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The only significant variables in the final multivariable model were the metatarsus adductus angle (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.08 to 1.25) and fourth/fifth intermetatarsal angle (OR 0.69, 95% CI 0.57 to 0.83)—both measures of static forefoot adduction.

Variables included in the multivariable model were chosen according to univariate analyses, their relevance according to the literature, and the likelihood of collinearity based upon clinical judgment.

Independent predictors (at admission) in the multivariable model were Bilirubin/platelet ratio, Albumin, Lymphopenia, Diabetes, Urea, and Shock index, which were combined into a new clinical rule (BALDUS score).

Other variables that were eligible for consideration in a multivariable model were whether or not the horse was unraced (p = 0.10), prize money won per year of age of the horse (p = 0.06) and number of seasons raced per year of age (p = 0.15).

These covariates for the multivariable model were selected based on standard model building strategies [ 30].

Independent variables in the final multivariable model were selected using a stepwise forward process.

Second, the novel grey multivariable model is established, combined with the changing trends of driving variables.

The final multivariable model is demonstrated in Table 3.

A single multivariable model was produced.

A main effect multivariable model was applied.

In each sample a multivariable model was built.