Insight into the Burden of Antimicrobial Resistance among Bacterial Pathogens Isolated from Patients Admitted in ICUs of a Tertiary Care Hospital in India

被引:0
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作者
Gautam, Garima [1 ]
Satija, Shweta [2 ]
Kaur, Ravinder [2 ]
Kumar, Anil [2 ]
Sharma, Divakar [2 ]
Dhakad, Megh Singh [3 ]
机构
[1] Indraprastha Apollo Hosp, New Delhi, India
[2] Lady Hardinge Med Coll & Associated Hosp, Dept Microbiol, New Delhi 110001, India
[3] Maulana Azad Med Coll & Associated Hosp, Dept Microbiol, New Delhi 110002, India
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D O I
10.1155/2024/7403044
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Intensive care unit (ICU) patients are prone to develop infections by hospital prevalent organisms. The aim of the study was to determine the bacteriological profiles and their drug resistance pattern among different infections in ICU patients of a tertiary care hospital. The record-based retrospective data of culture reports of the patients admitted to all the ICUs of a tertiary care hospital during the period from January 2020 to May 2022 were analyzed. A total of 3,056 samples were obtained from 2308 patients. The infection rate among ICU patients was found to be 53.40%. Isolates belonged equally to males (50.86%) and females (49.14%). The most common culture-positive clinical specimen received was blood (39.08%) followed by respiratory samples (29.45%). Acinetobacter sp. (33.02%) was the most common organism isolated from various clinical specimens, followed by Klebsiella pneumoniae (20.89%), and Escherichia coli (13.8%). More than 80% of Acinetobacter species were found to be resistant to third-generation cephalosporins, aminoglycosides, and carbapenems, whereas minocycline (56.31% S) and colistin (100% S) were the most effective drugs. Klebsiella sp. was found to be more resistant than E.coli, and the least resistance was observed to be tetracycline (43.97%) and doxycycline (55.84%). Among Staphylococcus aureus, 82.78% of strains were methicillin-resistant (MRSA). Vancomycin-resistant Enterococci (VRE) sp. accounted for 16.67% of the isolates. Evidence-based knowledge regarding the local bacterial organisms and their antimicrobial resistance pattern is pivotal in deciding empirical drug therapy, ultimately leading to the management of antimicrobial resistance (AMR).
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