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  • Title: Predicting return to racing after repair of fractures of the metacarpal/metatarsal condyles in Thoroughbred racehorses.
    Author: Young N, Corletto F, Wright I.
    Journal: Vet Surg; 2022 Jul; 51(5):753-762. PubMed ID: 35527476.
    Abstract:
    OBJECTIVE: To identify prognostic factors for return to racing after lag screw repair of condylar fractures and develop a predictive model for return to racing. STUDY DESIGN: Retrospective cohort study. ANIMALS: A total of 356 horses referred to a single referral hospital in the UK with a third metacarpal/metatarsal condylar fracture between January 1999 and December 2018. METHODS: Age, sex, fracture site, fracture characteristics, surgery related variables and complications were retrieved from case records. Data were divided into two sets for model training and model validation. Univariable analyses were performed, and predictors were selected in a stepwise fashion for inclusion in the multivariable logistic regression model. Sensitivity and specificity were evaluated using the second dataset. RESULTS: Older horses, fillies, fractures of forelimbs, complex, complete, displaced or propagating fractures and concurrent proximal sesamoid bone fracture were negatively associated with return to racing. Colts and geldings were 3 and 4 times more likely to race than fillies, respectively. Horses with hindlimb, incomplete or nonpropagating fractures were 4, 5 and 4 times more likely to race than those with a forelimb, complete or propagating fracture, respectively. Using a predicted probability cut-off threshold of 0.5, a predictive model was created within one dataset (sensitivity = 84%, specificity = 50.5%) and applied to another (sensitivity = 83.1%, specificity = 24.0%). CONCLUSION: Negative prognostic factors were identified and led to a predictive model with acceptable sensitivity and specificity in the tested population. CLINICAL SIGNIFICANCE: The results provide proof of concept for the model in the reported population and justify further validation in different populations of horses.
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