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Updated: May 27, 2026

Tools for the Real-Time Assessment of a Pseudomonas aeruginosa Infection Model
Published on: April 6, 2021
A model to predict mortality following Pseudomonas aeruginosa bacteremia
Elizabeth B Hirsch1, Jessica M Cottreau, Kai-Tai Chang
1University of Houston College of Pharmacy, Houston, TX 77030, USA.
Abstract:
Infections caused by Pseudomonas aeruginosa are associated with significant mortality. Existing mathematical models identifying mortality risk factors lack validation. We developed and validated a model to predict mortality in patients with P. aeruginosa bacteremia. Risk factors for 30-day mortality were examined through multivariate logistic regression in 114 patients. Independent predictors of mortality included isolation of a multidrug-resistant strain, APACHE II ≥ 23, and age ≥ 65 years. Clonality was assessed for multidrug-resistant isolates. Predicted probability of 30-day mortality was validated in 49 patients, after conditioning the model by the identified risk factors. The patients were split into 'high-risk' and 'low-risk' groups based on model-predicted mortality; the observed/expected ratios were 1.21 and 1.92, respectively. Our model was reasonable in predicting 30-day mortality in patients with P. aeruginosa bacteremia. Our results may be useful for developing strategies to reduce mortality attributed to P. aeruginosa.
