PHENOTYPIC ANTIMICROBIAL RESISTANCE PATTERNS AND RESISTANCE GENE DISTRIBUTION ACROSS CLINICAL SPECIMENS: ASSOCIATIONS WITH PATIENT CHARACTERISTICS AND CLINICAL OUTCOMES

  • Prof. Ayodele Oluwaseun Ajayi Department of Microbiology, Federal University Oye-Ekiti, Ekiti State, Nigeria,
  • Prof. Dwij Raj Bhatta Central Department of Microbiology, Tribhuvan University, Kathmandu, Nepal
  • Ayush Kumar Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada
  • Dr. Inshad Ali Khan Department of Microbiology, Central University of Rajasthan, Ajmer, Rajasthan, India
Keywords: Antimicrobial resistance, phenotypic susceptibility, resistance genes, clinical specimens, clinical outcomes

Abstract

Antimicrobial resistance represents an increasing clinical and microbiological challenge, requiring integrated assessment of phenotypic susceptibility, resistance genes, and patient-related outcomes. This study evaluated phenotypic antimicrobial resistance patterns and resistance-gene distribution across clinical specimens and examined their associations with demographic characteristics and clinical outcomes using secondary data from 2,200 records. Susceptibility to amoxicillin, ciprofloxacin, meropenem, vancomycin, and colistin was classified as sensitive, intermediate, or resistant, while resistance burden was defined as the number of antibiotics classified as resistant. Descriptive statistics, Pearson chi-square tests, Cramer's V, Kruskal-Wallis testing, and multivariable binary logistic regression were applied. Meropenem showed the highest resistance proportion (34.3%), whereas colistin showed the lowest (31.9%). VIM was the most frequently recorded resistance gene (21.0%), followed by OXA-48 (20.5%). Resistance-gene distribution was not significantly associated with specimen type, and resistance burden did not differ significantly across recovered, ICU, and deceased groups. Multivariable analysis identified no significant independent predictors of adverse clinical outcome. The findings support integrated phenotypic, molecular, and clinical surveillance for antimicrobial resistance assessment.

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Published
2026-08-29
How to Cite
Prof. Ayodele Oluwaseun Ajayi, Prof. Dwij Raj Bhatta, Ayush Kumar, & Dr. Inshad Ali Khan. (2026). PHENOTYPIC ANTIMICROBIAL RESISTANCE PATTERNS AND RESISTANCE GENE DISTRIBUTION ACROSS CLINICAL SPECIMENS: ASSOCIATIONS WITH PATIENT CHARACTERISTICS AND CLINICAL OUTCOMES. IJRDO - JOURNAL OF BIOLOGICAL SCIENCE, 12(3), 152-167. https://doi.org/10.69980/bs.v12i3.6819