INTRODUCTION: This large, multicenter, Italian retrospective study aimed to describe clinical characteristics and risk factors associated with 30-day mortality in patients with Pseudomonas aeruginosa bloodstream infections (PA-BSI) admitted to internal medicine wards (IMW). To enhance clinical decision-making, we also developed and internally validated a bedside prognostic model to predict the 30-day mortality risk. METHODS: We conducted a retrospective, multicenter cohort study across 14 public hospitals in Italy, analyzing all adult patients admitted to IMW with PA-BSI between 2021 and 2022. RESULTS: Out of 285 eligible patients with PA-BSI, the median age was 73 years, and septic shock occurred in 13.3% of cases. Less than 5% of PA-BSI were caused by difficult-to-treat resistant P. aeruginosa (DTR-PA). Encouragingly, appropriate empiric therapy was administered in 69.8% of patients, yet the overall 30-day mortality remained 22.5%. Cox regression analysis identified age, and urinary catheter use as significant risk factors for mortality. Conversely, adequate source control and targeted therapy emerged as protective factors. Multivariate analysis confirmed septic shock at bloodstream infection onset (HR 6.96
95% CI, 1.72-28.12) as a strong independent predictor of mortality, whereas effective source control (HR 0.152
95% CI, 0.039-0.59) significantly improved survival odds. Using these insights, we developed a practical prognostic model capable of estimating the 30-day mortality risk, providing clinicians with a valuable predictive tool at the bedside. CONCLUSIONS: PA-BSI in IMWs is characterized by a relatively low incidence of septic shock and rate of resistance, alongside high rates of appropriate empiric therapy. Despite these favorable factors, meropenem may represent a valuable therapeutic option for PA-BSI with severe presentations in this setting since mortality remains substantial (22.5%). Our findings underscore the critical importance of early source control and identify septic shock as a key predictor of mortality even in the setting of IMW. The proposed bedside nomogram model could empower clinicians to identify high-risk patients early, facilitating timely interventions and improving outcomes in this vulnerable population.