:

73 Table 1. PO values (W) derived from CPHYP, CPSELF, and MLSS. Participant CPHYP CPSELF MLSS Mean 253* SD *Denotes significant difference from MLSS (p < 0.05). 63

74 Table 2. Group mean V O2 (L min -1 ) and HR (beats min -1 ) during 30-min rides at CPSELF and MLSS. V O2 HR 10 th min 30 th min 10 th min 30 th min CPSELF 3.33 ± ± ± ± 11 MLSS 3.44 ± ± ± ± 12 64

75 Figure 1. Bland-Altman plots displaying the agreement between individual measures of MLSS and CPSELF (left panel), and CPHYP and CPSELF (right panel). The differences between measures (y-axis) are plotted as a function of the mean of the two measures (x-axis) in absolute values (W). The mean difference (i.e. bias) is represented by the horizontal dashed line, whereas the limits of agreement (mean ± 2 SD) are represented by the paired horizontal dotted lines. 65

76 Figure 2. Group mean (with SD bars; + SD represents MLSS, and SD represents CPSELF.) V O2 (left panel) and HR (right panel) responses during the 30-min rides at MLSS and CPSELF, plotted as a function of time (min). The dashed vertical lines represent the onset of constant-power output exercise following baseline. 66

77 CHAPTER 4 Conclusions The concept of CP has been widely investigated since the work of Monod and Scherrer (1965), and then firstly applied to cycling by Moritani et al. (1981). The authors proposed that the asymptote from the power-time relationship represented the highest intensity at which exercise could be sustained for a prolonged time. In this regard, a distinction should be made between estimations of CP and the concept of CP. Whereas the former is an estimation subject to error and variability, the latter can be associated to physiological steady-state (Poole et al. 1988; Poole et al. 1990). Thus, CP should theoretically reflect the upper boundary of exercise intensity at which a metabolic steady-state can be achieved and sustained, and beyond which (i.e. very heavy intensity domain) time-to-exhaustion is predictable. In the first manuscript, the two methods used for estimation of CP (i.e. CPHYP and CP3MIN) resulted in similar mean POs that were both above MLSS. Even if the concept of CP was to be dissociated from that of physiological steady-state, the large variability between measures detracts from the practical applicability of performing CP tests, as over- or under-prediction of this exercise threshold intensity would result in performance being unsustainable or below the subject s capabilities, respectively. Thus, it is important to highlight that even though the concept of CP should represent the highest intensity of metabolic stability, its estimation might not be accurate, as suggested by the data presented in this thesis. Also, CP estimations are highly influenced by both protocol design and modelling strategies (Bishop et al. 1998b). Therefore, given the limitations of CP estimations as well as the time-consuming and costly protocol of MLSS, the CPSELF approach may be a promising method to identify an individual s highest sustainable metabolic steady-state. This physiological boundary demarcating the highest PO of steady-state exercise has important implications in aerobic fitness assessment as 67

78 well as in intensity domains determination for exercise prescription, for both performance and clinical population. Coaches and researchers should consider the potential benefits of including CPSELF when determination of exercise intensity thresholds plays an important role in the outcome of training interventions. However, better understanding of this topics warrants further investigations. Limitations A limitation of the present study lies in the determination of the highest exercise intensity that elicits a stable V O2 response. Prolonged rides of 30-minutes were performed at the intensity associated to MLSS as well as at 10 W above. Although the rides performed at the PO associated to MLSS were found to represent the highest intensity of stable V O2, thus characterizing the critical metabolic rate, it could be argued that narrower limits of POs should also be performed (i.e., < 10 W) in order to define this concept more precisely. The second manuscript does not present RPE values related to CPSELF. These data are useful for monitoring training interventions when the access to the adequate equipment (e.g., [La] analyzer) is not possible. In this regard, although the population studied in the present thesis were not professional, but experienced cyclists, further investigations should test whether or not the agreement between CPSELF and the maximal physiological steady state is reproducible in participants with no cycling experience. Despite the interesting results, it is still not possible to extrapolate the present results to a more general population. Even though the criterion used for the determination of the MLSS (i.e., [La] 1.0 mmol L -1 ) is the most accepted in the literature, it could be argued that a narrower [La] should be used to establish MLSS. However, the agreement of the ventilatory responses between MLSS and the 68

79 anaerobic threshold (defined as the RCP), as previously described by Keir et al. (2015), support the use of this criterion. Future directions A concept that still needs to be determined is the development of a mathematical model that could precisely retrieve a PO associated to RCP from a RI test that would elicit the highest physiological steady state during constant-load exercise. Such analysis is still challenging due to the heterogeneity of RI protocols as well as physiological responses from different populations. Regarding the power-time relationship, Bishop and colleagues (1998b) studied the influence of shorter compared to longer TTE trials on the CP estimation. However, the authors did not perform any measure of the participants maximal metabolic steady state to compare the results. Therefore, future research should investigate the influence of the range of TTE trials on the CP hyperbolic function in estimating the upper boundary of the heavy exercise intensity domain. Based on that, it would be possible to aim for the least amount of tests needed to estimate CP with precision. Moreover, in case CP is not to be related to a physiological boundary of exercise, such ranges in TTE and their estimations should also be compared to CPHYP (i.e., 5 TTE for estimation of CP). Perhaps, only two tests are needed in order to get the same value as CPHYP. Also, CPSELF should be tested with individuals with different backgrounds (i.e., in the present investigation it was tested experienced cyclists only), as well as different age and training status. Thus, it could become an important tool in a clinical setting, where maximal exercise tests are not doable. In this context, the use of RPE would complement and support 69

80 the implementation of CPSELF. Perhaps, different populations will present different RPE values when identifying their maximal sustainable exercise intensity. 70

81 BIBLIOGRAPHY Acevedo, E.O. and Goldfarb, A.H Increased training intensity effects on plasma lactate, ventilatory threshold, and endurance. Med Sci Sports Exerc 21: Aunola, S. and Rusko, H Does anaerobic threshold correlate with maximal lactate steadystate? J Sports Sci 10: Barstow, T.J., Casaburi, R., and Wasserman, K O2 uptake kinetics and the O2 deficit as related to exercise intensity and blood lactate. J Appl Physiol 75: Beaver, W.L., Wasserman, K., and Whipp, B.J A new method for detecting anaerobic threshold by gas exchange. J Appl Physiol (1985) 60: Beneke, R Methodological aspects of maximal lactate steady state-implications for performance testing. Eur J Appl Physiol 89: Beneke, R., Hutler, M., and Leithauser, R Maximal lactate-steady-state independent of performance. Med Sci Sports Exerc 32: Bergstrom, H.C., Housh, T.J., Zuniga, J.M., Traylor, D.A., Lewis, R.W., Camic, C.L., Schmidt, R.J., and Johnson, G.O Responses during exhaustive exercise at critical power determined from the 3-min all-out test. J Sports Sci 31: Binder, R.K., Wonisch, M., Corra, U., Cohen-Solal, A., Vanhees, L., Saner, H., and Schmid, J.P Methodological approach to the first and second lactate threshold in incremental cardiopulmonary exercise testing. Eur J Cardiovasc Prev Rehabil 15: Bishop, D. and Jenkins, D.G The influence of recovery duration between periods of exercise on the critical power function. Eur J Appl Physiol Occup Physiol 72: Bishop, D., Jenkins, D.G., and Howard, A. 1998b. The critical power function is dependent on the duration of the predictive exercise tests chosen. Int J Sports Med 19:

82 Boone, J. and Bourgois, J The oxygen uptake response to incremental ramp exercise: methodogical and physiological issues. Sports Med 42: Brickley, G., Doust, J., and Williams, C.A Physiological responses during exercise to exhaustion at critical power. Eur J Appl Physiol 88: Brooks, G.A Anaerobic threshold: review of the concept and directions for future research. Med Sci Sports Exerc 17: Bull, A.J., Housh, T.J., Johnson, G.O., and Perry, S.R Effect of mathematical modeling on the estimation of critical power. Med Sci Sports Exerc 32: Burnley, M., Doust, J.H., and Vanhatalo, A A 3-min all-out test to determine peak oxygen uptake and the maximal steady state. Med Sci Sports Exerc 38: Costill, D.L., Thomason, H., and Roberts, E Fractional utilization of the aerobic capacity during distance running. Med Sci Sports Exerc 5: Davies, C. and Sandstrom, E Maximal mechanical power output and capacity of cyclists and young adults. Eur J Appl Physiol Occup Physiol 58: De Roia, G., Pogliaghi, S., Adami, A., Papadopoulou, C., and Capelli, C Effects of priming exercise on the speed of adjustment of muscle oxidative metabolism at the onset of moderateintensity step transitions in older adults. Am J Physiol Regul Integr Comp Physiol 302: R Dekerle, J., Baron, B., Dupont, L., Vanvelcenaher, J., and Pelayo, P Maximal lactate steady state, respiratory compensation threshold and critical power. Eur J Appl Physiol 89: Dekerle, J., Barstow, T.J., Regan, L., and Carter, H The critical power concept in all-out isokinetic exercise. J Sci Med Sport 17: Dekerle, J., Brickley, G., Hammond, A.J., Pringle, J.S., and Carter, H Validity of the twoparameter model in estimating the anaerobic work capacity. Eur J Appl Physiol 96:

83 devries, H.A., Moritani, T., Nagata, A., and Magnussen, K The relation between critical power and neuromuscular fatigue as estimated from electromyographic data. Ergonomics 25: Di Prampero, P., Atchou, G., Brückner, J.-C., and Moia, C The energetics of endurance running. Eur J Appl Physiol Occup Physiol 55: Di Prampero, P., Capelli, C., Pagliaro, P., Antonutto, G., Girardis, M., Zamparo, P., and Soule, R Energetics of best performances in middle-distance running. J Appl Physiol 74: Faude, O., Kindermann, W., and Meyer, T Lactate threshold concepts: how valid are they? Sports Med 39: Fontana, P., Boutellier, U., and Knöpfli-Lenzin, C Time to exhaustion at maximal lactate steady state is similar for cycling and running in moderately trained subjects. Eur J Appl Physiol 107: Freund, H., Oyono-Enguelle, S., Heitz, A., Marbach, J., Ott, C., Zouloumian, P., and Lampert, E Work rate-dependent lactate kinetics after exercise in humans. J Appl Physiol 61: Gaesser, G.A. and Poole, D.C The slow component of oxygen uptake kinetics in humans. Exerc Sport Sci Rev 24: Gastin, P. and Lawson, D Variable resistance all-out test to generate accumulated oxygen deficit and predict anaerobic capacity. Eur J Appl Physiol Occup Physiol 69: Groslambert, A., Grappe, F., Bertucci, W., Perrey, S., Girard, A.J., and Rouillon, J.D A perceptive individual time trial performed by triathletes to estimate the anaerobic threshold. A preliminary study. J Sports Med Phys Fitness 44:

84 Grossl, T., de Lucas, R.D., de Souza, K.M., and Guglielmo, L.G.A Time to exhaustion at intermittent maximal lactate steady state is longer than continuous cycling exercise. Appl Physiol Nutr Metab 37: Harnish, C.R., Swensen, T.C., and Pate, R.R Methods for estimating the maximal lactate steady state in trained cyclists: University of South Carolina. Haverty, M., Kenney, W.L., and Hodgson, J.L Lactate and gas exchange responses to incremental and steady state running. Br J Sports Med 22: Heck, H., Mader, A., Hess, G., Mucke, S., Muller, R., and Hollmann, W Justification of the 4-mmol/l lactate threshold. Int J Sports Med 6: Hill, A. and Lupton, H Muscular exercise, lactic acid, and the supply and utilization of oxygen. QjM: Hill, D.W The critical power concept. A review. Sports Med 16: Hopkins, W.G., Schabort, E.J., and Hawley, J.A Reliability of power in physical performance tests. Sports medicine 31: Housh, D.J., Housh, T.J., and Bauge, S.M The accuracy of the critical power test for predicting time to exhaustion during cycle ergometry. Ergonomics 32: Housh, T.J., Devries, H.A., Housh, D.J., Tichy, M.W., Smyth, K.D., and Tichy, A.M The relationship between critical power and the onset of blood lactate accumulation. J Sports Med Phys Fitness 31: Hurley, B., Hagberg, J.M., Allen, W.K., Seals, D.R., Young, J., Cuddihee, R., and Holloszy, J Effect of training on blood lactate levels during submaximal exercise. J Appl Physiol 56:

85 Jenkins, D., Kretek, K., and Bishop, D The duration of predicting trials influences time to fatigue at critical power. J Sci Med Sport 1: Jenkins, D.G. and Quigley, B.M Blood lactate in trained cyclists during cycle ergometry at critical power. Eur J Appl Physiol Occup Physiol 61: Jenkins, D.G. and Quigley, B.M Endurance training enhances critical power. Med Sci Sports Exerc 24: Jeukendrup, A., Saris, W.H., Brouns, F., and Kester, A.D A new validated endurance performance test. Med Sci Sports Exerc 28: Jones and Carter, H. 2000a. The effect of endurance training on parameters of aerobic fitness. Sports Med 29: Jones, A.M. and Carter, H. 2000b. The effect of endurance training on parameters of aerobic fitness. Sports medicine 29: Jones, A.M., Wilkerson, D.P., Vanhatalo, A., and Burnley, M Influence of pacing strategy on O2 uptake and exercise tolerance. Scand J Med Sci Sports 18: Joyner, M.J Modeling: optimal marathon performance on the basis of physiological factors. J Appl Physiol 70: Karsten, B., Jobson, S.A., Hopker, J., Passfield, L., and Beedie, C The 3-min test does not provide a valid measure of critical power using the SRM isokinetic mode. Int J Sports Med 35: Keir, D.A., Benson, A.P., Love, L.K., Robertson, T.C., Rossiter, H.B., and Kowalchuk, J.M Influence of muscle metabolic heterogeneity in determining the Vo2p kinetic response to rampincremental exercise. J Appl Physiol 120:

86 Keir, D.A., Fontana, F.Y., Robertson, T.C., Murias, J.M., Paterson, D.H., Kowalchuk, J.M., and Pogliaghi, S Exercise Intensity Thresholds: Identifying the Boundaries of Sustainable Performance. Med Sci Sports Exerc 47: Kumagai, S., Tanaka, K., Matsuura, Y., Matsuzaka, A., Hirakoba, K., and Asano, K Relationships of the anaerobic threshold with the 5 km, 10 km, and 10 mile races. Eur J Appl Physiol Occup Physiol 49: Lamarra, N., Whipp, B.J., Ward, S.A., and Wasserman, K Effect of interbreath fluctuations on characterizing exercise gas exchange kinetics. J Appl Physiol 62: Léger, L., Mercier, D., and Gauvin, L The relationship between% VO2max and running performance time. Sport and elite performers. Champaign, IL: Human Kinetics: Londeree, B Effect of training on lactate/ventilatory thresholds: a meta-analysis. Med Sci Sports Exerc 29: Londeree, B.R. and Ames, S.A Maximal steady state versus state of conditioning. Eur J Appl Physiol Occup Physiol 34: Margaria, R., Cerretelli, P., and Mangili, F Balance and kinetics of anaerobic energy release during strenuous exercise in man. J Appl Physiol 19: Mattioni Maturana, F., Keir, D.A., McLay, K.M., and Murias, J.M Can measures of critical power precisely estimate the maximal metabolic steady state? Appl Physiol Nutr Metab. McLellan, T.M. and Cheung, K.S A comparative evaluation of the individual anaerobic threshold and the critical power. Med Sci Sports Exerc 24: Monod, H. and Scherrer, J The Work Capacity of a Synergic Muscular Group. Ergonomics 8:

87 Moritani, T., Nagata, A., devries, H.A., and Muro, M Critical power as a measure of physical work capacity and anaerobic threshold. Ergonomics 24: Morton, R.H A 3-parameter critical power model. Ergonomics 39: Morton, R.H The critical power and related whole-body bioenergetic models. Eur J Appl Physiol 96: Neder, J.A., Jones, P.W., Nery, L.E., and Whipp, B.J The effect of age on the power/duration relationship and the intensity-domain limits in sedentary men. Eur J Appl Physiol 82: Overend, T.J., Cunningham, D.A., Paterson, D.H., and Smith, W.D Physiological responses of young and elderly men to prolonged exercise at critical power. Eur J Appl Physiol Occup Physiol 64: Palgi, Y., Gutin, B., Young, J., and Alejandro, D Physiologic and anthropometric factors underlying endurance performance in children. Int J Sports Med 5: Péronnet, F., Thibault, G., Rhodes, E.C., and McKenzie, D.C Correlation between ventilatory threshold and endurance capability in marathon runners. Med Sci Sports Exerc 19: Perrey, S., Grappe, F., Girard, A., Bringard, A., Groslambert, A., Bertucci, W., and Rouillon, J.D Physiological and metabolic responses of triathletes to a simulated 30-min time-trial in cycling at self-selected intensity. Int J Sports Med 24: Poole and Gaesser, G.A Response of ventilatory and lactate thresholds to continuous and interval training. J Appl Physiol 58: Poole and Jones, A.M Oxygen uptake kinetics. Compr Physiol. 77

88 Poole, D.C., Burnley, M., Vanhatalo, A., Rossiter, H.B., and Jones, A.M Critical Power: An Important Fatigue Threshold in Exercise Physiology. Med Sci Sports Exerc. Poole, D.C., Ward, S.A., Gardner, G.W., and Whipp, B.J Metabolic and respiratory profile of the upper limit for prolonged exercise in man. Ergonomics 31: Poole, D.C., Ward, S.A., and Whipp, B.J The effects of training on the metabolic and respiratory profile of high-intensity cycle ergometer exercise. Eur J Appl Physiol Occup Physiol 59: Pringle, J.S. and Jones, A.M Maximal lactate steady state, critical power and EMG during cycling. Eur J Appl Physiol 88: Ready, A.E. and Quinney, H.A Alterations in anaerobic threshold as the result of endurance training and detraining. Med Sci Sports Exerc 14: Ribeiro, J.P., Hughes, V., Fielding, R.A., Holden, W., Evans, W., and Knuttgen, H.G Metabolic and ventilatory responses to steady state exercise relative to lactate thresholds. Eur J Appl Physiol Occup Physiol 55: Sady, S., Katch, V., Freedson, P., and Weltman, A Changes in metabolic acidosis: evidence for an intensity threshold. J Sports Med Phys Fitness 20: Saiki, H., Margaria, R., and Cuttica, F Lactic acid production in submaximal work. Internationale Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie 24: Scheen, A., Juchmes, J., and Cession-Fossion, A Critical analysis of the anaerobic threshold during exercise at constant workloads. Eur J Appl Physiol Occup Physiol 46: Scherr, J., Wolfarth, B., Christle, J.W., Pressler, A., Wagenpfeil, S., and Halle, M Associations between Borg's rating of perceived exertion and physiological measures of exercise intensity. Eur J Appl Physiol 113:

89 Scheuermann, B.W. and Kowalchuk, J.M Attenuated respiratory compensation during rapidly incremented ramp exercise. Respir Physiol 114: Sjodin, B. and Svedenhag, J Applied physiology of marathon running. Sports Med 2: Skinner, J.S. and McLellan, T.M The transition from aerobic to anaerobic metabolism. Res Q Exerc Sport 51: Smith, J.C. and Hill, D.W Stability of parameter estimates derived from the power/time relationship. Can J Appl Physiol 18: Snyder, A., Woulfe, T., Welsh, R., and Foster, C A simplified approach to estimating the maximal lactate steady state. Int J Sports Med 15: Sperlich, B., Haegele, M., Thissen, A., Mester, J., and Holmberg, H.C Are peak oxygen uptake and power output at maximal lactate steady state obtained from a 3-min all-out cycle test? Int J Sports Med 32: Svedahl, K. and MacIntosh, B.R Anaerobic threshold: the concept and methods of measurement. Can J Appl Physiol 28: Tegtbur, U., Busse, M.W., and Braumann, K.M Estimation of an individual equilibrium between lactate production and catabolism during exercise. Med Sci Sports Exerc 25: Tokmakidis, S., Leger, L., Mercier, D., Peronnet, F., and Thibault, G New approaches to predict VO2 max and endurance from running performances. J Sports Med Phys Fitness 27: Urhausen, A., Coen, B., Weiler, B., and Kindermann, W Individual anaerobic threshold and maximum lactate steady state. Int J Sports Med 14:

90 Vanhatalo, A., Doust, J.H., and Burnley, M Determination of critical power using a 3-min all-out cycling test. Med Sci Sports Exerc 39: Wasserman, K., Whipp, B.J., Koyl, S.N., and Beaver, W.L Anaerobic threshold and respiratory gas exchange during exercise. J Appl Physiol 35: Whipp, B.J., Davis, J.A., and Wasserman, K Ventilatory control of the 'isocapnic buffering' region in rapidly-incremental exercise. Respir Physiol 76: Whipp, B.J., Rossiter, H.B., and Ward, S.A Exertional oxygen uptake kinetics: a stamen of stamina? Biochem Soc Trans 30: Whipp, B.J., Ward, S.A., and Rossiter, H.B Pulmonary O2 uptake during exercise: conflating muscular and cardiovascular responses. Med Sci Sports Exerc 37: Williams, C.A., Ratel, S., and Armstrong, N Achievement of Peak During a 90-s Maximal Intensity Cycle Sprint in Adolescents. Can J Appl Physiol 30: Wonisch, M., Hofmann, P., Fruhwald, F.M., Hoedl, R., Schwaberger, G., Pokan, R., von Duvillard, S.P., and Klein, W Effect of β1-selective adrenergic blockade on maximal blood lactate steady state in healthy men. Eur J Appl Physiol 87: Yeh, M.P., Gardner, R.M., Adams, T.D., Yanowitz, F.G., and Crapo, R.O "Anaerobic threshold": problems of determination and validation. J Appl Physiol 55: Yoshida, T., Suda, Y., and Takeuchi, N Endurance training regimen based upon arterial blood lactate: effects on anaerobic threshold. Eur J Appl Physiol Occup Physiol 49:

91 APPENDICES Appendix A: Letter of Consent 81

92 Human Performance Laboratory Telephone: (403) Letter of Consent TITLE: Multiple versus single test for calculating critical power. INVESTIGATORS: Dr. Juan M. Murias This consent form is only part of the process of informed consent. It should give you the basic idea of what the research is about and what your participation will involve. If you would like more detail about something mentioned here, or information not included here, please ask. Take the time to read this carefully and to understand any accompanying information. You will receive a copy of this form. BACKGROUND You are being invited to participate in a study that compares the determination of critical power results using a 5-visit constant-load trials to exhaustion approach, compared to a short version 3- min all-out test. Critical power (CP) demarcates sustainable from unsustainable exercise intensity and it is an important determinant of endurance performance as it represents the highest power 82