Evidence map›Paper›PMID 41634543›Full record

ArticleBMC microbiology2026

The spectrum of nasal colonization: frequency and resistant patterns in diabetes versus non-diabetes population.

Maryam Rabeh, Samaneh Shahrokh, Mojtaba Akbari, Najmeh Ansari, Mansour Siavash, Maryam Yazdi

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Article in BMC microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Maryam RabehDepartment of Microbiology, Faculty of Biological Sciences and Technology, Shahid Ashrafi Esfahani University, Isfahan, Iran.
Samaneh ShahrokhIsfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Khorram Street, Isfahan, Iran. s.shahrokh143@gmail.com.ORCID 0000-0002-9975-2020
Mojtaba AkbariIsfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Khorram Street, Isfahan, Iran.
Najmeh AnsariClinical Microbiology Laboratory, Imam Hussein Hospital, Isfahan, Iran.
Mansour SiavashIsfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Khorram Street, Isfahan, Iran.
Maryam YazdiChild Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Diseases, Isfahan University of Medical Sciences, Isfahan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe nasal cavity serves as a primary contact site and is a common location for colonization by symbiotic, opportunistic, and potentially pathogenic bacteria. Diabetic patients are more susceptible to colonization by opportunistic microorganisms due to impaired immune function, altered normal flora, and increased exposure to healthcare. This study aimed to investigate the nasal colonization of Gram-positive (Staphylococcus aureus) and Gram-negative (Enterobacteriaceae) bacteria in diabetic and non-diabetic individuals, assessing phenotypic traits including antibiotic resistance and biofilm production, as well as investigating the presence of resistant genes. MATERIALS AND

methodsIn this cross-sectional study, nasal swabs were collected from 150 diabetic and 150 non-diabetic individuals. Isolates were identified and evaluated phenotypically (Antibiotic resistance using the disk diffusion method and biofilm formation by the microtiter plate method) and genotypically (resistance genes including mecA, bla

resultsThe rate of S. aureus colonization was higher in diabetics (18.7%) than in non-diabetics (12.7%) and MRSA colonization was significantly higher in diabetics (8% vs. 1.3%). High antibiotic resistance was not observed except for tetracycline (nearly 50%) in S. aureus isolates from both groups. There was no statistically significant difference in the occurrence of MDR S. aureus between the diabetic (32.1%) and non-diabetic (31.6%) groups. Enterobacteriaceae colonization was 3.3% in diabetics and 7.3% in non-diabetics. Although none were phenotypically ESBL-positive, bla

conclusionNasal MRSA colonization was more common among diabetic patients than non-diabetics. The findings of this study highlight the need for ongoing monitoring of nasal colonization of MRSA in different populations and settings, which may lead to the development of effective preventive and therapeutic strategies to control infections caused by nasal colonization.

Indexed as

Carrier StateDiabetes MellitusDrug Resistance, BacterialEnterobacteriaceaeNasal CavityStaphylococcus aureusAdultAgedAnti-Bacterial AgentsBiofilmsCross-Sectional StudiesFemaleHumansMaleMicrobial Sensitivity TestsMiddle AgedAnti-Bacterial AgentsAntimicrobial resistanceColonizationDiabetesEnterobacteriaceaeNasalStaphylococcus aureus

Identifiers

PMID41634543
PMCPMC12958542

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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.