Downer cows: a reanalysis of an old data set

Abstract

ABSTRACT Aims To compare the performance of two predictive models for the survival of downer cows. Methods The first model had been developed in 1987 using a dataset containing missing values, while the second, new model was developed on the same dataset but using modern data imputation and analytical methods. Missing data were imputed using multiple imputation by chained equations and a logistic regression model fitted to the imputed data, with survival or not as the outcome variable. The predictive ability of the model built on the imputed data was contrasted with the original prognostic model by testing them both on a second smaller but complete data set, collected contemporaneously with the development of the original model but from a different region of New Zealand. Sensitivity, specificity, accuracy, and cut point for the two models were calculated. Results The original 1987 model had a slightly higher accuracy than that of the new one with a sensitivity of 0.85 (95% CI = 0.72–0.94) and a specificity of 0.82 (95% CI = 0.7–0.91), using a cut point for the probability of survival = 0.313. Conclusions The original prognostic formula published by Clark et al. in 1987 performed as well as a modern model built on an imputed data set. Clinical relevance The use of a prognostic test based on the Clark model should remain an important part of the clinical examination of downer cows by New Zealand veterinarians. Abbreviations: AUC: Area under the curve; AST: Aspartate transaminase activity; CK: Creatine phosphokinase activity; GAM: Generalised additive model; NSAID: Non-steroidal-anti-inflammatory drugs; PCV: Packed cell volume