Clinical gradient and predictors for stepwise resistance escalation of carbapenem-susceptible, carbapenem-resistant, and difficult-to-treat resistant Pseudomonas aeruginosa infections: a 6-year retrospective cohort study.
Difficult-to-treat resistant Pseudomonas aeruginosa (DTR-PA) represents the most severe antimicrobial resistance phenotype of P. aeruginosa, with limited therapeutic options and poor clinical outcomes. However, previous studies have largely focused on carbapenem-resistant P. aeruginosa (CRPA), and the factors associated with resistance acquisition and progression remain insufficiently characterized. This study aimed to investigate the clinical characteristics and risk factors associated with different resistance phenotypes of P. aeruginosa from the perspectives of both resistance acquisition and resistance escalation.
A retrospective case-control study was conducted from January 2020 to December 2025 at a tertiary teaching hospital. P. aeruginosa isolates were classified according to antimicrobial susceptibility profiles. All DTR-PA cases (n = 67) were included, and CRPA and carbapenem-susceptible P. aeruginosa (CSPA) controls were selected using a time-stratified 1:2:2 sampling strategy. Clinical data were collected, and three comparative models were developed to explore determinants of resistance acquisition and resistance escalation across different P. aeruginosa phenotypes: resistant P. aeruginosa (R-PA, defined as CRPA and DTR-PA) versus CSPA, DTR-PA versus CRPA, and DTR-PA versus non-DTR-PA.
During the study period, 2,692 P. aeruginosa clinical isolates were included for analysis, including 67 (2.5%) DTR-PA, 407 (15.1%) CRPA, and 2,218 (82.4%) CSPA. A total of 335 patients were included in the risk factor analysis. With increasing antimicrobial resistance severity, inflammatory markers showed a stepwise increase, whereas nutritional status, as reflected by serum albumin levels, demonstrated a progressive decline. In the R-PA versus CSPA model, invasive respiratory procedures, prolonged hospitalization, and polymicrobial co-infection were associated with increased risk, whereas higher BMI and serum albumin levels showed modest inverse associations with resistant P. aeruginosa infection. In the DTR-PA versus CRPA model, diabetes mellitus, chronic respiratory diseases, and recent ICU admission were associated with DTR-PA infection. In the DTR-PA versus non-DTR-PA model, prior antibiotic exposure, central venous catheterization, and invasive procedures were associated with DTR-PA infection.
Antimicrobial resistance in P. aeruginosa follows a dynamic, stage-dependent process with distinct risk profiles. Healthcare exposure primarily contributes to resistance emergence, whereas host comorbidities and intensive care exposure are more closely associated with progression to DTR-PA. This resistance gradient framework may support early identification, risk stratification, and infection control strategies.
A retrospective case-control study was conducted from January 2020 to December 2025 at a tertiary teaching hospital. P. aeruginosa isolates were classified according to antimicrobial susceptibility profiles. All DTR-PA cases (n = 67) were included, and CRPA and carbapenem-susceptible P. aeruginosa (CSPA) controls were selected using a time-stratified 1:2:2 sampling strategy. Clinical data were collected, and three comparative models were developed to explore determinants of resistance acquisition and resistance escalation across different P. aeruginosa phenotypes: resistant P. aeruginosa (R-PA, defined as CRPA and DTR-PA) versus CSPA, DTR-PA versus CRPA, and DTR-PA versus non-DTR-PA.
During the study period, 2,692 P. aeruginosa clinical isolates were included for analysis, including 67 (2.5%) DTR-PA, 407 (15.1%) CRPA, and 2,218 (82.4%) CSPA. A total of 335 patients were included in the risk factor analysis. With increasing antimicrobial resistance severity, inflammatory markers showed a stepwise increase, whereas nutritional status, as reflected by serum albumin levels, demonstrated a progressive decline. In the R-PA versus CSPA model, invasive respiratory procedures, prolonged hospitalization, and polymicrobial co-infection were associated with increased risk, whereas higher BMI and serum albumin levels showed modest inverse associations with resistant P. aeruginosa infection. In the DTR-PA versus CRPA model, diabetes mellitus, chronic respiratory diseases, and recent ICU admission were associated with DTR-PA infection. In the DTR-PA versus non-DTR-PA model, prior antibiotic exposure, central venous catheterization, and invasive procedures were associated with DTR-PA infection.
Antimicrobial resistance in P. aeruginosa follows a dynamic, stage-dependent process with distinct risk profiles. Healthcare exposure primarily contributes to resistance emergence, whereas host comorbidities and intensive care exposure are more closely associated with progression to DTR-PA. This resistance gradient framework may support early identification, risk stratification, and infection control strategies.
Authors
Chen Chen, Yin Yin, Hu Hu, Kang Kang, Rouzimaimaiti Rouzimaimaiti, Duan Duan, Hou Hou
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