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Likelihood of Inadequate Treatment A Novel Approach to Evaluating Drug-Resistance Patterns

Published online by Cambridge University Press:  02 January 2015

Heinz Burgmann ,
Brigitte Stoiser ,
Gottfried Heinz ,
Peter Schenk ,
Petra Apfalter ,
Konstantin Zedtwitz-Liebenstein ,
Michael Frass  and
Yehuda Carmeli
Heinz Burgmann*
Affiliation:
Division of Intensive Care 13i2, Medical University of Vienna, Vienna, Austria Department of Internal Medicine I, Division of Infectious Diseases, Medical University of Vienna, Vienna, Austria
Brigitte Stoiser
Affiliation:
Division of Intensive Care 13i2, Medical University of Vienna, Vienna, Austria Department of Internal Medicine I, Division of Infectious Diseases, Medical University of Vienna, Vienna, Austria
Gottfried Heinz
Affiliation:
Department of Internal Medicine II, Division of Intensive Care 13 H3, Medical University of Vienna, Vienna, Austria
Peter Schenk
Affiliation:
Department of Internal Medicine III, Division of Intensive Care 13 HI, Medical University of Vienna, Vienna, Austria
Petra Apfalter
Affiliation:
Department of Clinical Microbiology, Medical University of Vienna, Vienna, Austria
Konstantin Zedtwitz-Liebenstein
Affiliation:
Department of Internal Medicine I, Division of Infectious Diseases, Medical University of Vienna, Vienna, Austria
Michael Frass
Affiliation:
Division of Intensive Care 13i2, Medical University of Vienna, Vienna, Austria
Yehuda Carmeli
Affiliation:
Division of Epidemiology, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
*
Department of Internal Medicine I, Division of Infectious Diseases, Medical University of Vienna, Waehringer Guertel 18-20, A1090 Vienna, Austria( heinz.burgmann@meduniwien.ac.at)
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Abstract

Objective.

To provide a novel way to predict the likelihood that antibiotic therapy will result in prompt, adequate therapy on the basis of local microbiological data.

Design and Setting.

Prospective study conducted at 3 medical intensive care units at the Viennese General Hospital, a tertiary care medical university teaching hospital in Vienna, Austria.

Patients.

One hundred one patients who received mechanical ventilation and who met the criteria for having ventilator-associated pneumonia.

Design.

Fiberoptic bronchoscopic examination was performed, and bronchoalveolar samples were collected. Samples were analyzed immediately by a single technician. Minimum inhibitory concentrations were determined for imipenem, cephalosporins (cefepime and cefpirome), ciprofloxacin, and piperacillin-tazobactam, and drug resistance rates were calculated. These drug resistance rates were translated into the likelihood of inadequate therapy (LIT; the frequency of inadequately treated patients per antibiotic and drug-resistant strain), cumulative LIT (the cumulative frequency of inadequately treated patients), and syndrome-specific LIT.

Results.

Amongthe 101 bronchoalveolar samples, culture yielded significant (at least 1 × 104 colony-forming units per raL) polymicrobial findings for 34 and significant monomicrobial findings for 31; 36 culture results were negative. Of the isolates from patients with ventilator-associated pneumonia who had monomicrobial culture findings, 33% were gram-positive bacteria and 20% were gram-negative bacteria. LIT suggested that 1 of 2 patients was treated inadequately for Pseudomonas aeruginosa infection. The LIT for patients with ventilator-associated pneumonia revealed that the rank order of antibiotics for appropriate therapy was (1) imipenem, (2) cephalosporins, (3) ciprofloxacin, and (4) piperacillin-tazobactam. These calculations were based solely on microbiological data.

Conclusions.

The novel ratio LIT may help clinicians use microbiological data on drug resistance to predict which antimicrobial agents will provide adequate therapy. In daily practice, this new approach may be helpful for choosing adequate antimicrobial therapy.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 30 , Issue 7 , July 2009 , pp. 672 - 677
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2009

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