A decade-long analysis of trends in antimicrobial resistance at a neurosurgical hospital in Kathmandu, Nepal

Background: Multidrug-resistant (MDR) bacteria cause infections with higher risks of morbidity, mortality, and financial burden, emphasizing the importance of understanding pathogen-specific resistance patterns for effective treatment and resistance management. Therefore, this retrospective cohort study examined the prevalence, causes, and trends of antimicrobial resistance in bacterial infections in a neurosurgical hospital in Nepal.

Method: We analyzed the demographics, bacteriological profiles, and antimicrobial susceptibility results of patients who visited a neurosurgical hospital in Kathmandu, Nepal, between January 2014 and January 2024, using SPSS, version 17.00.

Results: Among 4,758 patients, 465 (9.77%) had infections caused by 571 bacteria. Of them, 435 (93.55%) patients had urinary tract infections, 89 (19.14%) had bloodstream infections, and 31 (6.67%) had respiratory tract infections. Klebsiella pneumoniae (n=172, 30.12%) was the predominant bacteria. Resistance rates for Enterobacterales and GPC against tetracyclines were 83.33% and 45.83%, cephalosporins were 78.02% and 40.45%, quinolones were 72.25% and 50.00%, aminoglycosides were 65.14% and 43.53%, carbapenems were 62.96% and 30.00%, penicillins were 54.55% and 57.89%, and penicillin with beta-lactamase inhibitors (PwBLIs) were 40.54% and 42.31%, respectively. Non-fermenters showed 100% resistance to these antibiotics. MDR isolates (n=118, 20.67%) were 100.00% susceptible to piperacillin-tazobactam and 83.33% to polymyxin B. Over the years, resistance increased for cephalosporins (48.15-60.53%) but decreased for carbapenems (50.00-33.33%), penicillins (64.29-42.31%), PwBLIs (50.00-12.50%), aminoglycosides (60.00-49.12%), tetracyclines (100.00-16.67%), and polymyxins (76.22-16.67%).

Conclusion: One-tenth of hospital-visiting patients had bacterial infections, with three-fourths involving Enterobacterales and one-fifth involving MDR bacteria. In recent years, resistance to cephalosporins has increased, while resistance to other beta-lactams, aminoglycosides, and polymyxins has decreased.

Methods
In the patient information sheet, outcome variables [bacterial pathogens and viral-bacterial coinfections (simultaneous occurrences)] and predictor variables (patient demographics, time frame, specimen type, type of bacterial isolate(s), and antimicrobial susceptibility patterns) were collected from the hospital records. The data were anonymized to ensure patient confidentiality.

Data was entered and managed using Microsoft Excel, version 13.0, and analyzed using Statistical Package for Social Sciences (SPSS), version 17.0. Descriptive data were analyzed in terms of frequency and percentage. Quantitative data were reported as mean, median, and interquartile range (IQR). Qualitative variables were analyzed using the Chi-square test, while quantitative variables were analyzed using the independent student t-test, with statistical significance determined at a p-value of <0.05 within a 95% confidence interval (CI).