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Record W2901856316 · doi:10.3168/jds.2018-14778

Short communication: Validation of a test-day milk test for β-hydroxybutyrate for identifying cows with hyperketonemia

2018· article· en· W2901856316 on OpenAlexaffabout
D.L. Renaud, D.F. Kelton, T.F. Duffield

Bibliographic record

VenueJournal of Dairy Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsKetosisAnimal scienceDairy cattleHerdMedicineGold standard (test)Internal medicineEndocrinologyBiologyDiabetes mellitus

Abstract

fetched live from OpenAlex

Subclinical ketosis is a common metabolic disorder affecting dairy cattle that results in a greater risk for the development of subsequent metabolic and infectious disease. Canwest Dairy Herd Improvement (DHI; Guelph, ON, Canada) has begun to use an infrared test (MilkoScan FT600, Foss Analytical A/S, Hillerød, Denmark) applied to metered composite milk samples to detect β-hydroxybutyrate (BHB) levels as a herd surveillance test for hyperketonemia. However, the test has not been compared with the gold standard, serum BHB as determined in a reference diagnostic laboratory. The objective of this cross-sectional diagnostic accuracy study was to validate the DHI milk BHB test to identify cows with hyperketonemia as determined by quantification of BHB in serum. A total of 316 cows from 17 dairy herds in southwestern Ontario had a milk and blood sample taken. Milk was collected at a routine DHI test, and blood from the same cow was sampled within 24 h of the milk test. The BHB concentration in milk was determined using the DHI milk BHB test, and serum was sent to the Animal Health Laboratory at the University of Guelph (Guelph, ON, Canada). A nonparametric receiver operating characteristic curve was generated to compare DHI milk BHB concentrations with serum BHB concentrations. Overall, a total of 34 cows (11%) had a level of serum BHB ≥1.2 mmol/L. The concentration of DHI milk BHB was moderately correlated with the concentration of serum BHB, yielding a coefficient of determination value of 0.61. The optimal cut point for determining hyperketonemia (≥1.2 mmol/L) on the DHI milk BHB test was ≥0.14 mmol/L, yielding a sensitivity of 81% and specificity of 92%. The performance of the DHI milk BHB test varied depending on the days in milk (DIM) of the cows tested, with a higher specificity being found in cows that were ≤25 DIM compared with cows tested >25 DIM. If the herd-level prevalence of hyperketonemia was ≥14%, the DHI milk BHB test had an improved sensitivity when compared with a herd-level prevalence of <14%. This study demonstrates that the DHI milk BHB test is a reliable measure for evaluating hyperketonemia using routine DHI milk samples and could be used as a herd-level monitoring tool for ketosis when evaluating nutritional management or preventative medicine strategies.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.054
GPT teacher head0.305
Teacher spread0.251 · 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 designBench or experimental
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

Citations20
Published2018
Admission routes2
Has abstractyes

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