The goal of this review is to present a comprehensive survey of the many intriguing facets of creatine (Cr) and creatinine metabolism, encompassing the pathways and regulation of Cr biosynthesis an...

http://www.afboard.com/library/creatinemetabolism.pdf

Creatine and Creatinine Metabolism

The ability to monitor training is critical to the process of quantitating training periodization plans. To date, no method has proven successful in monitoring training during multiple types of exercise. High-intensity exercise training is particularly difficult to quantitate. In this study we evaluate the ability of the session rating of perceived exertion (RPE) method to quantitate training during non-steady state and prolonged exercise compared with an objective standard based on heart rate (HR). In a 2-part design, subjects performed steady state and interval cycle exercise or practiced basketball. Exercise bouts were quantitated using both the session RPE method and an objective HR method. During cycle exercise, the relationship between the exercise score derived using the session RPE method and the HR method was highly consistent, although the absolute score was significantly greater with the session RPE method. During basketball, there was a consistent relationship between the 2 methods of monitoring exercise, although the absolute score was also significantly greater with the session RPE method. Despite using different subjects in the 2 parts of the study, the regression relationships between the session RPE method and the HR method were nearly overlapping, suggesting the broad applicability of this method. We conclude that the session RPE method is a valid method of quantitating exercise training during a wide variety of types of exercise. As such, this technique may hold promise as a mode and intensity-independent method of quantitating exercise training and may provide a tool to allow the quantitative evaluation of training periodization plans.

A new approach to monitoring exercise training.

Background There is dogma that higher training load causes higher injury rates. However, there is also evidence that training has a protective effect against injury. For example, team sport athletes who performed more than 18 weeks of training before sustaining their initial injuries were at reduced risk of sustaining a subsequent injury, while high chronic workloads have been shown to decrease the risk of injury. Second, across a wide range of sports, well-developed physical qualities are associated with a reduced risk of injury. Clearly, for athletes to develop the physical capacities required to provide a protective effect against injury, they must be prepared to train hard. Finally, there is also evidence that under-training may increase injury risk. Collectively, these results emphasise that reductions in workloads may not always be the best approach to protect against injury.

Main thesis This paper describes the ‘Training-Injury Prevention Paradox’ model; a phenomenon whereby athletes accustomed to high training loads have fewer injuries than athletes training at lower workloads. The Model is based on evidence that non-contact injuries are not caused by training per se , but more likely by an inappropriate training programme. Excessive and rapid increases in training loads are likely responsible for a large proportion of non-contact, soft-tissue injuries. If training load is an important determinant of injury, it must be accurately measured up to twice daily and over periods of weeks and months (a season). This paper outlines ways of monitoring training load (‘internal’ and ‘external’ loads) and suggests capturing both recent (‘acute’) training loads and more medium-term (‘chronic’) training loads to best capture the player's training burden. I describe the critical variable—acute:chronic workload ratio—as a best practice predictor of training-related injuries. This provides the foundation for interventions to reduce players risk, and thus, time-loss injuries.

Summary The appropriately graded prescription of high training loads should improve players’ fitness, which in turn may protect against injury, ultimately leading to (1) greater physical outputs and resilience in competition, and (2) a greater proportion of the squad available for selection each week.

https://bjsm.bmj.com/content/bjsports/50/5/273.full.pdf

The training—injury prevention paradox: should athletes be training smarter and harder?

Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on "Monitoring Athlete Training Loads-The Hows and the Whys" was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.

/pdf/monitoring-athlete-training-loads-consensus-statement-3fhlq6hr7y.pdf

Monitoring Athlete Training Loads: Consensus Statement.

During the last nearly 50 years, the blood lactate curve and lactate thresholds (LTs) have become important in the diagnosis of endurance performance. An intense and ongoing debate emerged, which was mainly based on terminology and/or the physiological background of LT concepts. The present review aims at evaluating LTs with regard to their validity in assessing endurance capacity. Additionally, LT concepts shall be integrated within the ‘aerobic-anaerobic transition’ — a framework which has often been used for performance diagnosis and intensity prescriptions in endurance sports. Usually, graded incremental exercise tests, eliciting an exponential rise in blood lactate concentrations (bLa), are used to arrive at lactate curves. A shift of such lactate curves indicates changes in endurance capacity. This very global approach, however, is hindered by several factors that may influence overall lactate levels. In addition, the exclusive use of the entire curve leads to some uncertainty as to the magnitude of endurance gains, which cannot be precisely estimated. This deficiency might be eliminated by the use of LTs. The aerobic-anaerobic transition may serve as a basis for individually assessing endurance performance as well as for prescribing intensities in endurance training. Additionally, several LT approaches may be integrated in this framework. This model consists of two typical breakpoints that are passed during incremental exercise: the intensity at which bLa begin to rise above baseline levels and the highest intensity at which lactate production and elimination are in equilibrium (maximal lactate steady state [MLSS]). Within this review, LTs are considered valid performance indicators when there are strong linear correlations with (simulated) endurance performance. In addition, a close relationship between LT and MLSS indicates validity regarding the prescription of training intensities. A total of 25 different LT concepts were located. All concepts were divided into three categories. Several authors use fixed bLa during incremental exercise to assess endurance performance (category 1). Other LT concepts aim at detecting the first rise in bLa above baseline levels (category 2). The third category consists of threshold concepts that aim at detecting either the MLSS or a rapid/distinct change in the inclination of the blood lactate curve (category 3). Thirty-two studies evaluated the relationship of LTs with performance in (partly simulated) endurance events. The overwhelming majority of those studies reported strong linear correlations, particularly for running events, suggesting a high percentage of common variance between LT and endurance performance. In addition, there is evidence that some LTs can estimate the MLSS. However, from a practical and statistical point of view it would be of interest to know the variability of individual differences between the respective threshold and the MLSS, which is rarely reported. Although there has been frequent and controversial debate on the LT phenomenon during the last three decades, many scientific studies have dealt with LT concepts, their value in assessing endurance performance or in prescribing exercise intensities in endurance training. The presented framework may help to clarify some aspects of the controversy and may give a rationale for performance diagnosis and training prescription in future research as well as in sports practice.

Lactate threshold concepts: how valid are they?

The relationships between the mean intensity of a training season, training volume and frequency, and the variations in performance were studied in a group of 18 elite swimmers. Additionally, diffe...

Effects of Training on Performance in Competitive Swimming

ATLAOUI, D., M. DUCLOS, C. GOUARNE, L. LACOSTE, F. BARALE, and J-C. CHATARD. The 24-h Urinary Cortisol/Cortisone Ratio for Monitoring Training in Elite Swimmers. Med. Sci. Sports Exerc., Vol. 36, No. 2, pp. 218–224, 2004.PurposeThe effect of training variations on 24-h urinary cortisol/corti

The 24-h urinary cortisol/cortisone ratio for monitoring training in elite swimmers.

The aim of this study was to model the residual effects of training on the swimming performance and to compare a model that includes threshold saturation (MM) with the Banister model (BM). Seven Olympic swimmers were studied over a period of 4 +/- 2 years. For 3 training loads (low-intensity w(LIT), high-intensity w(HIT), and strength training w(ST)), 3 residual training effects were determined: short-term (STE) during the taper phase (i.e., 3 weeks before the performance [weeks 0, 1, and 2]), intermediate-term (ITE) during the intensity phase (weeks 3, 4, and 5), and long-term (LTE) during the volume phase (weeks 6, 7, and 8). ITE and LTE were positive for w(HIT) and w(LIT), respectively (p < 0.05). Low-intensity training load during taper was related to performances by a parabolic relationship (p < 0.05). Different quality measures indicated that MM compares favorably with BM. Identifying individual training thresholds may help individualize the distribution of training loads.

https://www.hal.inserm.fr/inserm-00149779/document

Modeling the residual effects and threshold saturation of training: a case study of Olympic swimmers.

The aim of this study was to carry out a statistical analysis of the Banister model to verify how useful it is in monitoring the training programmes of elite swimmers. The accuracy, the ill-conditioning and the stability of this model were thus investigated. The training loads of nine elite swimmers, measured over one season, were related to performances with the Banister model. First, to assess accuracy, the 95% bootstrap confidence interval (95% CI) of parameter estimates and modelled performances were calculated. Second, to study ill-conditioning, the correlation matrix of parameter estimates was computed. Finally, to analyse stability, iterative computation was performed with the same data but minus one performance, chosen at random. Performances were related to training loads for all participants (R 2 = 0.79 ± 0.13, P < 0.05) and the estimation procedure seemed to be stable. Nevertheless, the range of 95% CI values of the most useful parameters for monitoring training was wide: τ a  = 38 (17...

https://www.hal.inserm.fr/inserm-00149782/document

Assessing the limitations of the Banister model in monitoring training.

This study was conducted to examine the effects of creatine (Cr) supplementation on sprint swimming performance and energy metabolism. Twenty highly trained swimmers (9 female, 11 male) were tested for blood ammonia and for blood lactate after the 25-, 50-, and 100-m performance in their best stroke on two occasions 7 d apart. After the first trial, subjects were evenly and randomly assigned to either a creatine (5 g creatine monohydrate 4 times per day for 5 d) or a placebo group (same dosage of a lactose placebo) in a double-blind research design. No significant differences in performance times were observed between trials. Post-exercise blood ammonia concentration decreased in the 50- and 100-m trials in the creatine group and in the 50-m trial in the placebo group. The supplementation period had no effect on post-exercise blood lactate. Therefore, creatine supplementation cannot be considered as an ergogenic aid for sprint performance in highly trained swimmers although adenine nucleotide degradation may be reduced during sprint exercise after 5 d of creatine ingestion.

Creatine supplementation does not improve sprint performance in competitive swimmers.

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