Clinical prediction score for community-onset bloodstream infections caused by extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella species

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Abstract

Background: This study aimed to identify the predictors and build a prediction score for community-onset bloodstream infections (CO-BSIs) caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella species. Methods: All CO-BSIs caused by E. coli and Klebsiella species from 2012 to 2015 were grouped into derivation (BSIs from 2012 to 2014) and validation (BSIs in 2015) cohorts. A prediction score was built using the coefficients of the multivariate logistic regression model from the derivation cohort. Results: The study included 886 CO-BSIs (594 and 292 in the derivation and validation cohorts, respectively). The independent predictors of CO-BSIs caused by ESBL-producing E. coli and Klebsiella species included: 1) identification of ESBL-producing microorganisms from any clinical culture within one year of admission, 2) beta-lactam or fluoroquinolone treatment within 30 days (with 2 or more courses within 90 days; with 1 course within 90 days), 3) hospitalization within one year, 4) the presence of an indwelling urinary catheter at the time of admission. The area under the curve (AUC) of the clinical prediction score was 0.72 (95% confidence interval [CI], 0.68-0.77). In the validation cohort, the AUC was 0.70 (95% CI, 0.63-0.77). Conclusions: The results of this study suggest a simple and easy-to-use scoring system to predict CO-BSIs caused by ESBL-producing E. coli and Klebsiella species.

Original languageEnglish
Article numbere116
JournalJournal of Korean Medical Science
Volume34
Issue number14
DOIs
StatePublished - 15 Apr 2019

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Klebsiella
beta-Lactamases
Escherichia coli
Infection
Area Under Curve
Logistic Models
Confidence Intervals
Escherichia coli Infections
Urinary Catheters
Indwelling Catheters
Fluoroquinolones
beta-Lactams
Hospitalization
Therapeutics

Keywords

  • Bloodstream infection
  • Community-onset infection
  • Escherichia coli
  • Extended-spectrum beta-lactamase
  • Klebsiella
  • Prediction score

Cite this

@article{1e910c31dca2407c820b8b298b5970f2,
title = "Clinical prediction score for community-onset bloodstream infections caused by extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella species",
abstract = "Background: This study aimed to identify the predictors and build a prediction score for community-onset bloodstream infections (CO-BSIs) caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella species. Methods: All CO-BSIs caused by E. coli and Klebsiella species from 2012 to 2015 were grouped into derivation (BSIs from 2012 to 2014) and validation (BSIs in 2015) cohorts. A prediction score was built using the coefficients of the multivariate logistic regression model from the derivation cohort. Results: The study included 886 CO-BSIs (594 and 292 in the derivation and validation cohorts, respectively). The independent predictors of CO-BSIs caused by ESBL-producing E. coli and Klebsiella species included: 1) identification of ESBL-producing microorganisms from any clinical culture within one year of admission, 2) beta-lactam or fluoroquinolone treatment within 30 days (with 2 or more courses within 90 days; with 1 course within 90 days), 3) hospitalization within one year, 4) the presence of an indwelling urinary catheter at the time of admission. The area under the curve (AUC) of the clinical prediction score was 0.72 (95{\%} confidence interval [CI], 0.68-0.77). In the validation cohort, the AUC was 0.70 (95{\%} CI, 0.63-0.77). Conclusions: The results of this study suggest a simple and easy-to-use scoring system to predict CO-BSIs caused by ESBL-producing E. coli and Klebsiella species.",
keywords = "Bloodstream infection, Community-onset infection, Escherichia coli, Extended-spectrum beta-lactamase, Klebsiella, Prediction score",
author = "Moonsuk Kim and Kyoung-Ho Song and Kim, {Chung Jong} and Choe, {Pyoeng Gyun} and Park, {Wan Beom} and Bang, {Ji Hwan} and Kim, {Eu Suk} and Sang-Won Park and Kim, {Nam Joong} and Myoung-Don Oh and Kim, {Hong Bin}",
year = "2019",
month = "4",
day = "15",
doi = "10.3346/jkms.2019.34.e116",
language = "English",
volume = "34",
journal = "Journal of Korean medical science",
issn = "1011-8934",
publisher = "Korean Academy of Medical Science",
number = "14",

}

TY - JOUR

T1 - Clinical prediction score for community-onset bloodstream infections caused by extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella species

AU - Kim, Moonsuk

AU - Song, Kyoung-Ho

AU - Kim, Chung Jong

AU - Choe, Pyoeng Gyun

AU - Park, Wan Beom

AU - Bang, Ji Hwan

AU - Kim, Eu Suk

AU - Park, Sang-Won

AU - Kim, Nam Joong

AU - Oh, Myoung-Don

AU - Kim, Hong Bin

PY - 2019/4/15

Y1 - 2019/4/15

N2 - Background: This study aimed to identify the predictors and build a prediction score for community-onset bloodstream infections (CO-BSIs) caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella species. Methods: All CO-BSIs caused by E. coli and Klebsiella species from 2012 to 2015 were grouped into derivation (BSIs from 2012 to 2014) and validation (BSIs in 2015) cohorts. A prediction score was built using the coefficients of the multivariate logistic regression model from the derivation cohort. Results: The study included 886 CO-BSIs (594 and 292 in the derivation and validation cohorts, respectively). The independent predictors of CO-BSIs caused by ESBL-producing E. coli and Klebsiella species included: 1) identification of ESBL-producing microorganisms from any clinical culture within one year of admission, 2) beta-lactam or fluoroquinolone treatment within 30 days (with 2 or more courses within 90 days; with 1 course within 90 days), 3) hospitalization within one year, 4) the presence of an indwelling urinary catheter at the time of admission. The area under the curve (AUC) of the clinical prediction score was 0.72 (95% confidence interval [CI], 0.68-0.77). In the validation cohort, the AUC was 0.70 (95% CI, 0.63-0.77). Conclusions: The results of this study suggest a simple and easy-to-use scoring system to predict CO-BSIs caused by ESBL-producing E. coli and Klebsiella species.

AB - Background: This study aimed to identify the predictors and build a prediction score for community-onset bloodstream infections (CO-BSIs) caused by extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella species. Methods: All CO-BSIs caused by E. coli and Klebsiella species from 2012 to 2015 were grouped into derivation (BSIs from 2012 to 2014) and validation (BSIs in 2015) cohorts. A prediction score was built using the coefficients of the multivariate logistic regression model from the derivation cohort. Results: The study included 886 CO-BSIs (594 and 292 in the derivation and validation cohorts, respectively). The independent predictors of CO-BSIs caused by ESBL-producing E. coli and Klebsiella species included: 1) identification of ESBL-producing microorganisms from any clinical culture within one year of admission, 2) beta-lactam or fluoroquinolone treatment within 30 days (with 2 or more courses within 90 days; with 1 course within 90 days), 3) hospitalization within one year, 4) the presence of an indwelling urinary catheter at the time of admission. The area under the curve (AUC) of the clinical prediction score was 0.72 (95% confidence interval [CI], 0.68-0.77). In the validation cohort, the AUC was 0.70 (95% CI, 0.63-0.77). Conclusions: The results of this study suggest a simple and easy-to-use scoring system to predict CO-BSIs caused by ESBL-producing E. coli and Klebsiella species.

KW - Bloodstream infection

KW - Community-onset infection

KW - Escherichia coli

KW - Extended-spectrum beta-lactamase

KW - Klebsiella

KW - Prediction score

UR - http://www.scopus.com/inward/record.url?scp=85064814275&partnerID=8YFLogxK

U2 - 10.3346/jkms.2019.34.e116

DO - 10.3346/jkms.2019.34.e116

M3 - Article

VL - 34

JO - Journal of Korean medical science

JF - Journal of Korean medical science

SN - 1011-8934

IS - 14

M1 - e116

ER -