Bacteremia prediction model using a common clinical test in patients with community-acquired pneumonia

Am J Emerg Med. 2014 Jul;32(7):700-4. doi: 10.1016/j.ajem.2014.04.010. Epub 2014 Apr 18.

Abstract

Purpose: The aim of this study was to construct a bacteremia prediction model using commonly available clinical variables in hospitalized patients with community-acquired pneumonia (CAP).

Basic procedures: A prospective database including patients who were diagnosed with CAP in the emergency department was analyzed. Independent risk factors were investigated by using multivariable analysis in 60% of the cohort. We assigned a weighted value to predictive factor and made a prediction rule. This model was validated both internally and externally with the remaining 40% of the cohort and a cohort from an independent hospital. The low-risk group for bacteremia was defined as patients who have a risk of bacteremia less than 3%.

Main findings: A total of 2422 patients were included in this study. The overall rate of bacteremia was 5.7% in the cohort. The significant factors for predicting bacteremia were the following 7 variables: systolic blood pressure less than 90 mm Hg, heart rate greater than 125 beats per minute, body temperature less than 35 °C or greater than 40 °C, white blood cell less than 4000 or 12,000 cells per microliter, platelets less than 130,000 cells per microliter, albumin less than 3.3 g/dL, and C-reactive protein greater than 17 mg/dL. After using our prediction rule for the validation cohorts, 78.7% and 74.8% of the internal and external validation cohorts were classified as low-risk bacteremia groups. The areas under the receiver operating characteristic curves were 0.75 and 0.79 for the internal and external validation cohorts.

Principal conclusions: This model could provide guidelines for whether to perform blood cultures for hospitalized CAP patients with the goal of reducing the number of blood cultures.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Bacteremia / diagnosis*
  • Bacteremia / etiology
  • Blood Pressure*
  • Body Temperature*
  • Cohort Studies
  • Community-Acquired Infections
  • Databases, Factual
  • Decision Support Techniques
  • Emergency Service, Hospital
  • Female
  • Heart Rate*
  • Humans
  • Leukocyte Count*
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Platelet Count*
  • Pneumonia / complications
  • Pneumonia / diagnosis*
  • Prospective Studies
  • Risk Assessment
  • Risk Factors