A model to predict mortality following Pseudomonas aeruginosa bacteremia

Elizabeth B. Hirsch, Jessica M. Cottreau, Kai Tai Chang, Juan Pablo Caeiro, Michael L. Johnson, Vincent H. Tam

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)97-102
Number of pages6
JournalDiagnostic Microbiology and Infectious Disease
Volume72
Issue number1
DOIs
StatePublished - Jan 2012

Bibliographical note

Funding Information:
No funding support for this study was provided. E.B.H. has received research funding from Ortho-McNeil-Janssen Pharmaceuticals. V.H.T. has received research grants from Achaogen, AstraZeneca, Merck, and Ortho-McNeil-Janssen Pharmaceuticals. All other authors: no conflicts of interest.

Keywords

  • Bloodstream infection
  • Health care-associated infection
  • Mathematical modeling
  • Multidrug-resistant
  • Probability

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