Literature DB >> 27863948

Tree-structured survival analysis of patients with Pseudomonas aeruginosa bacteremia: A multicenter observational cohort study.

Young Kyung Yoon1, Hyun Ah Kim2, Seong Yeol Ryu2, Eun Jung Lee3, Mi Suk Lee4, Jieun Kim5, Seong Yeon Park6, Kyung Sook Yang7, Shin Woo Kim8.   

Abstract

This study aimed to construct a prediction algorithm, which is readily applicable in the clinical setting, to determine the mortality rate for patients with P. aeruginosa bacteremia. A multicenter observational cohort study was performed retrospectively in seven university-affiliated hospitals in Korea from March 2012 to February 2015. In total, 264 adult patients with monomicrobial P. aeruginosa bacteremia were included in the analyses. Among the predictors independently associated with 30-day mortality in the Cox regression model, Pitt bacteremia score >2 and high-risk source of bacteremia were identified as critical nodes in the tree-structured survival analysis. Particularly, the empirical combination therapy was not associated with any survival benefit in the Cox regression model compared to the empirical monotherapy. This study suggests that determining the infection source and evaluating the clinical severity are critical to predict the clinical outcome in patients with P. aeruginosa bacteremia.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bacteremia; Mortality; Pseudomonas aeruginosa

Mesh:

Year:  2016        PMID: 27863948     DOI: 10.1016/j.diagmicrobio.2016.10.008

Source DB:  PubMed          Journal:  Diagn Microbiol Infect Dis        ISSN: 0732-8893            Impact factor:   2.803


  7 in total

1.  Antipseudomonal monotherapy or combination therapy for older adults with community-onset pneumonia and multidrug-resistant risk factors: a retrospective cohort study.

Authors:  Obiageri O Obodozie-Ofoegbu; Chengwen Teng; Eric M Mortensen; Christopher R Frei
Journal:  Am J Infect Control       Date:  2019-03-21       Impact factor: 2.918

2.  A New Scoring System for the Differential Diagnosis between Tuberculous Meningitis and Viral Meningitis.

Authors:  Sang-Ah Lee; Shin-Woo Kim; Hyun-Ha Chang; Hyejin Jung; Yoonjung Kim; Soyoon Hwang; Sujeong Kim; Han-Ki Park; Jong-Myung Lee
Journal:  J Korean Med Sci       Date:  2018-06-14       Impact factor: 2.153

3.  Risk factors and the resistance mechanisms involved in Pseudomonas aeruginosa mutation in critically ill patients.

Authors:  Stéphanie Druge; Stéphanie Ruiz; Fanny Vardon-Bounes; Marion Grare; François Labaste; Thierry Seguin; Olivier Fourcade; Vincent Minville; Jean-Marie Conil; Bernard Georges
Journal:  J Intensive Care       Date:  2019-07-19

4.  Comparison of mono- and combination antibiotic therapy for the treatment of Pseudomonas aeruginosa bacteraemia: A cumulative meta-analysis of cohort studies.

Authors:  Su Yu Tang; Shun Wen Zhang; Jiang Dong Wu; Fang Wu; Jie Zhang; Jiang Tao Dong; Peng Guo; Da Long Zhang; Jun Ting Yang; Wan Jiang Zhang
Journal:  Exp Ther Med       Date:  2018-01-09       Impact factor: 2.447

Review 5.  Antibiotic selection in the treatment of acute invasive infections by Pseudomonas aeruginosa: Guidelines by the Spanish Society of Chemotherapy.

Authors:  J Mensa; J Barberán; A Soriano; P Llinares; F Marco; R Cantón; G Bou; J González Del Castillo; E Maseda; J R Azanza; J Pasquau; C García-Vidal; J M Reguera; D Sousa; J Gómez; M Montejo; M Borges; A Torres; F Alvarez-Lerma; M Salavert; R Zaragoza; A Oliver
Journal:  Rev Esp Quimioter       Date:  2018-02-23       Impact factor: 1.553

6.  A retrospective analysis of Pseudomonas aeruginosa bloodstream infections: prevalence, risk factors, and outcome in carbapenem-susceptible and -non-susceptible infections.

Authors:  Qingyi Shi; Chen Huang; Tingting Xiao; Zhenzhu Wu; Yonghong Xiao
Journal:  Antimicrob Resist Infect Control       Date:  2019-04-25       Impact factor: 4.887

7.  Effect of Different Piperacillin-Tazobactam Dosage Regimens on Synergy of the Combination with Tobramycin against Pseudomonas aeruginosa for the Pharmacokinetics of Critically Ill Patients in a Dynamic Infection Model.

Authors:  Jessica R Tait; Hajira Bilal; Kate E Rogers; Yinzhi Lang; Tae-Hwan Kim; Jieqiang Zhou; Steven C Wallis; Jürgen B Bulitta; Carl M J Kirkpatrick; David L Paterson; Jeffrey Lipman; Phillip J Bergen; Jason A Roberts; Roger L Nation; Cornelia B Landersdorfer
Journal:  Antibiotics (Basel)       Date:  2022-01-13
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.