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Antimicrobial Agents and Chemotherapy, February 2007, p. 417-422, Vol. 51, No. 2
0066-4804/07/$08.00+0     doi:10.1128/AAC.00851-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.

Clinical Prediction Tool To Identify Patients with Pseudomonas aeruginosa Respiratory Tract Infections at Greatest Risk for Multidrug Resistance{triangledown}

Thomas P. Lodise,1,2* Christopher D. Miller,1,3 Jeffrey Graves,1 Jon P. Furuno,4 Jessina C. McGregor,4 Ben Lomaestro,5 Eileen Graffunder,6 and Louise-Anne McNutt7

Pharmacy Practice Department, Albany College of Pharmacy, Albany, New York,1 Ordway Research Institute, Albany, New York,2 Division of HIV Medicine, Albany Medical College, Albany, New York,3 Department of Epidemiology and Preventive Medicine, University of Maryland, Baltimore, Baltimore, Maryland,4 Department of Pharmacy, Albany Medical Center Hospital, Albany, New York,5 Department of Epidemiology, Albany Medical Center Hospital, Albany, New York,6 Department of Epidemiology, School of Public Health, University at Albany, State University of New York, Albany, New York7

Received 12 July 2006/ Returned for modification 17 August 2006/ Accepted 30 November 2006

Despite the increasing prevalence of multiple-drug-resistant (MDR) Pseudomonas aeruginosa, the factors predictive of MDR have not been extensively explored. We sought to examine factors predictive of MDR among patients with P. aeruginosa respiratory tract infections and to develop a tool to estimate the probability of MDR among such high-risk patients. This was a single-site, case-control study of patients with P. aeruginosa respiratory tract infections. Multiple-drug resistance was defined as resistance to four or more antipseudomonal antimicrobial classes. Clinical data on demographics, antibiotic history, and microbiology were collected. Classification and regression tree analysis (CART) was used to identify the duration of antibiotic exposure associated with MDR P. aeruginosa. Log-binomial regression was used to model the probability of MDR P. aeruginosa. Among 351 P. aeruginosa-infected patients, the proportion of MDR P. aeruginosa was 35%. A significant relationship between prior antibiotic exposure and MDR P. aeruginosa was found for all of the antipseudomonal antibiotics studied, but the duration of prior exposure associated with MDR varied between antibiotic classes; the shortest prior exposure duration was observed for carbapenems and fluoroquinolones, and the longest duration was noted for cefepime and piperacillin-tazobactam. Within the final model, the predicted MDR P. aeruginosa likelihood was most dependent upon length of hospital stay, prior culture sample collection, and number of CART-derived prior antibiotic exposures. A history of a prolonged hospital stay and exposure to antipseudomonal antibiotics predicts multidrug resistance among patients with P. aeruginosa respiratory tract infections at our institution. Identifying these risk factors enabled us to develop a prediction tool to assess the risk of resistance and thus guide empirical antibiotic therapy.

* Corresponding author. Mailing address: Albany College of Pharmacy, Department of Pharmacy Practice, 106 New Scotland Avenue, Albany, NY 12208-3492. Phone: (518) 445-7292. Fax: (518) 694-7062. E-mail: lodiset{at}acp.edu.

{triangledown} Published ahead of print on 11 December 2006.

Antimicrobial Agents and Chemotherapy, February 2007, p. 417-422, Vol. 51, No. 2
0066-4804/07/$08.00+0     doi:10.1128/AAC.00851-06
Copyright © 2007, American Society for Microbiology. All Rights Reserved.



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  • El Solh, A. A., Alhajhusain, A. (2009). Update on the treatment of Pseudomonas aeruginosa pneumonia. J Antimicrob Chemother 64: 229-238 [Abstract] [Full Text]  
  • Patel, N., McNutt, L.-A., Lodise, T. P. (2008). Relationship between Various Definitions of Prior Antibiotic Exposure and Piperacillin-Tazobactam Resistance among Patients with Respiratory Tract Infections Caused by Pseudomonas aeruginosa. Antimicrob. Agents Chemother. 52: 2933-2936 [Abstract] [Full Text]  


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