{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T18:21:48Z","timestamp":1790965308728,"version":"4.1.0"},"reference-count":24,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T00:00:00Z","timestamp":1741651200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Antibiotics"],"abstract":"<jats:p>Objectives: This study aimed to analyze the antibiotic resistance patterns of microorganisms isolated from intensive care unit (ICU) patients and evaluate their impact on mortality and length of ICU stay. Given the increasing prevalence of multidrug-resistant (MDR) pathogens in critically ill patients, understanding their resistance profiles is crucial for optimizing empirical antibiotic therapy and improving patient outcomes. Methods: This retrospective study included 237 ICU patients admitted between 1 July 2022, and 1 January 2024. The initial culture growth results from blood and urine samples were analyzed. Microorganism identification was performed using VITEK 2 Compact and conventional bacteriological methods, while antibiotic susceptibility testing followed CLSI 2022 and EUCAST 2022 guidelines. Results: A total of 237 ICU patients were included in this study. The most frequently isolated microorganisms were Escherichia coli (E. coli) (44.3%), Klebsiella pneumoniae (K. pneumoniae) (35.0%), and Pseudomonas aeruginosa (P. aeruginosa) (25.3%), with Acinetobacter baumannii (A. baumannii) (31.2%) being the most resistant pathogen. Among Gram-positive bacteria, methicillin-resistant\u00a0Staphylococcus aureus (MRSA) (12.2%) and vancomycin-resistant enterococci (VRE) (21.5%) were the most frequently identified multidrug-resistant (MDR) pathogens. Regarding antimicrobial resistance, carbapenem resistance was highest in A. baumannii (55%), followed by P. aeruginosa (40%) and K. pneumoniae (30%). Additionally, ESBL-producing E. coli (43.2%) and K. pneumoniae (38.5%), as well as carbapenemase-producing K. pneumoniae (18.6%) and E. coli (9.2%), were identified as key resistance mechanisms impacting clinical outcomes. Patients with MDR infections had significantly longer ICU stays (p &lt; 0.05) and higher mortality rates. The Kaplan\u2013Meier survival analysis revealed that A. baumannii infections were associated with the highest mortality risk (HR: 4.6, p &lt; 0.001), followed by MRSA (HR: 3.5, p = 0.005) and P. aeruginosa (HR: 2.8, p = 0.01). Among laboratory biomarkers, elevated procalcitonin (\u22652 ng\/mL, OR: 2.8, p = 0.008) and CRP (\u2265100 mg\/L, OR: 2.2, p = 0.01) were significantly associated with ICU mortality. Additionally, patients who remained in the ICU for more than seven days had a 1.4-fold increased risk of mortality (p = 0.02), further emphasizing the impact of prolonged hospitalization on adverse outcomes. Conclusions: MDR pathogens, particularly A. baumannii, MRSA, P. aeruginosa, and K. pneumoniae, are associated with longer ICU stays and higher mortality rates. Carbapenem, cephalosporin, fluoroquinolone, and aminoglycoside resistance significantly impact clinical outcomes, emphasizing the urgent need for antimicrobial stewardship programs. ESBL, p-AmpC, and carbapenemase-producing Enterobacterales further worsen patient outcomes, highlighting the need for early infection control strategies and optimized empirical antibiotic selection. Biomarkers such as procalcitonin and CRP, alongside clinical severity scores, serve as valuable prognostic tools for ICU mortality.<\/jats:p>","DOI":"10.3390\/antibiotics14030290","type":"journal-article","created":{"date-parts":[[2025,3,11]],"date-time":"2025-03-11T06:52:30Z","timestamp":1741675950000},"page":"290","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Antibiotic Resistance and Mortality in ICU Patients: A Retrospective Analysis of First Culture Growth Results"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1813-1274","authenticated-orcid":false,"given":"Metin","family":"Kilinc","sequence":"first","affiliation":[{"name":"Department of Anesthesiology and Reanimation, Faculty of Medicine, Mardin Artuklu University, Mardin 47200, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Segmen, F., Aydemir, S., Kucuk, O., Dogu, C., and Dokuyucu, R. 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