Isolation of Pseudomonas Aeruginosa from various clinical samples and its Correlation with Biofilm and Antimicrobial Susceptibility Pattern at Tertiary Care Centre

Abstract

INTRODUCTION: Pseudomonas aeruginosa can cause community acquired or
hospital acquired infections and has potential to develop antimicrobial resistance.
Biofilm is one of the factors that help in the establishment of the organism on
different host tissues. The current study aims to identify the multidrug resistant
P.aeruginosa and correlate the relationship of drug resistance with biofilm
production.
MATERIALS AND METHODS: In this cross-sectional study, a total of 1440
clinical specimens were included. All clinical samples including sputum, urine, pus,
wound swabs, ET secretions, high vaginal swabs were processed for culture and
sensitivity as per the standard guidelines. Biofilm testing of Pseudomonas isolates
was done by Tissue Culture Plate Method (TCPM). Categorical variables were tested
by chi square analysis, the p value <0.05 is considered as statistically significant.
RESULTS: Out of 168 isolates, maximum number were from sputum 58 (34.5%)
followed by pus 44(26.1%) urine 42 (25%), wound swabs 15 (8.9%), high vaginal
swabs (HVS) 6 (3.5%) and ET secretions of 3 (1.7%) isolates. MDR percentage
among Pseudomonas isolates noted was 48.2%. Out of 168 Pseudomonas isolates 42
(25%) were Biofilm producers and remaining 126 (75%) were non biofilm
producers. Among 42 biofilm producers, 66.6% (28/42) were weakly adherent, 10
(23.8%) were moderate adherent and remaining 4 (9.5%) were strongly adherent.
Biofilm producers and non biofilm producers in relation to multidrug resistance
pattern was found statistically significant.
CONCLUSION: To combat the drug resistant of P.aeruginosa a stringent measures
of infection control policies and microbiological screening to start accurate therapy
during the critical time will definitely help. Regular antibiogram plotting in the
hospital and early screening microbiological screening methods implementation will
aid clinicians to give the prompt and accurate treatment to patients.