Evidence Hub

Bacteriological Profile and Antibiotic Sensitivity Pattern of Urinary Tract Infection

Muhammed Muhiuddin Mazumder, Mesbah Uddin Noman, A. K. M. Tariqul Hasan, Tofael Ahammod, Ali Abdullah Rafique, Mijanur Rahman

East West Medical College Journal, 2025

1 citation

Abstract

Introduction:Urinary tract infection (UTI) is a common infection that may occur in any part of the urinary system - kidneys, ureters, bladder and urethra. UTIs are caused by a wide range of pathogens, and recurrence rates of UTIs are high. Antibiotic resistance to microorganism is a burning issue all over the world due to inappropriate antibiotic use. Antibiotic resistance leads to morbidity, mortality and overall, the economic burden. Therefore, surveillance of antimicrobial resistance of UTI is essential to see its impact on population health and local treatment practices.

Objective: This study was conducted to identify the bacterial agents of urinary tract infections and determine antibiogram patterns.

Methods: A cross-sectional study was conducted at the outpatient service. The study included all patients who presented with UTIs and the symptoms included urinary frequency, urgency, hematuria, dysuria, and suprapubic discomfort. Those patients with clinical manifestations but are on antibiotics or antibiotics completed within the past five days were excluded.

Results: The prevalence of UTI is high among females (88.67%) than males (13.33%). Among 30 samples, the pathogens implicated were Escherichia coli (E. coli) 24 (80%), Klebsiella 3. Organisms showed higher sensitivity toward Meropenem and Imipenem (100%) followed by Amikacin and Nitrofurantoin (96.6%). Isolates organisms showed high resistance levels to betalactamaes ampicillin (60%) and cephalosporines groups.…

How strong is the evidence?

Evidence Hub reads this as a cross-sectional. 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