Active Surveillance of Health Care Associated Infections in Neurosurgical Patients
DC01-DC04
Correspondence
Dr. Sarita Mohapatra,
Room no 8004, Convergence block, AIIMS, New Delhi-110029, India.
E-mail: saritarath2005@yahoo.co.in
Introduction: Health Care Associated Infections (HCAI) are frequent complications in neurosurgery. There is limited data available on the incidence and burden of HCAI in neurosurgical patients of Southeast Asian region.
Aim: To identify various HCAIs, associated aetiological agents and their antimicrobial susceptibility pattern among the patients admitted in the neurosurgery unit.
Materials and Methods:An observational prospective study was carried out for three months duration on all neurosurgical patients admitted to a tertiary-care center. The site-specific nosocomial infection rates and device utilization ratios were calculated. Data on demographic profiles, invasive procedures, HCAI, isolated microorganisms and antimicrobial susceptibilities were recorded. Statistical analysis of all the variables was done. The association between categorical variables was assessed by Chi-square/Fisher-exact test. Continuous variables such as infected and non-infected were compared by Wilcoxon rank-sum test. A p-value of less than 0.05 was considered significant.
Results: A total of 330 patients with 4054 patient-days were analysed for HCAI. Twenty-two HCAIs were identified in 21 patients. The overall rate of HCAI was 6.67% and 5.42 per 1000 patient-days. Urinary Tract Infection (UTI) was most common (71.4%) followed by Laboratory Confirmed Blood-Stream Infection (LCBI) (28.5%) and pneumonia (4.7%). No central line-associated blood stream infection was identified. Klebsiella pneumoniae and Escherichia coli were the most common organisms causing UTI and LCBI. All the isolates (100%) were found to be multidrug resistant.
Conclusion: This study generates a baseline data for records of device-associated infection in neurocritical care patients, which will further help monitoring its trend of infection and antimicrobial resistance pattern. Moreover, it will help in the formulation of the antibiotic policy and the preventive measures which may reduce morbidity and mortality.