Evidence map›Paper›PMID 39897495›Full record

ArticlePeerJ2025

Clinical considerations on antimicrobial resistance potential of complex microbiological samples.

Norbert Solymosi, Adrienn Gréta Tóth, Sára Ágnes Nagy, István Csabai, Csongor Feczkó, Tamás Reibling, Tibor Németh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Norbert SolymosiCentre for Bioinformatics, University of Veterinary Medicine, Budapest, Hungary.ORCID 0000-0003-1783-2041
Adrienn Gréta TóthCentre for Bioinformatics, University of Veterinary Medicine, Budapest, Hungary.
Sára Ágnes NagyDepartment of Physics of Complex Systems, Eötvös Loránd University, Budapest, Hungary.
István CsabaiDepartment of Physics of Complex Systems, Eötvös Loránd University, Budapest, Hungary.
Csongor FeczkóCentre for Bioinformatics, University of Veterinary Medicine, Budapest, Hungary.
Tamás ReiblingCentre for Bioinformatics, University of Veterinary Medicine, Budapest, Hungary.
Tibor NémethDepartment and Clinic of Surgery and Ophthalmology, University of Veterinary Medicine, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) is one of our greatest public health challenges. Targeted use of antibiotics (ABs) can reduce the occurrence and spread of AMR and boost the effectiveness of treatment. This requires knowledge of the AB susceptibility of the pathogens involved in the disease. Therapeutic recommendations based on classical AB susceptibility testing (AST) are based on the analysis of only a fraction of the bacteria present in the disease process. Next and third generation sequencing technologies allow the identification of antimicrobial resistance genes (ARGs) present in a bacterial community. Using this metagenomic approach, we can map the antimicrobial resistance potential (AMRP) of a complex, multi-bacterial microbial sample. To understand the interpretiveness of AMRP, the concordance between phenotypic AMR properties and ARGs was investigated by analyzing data from 574

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialEscherichia coliGenotypeHumansMetagenomicsMicrobial Sensitivity TestsPhenotypeAnti-Bacterial AgentsAntimicrobial resistanceClinical metagenomicsComplex microbial sampleGenomics

Identifiers

PMID39897495
PMCPMC11784533

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.