Abstract

Three transition monitors were developed in this study that serve on 2 levels: the individual cow level and the herd level. On the first level they screen all cows for potential onset of postparturient health disorders and could be used to trigger implementation of more specific diagnostic initiatives. On the second level they can be used within herd to monitor the implementation of transition protocols and evaluate the transition management on the farm, signaling potential problems before clinical disease onset. The performance of 3 transition monitors based on daily milk yield (MY) within the first 7d in milk was evaluated in 3 herds with differing transition management intensity. The 3 monitors considered were increase in MY (LINE), average MY (MY7), and the difference between MY7 and expected MY (transition success measure, TSM). Transition monitors were evaluated not only as within-herd predictors of individual cow transition problems but also as indicators of herd transition management failures by relating their value with probability of early-lactation health disorders, culling, and treatment cost. Analysis of logistic models, correlations, and sensitivity and specificity estimates identified TSM as the most reliable measure of transition failure on both the individual cow level as well as the farm level across all study herds, with best performance achieved in herds with the most intensive postpartum cow management. As evaluated by logistic regression models, TSM was able to successfully predict the probability of a cow remaining healthy for the first 21d of lactation (c-statistic between 0.68 and 0.78), and probability of culling by 100d in milk (c-statistic between 0.73 and 0.86). Total cost of treatment by 21d in milk also showed the strongest correlation with TSM, with correlation coefficients ranging between 0.2 and 0.4. Statistical-process control cumulative sum charts for TSM designed to monitor postpartum management process in the herd identified transition failure events with at least 90% sensitivity at specificity above 92% within a 14-d window of 7d before and 7d after the event.

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