Efficacy of <i>Borrelia burgdorferi</i> vaccine in dogs in North America: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Lyme borreliosis, a tick-borne disease, is endemic to some parts of North America and is an emerging disease in other parts of the world. Vaccination is an increasingly common, although controversial, method used in the prevention of Lyme disease in dogs; the reported efficacies of Borrelia burgdorferi vaccines in dogs are highly variable, ranging from 50% to 100%. OBJECTIVES: To determine the efficacy of vaccines for prevention of Lyme disease in dogs in North America. METHODS: Experimental and observational study designs were eligible for inclusion. The outcome of interest was the reduction of incidence of clinical illness after exposure to B. burgdorferi. Electronic databases searched were MEDLINE, Web of Science, and Centre for Agricultural Biosciences Abstracts. Clinical signs were extracted as dichotomous outcomes: lameness, anorexia, pyrexia, depression, and lymphadenopathy. Study quality was assessed using tools from the Cochrane collaboration. RESULTS: In total, 3 observational studies and 13 challenge trials were included. None of the challenge trials assessed lymphadenopathy, but for each of the remaining 4 clinical signs, a meta-analysis was performed. Compared to unvaccinated dogs, vaccinated dogs had a reduced odds of developing lameness, depression, pyrexia, and anorexia (odds ratio: 0.15-0.23). CONCLUSIONS AND CLINICAL IMPORTANCE: Based on the quantitative synthesis of results from challenge studies, vaccinated dogs are less likely to develop clinical signs after exposure to B. burgdorferi compared to unvaccinated dogs. These results should be interpreted with caution, however, as several shortcomings related to quality and study design were identified. Future studies should focus on larger sample sizes in field conditions.
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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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.029 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".