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oai:figshare.com:article/33920311 2026-09-18T05:27:42Z category_8 portal_316 item_type_3 month_year_09_2026

Table 1_Longitudinal trends in antimicrobial resistance phenotypes in Pseudomonas aeruginosa: a seven-year study.docx Wael A. Alghamdi (25070005) Khalid M. Orayj (25070008) Ahmed R. N. Ibrahim (17360086) Marim A. Abdelsalam (25070011) Abdullah M. Alshehri (8671671) Microbiology antimicrobial resistance difficult-to-treat resistance extensively drug-resistant multidrug resistance Pseudomonas aeruginosa Background<p>Pseudomonas aeruginosa is a major cause of healthcare-associated infections and is increasingly associated with antimicrobial resistance. Continuous local surveillance is essential to monitor evolving resistance patterns and inform empirical antimicrobial therapy and antimicrobial stewardship.</p>Methods<p>This retrospective laboratory-based surveillance study analyzed non-duplicate P. aeruginosa isolates recovered from hospitalized patients at a secondary healthcare setting in Saudi Arabia between 2018 and 2024. Resistance phenotypes were classified as multidrug-resistant (MDR), extensively drug-resistant (XDR), and difficult-to-treat resistance (DTR) according to established international definitions. Temporal trends were evaluated using logistic regression.</p>Results<p>A total of 368 non-duplicate P. aeruginosa isolates were included. Respiratory tract specimens were the most common source of isolates. MDR prevalence increased from 51.0% in 2018 to a peak of 87.3% in 2022 before declining to 69.6% in 2024, while XDR reached its highest prevalence of 68.3% in 2023 before declining to 39.1% in 2024. When year was analyzed categorically, significant differences across years were observed for MDR (P < 0.001) and XDR (P = 0.003), but not DTR (P = 0.144).</p>Conclusion<p>This seven-year surveillance study demonstrated a substantial burden of antimicrobial resistance among P. aeruginosa isolates, with significant year-to-year variation in MDR and XDR prevalence. These findings provide locally relevant surveillance data that may inform empirical antimicrobial therapy, antimicrobial stewardship, and ongoing institutional resistance surveillance.</p> 2026-09-18T05:27:42Z Dataset Dataset 10.3389/frabi.2026.1912287.s001 https://figshare.com/articles/dataset/Table_1_Longitudinal_trends_in_antimicrobial_resistance_phenotypes_in_Pseudomonas_aeruginosa_a_seven-year_study_docx/33920311 CC BY 4.0