Evidence map›Paper›PMID 36057710›Full record

ArticleBMC veterinary research2022

Patterns of antimicrobial resistance in Salmonella isolates from fattening pigs in Spain.

Kendy Tzu-Yun Teng, Marc Aerts, Stijn Jaspers, Maria Ugarte-Ruiz, Miguel A Moreno, Jose Luis Saez, Soledad Collado, Cristina de Frutos, Lucas Dominguez, Julio Alvarez

Open access · goldAbstract read
In one paragraph

Article in BMC veterinary research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Kendy Tzu-Yun TengVISAVET Health Surveillance Centre, Universidad Complutense, Madrid, Spain. kendy.t.teng@gmail.com.
Marc AertsInteruniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
Stijn JaspersInteruniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium.
Maria Ugarte-RuizVISAVET Health Surveillance Centre, Universidad Complutense, Madrid, Spain.
Miguel A MorenoVISAVET Health Surveillance Centre, Universidad Complutense, Madrid, Spain.
Jose Luis SaezSubdirección General de Sanidad e Higiene Animal y Trazabilidad, Dirección General de La Producción Agraria, Ministerio de Agricultura, Pesca y Alimentación, Madrid, Spain.
Soledad ColladoSubdirección General de Sanidad e Higiene Animal y Trazabilidad, Dirección General de La Producción Agraria, Ministerio de Agricultura, Pesca y Alimentación, Madrid, Spain.
Cristina de FrutosLaboratorio Central de Veterinaria (LCV Algete), Ministerio de Agricultura, Pesca y Alimentación, Madrid, Spain.
Lucas DominguezVISAVET Health Surveillance Centre, Universidad Complutense, Madrid, Spain.
Julio AlvarezVISAVET Health Surveillance Centre, Universidad Complutense, Madrid, Spain.
Universidad Complutense de Madrid · ESMinisterio de Agricultura, Pesca y Alimentación · ESHasselt University · BE

Funding

The European Union's Horizon 2020 Research and Innovation program Grant Agreement No 773830
6 · The paper itself

Abstract

backgroundSwine are considered a major source of foodborne salmonellosis, a public health issue further complicated by the circulation of multidrug-resistant Salmonella strains that threaten the safety of the food chain. The current study aimed to identify patterns that can help to understand the epidemiology of antimicrobial resistance (AMR) in Salmonella in pigs in Spain through the application of several multivariate statistical methods to data from the AMR national surveillance programs from 2001 to 2017.

resultsA total of 1,318 pig Salmonella isolates belonging to 63 different serotypes were isolated and their AMR profiles were determined. Tetracycline resistance across provinces in Spain was the highest among all antimicrobials and ranged from 66.7% to 95.8%, followed by sulfamethoxazole resistance (range: 42.5% - 77.8%), streptomycin resistance (range: 45.7% - 76.7%), ampicillin resistance (range: 24.3% - 66.7%, with a lower percentage of resistance in the South-East of Spain), and chloramphenicol resistance (range: 8.5% - 41.1%). A significant increase in the percentage of resistant isolates to chloramphenicol, sulfamethoxazole, ampicillin and trimethoprim from 2013 to 2017 was observed. Bayesian network analysis showed the existence of dependencies between resistance to antimicrobials of the same but also different families, with chloramphenicol and sulfamethoxazole in the centre of the networks. In the networks, the conditional probability for an isolate susceptible to ciprofloxacin that was also susceptible to nalidixic acid was 0.999 but for an isolate resistant to ciprofloxacin that was also resistant to nalidixic acid was only 0.779. An isolate susceptible to florfenicol would be expected to be susceptible to chloramphenicol, whereas an isolate resistant to chloramphenicol had a conditional probability of being resistant to florfenicol at only 0.221. Hierarchical clustering further demonstrated the linkage between certain resistances (and serotypes). For example, a higher likelihood of multidrug-resistance in isolates belonging to 1,4,[5],12:i:- serotype was found, and in the cluster where all isolates were resistant to tetracycline, chloramphenicol and florfenicol, 86.9% (n = 53) of the isolates were Typhimurium.

conclusionOur study demonstrated the power of multivariate statistical methods in discovering trends and patterns of AMR and found the existence of serotype-specific AMR patterns for serotypes of public health concern in Salmonella isolates in pigs in Spain.

Indexed as

Anti-Bacterial AgentsDrug Resistance, Multiple, BacterialAnimalsBayes TheoremChloramphenicolCiprofloxacinDrug Resistance, BacterialMicrobial Sensitivity TestsNalidixic AcidSalmonellaSpainSulfamethoxazoleSwineAnti-Bacterial AgentsChloramphenicolCiprofloxacinNalidixic AcidSulfamethoxazole1,4,[5],12:i:-Bayesian network analysisHierarchical clusteringMultidrug resistanceMultivariate analysisTyphimurium

Identifiers

PMID36057710
PMCPMC9440507
OpenAlexW4294415279

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.