Likelihood of inadequate treatment: a novel approach to evaluating drug-resistance patterns.
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.


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


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


METHODS
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
Among the 101 bronchoalveolar samples, culture yielded significant (at least 1 x 10(4) colony-forming units per mL) 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.
Burgmann
Heinz
H
Division of Intensive Care, Department of Internal Medicine I, Medical University of Vienna, Vienna, Austria. heinz.burgmann@meduniwien.ac.at
Stoiser
Brigitte
B
Heinz
Gottfried
G
Schenk
Peter
P
Apfalter
Petra
P
Zedtwitz-Liebenstein
Konstantin
K
Frass
Michael
M
Carmeli
Yehuda
Y
D000328:Adult; D000368:Aged; D000900:Anti-Bacterial Agents / Q000494:pharmacology / Q000627:therapeutic use; D001317:Austria; D001992:Bronchoalveolar Lavage Fluid / Q000382:microbiology; D024881:Drug Resistance, Bacterial; D005260:Female; D006090:Gram-Negative Bacteria / Q000145:classification / Q000187:drug effects*; D016905:Gram-Negative Bacterial Infections / Q000188:drug therapy / Q000382:microbiology; D016908:Gram-Positive Bacterial Infections / Q000188:drug therapy / Q000382:microbiology; D006095:Gram-Positive Cocci / Q000145:classification / Q000187:drug effects*; D006785:Hospitals, University; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008826:Microbial Sensitivity Tests; D008875:Middle Aged; D053717:Pneumonia, Ventilator-Associated / Q000188:drug therapy* / Q000382:microbiology; D011552:Pseudomonas Infections / Q000188:drug therapy / Q000382:microbiology; D011550:Pseudomonas aeruginosa / Q000187:drug effects; D016896:Treatment Outcome
D000900:Anti-Bacterial Agents