Antimicrobial resistance patterns among critical priority pathogens in an intensive care unit at a tertiary hospital in Egypt: a descriptive analysis comparing pre- and COVID-19 eras

Abstract

Background. The intensified global challenge of antimicrobial resistance, set against the backdrop of the COVID-19 pandemic, is a cause for major concern. Within healthcare settings, intensive care units are recognized as focal points for Gram-negative infections. The study pursued to assess the prevalence and antimicrobial resistance patterns of critical priority pathogens (Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacteriaceae, comprising Klebsiella pneumoniae and Escherichia coli) during both pre- and COVID-19 periods. Gap Statement. The decision to explore this topic stemmed from the urgent need to understand how the exceptional healthcare crisis of COVID-19 affected AMR patterns. Methods. This was an observational retrospective analysis of 1056 clinical specimens obtained from 950 patients who were admitted to the Medical Intensive Care Unit at Kasr Al-Aini Hospital, Cairo University, Egypt. Results. In the period before COVID-19, 342 pathogenic isolates (135 K. pneumoniae, 83 P. aeruginosa, 76 A. baumannii and 48 E. coli) were obtained from samples collected from 450 patients. Conversely, during the COVID-19 period, 714 isolates (237 K. pneumoniae, 205 A. baumannii, 199 P. aeruginosa and 73 E. coli) were collected from the same number of patients. In the course of the pandemic, there is a slight increase in A. baumannii and P. aeruginosa infections, whereas E. coli and K. pneumoniae exhibit a distinct trend with a noticeable reduction in infection rates during COVID-19. During the COVID-19 period, a noticeable rise in resistance rates was observed for all antibiotics utilized. The results from Fisher’s exact test indicated a substantial increase in resistance towards certain antibiotics. Specifically, a significant rise in resistance was observed for E. coli to ciprofloxacin (P = 0.00), gentamicin and P. aeruginosa (P = 0.02), levofloxacin and A. baumannii (P = 0.01), piperacillin-tazobactam and A. baumannii (P = 0.04), and piperacillin-tazobactam and P. aeruginosa (P = 0.01). Conclusion. Our results display how the pandemic impacted bacterial infections and antibiotic resistance, indicating a general increase in resistance rates. These findings are crucial for guiding healthcare practices, emphasizing the need for continued surveillance and potentially checking antibiotic usage schemes.