SynthesisBMC veterinary research2025
Text mining and topic modeling insights on fish welfare and antimicrobial use in aquaculture.
Synthesis in BMC veterinary research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Quantitative assessment of china's policies on the online sale of prescription drugs.PloS one · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antimicrobial use (AMU) and antibiotic resistance (AR) in aquaculture present growing concerns for public health. Furthermore, there exists a correlation between fishes' welfare and AMU. This systematic review aims to analyze the scientific literature on fishes' welfare and AMU/AR over the last 32 years, identifing the main research topics, and the fields where investigation has been imitated. A comprehensive search was conducted using Scopus, employing specific keywords related to AMU/AR and welfare and preselected filters. The study employed a systematic approach following the PRISMA guidelines, and machine learning techniques were used. From 2,019 records retrieved, only those focused-on fishes welfare and AMU/AR were retained. Ultimately, 185 records showing a connection between these topics were included in the qualitative analysis. Text mining analysis revealed terms with the highest weighted frequency in the data corpus, while topic analysis identified the top five core areas: Topic 1 (Antibiotic resistance and strain genetic isolation), Topic 2 (Aquaculture and Human Health, environment, and food), Topic 3 (Fish response to stress and indicators), Topic 4 (Control of water and fish growth), and Topic 5 (Aquaculture research and current farming methods). The results indicate a growing interest in fish welfare and AMU/AR, while also highlighting areas that require further investigation, such as the link between these research fields. Improving fish welfare can reduce AR, aligning with the One Health policy.
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.