Transition Diseases in Grazing Dairy Cows Are Related to Serum Cholesterol and Other Analytes
Bibliographic record
Abstract
The objectives of this study were to describe the incidence of postpartum disease and to evaluate the association with serum cholesterol concentrations during the first 3 weeks after calving in grazing dairy cows. The association between non-esterified fatty acids (NEFA), β-hydroxybutyrate (BHBA), calcium and postpartum diseases was also evaluated. A total of 307 Holstein dairy cows from 6 commercial grazing herds in Osorno, Chile, were monitored from calving until 21 days in milk. Cases of retained placenta, clinical hypocalcemia and clinical mastitis were recorded by the farmer using established definitions. Twice weekly, cows were evaluated for metritis by the same veterinarian based on vaginal discharge and body temperature. Postpartum blood samples were collected weekly and analyzed for serum concentrations of cholesterol, NEFA, BHBA and calcium. Cows were considered as having subclinical ketosis if BHBA >1.2 mmol/L, and subclinical hypocalcemia if calcium <2.0 mmol/L in any of the 3 weekly samples. Overall, 56% of the cows studied developed at least one clinical or subclinical disease after calving. Incidence of individual diseases was 8.8% for retained placenta, 4.2% for clinical hypocalcemia, 11.7% for clinical mastitis, 41.1% for metritis, 19.9% for subclinical hypocalcemia and 16.6% for subclinical ketosis. Lower postpartum cholesterol in cows was associated with developing severe metritis or having more than one clinical disease after calving. For every 0.4 mmol/L decrease in serum cholesterol cows were nearly twice as likely to be diagnosed with multiple clinical diseases after calving. Higher BHBA concentrations and lower calcium concentrations during week 1 were associated with severe cases of metritis. Low serum calcium concentration during week 1 was also associated with developing more than one clinical disorder after calving. In conclusion, the incidence of postpartum diseases can be high even in grazing herds and lower serum cholesterol concentrations were associated with occurrence of clinical postpatum disorders.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".