Literature DB >> 24856736

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

Jungyoup Lee1, Seung Sik Hwang2, Kyuseok Kim3, You Hwan Jo1, Jae Hyuk Lee1, Joonghee Kim1, Joong Eui Rhee1, Chanjong Park1, Heajin Chung1, Jae Yun Jung4.   

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.
Copyright © 2014 Elsevier Inc. All rights reserved.

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Year:  2014        PMID: 24856736     DOI: 10.1016/j.ajem.2014.04.010

Source DB:  PubMed          Journal:  Am J Emerg Med        ISSN: 0735-6757            Impact factor:   2.469


  11 in total

1.  Predictive factors of true bacteremia and the clinical utility of blood cultures as a prognostic tool in patients with community-onset pneumonia.

Authors:  Jong Hoo Lee; Yee Hyung Kim
Journal:  Medicine (Baltimore)       Date:  2016-10       Impact factor: 1.889

2.  Machine learning for fast identification of bacteraemia in SIRS patients treated on standard care wards: a cohort study.

Authors:  Franz Ratzinger; Helmuth Haslacher; Thomas Perkmann; Matilde Pinzan; Philip Anner; Athanasios Makristathis; Heinz Burgmann; Georg Heinze; Georg Dorffner
Journal:  Sci Rep       Date:  2018-08-15       Impact factor: 4.379

3.  The change in age distribution of CAP population in Korea with an estimation of clinical implications of increasing age threshold of current CURB65 and CRB65 scoring system.

Authors:  Byunghyun Kim; Joonghee Kim; You Hwan Jo; Jae Hyuk Lee; Ji Eun Hwang
Journal:  PLoS One       Date:  2019-08-15       Impact factor: 3.240

4.  Bacterial infections and death among patients with Covid-19 versus non Covid-19 patients with pneumonia.

Authors:  Hayley Scott; Aleena Zahra; Rafael Fernandes; Bettina C Fries; Henry C Thode; Adam J Singer
Journal:  Am J Emerg Med       Date:  2021-09-28       Impact factor: 4.093

5.  Diagnostic Accuracy of Procalcitonin for Predicting Blood Culture Results in Patients With Suspected Bloodstream Infection: An Observational Study of 35,343 Consecutive Patients (A STROBE-Compliant Article).

Authors:  Abderrahim Oussalah; Janina Ferrand; Pierre Filhine-Tresarrieu; Nejla Aissa; Isabelle Aimone-Gastin; Fares Namour; Matthieu Garcia; Alain Lozniewski; Jean-Louis Guéant
Journal:  Medicine (Baltimore)       Date:  2015-11       Impact factor: 1.889

6.  A model for predicting bacteremia in patients with community-acquired pneumococcal pneumonia: a retrospective observational study.

Authors:  Yasuyoshi Washio; Akihiro Ito; Shogo Kumagai; Tadashi Ishida; Akio Yamazaki
Journal:  BMC Pulm Med       Date:  2018-01-30       Impact factor: 3.317

7.  Impact of bacteremia prediction rule in CAP: Before and after study.

Authors:  Byunghyun Kim; Kyuseok Kim; Jieun Lee; Joonghee Kim; Yoo Hwan Jo; Jae Hyuk Lee; Ji Eun Hwang
Journal:  Am J Emerg Med       Date:  2017-10-04       Impact factor: 2.469

8.  Risk of bacteremia in patients presenting with shaking chills and vomiting - a prospective cohort study.

Authors:  M Holmqvist; M Inghammar; L I Påhlman; J Boyd; P Åkesson; A Linder; F Kahn
Journal:  Epidemiol Infect       Date:  2020-03-31       Impact factor: 2.451

9.  Case report: appendicitis induced Staphylococcus aureus and Klebsiella pneumoniae bacteremia in a young healthy male.

Authors:  Jan Arne Arne Deodatus; Sander Ferdinand Emiel Paas; Gerrit Hendrik Johan Wagenvoort; Marije Matilde de Kubber
Journal:  Int J Emerg Med       Date:  2021-07-19

10.  Can We Reduce Negative Blood Cultures With Clinical Scores and Blood Markers? Results From an Observational Cohort Study.

Authors:  Svenja Laukemann; Nina Kasper; Prasad Kulkarni; Deborah Steiner; Anna Christina Rast; Alexander Kutz; Susan Felder; Sebastian Haubitz; Lukas Faessler; Andreas Huber; Christoph A Fux; Beat Mueller; Philipp Schuetz
Journal:  Medicine (Baltimore)       Date:  2015-12       Impact factor: 1.817

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