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Clinical predictive model of multidrug resistance in neutropenic cancer patients with bloodstream infection due to Pseudomonas aeruginosa

  • C. Gudiol
  • , A. Albasanz-Puig
  • , J. Laporte-Amargós
  • , N. Pallarès
  • , A. Mussetti
  • , I. Ruiz-Camps
  • , P. Puerta-Alcalde
  • , E. Abdala
  • , C. Oltolini
  • , M. Akova
  • , M. Montejo
  • , M. Mikulska
  • , P. Martín-Dávila
  • , F. Herrera
  • , O. Gasch
  • , L. Drgona
  • , H. Paz Morales
  • , A. S. Brunel
  • , E. García
  • , B. Isler
  • W. V. Kern, I. Morales, G. Maestro-De La Calle, M. Montero, S. S. Kanj, O. R. Sipahi, S. Calik, I. Márquez-Gómez, J. I. Marin, M. Z.R. Gomes, P. Hemmatti, R. Araos, M. Peghin, J. L. Del Pozo, L. Yáñez, R. Tilley, A. Manzur, A. Novo, J. Carratalà, Guillermo Cuervo, Francesc Escrihuela-Vidal, Fe Tubau, Cristian Tebé, Marisol Rodríguez Arias, Juan Aguilar-Company, Nieves Larrosa, Celia Cardozo, Carolina Garcia-Vidal, Ibrahim Karim-Yaqub, Raffaella Greco, Paola Cichero, Caglayan Merve Ayaz, Roberto Céspedes, Leire López-Soria, Laura Magnasco, Jesús Fortún, Diego Torres, Anna Boté, Mateu Espasa, Mia Hold Montaguti, Pierre Yves Bochud, Oriol Manuel, Salvador Tabares Carrasco, Josefina Serrano López, Hartmut Bertz, Siegbert Rieg, Marina De Cueto, Jesús Rodríguez-Baño, Manuel Lizasoain, José María Aguado, Juan Pablo Horcajada, Saeed El Zein, Jean Francois Jabbour, Ayse Uyan-Onal, Arzu Nazli-Zeka, Begoña Palop, Lina Clemencia Correa, Amanda Aparecida Da Silva Machado, João Pedro Silva Tonhá, Georg Maschmeyer, Jose Munita, Matteo Bassetti, Nadia Castaldo, Paloma Sangro Del Alcázar

Research output: Contribution to journalArticlepeer-review

59 Citations (Scopus)

Abstract

We aimed to assess the rate and predictive factors of bloodstream infection (BSI) due to multidrug-resistant (MDR) Pseudomonas aeruginosa in neutropenic cancer patients. We performed a multicenter, retrospective cohort study including oncohematological neutropenic patients with BSI due to P. aeruginosa conducted across 34 centers in 12 countries from January 2006 to May 2018. A mixed logistic regression model was used to estimate a model to predict the multidrug resistance of the causative pathogens. Of a total of 1,217 episodes of BSI due to P. aeruginosa, 309 episodes (25.4%) were caused by MDR strains. The rate of multidrug resistance increased significantly over the study period (P = 0.033). Predictors of MDR P. aeruginosa BSI were prior therapy with piperacillin-tazobactam (odds ratio [OR], 3.48; 95% confidence interval [CI], 2.29 to 5.30), prior antipseudomonal carbapenem use (OR, 2.53; 95% CI, 1.65 to 3.87), fluoroquinolone prophylaxis (OR, 2.99; 95% CI, 1.92 to 4.64), underlying hematological disease (OR, 2.09; 95% CI, 1.26 to 3.44), and the presence of a urinary catheter (OR, 2.54; 95% CI, 1.65 to 3.91), whereas older age (OR, 0.98; 95% CI, 0.97 to 0.99) was found to be protective. Our prediction model achieves good discrimination and calibration, thereby identifying neutropenic patients at higher risk of BSI due to MDR P. aeruginosa. The application of this model using a web-based calculator may be a simple strategy to identify high-risk patients who may benefit from the early administration of broad-spectrum antibiotic coverage against MDR strains according to the local susceptibility patterns, thus avoiding the use of broad-spectrum antibiotics in patients at a low risk of resistance development.

Original languageEnglish
Article numbere02494
JournalAntimicrobial Agents and Chemotherapy
Volume64
Issue number4
DOIs
Publication statusPublished - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Bacteremia
  • Bloodstream infection
  • Cancer
  • Multidrug resistant
  • Neutropenia
  • Predictive model
  • Pseudomonas aeruginosa
  • Risk factors

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