Evidence map›Paper›PMID 38854980›Full record

ArticleIranian journal of microbiology2024

Sequence-subtype association of multi-drug-resistant diarrheagenic

Nastaran Farzi, Zahra Pourramezan, Fatemeh Akhavan Attar, Saeid Mostaan, Mana Oloomi

Abstract read
In one paragraph

Article in Iranian journal of microbiology, 2024. 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

5 authors.

Nastaran FarziDepartment of Molecular Biology, Pasteur Institute of Iran, Tehran, Iran.
Zahra PourramezanDepartment of Molecular Biology, Pasteur Institute of Iran, Tehran, Iran.
Fatemeh Akhavan AttarDepartment of Molecular Biology, Pasteur Institute of Iran, Tehran, Iran.
Saeid MostaanDepartment of Molecular Biology, Pasteur Institute of Iran, Tehran, Iran.
Mana OloomiDepartment of Molecular Biology, Pasteur Institute of Iran, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Multi-drug-resistant pathogens pose a significant threat as they can rapidly spread, leading to severe healthcare-associated invasive infections. In developing countries, diarrheagenic Materials and Methods: The phylogenetic grouping was defined using PCR and multi-locus sequence type (MLST) methods. Results: Among the isolates analyzed, 14 were identified as resistant and were classified into eight distinct sequence types: ST3, ST53, ST77, ST483, ST512, ST636, ST833, and ST774, indicating genetic diversity among the resistant strains. Certain sequence types, notably ST512 and ST636, were found to be associated with multiple antibiotic resistance in DEC. Regarding antibiotic susceptibility, strains showed the highest resistance to amoxicillin, suggesting that this antibiotic may not be effective in treating DEC infections. On the other hand, the isolates demonstrated susceptibility to amikacin and chloramphenicol, implying that these antibiotics could be more suitable treatment options for DEC infections. Conclusion: The findings underscore the importance of promptly identifying antibiotic resistance patterns and their correlation with specific pathogenic virulence categories, as this knowledge can aid in selecting the most appropriate antibiotics for treating DEC infections. Considering the antibiotic resistance profiles and associated resistance genes is crucial in managing and containing diarrheal outbreaks and in selecting effective antibiotic therapies for DEC infections.

Indexed as

Escherichia coliMultidrug resistantMultilocus sequence typingVirulence factorsβ-lactams

Identifiers

PMID38854980
PMCPMC11162169

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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.