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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., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background and Objective: Activated clotting time (ACT) is a point-of-care test used to monitor the effect of unfractionated heparin (UFH) during cardiopulmonary bypass (CPB). This test sometimes returns aberrant values, which can lead to the administration of an inappropriate dosing regimen. The development of a population-robust K-PD model of UFH could allow the individualisation and automation of UFH therapy during CPB., Methods: We conducted a prospective observational study to collect ACT measurements from patients undergoing surgery using CPB. The ACT data were split into a development and validation cohort. The development cohort was used to estimate a standard and robust population K-PD model characterised by a residual error following a normal distribution and student's t-distribution. The ACT prediction performance using Bayesian estimates of individual K-PD parameters was evaluated by comparing predicted versus observed ACTs. Using estimates of the robust K-PD model, a Bayesian individualisation strategy to automate UFH administration was proposed and evaluated using Monte Carlo simulations., Results: A total of 295 patients were included in the study, and 1561 ACTs were collected. In patients without outlier values, Bayesian estimates (based on four ACT measurements) from both standard and robust K-PD models had similar performances, with a median prediction bias close to 0 s. In patients with outlier measurements, the use of the robust K-PD model greatly improved the prediction bias and root-mean-square error (RMSE), with a mean prediction bias of 3.25 s, IQR = [-19.9; 46.03] versus -86 s IQR = [-135.7; -63.8] for the standard model. Monte Carlo simulations showed that the robust Bayesian individualisation strategy allowed the ACT to be maintained above the target using only two to three ACT measurements., Conclusions: The use of a robust K-PD model reduced prediction bias and RMSE in patients with outlier ACT measurements. The Bayesian individualisation strategy using robust estimates of individual parameters may help automate UFH dosing regimens. Proper clinical validation is warranted before its use in daily clinical practice., Competing Interests: Declaration of Competing Interest There are no competing interests to declare., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Unfractionated heparin (UFH) is a widely used anticoagulant that possess numerous properties including anti-inflammatory, anti-viral, anti-angiogenesis, and anti-metastatic effects. The effect of this drug was evaluated on the podocyte, an important actor of the glomerular filtration. Using a functional approach, we demonstrate that heparin treatment leads to a functional podocyte perturbation characterized by the increase of podocyte monolayer permeability. This effect is enhanced with time of exposure. Proteomic study reveals that heparin down regulate focal adhesion and cytoskeletal protein expressions as well as the synthesis of glomerular basement membrane components. This study clearly demonstrates that UFH may affect podocyte function by altering cytoskeleton organization, cell-cell contacts and cell attachment., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background. Unfractionated heparin is administered in patients undergoing veno-arterial extracorporeal membrane oxygenation (VA-ECMO). Anticoagulation monitoring is recommended, with an anti-activated factor X (anti-Xa) targeting 0.3 to 0.7 IU/mL. Owing to heparin's heterogeneous pharmacokinetic properties, anti-Xa is unpredictable, generating a challenge in anticoagulation practices. The aim of this study was to build a pharmacokinetic model of heparin accounting for potential confounders, and derive an optimized dosing regimen for a given anti-Xa target. Methods. Adult patients undergoing VA-ECMO were included between January 2020 and June 2021. Anticoagulation was managed with an initial 100 IU/kg heparin loading dose followed by a continuous infusion targeting 0.2 to 0.7 IU/mL anti-Xa. The data were split into model development and model validation cohorts. Statistical analysis was performed using a nonlinear mixed effects modeling population approach. Model-based simulations were performed to develop an optimized dosing regimen targeting the desired anti-Xa. Results. A total of 74 patients were included, with 1703 anti-Xa observations. A single-compartment model best fitted the data. Interpatient variability for distribution volume was best explained by body weight, C-reactive protein and ECMO indication (post-cardiotomy shock or medical cardiogenic shock), and interpatient variability for elimination clearance was best explained by serum creatinine and C-reactive protein. Simulations using the optimized regimen according to these covariates showed accurate anti-Xa target attainment. Conclusion. In adult patients on VA-ECMO, heparin's effect increased with serum creatinine and medical indication, whereas it decreased with body weight and systemic inflammation. We propose an optimized dosing regimen accounting for key covariates, capable of accurately predicting a given anti-Xa target. [ABSTRACT FROM AUTHOR]