SynthesisScientific reports2022
Systematic review and network meta-analysis to compare vaccine effectiveness against porcine edema disease caused by Shiga toxin-producing Escherichia coli.
Synthesis in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Quantitative evaluation of the efficacy of non-replicating vaccines for controlling African swine fever in domestic pigs: a systematic review and meta-analysis.Frontiers in veterinary science · 2025Pooled it
- Practical Review on Aetio-Pathogenesis and Symptoms in Pigs Affected by Clinical and Subclinical Oedema Disease and the Use of Commercial Vaccines Under Field Conditions.Animals : an open access journal from MDPI · 2025Review
- Phenotypic and genotypic profiling of swine-derived Shiga toxin-producingFrontiers in microbiology · 2025Article
- Shiga Toxin: Emerging Producer Strains, Prophylactic Approaches, and Application in Cancer Therapy.Journal of cancer prevention · 2024Review
- Article
- Evaluation of the Humoral Response after Immunization with a Chimeric Subunit Vaccine against Shiga Toxin-ProducingVaccines · 2024Article
- Tobacco Seed-Based Oral Vaccination against Verocytotoxic O138Antibiotics (Basel, Switzerland) · 2023Article
- Targeted delivery of oral vaccine antigens to aminopeptidase N protects pigs against pathogenicFrontiers in immunology · 2023Article
- Evidence-Based Approaches for Determining Effective Target Antigens to Develop Vaccines against Post-Weaning Diarrhea Caused by EnterotoxigenicAnimals : an open access journal from MDPI · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The comprehensive effect size of several commercial vaccines and vaccine candidates against edema disease (ED) has not been evaluated to date. To integrate the effectiveness of ED vaccines reported so far and to compare and evaluate the posterior-effect estimates of each vaccine type with network models, we identified eligible studies (n = 12) from the electronic databases using specified search strings. Data for dichotomous outcomes (i.e., mortality and clinical symptoms) and continuous outcomes (i.e., fecal shedding and average daily gain) were extracted and analyzed. Conventional meta-analysis shows that, compared with that in non-vaccinated pigs, vaccinated animals are likely to show reduced mortality (OR = 0.07) and clinical signs of ED (OR = 0.11), and increased productivity (SMD = 0.73). Although reduced fecal shedding (SMD = - 1.29) was observed in vaccinated pigs, this could not be fully determined on insufficient grounds. In contrast to mortality and clinical symptoms, fecal shedding (I
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.