The hidden cost of disease: II. Impact of the first incidence of lameness on production and economic indicators of primiparous dairy cows
Bibliographic record
Abstract
Lameness is a persistent and underreported health and welfare problem in the dairy industry, resulting in reduced cow performance and profitability as well as early culling. The study objectives were (1) to quantify the impact of the first instance of lameness, at different stages of lactation, on production and economic performance, and (2) to further quantify the impacts of the first instance of lameness when only cows that remain in the herd for at least 100 d in milk (DIM) and those that remain for 305 DIM are included in the analysis. A retrospective longitudinal study was conducted using pre-existing data from animal health records and Dairy Herd Improvement Association records. Data were edited based on selected inclusion criteria, yielding a data set containing records from 15,159 first-lactation Holstein cows from 120 herds with year of first calving between 2003 and 2014. Lame cows were assigned to 1 of 4 groups based on when in the lactation the first event of lameness occurred: transition (1-21 DIM), early lactation (22-100 DIM), mid-lactation (101-200 DIM), or late lactation (201+ DIM). Mid- and late-lactation lame cows were also stratified by cumulative milk yield before the lameness event. Healthy cows (i.e., no recorded lameness event) were randomly assigned for each lactation stage, with mid-lactation healthy and late-lactation healthy cows similarly stratified. Production performance (cumulative milk, fat, and protein yield) and economic performance [milk value, margin over feed cost (MOFC), and gross profit] were analyzed using a mixed model with herd as a random effect. Cumulative milk yields were 811 to 1,290 kg lower for lame cows than for healthy cows, with milk component yields undergoing similar reductions. Reductions in milk yield contributed to losses in milk value (-Can$527 to -Can$1,083; -US$419 to -US$862) and MOFC (-Can$510 to -Can$774; -US$406 to -US$616). Higher losses were reported using gross profit (-Can$753 to -Can$1,052; -US$599 to -US$837), which includes all lameness-related costs. Production and performance losses were smaller when 100 DIM and 305 DIM thresholds were applied (i.e., exclusion of cows culled before 100 and 305 DIM, respectively), however, mid- and late-lactation lame cows maintained high levels of significant losses for all 6 variables analyzed. Lameness also led to higher levels of culling, masking losses for transition and early-lactation lame cows in the 305-DIM analysis. Increasing producer understanding of the costs associated with lameness not only serves to provide insight to producers for more informed culling decisions, but may also help producers weigh the costs of adopting new methods and technologies targeted at reducing on-farm lameness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".