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. 2013 Oct;19(10):948-54.
doi: 10.1111/1469-0691.12085. Epub 2012 Nov 27.

Predictive scoring model of mortality in Gram-negative bloodstream infection

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Free article

Predictive scoring model of mortality in Gram-negative bloodstream infection

M N Al-Hasan et al. Clin Microbiol Infect. 2013 Oct.
Free article

Abstract

Mortality is a well-recognized complication of Gram-negative bloodstream infection (BSI). The aim of this study was to develop a model to predict mortality in patients with Gram-negative BSI by using the Pitt bacteraemia score (PBS) and other clinical and laboratory variables. A cohort of 683 unique adult patients who were followed for at least 28 days after admission to Mayo Clinic Hospitals with Gram-negative BSI from 1 January 2001 to 31 October 2006 and who received clinically predefined appropriate empirical antimicrobial therapy was retrospectively identified. Multivariable logistic regression was used to identify independent risk factors for 28-day all-cause mortality. Regression coefficients from a multivariable model were used to develop a risk score to predict mortality following Gram-negative BSI. Malignancy (OR 3.48, 95% CI 1.94-6.22), liver cirrhosis (OR 5.42, 95% CI 2.52-11.65), source of BSI other than urinary tract or central venous catheter infection (OR 5.54, 95% CI 2.42-12.69), and PBS (OR 1.98, 95% CI 0.92-4.25 for PBS of 2-3 and OR 6.42, 95% CI 3.11-13.24 for PBS ≥4) were identified as independent risk factors for 28-day mortality in patients with Gram-negative BSI. A risk-score model was created by adding points for each independent risk factor, and had a c-statistic of 0.84. Patients with risk scores of 0, 4, 8, 12 and 16 had estimated 28-day mortality rates of approximately 0%, 3%, 14%, 45%, and 81%, respectively. The Gram-negative BSI risk score described herein estimated mortality risk with high discrimination in patients with Gram-negative BSI who received clinically adequate empirical antimicrobial therapy.

Keywords: Bacteraemia; Pitt bacteraemia score; outcome; risk factors; sepsis.

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