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Record W4391071289 · doi:10.3168/jdsc.2023-0510

Herd-level associations between the proportion of elevated prepartum nonesterified fatty acid concentrations and postpartum diseases, reproduction, or culling on dairy farms

2024· article· en· W4391071289 on OpenAlexaff
J. Denis-Robichaud, Isabella Nicola, H. Chupin, Jean‐Philippe Roy, Sébastien Buczinski, V. Fauteux, Nicole Picard‐Hagen, R.I. Cue, J. Dubuc

Bibliographic record

VenueJDS Communications · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsMcGill UniversityUniversité de MontréalService de Recherche et d'EXpertise en Transformation des Produits Forestiers
Fundersnot available
KeywordsMetritisCullingHerdRetained placentaIce calvingMastitisNEFAMedicineAnimal scienceOdds ratioObstetricsDairy cattlePregnancyLactationInternal medicineVeterinary medicineBiologyPlacentaFetus

Abstract

fetched live from OpenAlex

The objectives of this herd-level prospective observational cohort study were to describe the proportion of cows with elevated prepartum nonesterified fatty acid concentrations (PropElevNEFA) in dairy herds and to assess the herd-level associations between PropElevNEFA and postpartum diseases, reproductive performance, and culling. From November 2018 to December 2020, a convenience sample of 49 herds was enrolled in this study. Blood sampling (16 to 29 cows per herd) was performed during the week before and during the 2 wk following calving to quantify the concentration of nonesterified fatty acids (NEFA) and β-hydroxybutyrate acids (BHBA), respectively. Elevated NEFA was defined as ≥280 µmol/L and hyperketonemia as BHBA ≥1.4 mmol/L. Retained placenta, metritis, purulent vaginal discharge, endometritis, and mastitis were diagnosed on-farm following standardized definitions, and success at first artificial insemination (AI) and culling events were recorded. The associations between PropElevNEFA and each individual disease, success at first AI, and culling were evaluated using Bayesian aggregated binomial regression models with weakly informative priors, from the which odds ratio (OR) and the 95% credible intervals (BCI) were obtained. A total of 981 cows were included in the statistical analyses representing 16 to 29 (median = 19) cows per herd. Cows were enrolled in the prepartum period of their first to tenth (median = third) lactation, and 41% of them had an elevated prepartum NEFA concentration. At the herd level, PropElevNEFA varied between 11% and 78% (median = 39%). The odds of metritis (OR = 1.37, 95% BCI = 1.13-1.67) increased for every 10-point increase in PropElevNEFA, whereas the odds of success at first AI decreased (OR = 0.69, 95% BCI = 0.59-0.80). The PropElevNEFA was not associated with the other tested diseases or culling. Our results suggest that the herd-level proportion of cows having elevated prepartum NEFA concentrations is associated with metritis and poor success at first AI in dairy herds.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.090
GPT teacher head0.312
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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