Journal of Krishna Institute of Medical Sciences University (Apr 2024)
Risk factors, bacterial profile, and outcomes of urinary tract infection among children treated at a secondary care hospital in Oman
Abstract
Background: Urinary Tract Infection (UTI) is a prevalent issue in children, which is associated with significant morbidity and mortality. This study aimed to understand the bacterial etiology, antibiotic susceptibility patterns, and associated risk factors for UTIs in children aged 0–13 years. Aim and Objectives: Our study aimed to determine the prevalence of pediatric UTI, clinical profile, risk factors, etiology, and antimicrobial resistance pattern with a special emphasis on change in resistance pattern. Material and Methods: The retrospective study, approved by Oman's research committee, involved children aged 0–13 diagnosed with UTI from January 2017 to December 2022. The relevant data of the study subjects was retrieved from hospital electronic health records. Data were analyzed using SPSS version 26, with qualitative data reported in frequencies and percentages, while quantitative data were represented by the mean and standard deviation. Results: The study involved 295 non-duplicate bacterial isolates recovered from 275 patients. The frequency of isolation was predominant in females (65.5%) and in infants (37.5%). Congenital anomalies such as prenatal hydronephrosis (6.5%) and vesicoureteral reflux (3.6%) were the most common risk factors for UTI in children. Poor fluid intake (5.8%), urolithiasis (1.8%), obesity (1.5%), and infrequent voiding of urine (1.5%) were the other independent risk factors for UTI noticed in our study. Septicemia was observed in 1.5% of the subjects. Escherichia coli (55.3%), Klebsiella pneumoniae (22.3%), and Pseudomonas aeruginosa (5.8%) were the most common etiological agents causing UTI. Extended-Spectrum Beta-Lactamases (ESBL) production was observed in 32.3% and 29.4% of K. pneumoniae and E. colistrains, respectively. Conclusion: In summary, the updated knowledge of local data will help clinicians manage cases, administer appropriate antibiotic treatment, and alleviate antibiotic resistance.