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Record W4307581083 · doi:10.3168/jds.2022-22187

Evaluating the effectiveness of colostrum as a therapy for diarrhea in preweaned calves

2022· article· en· W4307581083 on OpenAlexaffabout
H.S.M. Carter, M.A. Steele, J.H.C. Costa, D.L. Renaud

Bibliographic record

VenueJournal of Dairy Science · 2022
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsColostrumDiarrheaMedicineFecesAnimal scienceInternal medicineBiologyAntibodyImmunologyMicrobiology

Abstract

fetched live from OpenAlex

Diarrhea is the primary cause of morbidity and mortality in dairy calves. Many cases of diarrhea in calves are treated with antimicrobials, increasing the risk of antimicrobial resistance, therefore, creating a need for alternative therapies. The objective of this study was to evaluate the effects of feeding spray-dried maternal derived bovine colostrum replacer at the onset of diarrhea on calf growth and duration and severity of the disease in preweaning dairy calves. At a calf-raising facility in southern Ontario, calves were scored for fecal consistency twice daily on a scale of 0 to 3 and enrolled into the trial when they had 2 consecutive fecal scores of 2 (runny or spreads readily) or one fecal score of 3 (liquid consistency, splatters). Calves were then randomly allocated to receive one of the following 3 treatments: (1) control (CON; n = 35): 8 feedings over 4 d of 2.5 L of milk replacer at a concentration of 130 g/L (26% crude protein and 17% fat); (2) short-term colostrum supplementation (STC; n = 35): 4 feedings over the first 2 d of 2.5 L of a mixture of milk replacer at 65 g/L and bovine colostrum replacer at 65 g/L (26% IgG and 14.5% fat) followed by 4 feedings over 2 d of 2.5 L of milk replacer at a concentration of 130 g/L; or (3) long-term colostrum supplementation (LTC; n = 38): 8 feedings over 4 d of 2.5 L of a mixture of milk replacer at 65 g/L and bovine colostrum replacer at 65 g/L. Serum IgG was determined at arrival to the facility and body weight, days to enrollment since facility arrival, and severity of diarrhea were recorded at enrollment. Daily health exams evaluating fecal consistency were performed for 28 consecutive days after enrollment and body weight was measured at d 0, 1, 2, 3, 4, 7, 14, 21, 28, 42 and 56 after enrollment. The median days to resolution of a case of diarrhea was 3.5 d (range: 0.5-11.5 d), 2.75 d (range: 0.5-11.0 d), and 2.75 d (range: 0.5-7.0 d) in CON, STC, and LTC, respectively. Using a Cox proportional hazards model, it was found that calves in LTC group had faster resolution of diarrhea compared with calves in the CON group. In addition, there was an association between both days to enrollment since facility arrival and body weight and resolution of diarrhea, where calves who were at the facility longer before enrollment and heavier at the onset of diarrhea, resolved diarrhea quicker. In addition, calves with a fecal score of 3 at enrollment took longer to resolve their case of diarrhea. With respect to body weight, a linear regression model was built and found that over the 56 d following enrollment calves in the LTC treatment grew 98 g/d more than calves in the CON group. These results suggest that bovine colostrum may be an effective therapy for diarrhea in preweaning calves.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.446
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2022
Admission routes2
Has abstractyes

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