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

doi:10.1016/j.diagmicrobio.2011.09.018

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

Experimental and Clinical Pharmacology

Research output: Contribution to journal › Article › peer-review

21 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 language	English (US)
Pages (from-to)	97-102
Number of pages	6
Journal	Diagnostic Microbiology and Infectious Disease
Volume	72
Issue number	1
DOIs	https://doi.org/10.1016/j.diagmicrobio.2011.09.018
State	Published - 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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.diagmicrobio.2011.09.018

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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.",

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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. ",

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AU - Tam, Vincent H.

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A model to predict mortality following Pseudomonas aeruginosa bacteremia

Abstract

Bibliographical note

Keywords

UN SDGs

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