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Record W3007031632 · doi:10.1017/s1466252319000173

Efficacy of bacterial vaccines to prevent respiratory disease in swine: a systematic review and network meta-analysis

2019· review· en· W3007031632 on OpenAlexaff
Jan M. Sargeant, Bhumika Deb, Michele D. Bergevin, Katheryn J. Churchill, Kaitlyn Dawkins, Jennifer Dunn, Dapeng Hu, Carly M. Moody, Annette M. O’Connor, Terri L. O’Sullivan, Mark Reist, Chong Wang, Barbara Wilhelm, Charlotte B. Winder

Bibliographic record

VenueAnimal Health Research Reviews · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMycoplasma hyopneumoniaePleuropneumoniaMedicinePasteurella multocidaActinobacillus pleuropneumoniaeBordetella bronchisepticaClinical trialIntensive care medicineSystematic reviewMeta-analysisImmunologyInternal medicineMEDLINEBiologyVirology

Abstract

fetched live from OpenAlex

A systematic review and network meta-analysis (MA) was conducted to address the question, 'What is the efficacy of bacterial vaccines to prevent respiratory disease in swine?' Four electronic databases and the grey literature were searched to identify clinical trials in healthy swine where at least one intervention arm was a commercially available vaccine for one or more bacterial pathogens associated with respiratory disease in swine, including Mycoplasma hyopneumoniae, Actinobacillus pleuropneumonia, Actinobacillus suis, Bordetella bronchiseptica, Pasteurella multocida, Stretococcus suis, Haemophils parasuis, and Mycoplasma hyorhinis. To be eligible, trials had to measure at least one of the following outcomes: incidence of clinical morbidity, mortality, lung lesions, or total antibiotic use. There were 179 eligible trials identified in 146 publications. Network MA was undertaken for morbidity, mortality, and the presence or absence of non-specific lung lesions. However, there was not a sufficient body of research evaluating the same interventions and outcomes to allow a meaningful synthesis of the comparative efficacy of the vaccines. To build this body of research, additional rigor in trial design and analysis, and detailed reporting of trial methods and results are warranted.

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)0.020
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.809
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0160.003
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.434
GPT teacher head0.529
Teacher spread0.095 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations22
Published2019
Admission routes1
Has abstractyes

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