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Record W2054775208 · doi:10.3168/jds.2011-4711

Manageable risk factors associated with the lactational incidence, elimination, and prevalence of Staphylococcus aureus intramammary infections in dairy cows

2012· article· en· W2054775208 on OpenAlexafffundabout
Simon Dufour, Ian R. Dohoo, Herman W. Barkema, Luc DesCôteaux, T.J. DeVries, Kristen K. Reyher, J.-P. Roy, D.T. Scholl

Bibliographic record

VenueJournal of Dairy Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Prince Edward IslandUniversity of GuelphUniversity of CalgaryUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicineIncidence (geometry)MastitisPrevalenceHerdInterquartile rangeVeterinary medicineLogistic regressionStaphylococcus aureusEnvironmental healthEpidemiologyBiologyInternal medicine

Abstract

fetched live from OpenAlex

Staphylococcus aureus intramammary infections (IMI) are a major cause of mastitis on farms worldwide. Incidence and elimination rates are the key determinants of prevalence of Staph. aureus, and risk factors associated with these rates must be identified, prioritized, and controlled to obtain long-term reduction in prevalence. The objectives of this study were to identify manageable risk factors associated with the lactational incidence, elimination, and prevalence of Staph. aureus IMI. A cohort of 90 Canadian dairy farms was recruited and followed in 2007 and 2008. Quarter milk samples were collected repeatedly from a selection of cows, and bacteriological culture was realized to assess incidence, elimination, and prevalence of Staph. aureus IMI. Practices used on farms were measured using direct observations and a validated questionnaire. A linear regression model was used to explore the relationship between herd IMI prevalence and incidence and elimination rates. Multilevel logistic regression models were used to compute measures of associations between practices used on farms and IMI incidence, elimination, and prevalence. The herd incidence rate was the most important predictor of herd IMI prevalence: a reduction of the incidence rate equivalent to its interquartile range (0.011 new IMI/quarter-month) was associated with a prevalence reduction of 2.2 percentage points; in comparison, an equivalent increase of the elimination rate by its interquartile range (0.36 eliminated IMI/quarter-month) resulted in a prevalence reduction of 0.4 percentage points. Postmilking teat disinfection and blanket dry-cow therapy were already implemented by most herds. Most of the practices associated with Staph. aureus IMI incidence were related to milking procedures. Among these, wearing gloves during milking showed desirable associations with IMI incidence, elimination, and prevalence. Similarly, adequate teat-end condition and use of premilking teat disinfection were associated with lower IMI incidence and prevalence. The initial herd prevalence of Staph. aureus IMI was positively associated with subsequent IMI incidence. This indicates that, in some situations, an initial reduction of the pool of infected quarters could be justified. Some housing practices were associated with IMI incidence, elimination, or prevalence. The effects of these latter practices, however, were often influenced by specific cow characteristics such as parity or days in milk. These results highlight the importance of good milking practices to prevent Staph. aureus IMI acquisition and, therefore, reduce their prevalence.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0000.000
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 head0.022
GPT teacher head0.246
Teacher spread0.225 · 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

Citations106
Published2012
Admission routes3
Has abstractyes

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