Veterinary Clinical Sciences - Research Publications
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ItemTraining practices, speed and distances undertaken by Thoroughbred racehorses in Victoria, Australia(WILEY, 2020-03)BACKGROUND: Musculoskeletal injuries (MSI) in racehorses are commonly due to bone fatigue, a function of the number of cycles (strides) and the magnitude of load applied to the limb. These parameters can be estimated using speed and distance, with greater than 6000 m/month at a gallop (>14 m/s), in combination with canter distances greater than 44,000 m/month, reported to increase fracture risk. Despite their importance, there are limited data on the distances and speeds horses are exposed to during training. OBJECTIVES: Estimate training volume at different speeds undertaken by Australian Thoroughbred racehorses. STUDY DESIGN: Cross-sectional study. METHODS: Registered trainers (n = 66) in Victoria, Australia were surveyed. Questions were designed to assess the full training workload from initial pre-training to training performed to achieve and maintain race fitness, as well as information on rest periods. Descriptive analyses were stratified by trainer- and horse-level factors, with assessment of variance within and between groups. Cluster analyses were used to identify similar workload intensity groups. RESULTS: Horse-level factors (age, targeted race distance) were associated with workload (younger
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ItemVariation in GPS and accelerometer recorded velocity and stride parameters of galloping Thoroughbred horses(WILEY, 2021-09)BACKGROUND: With each stride, galloping horses generate large skeletal loads which influence bone physiology, and may contribute to musculoskeletal injury. Horse speed and stride characteristics are related, but the usefulness of using horse speed and distance travelled as a proxy for stride characteristics is unknown. OBJECTIVES: We aimed to determine stride characteristics, their variance and their relationship with speed in horses performing maximally. STUDY DESIGN: Retrospective cross-sectional analysis of archived data. METHODS: Stride characteristics obtained using GPS and inertial sensors in Thoroughbred horses were retrieved. Data per 200 m race segment ('sectionals') for horses competing in races (N = 25,259 race starts) were analysed to determine if speed predicted stride parameters. Multivariable mixed-effects linear regression models were fitted. RESULTS: Mean (±SD) stride length, stride count (number of strides per 200 m), duration and speed were 7.08 ± 0.39 m, 28.32 ± 1.56 strides/200 m, 0.43 ± 0.02 s/stride and 16.63 ± 1.04 m/s across all sectionals and starts. Speed and stride length decreased, and stride count increased with race progression (P < 0.001). Male sex, greater race distance, better finishing position and firmer track surfaces were associated with less strides per 200 m and longer stride durations. MAIN LIMITATIONS: Lack of an independent party validation of the measurement system used in this study. CONCLUSIONS: There was a substantial inter-horse variation in stride parameters, with speed predicting half or less of this variation. Speed alone does not fully explain stride characteristics in horses. Future studies aimed at investigating the impact of gait on bone biology and pathology would benefit from accounting for stride characteristics (eg length and duration).