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

[https://doi.org/10.5061/dryad.zpc866thj](https://doi.org/10.5061/dryad.zpc866thj)

## Description of the data and file structure

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

The dataset is of hospital-visiting individuals who were with and without bacterial infections.

The dataset consists of two sheets. The first sheet details clinico-demographic information, such as patient age group, gender, specimen type, and bacterial infection status. The exact age is removed and categorized as an age group to anonymize the data. The second sheet details the year, bacterial species, and antimicrobial susceptibility patterns. Given that the patient identification number and specimen number are classified as human subject data and require anonymization, these identifiers have been removed from the dataset.

Not availabl...