Literature DB >> 26492818

Demographic and infection characteristics of patients with carbapenem-resistant Enterobacteriaceae in a community hospital: Development of a bedside clinical score for risk assessment.

Brooke M Miller1, Steven W Johnson2.   

Abstract

BACKGROUND: The objective of this study was to identify risk factors associated with the presence of carbapenem-resistant Enterobacteriaceae (CRE) infections to develop a clinical prediction model that can be used at patient bedside to identify subjects likely infected with a CRE pathogen.
METHODS: This case-control study included patients aged ≥18 years admitted to Novant Health Forsyth Medical Center between January 1, 2012, and December 31, 2013, with CRE infections (cases) or non-CRE infections (controls). Controls were matched to their corresponding resistant case (3:1) based on pathogen, place of likely acquisition, isolate source, year of admission, and level of care. A risk prediction model was developed using variables independently associated with CRE isolation. Sensitivities and specificities were obtained at various point cutoffs, and a determination of the receiver operator characteristic (ROC) area under the curve (AUC) was performed.
RESULTS: A total of 164 subjects were included. Independent risk factors for CRE included recent antibiotic therapy, recent immunosuppression, and Charlson Comorbidity Index score ≥4. Adjusted odds ratios were 13.37 (95% confidence interval [CI], 4.16-61.19), 6.69 (95% CI, 1.85-29.65), and 3.30 (95% CI, 1.34-8.40), respectively. Diagnostic performance of various score cutoffs for the model indicated a score ≥5 correlated with the highest accuracy (79%). The ROC AUC was 0.83.
CONCLUSION: The risk prediction model displayed good discrimination and was an excellent predictor of CRE infection.
Copyright © 2016 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CRE; Carbapenem-resistant Enterobacteriaceae; Enterobacteriaceae; Prediction model; Risk factors

Mesh:

Substances:

Year:  2015        PMID: 26492818     DOI: 10.1016/j.ajic.2015.09.006

Source DB:  PubMed          Journal:  Am J Infect Control        ISSN: 0196-6553            Impact factor:   2.918


  14 in total

1.  Antimicrobial resistance and antibiotic stewardship programs in the ICU: insistence and persistence in the fight against resistance. A position statement from ESICM/ESCMID/WAAAR round table on multi-drug resistance.

Authors:  Jan J De Waele; Murat Akova; Massimo Antonelli; Rafael Canton; Jean Carlet; Daniel De Backer; George Dimopoulos; José Garnacho-Montero; Jozef Kesecioglu; Jeffrey Lipman; Mervyn Mer; José-Artur Paiva; Mario Poljak; Jason A Roberts; Jesus Rodriguez Bano; Jean-François Timsit; Jean-Ralph Zahar; Matteo Bassetti
Journal:  Intensive Care Med       Date:  2017-12-29       Impact factor: 17.440

2.  A Systematic Review and Meta-analyses of the Clinical Epidemiology of Carbapenem-Resistant Enterobacteriaceae.

Authors:  Karlijn van Loon; Anne F Voor In 't Holt; Margreet C Vos
Journal:  Antimicrob Agents Chemother       Date:  2017-12-21       Impact factor: 5.191

Review 3.  The rapid spread of carbapenem-resistant Enterobacteriaceae.

Authors:  Robert F Potter; Alaric W D'Souza; Gautam Dantas
Journal:  Drug Resist Updat       Date:  2016-09-19       Impact factor: 18.500

Review 4.  Carbapenem-resistant Enterobacteriaceae in the community: a scoping review.

Authors:  Ana M Kelly; Barun Mathema; Elaine L Larson
Journal:  Int J Antimicrob Agents       Date:  2017-06-21       Impact factor: 5.283

5.  Risk Factors for Development of Carbapenem Resistance Among Gram-Negative Rods.

Authors:  Stefan E Richter; Loren Miller; Jack Needleman; Daniel Z Uslan; Douglas Bell; Karol Watson; Romney Humphries; James A McKinnell
Journal:  Open Forum Infect Dis       Date:  2019-01-23       Impact factor: 3.835

6.  Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model.

Authors:  Yi Li; Hui Shen; Cheng Zhu; Yuetian Yu
Journal:  Biomed Res Int       Date:  2019-03-27       Impact factor: 3.411

7.  Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections.

Authors:  Thomas P Lodise; Nicole Gidaya Bonine; Jiatao Michael Ye; Henry J Folse; Patrick Gillard
Journal:  BMC Infect Dis       Date:  2019-08-14       Impact factor: 3.090

8.  Bacterial characteristics of carbapenem-resistant Enterobacteriaceae (CRE) colonized strains and their correlation with subsequent infection.

Authors:  Qun Lin; Yue Wang; Jing Yu; Shusheng Li; Yicheng Zhang; Hui Wang; Xiaoquan Lai; Dong Liu; Liyan Mao; Ying Luo; Guoxing Tang; Zhongju Chen; Ziyong Sun
Journal:  BMC Infect Dis       Date:  2021-07-02       Impact factor: 3.090

9.  Factors associated with acquisition of carbapenem-resistant Enterobacteriaceae.

Authors:  Lilian Silva Lavagnoli; Bil Randerson Bassetti; Thais Dias Lemos Kaiser; Kátia Maria Kutz; Crispim Cerutti
Journal:  Rev Lat Am Enfermagem       Date:  2017-10-05

10.  Human MAIT cell cytolytic effector proteins synergize to overcome carbapenem resistance in Escherichia coli.

Authors:  Caroline Boulouis; Wan Rong Sia; Muhammad Yaaseen Gulam; Jocelyn Qi Min Teo; Yi Tian Png; Thanh Kha Phan; Jeffrey Y W Mak; David P Fairlie; Ivan K H Poon; Tse Hsien Koh; Peter Bergman; Chwee Ming Lim; Lin-Fa Wang; Andrea Lay Hoon Kwa; Johan K Sandberg; Edwin Leeansyah
Journal:  PLoS Biol       Date:  2020-06-08       Impact factor: 8.029

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.