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

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.