Objective: To determine frequency of Endogenous Methicillin Resistant Staphylococcus aureus (MRSA) in pre-operative patients and its frequency in Surgical Site Infections (SSIs) post operatively.
Methods: It was a descriptive cross sectional conducted at Department of Microbiology, Fauji Foundation Hospital Rawalpindi (FFH), Pakistan. Samples were collected from 1st November-31st May 2018. Total 75 samples were collected during the period. Consecutive non-probability sampling technique was utilized. Specimens were collected from nose, axilla and groin of preoperative patients. Methicillin Resistant Staphylococcus aureus was identified if only isolated from these sites. Patients were followed till his/her discharge from the hospital and if they developed infection post operatively, pus specimen from infected site was also collected and identified.
Results: Out of 75 specimen preoperatively, 11(14.7%) were identified as endogenous MRSA. From these, 33(44%) developed Surgical site infections (SSIs), among them 19(57%) were MRSA (09 endogenous, 10 exogenous), 7(21.2%) were Escherichia coli, 3(9.1%) were Klebsiella pneumoniae, 3(9.1%) were Enterococcus faecalis and 1(3%) was Methicillin Sensitive Staphylococcus aureus.
Conclusions: The results of this study determined that Endogenous Methicillin Resistant Staphylococcus aureus (MRSA) could be isolated from patients going for surgery if microbiological screening was done at the time of admission. This could prevent patients from Surgical Site Infection Post operatively by these endogenous MRSA. This search and wipe out strategy is able to curtail the events of outbreak, reduce hospital stay and decrease budget of the hospital by providing guidance in choice of empirical therapy for infection.
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http://dx.doi.org/10.47391/JPMA.649 | DOI Listing |
Phytother Res
January 2025
College of Veterinary Medicine, Yangzhou University, Yangzhou, China.
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December 2024
Department of Laboratory Medicine, Clinical Microbiology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
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December 2024
Faculty of Health and Life Sciences, INTI International University, Nilai, Malaysia.
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Center for Animal Disease Modeling and Surveillance, Department of Veterinary Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, Davis, CA, United States.
Electronic health records (EHR) are increasingly used in public health research. However, biases may exist when using EHR due to whether someone is captured in the data. Assessing the impact of bias in generating disparities identified with EHR data is difficult because information about healthcare-seeking behaviors is not included in the record.
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