Unraveling Ceftriaxone Dosing: Free Drug Prediction, Threshold Optimization, and Model Validation.

Ceftriaxone is pivotal in treating severe infections; however, predicting unbound plasma ceftriaxone (CEF) from total ceftriaxone (CEF) remains challenging. This study aimed to (1) predict CEF from CEF, (2) determine optimal target for CEF trough concentration in plasma, (3) perform an external validation of published models, and (4) to ascertain whether the CEF dosing regimen was sufficient to achieve the therapeutic objectives. CEF predictions based on CEF were evaluated using previously published models. Optimal CEF targets for an MIC of 1mg/L were calculated to achieve CEF concentrations above MIC and 4xMIC 100% of the time. External validation was conducted assessing serum albumin, CEF and CEF and comparing predicted CEF across models. Retrospective data, comprising 408 CEF from 222 patients, were analyzed to assess the probability of target attainment (PTA) based on model predicted CEF. CEF predictions based on CEF were evaluated using previously published models. Optimal CEF targets for an MIC of 1mg/L were calculated to achieve CEF concentrations above MIC and 4xMIC 100% of the time. External validation was conducted assessing serum albumin, CEF and CEF and comparing predicted CEF across models. Retrospective data, comprising 408 CEF from 222 patients, were analyzed to assess the probability of target attainment (PTA) based on model predicted CEF. Optimal CEF trough concentration targets ranged from 2.0 mg/L to 16.9 mg/L (1xMIC) and from 7.9 mg/L to 56.2 mg/L (4xMIC) across models. Some models accurately predicted CEF obtained from prospective external validation. In the retrospective cohort, PTA ranged from 94.4% to 98.7% for 1xMIC and from 66.9% to 97.3% for 4xMIC. Modeling or direct quantification of CEF may improve patient outcomes, but achieving this requires standardized analytical approaches and further research to assess the ability of published models to accurately predict CEF.