Importance et conséquences de l'hypocalcémie subclinique chez la vache laitière en péri-partum : exemple d'une clientèle vétérinaire des Vosges
Bibliographic record
Abstract
A high prevalence of subclinical hypocalcemia (SCH) at parturition in the American dairy farms (37% of dairy cows under the threshold of 80 mg/L, Reinhardt et al., 2011) highlighted in 2011, led researchers to focus on this still understudied situation. Despite the lack of a consensus on the threshold to define it, tens of studies recently published confirm that SCH affects a large part of cows around parturition in most countries worldwide, including France (Gillet, 2015; Astruc, 2018). However, many grey areas regarding risk factors and, most importantly, potential aftereffects remain today. Aiming at bringing additional data and to assess the French situation a new study was undertaken in a veterinary practice in the Vosges, Eastern France. In total, 96 dairy cows were included in the sample group. For each one, calcemia was measured on average 4.9 days before calving, in the 12 hours following parturition and, then, at 24h, 48h, 72h, 7 days and 14 days after calving, as long as calcemia was strictly under 86 mg/L. In the sample, 61.5% of the cows had a calcemia below 86 mg/L before or within the 12 hours following calving, a prevalence that reached 36.5% when the threshold of 80 mg/L is considered. Independently of the threshold, more than a quarter of hypocalcemic cows at calving remained 72 hours later (26.4%). Similar to clinical hypocalcemia, third or more lactation cows were significantly more affected than cows in 1st or 2nd lactation (p<0.05), as well as cows with a higher milk yield during the previous lactation (p=0.01). Cows affected by SCH at calving (<80 mg/L) were significantly more affected by subclinical ketosis (p<0.05) and showed a higher milk production at the official milk-recording conducted between 21 and 60 days after parturition (p<0.01) with a lower percentage of protein (p<0.01). Moreover, cows suffering of at least one of 5 postpartum diseases (subclinical ketosis, mastitis, retained placenta, uterine infection, abnormalities of ovarian cyclicality), had an average calcemia lower at parturition (p<0.05). Finally, with a threshold of 80 mg/L, the number of cows in SCH affected by one or more of these five illnesses tended to be significantly higher (p=0.053).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".