Optimization of XXXX therapy.

@entity1 @entity137 @entity281 @entity581 @entity4028
@entity581 are experiencing a resurgence in use because of the spread of multiresistant Gram-negative pathogens. Use of these agents is attended by the occurrence of nephrotoxicity. @entity4028 optimization of dose can be defined as the dose having the highest likelihood of a good outcome and the lowest likelihood of @entity137 . We have defined the metric /\ as the difference between the likelihoods of good outcome and @entity137 , with higher values being better. We developed a method for explicitly evaluating /\ for different daily doses of drug and different schedules of administration. In the empirical therapy setting, when @entity581 are administered every 12 h, treatment of @entity281 caused by microbes with MIC values greater than 1 mg/liter cannot attain a high enough likelihood of a good outcome without engendering an unacceptable @entity137 likelihood. Daily administration, by decrementing the likelihood of @entity137 , allows higher doses to be employed with more acceptable probabilities of @entity137 . Obtaining @entity1 -specific information (concentration-time data) allows better identification of the @entity1 's specific pharmacokinetic parameters and dispersion. As these become better identified, optimal doses become rapidly identified so that optimal outcomes are attained. Optimization of therapy for @entity581 requires understanding the relationship between exposure and response as well as that between exposure and @entity137 . Furthermore, daily administration is much preferred, and stopping therapy as quickly as possible (a week or less may be optimal) will contribute to the ability to optimize therapy.
