Effects of calfhood respiratory disease on health and performance of dairy cattle: A systematic review and meta-analysis
Bibliographic record
Abstract
Bovine respiratory disease (BRD) is one of the most common calfhood diseases in dairy cattle. Unfortunately, published data on the short- and long-term effects of calfhood BRD on health and performance are scarce and, when available, often conflicting and uncertain. The objective of this study was therefore to review the scientific literature on the effects of calfhood BRD on health and performance of dairy cattle and summarize the research findings using a meta-analysis approach. The systematic review and meta-analysis were performed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed and CAB Abstract databases were screened for relevant studies that were published in English (until February 3, 2020). Only studies reporting naturally occurring BRD cases from birth to 12 mo of age in dairy calves in Europe and North America were considered eligible. Both observational studies and randomized controlled trials were included. Random-effect meta-analysis models were used to quantify the effect of BRD on outcomes for which at least 5 studies reported a numeric estimation of the effect of BRD. From an initial pool of 525 references, 27 full-text articles with original data were included in the manuscript. Meta-analysis models were prepared for 4 outcomes: odds of mortality (n = 7 studies), odds of herd removal before first calving (n = 5 studies), average daily gain (n = 10 studies), and milk production during first lactation (n = 5 studies). In these models, heifers diagnosed with BRD during calfhood had 2.85 times higher odds of dying (95% confidence interval: 1.22 to 6.69) and 2.30 times higher odds of herd removal (i.e., dead, culled, or sold) before the first calving (95% confidence interval: 1.75 to 3.03) compared with heifers not diagnosed with this condition. Heifers experiencing calfhood BRD also had an average daily gain reduced by 0.067 kg/d (95% confidence interval: -0.099 to -0.034) and they produced 121.2 kg (95% confidence interval: -184.9 to -57.5) less milk during their first lactation. Other health and performance outcomes, such as age at first calving and odds of not finishing the first lactation, were also investigated but not summarized using a meta-analysis approach. Pooled estimates obtained in the present study may provide more accurate estimates of the overall economic losses associated with calfhood BRD in dairy cattle.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.049 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".