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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

Musculoskeletal injuries are observed in Thoroughbred racehorses and may become catastrophic. Currently there are limited methods for early detection of such injuries. Most injuries develop gradually due to accumulated damage, providing the opportunity for early detection. Horses experiencing pain or lameness may exhibit changes in behaviour so development of an objective, real-time system monitoring horse behaviour may enable detection of bone injuries before catastrophic failure.To determine whether intensive, observational methods of assessing horse behaviour, can be replaced by use of Inertial Measurement Units (IMUs).Validation study assessing IMU use against video observation.Six hospitalised Thoroughbreds (algorithm training data) and 19 Thoroughbred racehorses in-training (algorithm testing data) were equipped with an IMU placed on the lateral side of both forelimbs (left fore, LF; right fore, RF) and monitored in a stable for four hours. An algorithm was developed to classify behaviour and then validated against video recordings.Standing was the most prevalent behaviour (LF 88.8%, 95% CI 88.7, 89.0; RF 88.5%, 95% CI 88.4, 88.7). IMU classification of recumbent and standing activities showed excellent agreement (sensitivity) with video observation (98%). This was followed by stepping (LF 89.4%, RF 85.5%) then weight shifting (LF 54.3%, RF 61.5%). Predictions from the algorithm showed misclassification of 2.5% (LF 5500/225,352, RF 5218/210,170). Excluding standing, misclassification was 6.8% (1705/25,158) and 7.5% (1812/24,077) for the left and right forelimbs, respectively, with pawing and weight-shifting most frequently misclassified.Increasing the number of horses and types of behaviours observed may improve predictions.IMUs displayed a high sensitivity to movement on a small number of horses, and with further validation they have the potential to effectively monitor behaviour of racehorses in training. However, more sensitive methods may be needed to validate the classification of weight shifting behaviour. Future studies should evaluate the association between each behaviour and musculoskeletal injury.

Fatigue life (FL) is the number of cycles of load sustained by a material before failure, and is dependent on the load magnitude. For athletes, ‘cycles’ translates to number of strides, with load proportional to speed. To improve previous investigations estimating workload from distance, we used speed (m/s, x) per stride collected using 5 Hz GPS/800 Hz accelerometer sensors as a proxy for limb load to investigate factors associated with FL in a Thoroughbred race start model over 25,234 race starts, using a combination of mathematical and regression modelling. Fore-limb vertical force (NKg-1) was estimated using a published equation: Vertical force = 2.778 + 2.1376x − 0.0535x2. Joint load (σ) was estimated based on the vertical force, scaled according to the maximum speed and defined experimental loads for the expected variation in load distribution across a joint surface (54-90 MPa). Percentage FL (%FL) was estimated using a published equation for cycles to failure (Nf) summed across each race start: Nf = 10(σ-134.2)/−14.1. Multivariable mixed-effects linear regression models were generated on %FL, adjusting for horse-level clustering, presented as coefficients; 95%CI. Scaled to the highest joint load, individual starts accrued a mean of 9.34%FL (sd. 1.64). Older age (coef. 0.03; 0.002–0.04), longer race-distances (non-linear power transformed), and firmer track surfaces (ref. Heavy 10: Good 3 coef. 2.37; 2.26–2.48) were associated with greater %FL, and males accrued less than females (p

We aimed to determine the extent of use of water-based exercise and to describe swimming training practices in Thoroughbred racehorses in Victoria, Australia. A convenience sample of 118 trainers were interviewed, information relating to swimming protocols, perceived benefits and contra-indications, and use of other water-based exercise recorded and descriptive data analyses performed. Water-based exercise was used by 85.6% (n=101) trainers: 82.2% (n=97) swimming, 25.4% (n=30) using a water walker, 13.6% (n=16) incorporating ridden trotting (‘surging’) exercise in chest deep water, and 1.7% (n=2) using an underwater treadmill. Common reasons (and trainer %) for swimming were training variety and mental ‘freshness’ (62.9%), part of the exercise regime on ‘slow’ days (61.9%) and fitness benefits (60.8%). These horses swam a median of 50-90 m (ranging from a minimum of 40-180 m to a maximum of 40-450 m), continuously or as intervals, after track work, once or twice daily a median 3 days/week (range 0.5-7). Swimming for 50 (range 40-120 m) to 90 m (range 40-200 m) before track work 7 days/week (range 3-7) was used by 43 of the 97 trainers (44.3%) to manage horses prone to exertional rhabdomyolysis. Swimming was used to replace fast work by three trainers who swam horses with limb injuries up to 270-450 m. Common reasons (and % trainers) for not swimming individual horses were demeanour/distress (73.2%), previous swim colic (35.1%) or exercise induced pulmonary haemorrhage (35.1%) although only five trainers had ever seen epistaxis after swimming exercise. Swimming is widely used in training Thoroughbred horses in Australia yet trainer opinions particularly on fitness benefits, contra-indications and protocols vary widely and need to be scientifically validated. Diversifying training activities is a common strategy for managing racehorses in training, yet a better understanding of the best use of swimming and other cross-training options is needed so that evidence-based recommendations can be made.

Catastrophic musculoskeletal injuries (CMI) pose a major welfare concern to horses and their riders, yet limited data are available describing their occurrence in South America. Using a retrospective cohort and case-control design, the objective of the study was to determine the incidence of CMI for Thoroughbreds in training and racing, and associated horse-level risk factors in Uruguay. Seventy-seven Thoroughbreds sustained a CMI, 37 of which were age- and sex-matched to 111 control horses in the same race. Training and racing data from 2011 to 2017 were collected. Incidence of race day CMI per 1,000 race starts and training CMI incidence per 100 horse months were calculated using Poisson regression. Univariable logistic regression was used to assess relationships between race history and occurrence of CMI by fracture location, and multivariable for all fracture locations. Overall race day incidence of CMI was 0.42 per 1,000 race starts (95% CI 0.29, 0.60). The incidence of CMI in training was 0.059 per 100 horse months. Twenty-nine percent (22/77) of horses that sustained a CMI had not raced prior. Most fractures were of the forelimbs (80.3%). There were 32 (41.6%) distal and 39 (50.6%) proximal limb fractures. The risk of CMI was greater for horses with fewer places (P = .001), and greater time between the previous race and the race in which CMI occurred (P = .020). The rate of race day CMI was low, despite Uruguay being a racing jurisdiction with policies and risk factors associated with greater CMI rates compared to other jurisdictions. Lightly raced horses with long periods since their previous race start should be monitored closely.

Objectives To determine swimming training practices in Australian harness racing horses and potential targets for future research. Methods An online survey of Australian Standardbred trainers and telephone interviews with 20 leading trainers were conducted. Questions relating to swimming facility and protocol, perceived benefits and contraindications were included. Descriptive data analysis was performed. Results Data were collected from 270 trainers: 250 by online survey (250/1770, response rate 14.1%) and 20 by interview. Of these, 103 trainers (38.1%), including 91 surveyed trainers (91/250, 36.4%) and 12 interviewed trainers (12/20, 60.0%), used swimming exercise. The most popular reasons for swimming were to replace trackwork for horses with limb injuries (79.4%), improve or maintain fitness (62.7%) and provide mental stimulation through variety in training (40.0%). Free swimming (78.4%) was more common than tethered, but the frequency and duration for horses in full training varied widely between trainers, with a median of four swim sessions per horse each week (range 0.5-12) for a median of 7 min (range 1.5-30 min) per session, mostly as a continuous swim, but sometimes as intervals. The main reasons given by those not swimming horses were lack of an adequate facility (60.5%) and lack of perceived benefit (16.2%). Reasons for not swimming individual horses varied widely. Conclusions Trainer opinions and protocols varied widely with respect to swimming exercise for Standardbred race horses. The role of swimming exercise requires further study so that evidence-based recommendations can be made.

Simple Summary Musculoskeletal injury rates for Thoroughbred racehorses in training and racing differ between racing jurisdictions. The aetiology of these injuries is multifactorial, but one potentially important and modifiable risk factor is the track surface on which horses train. However, the extent to which different track surfaces are used by trainers has not been clearly established. Similarly, the extent of use of alternatives to ridden exercise between different jurisdictions is unknown. Trainers in Victoria, Australia, use a combination of turf, sand, synthetic and dirt training track surfaces. Sand or synthetic surfaces were most commonly used for slow workouts and turf or synthetic tracks for fast workouts. A high proportion of trainers raced horses on surfaces that were not regularly used for training, and 89% of trainers used alternative exercise methods in addition to overground ridden workouts. Determining types of surfaces and alternatives to ridden exercise used during training, and to what extent they are used, is the first step in understanding their association with the risk of injury. The future aim is mitigating injury risk by recommending safer track surfaces. Abstract Little is known about the types of surfaces used during training of Thoroughbred racehorses or methods of exercise used in addition to ridden track-work. Our aims were to (1) describe the types of surfaces used in the training of Thoroughbred racehorses and to (2) identify alternative approaches used to exercise horses in addition to, or in place of, ridden overground track-work. Information regarding surface and alternative exercise methods was collected as part of an in-person survey of training practices of 66 registered Thoroughbred trainers in Victoria, Australia. Sand and synthetic surfaces were used by 97% and 36% of trainers respectively for slow-workouts, with galloping on turf training tracks used in training regimens by 82% and synthetic by 58% of trainers. Of those trainers utilising turf tracks, only 34% of gallop training was completed on turf despite turf being the predominant racing surface. Almost 90% of trainers used alternatives to ridden exercise. There is substantial variation in training surface used and alternative types of exercise undertaken by Victorian trainers. Future research should focus on how such practices relate to injury risk, particularly as it relates to the importance of musculoskeletal adaptation to specific race-day surfaces.

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

Studies of racehorse injury or fatality in various countries have identified common, and in some cases conflicting, risk factors. We conducted a systematic search of the relevant literature published from 1990 to 2017. Peer-reviewed articles were included if they reported the incidence of fatal or catastrophic musculoskeletal injury (CMI) in Thoroughbred flat races (n=21) or risk factors for CMI (n=65). Pooled effect sizes were estimated using the random-effects DerSimonian-Laird model. The pooled incidence of CMI was 1.17 (95% confidence interval 0.90, 1.44) per 1000 race starts. Almost 300 factors have been investigated in epidemiological studies for potential associations with CMI. Factors found to have consistent evidence of increasing risk of CMI are: (1) Horse-level factors such as older horse age and age at first start, male sex, and higher race class or lower claiming price; (2) Race-level factors such as firmer track conditions on turf and wetter conditions on dirt, longer race distance, and a greater number of starters; and (3) Management-related factors including more time since previous start, greater number of starts, longer career length, issues identified at pre-race examination, previous injury, and recent administration of medication or injections. Studies investigating recent cumulative distance of high-speed exercise were conflicting and suggestive of at least two mechanisms of injury related to the accumulation of bone damage: (1) In well adapted bone following a period of intense training; and (2) In poorly adapted bone at relatively low levels of training intensity. Future studies should evaluate success of interventions and mechanisms for injury.