Frequency, Risk Factors, and Antibiogram of Acinetobacter Species Isolated from Various Clinical Samples in a Tertiary Care Hospital in Odisha, India

Overview

Journal Avicenna J Med

Publisher Thieme

Specialty General Medicine

Date 2013 Dec 12

PMID 24327968

Citations 9

Authors

Muktikesh Dash

Sanghamitra Padhi

Swetlana Pattnaik

Indrani Mohanty

Pooja Misra

Affiliations

Soon will be listed here.

Abstract

Background: For the past two decades, Acinetobacter spp. have emerged as an important pathogen globally in various infections.

Objectives: This study was conducted to determine the frequency, risk factors, and antibiotic resistance pattern of Acinetobacter spp. from various clinical samples.

Materials And Methods: This retrospective, hospital record-based, cross-sectional study included a total of 8749 clinical samples collected from patients at a tertiary care hospital in Odisha, India from July 2010 to December 2012. The samples were processed and identified by standard protocol. The Acinetobacter isolates were tested for antibiotic resistance by Kirby-Bauer disk diffusion method [according to the Clinical and Laboratory Standards Institute (CLSI) guidelines].

Results: From 8749 clinical samples, 4589 (52.5%) yielded significant growth and only 137 (3%, 137/4589) Acinetobacter spp. were isolated. Maximum (56.9%) isolates were obtained from pus/swab, followed by blood (13.1%) and urine (12.4%). Elderly age, being inpatients, longer duration of stay in the hospital, associated co-morbidity, and invasive procedure were found to be significant risk factors in the setup investigated (P is less than 0.05). Out of 137 isolates, 75 (54.7%) were resistant to more than three classes of antibiotics (multidrug resistant) and 8 (5.8%) were resistant to all commonly used antibiotics (pan-drug resistant). Majority of the isolates were sensitive to imipenem, meropenem, and piperacillin/tazobactam, and showed resistance rates of 19%, 22%, and 23%, respectively. All eight pan-drug resistant isolates were 100% sensitive to colistin.

Conclusion: This hospital-based epidemiological data will help to implement better infection control strategies and improve the knowledge of antibiotic resistance patterns in our region.

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