Racehorse Training and Drug History Needed to Understand Breakdowns

POSTED ON  |  07-08-2019

Tim Parkin
Over the six-month meet at Santa Anita racetrack, in Arcadia, California, 30 Thoroughbred racehorses died or were euthanized due to injuries sustained while training or racing. When the precise reasons for catastrophic racehorse injuries aren’t clear, as is the case at Santa Anita, science—specifically, collections of data—can help. But for that data to be most useful for preventing future injuries, it needs to include comprehensive, accurate medication and training history data, says Prof. Tim Parkin, Sc, BVSc, PhD, DECVPH, MRCVS, veterinarian and epidemiologist at the University of Glasgow and consultant to The Jockey Club’s Equine Injury Database (EID).

An epidemiologist is someone who seeks to find the cause of health outcomes and disease in populations. In his EID role Parkin analyzes information on all horses at participating tracks that die or are euthanized as a direct result of injuries sustained while participating in a race and within 72 hours of a race (this includes musculoskeletal injuries, nonmusculoskeletal injuries, and sudden deaths). The database also contains information on training and nonracing fatalities, though those are not included in the EID annual statistics.

We at The Horse were curious about the data the EID is collecting and how the industry could make it even stronger and more useful, so we interviewed Prof. Parkin.

The Horse: Could you describe the gamut of data you collect surrounding each catastrophic injury, please? Surface type, distance, and age are in the reports, but what further data do you collect, if it’s more expansive? 

Parkin: There is plenty of other information available to us from The Jockey Club that relates to the racing history of the horse, the conditions on the day of the race and, to a certain extent, prior workout data. Perhaps more importantly we create a lot of new potential risk factors from the data provided.

For example, we calculate for every start the number of prior starts in the last 30 days, 30 to 60 days, and 60 to 90 days, etc. In the next iteration of the models (which assess how successfully a potential risk factor does its job in predicting whether a horse sustains an injury) we are developing, we will also include measures of changes in intensity of racing or working at speed that are likely to help improve the predictive ability of the models. Those models will now include on initial assessment close to 150 different potential risk factors. The two peer-reviewed publications so far … include details of all significant variables we have investigated.

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