4.7 Article

Clinical Pharmacodynamics of Antipseudomonal Cephalosporins in Patients with Ventilator-Associated Pneumonia

Journal

ANTIMICROBIAL AGENTS AND CHEMOTHERAPY
Volume 58, Issue 3, Pages 1359-1364

Publisher

AMER SOC MICROBIOLOGY
DOI: 10.1128/AAC.01463-13

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Advanced-generation cephalosporins are frequently used for empirical coverage of ventilator-associated pneumonia (VAP) due to their activity against a broad spectrum of Gram-positive and Gram-negative aerobic bacteria, including Pseudomonas aeruginosa and Enterobacteriaceae. Providing optimal antibiotic exposure is essential to achieving successful response in patients with VAP. We evaluated exposures of two antipseudomonal cephalosporins, ceftazidime and cefepime, in patients with VAP due to Gram-negative bacilli to identify the pharmacodynamic parameter predictive of microbiological success. Population pharmacokinetic models were used to estimate individual free drug exposures. Pharmacodynamic indices were determined for each patient using the baseline Gram-negative bacilli with the highest drug MIC. Classification and regression tree analysis was utilized to partition exposure breakpoints, and multivariate logistic regression was conducted to identify predictors of microbiological success. A total of 73 patients (18 receiving ceftazidime therapy and 55 receiving cefepime therapy) were included. MICs ranged widely from 0.047 to 96 mu g/ml. The microbiological success rate was 58.9%. Predictive breakpoints were identified for all pharmacodynamic parameters, including a serum fT > MIC greater than 53% (P = 0.02). When controlling for APACHE II (odds ratio [OR], 1.01; 95% confidence interval, 0.93 to 1.09; P = 0.85) and combination therapy (OR, 0.74; 95% confidence interval, 0.25 to 2.19; P = 0.59), achieving a greater than 53% fT > MIC remained a significant predictor of success (OR, 10.3; 95% confidence interval, 1.1 to 92.3; P = 0.04). In patients with VAP due to Gram-negative bacilli, serum exposure of greater than 53% fT > MIC was found to be a significant predictor of favorable microbiological response for antipseudomonal cephalosporins. These data are useful when determining dosing regimens for cephalosporin agents under development for pneumonia.

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