Isolates from the Intensive Care Unit at South Qunfudah Hospital in Saudi Arabia: An Emerging Antimicrobial Resistance Profile.

INTRODUCTION

is a significant pathogen in healthcare settings, particularly in the Intensive Care Unit (ICU). Its antimicrobial resistance poses a serious threat to infection control and patient outcomes. This study aims to analyze the developing antimicrobial resistance profile of isolates in the ICU.

METHODS

A big hospital in Qunfudah provided 137 cases of infected individuals for this retrospective analysis. It was conducted on the available data on ICU patients' records. Various types of specimens were used. The data collected includes patients' demographic data, laboratory investigation, and tests for antimicrobial susceptibility. The isolates were identified and subjected to antimicrobial susceptibility tests using the compact system identification method. Data input and analysis were done using SPSS, version 26.

RESULTS

The outcomes of this study reflected that more than half of were isolated from males (62.4%), many of them are Patients aged 76-95 years (n;43) were the most infected, followed by individuals aged 56-75 years (n; 27), 36-55 years (n;14), 96-105 years (n;7), and 16-35 years (n;2). The high frequency of specimens, sputum, urine, blood, and endotracheal tube (37.2%, 19%,18.2%,16.1%), respectively. Sputum had the highest culture positivity (n 51; 37.2%) for pathogens, followed by urine (n 26;19%), blood (n 25;18.2%), endotracheal tube (n 22; 16.1%), wound swabs (n 8; 5.8%), central line tip (n 3; 2.2%) stool and urethral swab (n 1; 0.7% for each). demonstrated high resistance rates (100%) for Cefalotin, Cefoxitin, Ceftriaxone, Cefepime, and Ampicillin, followed by Ciprofloxacin and Trimethoprim/Sulfamethoxazole (97.8%), Nitrofurantion (94.6%), Meropenem (91.4%), Amikacin (90.3%) and Gentamicin (87.1%). The lowest resistance rate was Imipenem (30.10%).

CONCLUSION

In conclusion, this study examines the antimicrobial resistance of in the ICU of South Qunfudah Hospital, focusing on specific location data rather than general resistance trends.