Association between prepartum nonesterified fatty acid serum concentrations and postpartum diseases in dairy cows
Bibliographic record
Abstract
The objective of the present study was to quantify the relationships between prepartum nonesterified fatty acid (NEFA) concentrations and the development of subsequent diseases or culling and to identify the optimal thresholds allowing identification of animals at high risk of developing postpartum diseases or being culled. A total of 1,299 Holstein cows from 50 commercial herds located around Saint-Hyacinthe (QC, Canada) were enrolled in this observational study. Blood samples were collected from enrolled cows between 1 and 14 d before calving for serum NEFA quantification. Data concerning postpartum diseases and culling were collected from computerized record systems. The association between prepartum NEFA concentrations and postpartum diseases and culling was quantified using generalized linear mixed models, accounting for parity, season, week of sampling, and herd. Optimal NEFA thresholds were evaluated with receiver operator characteristic curves analysis for all diseases and then confirmed with generalized linear mixed models, considering NEFA as a categorical variable (high or low). Prepartum serum NEFA concentrations were associated with diseases diagnosed during the first 30 d in milk (DIM) and culling within the first 50 DIM. The optimal NEFA threshold associated with diseases was ≥290 µmol/L for retained placenta, ≥300 µmol/L for metritis and abomasal displacement, and ≥280 µmol/L for clinical mastitis and hyperketonemia. The level associated with the occurrence of at least one of these diseases in the first 30 DIM was ≥280 µmol/L, but it was ≥260 µmol/L for culling in the first 50 DIM. No relationship was found between NEFA concentrations and reproductive tract diseases (purulent vaginal discharge or cytological endometritis) or subclinical intramammary infection. Despite the strong relationship between prepartum NEFA concentrations and many diseases, the NEFA optimal threshold accuracy found in our study was low. In conclusion, our results demonstrate a relationship between NEFA concentrations in the 14-d period before calving and the subsequent development of diseases and culling. Prepartum NEFA concentrations thresholds between ≥260 and 300 µmol/L appear to be a strategic choice. However, considering the low accuracy, their use at the cow level should be performed with caution.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".