A Simple Bacteremia Score for Predicting Bacteremia in Patients with Suspected Infection in the Emergency Department: A Cohort Study

Bacteremia is a life-threatening condition that has increased in prevalence over the past two decades. Prompt recognition of bacteremia is important; however, identification of bacteremia requires 1 to 2 days. This retrospective cohort study, conducted from 10 November 2014 to November 2019, among p...

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Veröffentlicht in:Journal of personalized medicine 2024-01, Vol.14 (1), p.57
Hauptverfasser: Han, Hyelin, Kim, Da Seul, Kim, Minha, Heo, Sejin, Chang, Hansol, Lee, Gun Tak, Lee, Se Uk, Kim, Taerim, Yoon, Hee, Hwang, Sung Yeon, Cha, Won Chul, Sim, Min Sub, Jo, Ik Joon, Park, Jong Eun, Shin, Tae Gun
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container_issue 1
container_start_page 57
container_title Journal of personalized medicine
container_volume 14
creator Han, Hyelin
Kim, Da Seul
Kim, Minha
Heo, Sejin
Chang, Hansol
Lee, Gun Tak
Lee, Se Uk
Kim, Taerim
Yoon, Hee
Hwang, Sung Yeon
Cha, Won Chul
Sim, Min Sub
Jo, Ik Joon
Park, Jong Eun
Shin, Tae Gun
description Bacteremia is a life-threatening condition that has increased in prevalence over the past two decades. Prompt recognition of bacteremia is important; however, identification of bacteremia requires 1 to 2 days. This retrospective cohort study, conducted from 10 November 2014 to November 2019, among patients with suspected infection who visited the emergency department (ED), aimed to develop and validate a simple tool for predicting bacteremia. The study population was randomly divided into derivation and development cohorts. Predictors of bacteremia based on the literature and logistic regression were assessed. A weighted value was assigned to predictors to develop a prediction model for bacteremia using the derivation cohort; discrimination was then assessed using the area under the receiver operating characteristic curve (AUC). Among the 22,519 patients enrolled, 18,015 were assigned to the derivation group and 4504 to the validation group. Sixteen candidate variables were selected, and all sixteen were used as significant predictors of bacteremia (model 1). Among the sixteen variables, the top five with higher odds ratio, including procalcitonin, neutrophil-lymphocyte ratio (NLR), lactate level, platelet count, and body temperature, were used for the simple bacteremia score (model 2). The proportion of bacteremia increased according to the simple bacteremia score in both cohorts. The AUC for model 1 was 0.805 (95% confidence interval [CI] 0.785-0.824) and model 2 was 0.791 (95% CI 0.772-0.810). The simple bacteremia prediction score using only five variables demonstrated a comparable performance with the model including sixteen variables using all laboratory results and vital signs. This simple score is useful for predicting bacteremia-assisted clinical decisions.
doi_str_mv 10.3390/jpm14010057
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Prompt recognition of bacteremia is important; however, identification of bacteremia requires 1 to 2 days. This retrospective cohort study, conducted from 10 November 2014 to November 2019, among patients with suspected infection who visited the emergency department (ED), aimed to develop and validate a simple tool for predicting bacteremia. The study population was randomly divided into derivation and development cohorts. Predictors of bacteremia based on the literature and logistic regression were assessed. A weighted value was assigned to predictors to develop a prediction model for bacteremia using the derivation cohort; discrimination was then assessed using the area under the receiver operating characteristic curve (AUC). Among the 22,519 patients enrolled, 18,015 were assigned to the derivation group and 4504 to the validation group. Sixteen candidate variables were selected, and all sixteen were used as significant predictors of bacteremia (model 1). Among the sixteen variables, the top five with higher odds ratio, including procalcitonin, neutrophil-lymphocyte ratio (NLR), lactate level, platelet count, and body temperature, were used for the simple bacteremia score (model 2). The proportion of bacteremia increased according to the simple bacteremia score in both cohorts. The AUC for model 1 was 0.805 (95% confidence interval [CI] 0.785-0.824) and model 2 was 0.791 (95% CI 0.772-0.810). The simple bacteremia prediction score using only five variables demonstrated a comparable performance with the model including sixteen variables using all laboratory results and vital signs. 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source MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; PubMed Central Open Access
subjects Antibiotics
Bacteremia
Blood
Body temperature
Cohort analysis
Emergency medical care
Emergency service
Health aspects
Hospitals
Infection
Infections
Leukocytes (neutrophilic)
Lymphocytes
Medical research
Medicine, Experimental
Neutrophils
Patients
Population studies
Prediction models
Procalcitonin
Regression analysis
Sepsis
Statistical analysis
Variables
title A Simple Bacteremia Score for Predicting Bacteremia in Patients with Suspected Infection in the Emergency Department: A Cohort Study
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