Individuals with lower limb loss often walk with altered/asymmetric movement mechanics, postulated as a catalyst for development of low back and knee pain. Here, the authors simultaneously investigated trunk-pelvic movement patterns and lower limb joint kinematics and kinetics among 38 males with traumatic, unilateral lower limb loss (23 transtibial and 15 transfemoral), and 15 males without limb loss, at a self-selected and 2 standardized (1.0 and 1.6 m/s) speeds. Individuals with versus without lower limb loss walked with greater trunk range of motion in the frontal and transverse planes at all speeds (despite ∼10% slower self-selected speeds). At all speeds, individuals with versus without limb loss exhibited +29% larger medial ground reaction forces, and at 1.6 m/s also exhibited +50% to 110% larger vertical hip power generation, +27% to 80% larger vertical hip power absorption, and +21% to 90% larger medial–lateral hip power absorption. Moreover, pervasive biomechanical differences between transtibial versus transfemoral limb loss identify amputation-level movement strategies. Overall, greater demands on the musculoskeletal system across walking speeds, particularly at the hip, knee, and low back, highlight potential risk factors for the development/recurrence of prevalent secondary musculoskeletal conditions (eg, joint degeneration and pain) following limb loss.
Joseph G. Wasser, Julian C. Acasio, Ross H. Miller, and Brad D. Hendershot
Hugh H.K. Fullagar, Rob Duffield, Sabrina Skorski, Aaron J. Coutts, Ross Julian, and Tim Meyer
While the effects of sleep loss on performance have previously been reviewed, the effects of disturbed sleep on recovery after exercise are less reported. Specifically, the interaction between sleep and physiological and psychological recovery in team-sport athletes is not well understood. Accordingly, the aim of the current review was to examine the current evidence on the potential role sleep may play in postexercise recovery, with a tailored focus on professional team-sport athletes. Recent studies show that team-sport athletes are at high risk of poor sleep during and after competition. Although limited published data are available, these athletes also appear particularly susceptible to reductions in both sleep quality and sleep duration after night competition and periods of heavy training. However, studies examining the relationship between sleep and recovery in such situations are lacking. Indeed, further observational sleep studies in team-sport athletes are required to confirm these concerns. Naps, sleep extension, and sleep-hygiene practices appear advantageous to performance; however, future proof-of-concept studies are now required to determine the efficacy of these interventions on postexercise recovery. Moreover, more research is required to understand how sleep interacts with numerous recovery responses in team-sport environments. This is pertinent given the regularity with which these teams encounter challenging scenarios during the course of a season. Therefore, this review examines the factors that compromise sleep during a season and after competition and discusses strategies that may help improve sleep in team-sport athletes.
Anne Hecksteden, Werner Pitsch, Ross Julian, Mark Pfeiffer, Michael Kellmann, Alexander Ferrauti, and Tim Meyer
Assessment of muscle recovery is essential for the daily fine-tuning of training load in competitive sports, but individual differences may limit the diagnostic accuracy of group-based reference ranges. This article reports an attempt to develop individualized reference ranges using a Bayesian approach comparable to that developed for the Athlete Biological Passport.
Urea and creatine kinase (CK) were selected as indicators of muscle recovery. For each parameter, prior distributions and repeated-measures SDs were characterized based on data of 883 squad athletes (1758 data points, 1–8 per athlete, years 2013–2015). Equations for the individualization procedure were adapted from previous material to allow for discrimination of 2 physiological states (recovered vs nonrecovered). Evaluation of classificatory performance was carried out using data from 5 consecutive weekly microcycles in 14 elite junior swimmers and triathletes. Blood samples were collected every Monday (recovered) and Friday according to the repetitive weekly training schedule over 5 wk. On the group level, changes in muscle recovery could be confirmed by significant differences in urea and CK and validated questionnaires. Group-based reference ranges were derived from that same data set to avoid overestimating the potential benefit of individualization.
For CK, error rates were significantly lower with individualized classification (P vs group-based: test-pass error rate P = .008; test-fail error rate P < .001). For urea, numerical improvements in error rates failed to reach significance.
Individualized reference ranges seem to be a promising tool to improve accuracy of monitoring muscle recovery. Investigating application to a larger panel of indicators is warranted.