Predicting Resistance to Piperacillin-Tazobactam, Cefepime and Meropenem in Septic Patients With Bloodstream Infection Due to Gram-Negative Bacteria | Zendy

Cristina Vazquez Guillamet | Zendy; Rodrigo Vazquez Guillamet | Zendy; Scott T. Micek | Zendy; Marin H. Kollef | Zendy

Open Access

Predicting Resistance to Piperacillin-Tazobactam, Cefepime and Meropenem in Septic Patients With Bloodstream Infection Due to Gram-Negative Bacteria

Author(s) -

Cristina Vazquez Guillamet,

Rodrigo Vazquez Guillamet,

Scott T. Micek,

Marin H. Kollef

Publication year - 2017

Publication title -

clinical infectious diseases

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.44

H-Index - 336

eISSN - 1537-6591

pISSN - 1058-4838

DOI - 10.1093/cid/cix612

Subject(s) - cefepime , medicine , meropenem , piperacillin , tazobactam , chaid , antibiotic resistance , piperacillin/tazobactam , antibiotics , logistic regression , intensive care medicine , microbiology and biotechnology , imipenem , pseudomonas aeruginosa , decision tree , biology , bacteria , machine learning , genetics , computer science

Predicting antimicrobial resistance in gram-negative bacteria (GNB) could balance the need for administering appropriate empiric antibiotics while also minimizing the use of clinically unwarranted broad-spectrum agents. Our objective was to develop a practical prediction rule able to identify patients with GNB infection at low risk for resistance to piperacillin-tazobactam (PT), cefepime (CE), and meropenem (ME).

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