J. Ruddy
Australian Catholic University
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Medicine and Science in Sports and Exercise | 2016
Ryan Timmins; J. Ruddy; Joel Presland; Nirav Maniar; Anthony Shield; Morgan D. Williams; David A. Opar
PURPOSE To determine the architectural adaptations of the biceps femoris long head (BFlh) after concentric or eccentric strength training interventions and the time course of adaptation during training and detraining. METHODS Participants in this intervention (concentric training group [n = 14], eccentric training group [n = 14], male subjects) completed a 4-wk control period, followed by 6 wk of either concentric- or eccentric-only knee flexor training on an isokinetic dynamometer and finished with 28 d of detraining. Architectural characteristics of BFlh were assessed at rest and during graded isometric contractions using two-dimensional ultrasonography at 28 d prebaseline; baseline; and days 14, 21, and 42 of the intervention and then again after 28 d of detraining. RESULTS BFlh fascicle length was significantly longer in the eccentric training group (P < 0.05; d range, 2.65-2.98) and shorter in the concentric training group (P < 0.05; d range, -1.62 to -0.96) after 42 d of training compared with baseline at all isometric contraction intensities. After the 28-d detraining period, BFlh fascicle length was significantly reduced in the eccentric training group at all contraction intensities compared with the end of the intervention (P < 0.05; d range, -1.73 to -1.55). There was no significant change in fascicle length of the concentric training group after the detraining period. CONCLUSIONS These results provide evidence that short-term resistance training can lead to architectural alterations in the BFlh. In addition, the eccentric training-induced lengthening of BFlh fascicle length was reversed and returned to baseline values after 28 d of detraining. The contraction mode specific adaptations in this study may have implications for injury prevention and rehabilitation.
Sports Medicine | 2018
Matthew N. Bourne; Ryan Timmins; David A. Opar; Tania Pizzari; J. Ruddy; Casey Sims; Morgan D. Williams; Anthony Shield
Strength training is a valuable component of hamstring strain injury prevention programmes; however, in recent years a significant body of work has emerged to suggest that the acute responses and chronic adaptations to training with different exercises are heterogeneous. Unfortunately, these research findings do not appear to have uniformly influenced clinical guidelines for exercise selection in hamstring injury prevention or rehabilitation programmes. The purpose of this review was to provide the practitioner with an evidence-base from which to prescribe strengthening exercises to mitigate the risk of hamstring injury. Several studies have established that eccentric knee flexor conditioning reduces the risk of hamstring strain injury when compliance is adequate. The benefits of this type of training are likely to be at least partly mediated by increases in biceps femoris long head fascicle length and improvements in eccentric knee flexor strength. Therefore, selecting exercises with a proven benefit on these variables should form the basis of effective injury prevention protocols. In addition, a growing body of work suggests that the patterns of hamstring muscle activation diverge significantly between different exercises. Typically, relatively higher levels of biceps femoris long head and semimembranosus activity have been observed during hip extension-oriented movements, whereas preferential semitendinosus and biceps femoris short head activation have been reported during knee flexion-oriented movements. These findings may have implications for targeting specific muscles in injury prevention programmes. An evidence-based approach to strength training for the prevention of hamstring strain injury should consider the impact of exercise selection on muscle activation, and the effect of training interventions on hamstring muscle architecture, morphology and function. Most importantly, practitioners should consider the effect of a strength training programme on known or proposed risk factors for hamstring injury.
Medicine and Science in Sports and Exercise | 2017
J. Ruddy; Anthony Shield; Nirav Maniar; Morgan D. Williams; Steven Duhig; Ryan Timmins; Jack Hickey; Matthew N. Bourne; David A. Opar
Purpose Three of the most commonly identified hamstring strain injury (HSI) risk factors are age, previous HSI, and low levels of eccentric hamstring strength. However, no study has investigated the ability of these risk factors to predict the incidence of HSI in elite Australian footballers. Accordingly, the purpose of this prospective cohort study was to investigate the predictive ability of HSI risk factors using machine learning techniques. Methods Eccentric hamstring strength, demographic and injury history data were collected at the start of preseason for 186 and 176 elite Australian footballers in 2013 and 2015, respectively. Any prospectively occurring HSI were reported to the research team. Using various machine learning techniques, predictive models were built for 2013 and 2015 within-year HSI prediction and between-year HSI prediction (2013 to 2015). The calculated probabilities of HSI were compared with the injury outcomes and area under the curve (AUC) was determined and used to assess the predictive performance of each model. Results The minimum, maximum, and median AUC values for the 2013 models were 0.26, 0.91, and 0.58, respectively. For the 2015 models, the minimum, maximum and median AUC values were, correspondingly, 0.24, 0.92, and 0.57. For the between-year predictive models the minimum, maximum, and median AUC values were 0.37, 0.73, and 0.52, respectively. Conclusions Although some iterations of the models achieved near perfect prediction, the large ranges in AUC highlight the fragility of the data. The 2013 models performed slightly better than the 2015 models. The predictive performance of between-year HSI models was poor however. In conclusion, risk factor data cannot be used to identify athletes at an increased risk of HSI with any consistency.
Faculty of Health; Institute of Health and Biomedical Innovation | 2016
Ryan Timmins; J. Ruddy; Joel Presland; Nirav Maniar; Anthony Shield; Morgan D. Williams; David A. Opar
British Journal of Sports Medicine | 2018
J. Ruddy; C. Pollard; Ryan Timmins; Morgan D. Williams; Anthony Shield; David A. Opar
Journal of Science and Medicine in Sport | 2015
Ryan Timmins; J. Ruddy; J. Presland; Nirav Maniar; Anthony Shield; Morgan D. Williams; David A. Opar
Journal of Science and Medicine in Sport | 2018
J. Ruddy; Nirav Maniar; S. Cormack; Ryan Timmins; David A. Opar
Journal of Science and Medicine in Sport | 2018
Ryan Timmins; D. Filopoulos; J. Ruddy; Nirav Maniar; Jack Hickey; J. Giannakis; V. Nguyen; David A. Opar
Faculty of Health; Institute of Health and Biomedical Innovation; School of Exercise & Nutrition Sciences | 2018
Matthew N. Bourne; Ryan Timmins; David A. Opar; Tania Pizzari; J. Ruddy; Casey Sims; Morgan D. Williams; Anthony Shield
Journal of Science and Medicine in Sport | 2017
J. Ruddy; Anthony Shield; Nirav Maniar; Morgan D. Williams; Steven Duhig; Ryan Timmins; Jack Hickey; David A. Opar