Factors Influencing Unfractionated Heparin Pharmacokinetics and Pharmacodynamics During a Cardiopulmonary Bypass.

BACKGROUND: Unfractionated heparin (UFH) is commonly used during cardiac surgery with a cardiopulmonary bypass to prevent blood clotting. However, empirical administration of UFH leads to variable responses. Pharmacokinetic and pharmacodynamic modeling can be used to optimize UFH dosing and perform real-time individualization. In previous studies, many factors that could influence UFH pharmacokinetics/pharmacodynamics had not been taken into account such as hemodilution or the type of UFH. Few covariates were identified probably owing to a lack of statistical power. This study aims to address these limitations through a meta-analysis of individual data from two studies. METHODS: An individual patient data meta-analysis was conducted using data from two single-center prospective observational studies, where different UFH types were used for anticoagulation. A pharmacodynamic/pharmacodynamic model of UFH was developed using a non-linear mixed-effects approach. Time-varying covariates such as hemodilution and fluid infusions during a cardiopulmonary bypass were considered. RESULTS: Activities of UFH's anti-activated factor/anti-thrombin were best described by a two-compartment model. Unfractionated heparin clearance was influenced by body weight and the specific UFH type. Volume of distribution was influenced by body weight and pre-operative fibrinogen levels. Pharmacodynamic data followed a log-linear model, accounting for the effect of hemodilution and the pre-operative fibrinogen level. Equations were derived from the model to personalize UFH dosing based on the targeted activated clotting time level and patient covariates. CONCLUSIONS: The population model effectively characterized UFH's pharmacokinetics/pharmacodynamics in cardiopulmonary bypass patients. This meta-analysis incorporated new covariates related to UFH's pharmacokinetics/pharmacodynamics, enabling personalized dosing regimens. The proposed model holds potential for individualization using a Bayesian estimation.

Development of a Bayesian estimation tool to determine the optimal duration of apixaban discontinuation before a high-bleeding risk procedure.

Apixaban is a direct oral anticoagulant (DOAC). Many studies have shown that it shows high pharmacokinetic interindividual and intraindividual variability (IIV). The risk of hemorrhage is a major concern for patients treated with apixaban to undergo an operation or an invasive procedure. Due to this large pharmacokinetic variability, the current recommendations concerning the optimal duration of apixaban discontinuation before a high-bleeding risk procedure concern the general population and not a specific patient. The aim of this study was (1) to investigate by simulation the distribution of decay time of apixaban concentration and (2) to develop and validate an easy-to-use web tool to estimate the individual decay time of apixaban in a "real-life" situation. A systematic review of the literature was conducted to select the relevant pharmacokinetic models for the creation of the web tool. For each model, pharmacokinetic profiles were simulated and the time to reach concentrations below the threshold of 30 ng/ml (T30) was calculated. One of the selected models was chosen to perform a Bayesian estimation and predict the optimal duration of apixaban discontinuation before a high-bleeding risk procedure. All these results were concatenated into the PrevBleed application developed with the R Shiny package.