Detection of Biofilm Formation among Drug-resistant Acinetobacter spp. Isolated from ICUs at a Tertiary Care Hospital: A Cross-sectional Study

Author:

Sharma Shweta R,Mishra Amit,Ahamad Imran,Singh Sudhir

Abstract

Introduction: Acinetobacter spp. has emerged as an important hospital-acquired and opportunistic agent due to its survival capability in adverse conditions, saprophytic presence, and increasing resistance to antimicrobials. The irrational use of antibiotics, along with biofilm formation, plays an important role in producing Extensively Drug-resistant (XDR) and MultidrugResistant (MDR) Acinetobacter species, especially Acinetobacter calcoaceticus-baumannii complex (Acb complex), in the hospital environment, contributing to morbidity and mortality. Aim: To detect biofilm production among Acinetobacter species isolated from various clinical samples received from Intensive Care Units (ICUs) as well as their antibiotic sensitivity pattern. Materials and Methods: A cross-sectional study was conducted in the Microbiology Department at Teerthanker Mahaveer Medical College and Research Centre, Moradabad, Uttar Pradesh, India from January 2022 to April 2023. Patients of all age groups and both genders were included in the study after obtaining informed consent. Clinical specimens, including endotracheal secretions, endotracheal tips, pus, urine, sputum, tissue, and other body fluids, were collected from ICUs where Acinetobacter spp. was detected. A total of 223 cases were included. The specimens were collected using clean, leak-proof, sterile containers with proper aseptic precautions. Antimicrobial susceptibility testing was performed according to the guidelines set by the Clinical and Laboratory Standards Institute (CLSI) in 2022 and identifies MDR and XDR strains. The biofilm production of isolates was determined using a quantitative adherence assay. The data generated was entered into Microsoft excel, and statistical analysis was conducted using International Business Machines (IBM) Statistical Package for Social Sciences (SPSS) statistical software version 28.0. The results were then presented as descriptive statistics. Results: Among the 223 Acinetobacter spp. isolates, 159 (71.3%) were identified as Acb complex (Acinetobacter calcoaceticusbaumannii complex), followed by A.lwofi with 39 (17.5%) isolates and A. haemolyticus with 16 (7.2%) isolates. Acinetobacter showed resistance, in descending order of frequency, to amoxicillin+clavulanic acid (211 isolates, 94.6%), ciprofloxacin (211 isolates, 94.6%), trimethoprim-sulfamethoxazole (208 isolates, 93.3%), cefotaxime (198 isolates, 88.8%), cefepime (187 isolates, 83.8%), gentamycin (178 isolates, 79.8%), amikacin (152 isolates, 68.2%), piperacillin-tazobactam (68 isolates, 30.5%), imipenem (72 isolates, 32.3%), meropenem (71 isolates, 31.8%), polymyxin B (12 isolates, 5.4%), and colistin (2 isolates, 0.9%). The maximum antibiotic resistance was observed in Acb complex, with 208 (93.3%) strains being MDR producers and 32 (14.3%) strains being XDR producers. Biofilm production was observed in 214 isolates (95.9%), with 127 (56.9%) exhibiting strong biofilm production 63 (28.2%) showing moderate biofilm production, and 24 (10.8%) showing weak biofilm production. All MDR strains were found to produce biofilm, and out of those, 127 (61.1%) exhibited strong biofilm production. Among the XDR strains, all 32 (100%) were found to produce strong biofilm. Conclusion: In conclusion, Acinetobacter spp. has a high propensity for developing MDR, and the formation of biofilms further aids the organism in surviving under strenuous conditions, making it difficult to treat. Therefore, regular surveillance of Hospital-acquired Infections (HAI), the prevention of misuse and overuse of antibiotics, prescribing antibiotics based on antibiogram patterns, formulating antibiotic policies, and implementing bundle care approaches for the prevention of HAI are crucial in preventing antibiotic resistance.

Publisher

JCDR Research and Publications

Subject

Clinical Biochemistry,General Medicine

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