Abstract
Objective—To develop a parsimonious statistical model to predict incidence of lameness in the subsequent lactation by use of data collected at cessation of lactation in dairy cows.
Animals—574 cows.
Procedures—At cessation of lactation during hoof trimming, body condition score (BCS), visual locomotion score, digital cushion thickness (DCT), and digital lesions were assessed.
Results—140 (24%) cows were treated for claw horn disruption lesions (CHDLs) at cessation of lactation (114 with sole ulcers [pododermatitis circumscripta] and 26 with white line disease). The BCS was highly associated with DCT. Cows with CHDLs at cessation of lactation had significantly lower DCT, compared with other cows. All 3 logistic regression models predicted the incidence of CHDLs in the subsequent lactation with good accuracy; the area under the receiver operating characteristic curves was 0.76, 0.76, and 0.77 for the first, second, and third logistic regression models, respectively.
Conclusion and Clinical Relevance—Evaluation of 3 logistic regression models indicated that lameness could be predicted with good accuracy by use of all 3. The ability to predict lameness will facilitate the implementation of lameness prevention strategies by targeting specific cows.
