Evidence Hub

Antibiotic Resistance and Resistant Genes among Isolates from Diabetic Patients with Urinary Tract Infections at Benjamin Mkapa Hospital: A Cross-Sectional Study

Mzelifa Daud, M. Varisanga, A. Gimbi

Open Microbiology Journal, 2026

Abstract

The emergence of antibiotic-resistant bacteria is a growing public health concern that complicates the prevention, control, and management of bacterial infections and has become a global challenge. Urinary tract infections (UTIs), which are among the most common bacterial infections worldwide, are increasingly associated with antibiotic-resistant pathogens. The present study focused on determining both the phenotypic and genotypic characteristics of antimicrobial-resistant bacteria isolated from diabetic patients with UTIs at Benjamin Mkapa Hospital in the Dodoma region, Tanzania.

This hospital-based cross-sectional study was conducted at Benjamin Mkapa Hospital (BMH) in Dodoma, Tanzania. Midstream urine samples were collected and inoculated onto blood agar and Cystine–Lactose–Electrolyte-Deficient (CLED) agar. Antibiotic susceptibility testing (AST) was performed using the Kirby–Bauer disc diffusion method, and results were interpreted according to the 2024 Clinical and Laboratory Standards Institute (CLSI) guidelines. Data were expressed as percentages and proportions. Sequencing results were analysed using the BLAST online search tool.

Out of 419 cultured samples, 261 (62.3%) showed significant bacterial growth. The isolates included coagulase-negative staphylococci (CoNS),

Escherichia coli

,

Klebsiella pneumoniae

,

Pseudomonas aeruginosa

, and

Staphylococcus aureus

. The majority of the isolates were susceptible to amikacin (97%), piperacillin–tazobactam (72%), imipenem…

How strong is the evidence?

Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free