Factors Influencing Unfractionated Heparin Pharmacokinetics and Pharmacodynamics During a Cardiopulmonary Bypass.
Journal
Clinical pharmacokinetics
ISSN: 1179-1926
Titre abrégé: Clin Pharmacokinet
Pays: Switzerland
ID NLM: 7606849
Informations de publication
Date de publication:
02 Jan 2024
02 Jan 2024
Historique:
accepted:
07
12
2023
medline:
4
1
2024
pubmed:
4
1
2024
entrez:
3
1
2024
Statut:
aheadofprint
Résumé
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. 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. 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. 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.
Sections du résumé
BACKGROUND
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
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
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
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.
Identifiants
pubmed: 38169065
doi: 10.1007/s40262-023-01334-3
pii: 10.1007/s40262-023-01334-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.
Références
Verstraete M. Pharmacotherapeutic aspects of unfractionated and low molecular weight heparins. Drugs. 1990;40(4):498–530. https://doi.org/10.2165/00003495-199040040-00003 .
doi: 10.2165/00003495-199040040-00003
pubmed: 1964634
Hirsh J, Raschke R, Warkentin TE, Dalen JE, Deykin D, Poller L. Heparin: mechanism of action, pharmacokinetics, dosing considerations, monitoring, efficacy, and safety. Chest. 1995;108(4 Suppl.):258S-S275. https://doi.org/10.1378/chest.108.4_supplement.258s .
doi: 10.1378/chest.108.4_supplement.258s
pubmed: 7555181
Hemker HC. A century of heparin: past, present and future. J Thromb Haemost. 2016;14(12):2329–38. https://doi.org/10.1111/jth.13555 . (Epub 2016 Dec 16).
doi: 10.1111/jth.13555
pubmed: 27862941
Bray B, Lane DA, Freyssinet JM, Pejler G, Lindahl U. Anti-thrombin activities of heparin. Effect of saccharide chain length on thrombin inhibition by heparin cofactor II and by antithrombin. Biochem J. 1989;262(1):225–32. https://doi.org/10.1042/bj2620225 .
doi: 10.1042/bj2620225
pubmed: 2818566
pmcid: 1133251
Gerotziafas GT, Petropoulou AD, Verdy E, Samama MM, Elalamy I. Effect of the anti-factor Xa and anti-factor IIa activities of low-molecular-weight heparins upon the phases of thrombin generation. J Thromb Haemost. 2007;5(5):955–62. https://doi.org/10.1111/j.1538-7836.2007.02477.x.Erratum.In:JThrombHaemost.2007Jun;5(6):1343 .
doi: 10.1111/j.1538-7836.2007.02477.x.Erratum.In:JThrombHaemost.2007Jun;5(6):1343
pubmed: 17461929
Machin D, Devine P. The effect of temperature and aprotinin during cardiopulmonary bypass on three different methods of activated clotting time measurement. J Extra Corpor Technol. 2005;37(3):265–71.
doi: 10.1051/ject/200537265
pubmed: 16350378
pmcid: 4680783
Hong X, Shan PR, Huang WJ, Zhu QL, Xiao FY, et al. Influence of body mass index on the activated clotting time under weight-based heparin dose. J Clin Lab Anal. 2016;30(2):108–13. https://doi.org/10.1002/jcla.21823 . (Epub 2014 Nov 25).
doi: 10.1002/jcla.21823
pubmed: 25425223
Inoue M, Hirose Y, Gamou M, Goto M. Effect of hemodilution with dextran and albumin on activated clotting time (ACT). Masui. 1997;46(6):809–12 (Japanese).
pubmed: 9223886
Azarnoush K, Pereira B, Lebreton A, Zenut MC, Chenaf C, Vedat E, et al. Are all heparins safe for on-pump heart surgery? Expert Opin Drug Saf. 2016;15(7):897–901. https://doi.org/10.1080/14740338.2016.1177020 . (Epub 2016 May 3).
doi: 10.1080/14740338.2016.1177020
pubmed: 27080923
Dyck L, Friesen RM. Do different heparin brands influence activated clotting times? J Extra Corpor Technol. 1998;30(2):73–6.
doi: 10.1051/ject/199830273
pubmed: 10182116
Subramaniam P, Skillington P, Tatoulis J. Heparin-rebound in the early postoperative phase following cardiopulmonary bypass. Aust N Z J Surg. 1995;65(5):331–3. https://doi.org/10.1111/j.1445-2197.1995.tb00648.x .
doi: 10.1111/j.1445-2197.1995.tb00648.x
pubmed: 7741676
Delavenne X, Ollier E, Chollet S, Sandri F, Lanoiselée J, Hodin S, et al. Pharmacokinetic/pharmacodynamic model for unfractionated heparin dosing during cardiopulmonary bypass. Br J Anaesth. 2017;118(5):705–12. https://doi.org/10.1093/bja/aex044 .
doi: 10.1093/bja/aex044
pubmed: 28510738
Jia Z, Tian G, Ren Y, Sun Z, Lu W, Hou X. Pharmacokinetic model of unfractionated heparin during and after cardiopulmonary bypass in cardiac surgery. J Transl Med. 2015;13:45. https://doi.org/10.1186/s12967-015-0404-5 .
doi: 10.1186/s12967-015-0404-5
pubmed: 25638272
pmcid: 4326208
Ayral G, Si Abdallah JF, Magnard C, Chauvin J. A novel method based on unbiased correlations tests for covariate selection in nonlinear mixed effects models: the COSSAC approach. CPT Pharmacometr Syst Pharmacol. 2021;10(4):318–29. https://doi.org/10.1002/psp4.12612 .
doi: 10.1002/psp4.12612
Prague M, Lavielle M. SAMBA: A novel method for fast automatic model building in nonlinear mixed-effects models. CPT Pharmacometr Syst Pharmacol. 2022;11(2):161–72. https://doi.org/10.1002/psp4.12742 . (Epub 2022 Feb 1).
doi: 10.1002/psp4.12742
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31–41. https://doi.org/10.1159/000180580 .
doi: 10.1159/000180580
pubmed: 1244564
Monolix 2019 User guide. Version 2021. http://monolix.lixoft.com/single-page/ . Accessed 21 Dec 2023.
Ito K, Murphy D. Application of ggplot2 to pharmacometric graphics. CPT Pharmacometr Syst Pharmacol. 2013;2(10): e79. https://doi.org/10.1038/psp.2013.56 .
doi: 10.1038/psp.2013.56
R: the R Project for Statistical Computing. https://www.r-project.org/ . Accessed 25 Jan 2023.
Chaux R, Lanoiselée J, Magand C, Zufferey P, Delavenne X, Ollier E. Robust K-PD model for activated clotting time prediction and UFH dose individualisation during cardiopulmonary bypass. Comput Methods Programs Biomed. 2022;214: 106553. https://doi.org/10.1016/j.cmpb.2021.106553 . (Epub 2021 Nov 27).
doi: 10.1016/j.cmpb.2021.106553
pubmed: 34883383
Al-Sallami H, Newall F, Monagle P, Ignjatovic V, Cranswick N, Duffull S. Development of a population pharmacokinetic-pharmacodynamic model of a single bolus dose of unfractionated heparin in paediatric patients. Br J Clin Pharmacol. 2016;82(1):178–84.
doi: 10.1111/bcp.12930
pubmed: 26972703
pmcid: 4917811
Salem AM, Niu T, Li C, Moffett BS, Ivaturi V, Gopalakrishnan M. Reassessing the pediatric dosing recommendations for unfractionated heparin using real-world data: a pharmacokinetic-pharmacodynamic modeling approach. J Clin Pharmacol. 2022;62(6):733–46.
doi: 10.1002/jcph.2007
pubmed: 34816442
Grimaud M, Urien S, Borgel D, et al. Abstract P-114: pharmacokinetic analysis of unfractionated heparin in critically ill children during extracorporeal membrane oxygenation: do we achieve the target? Pediatr Crit Care Med. 2018;19(6S):83–4.
doi: 10.1097/01.pcc.0000537571.01928.c4
Mohri H, Ohkubo T. Fibrinogen binds to heparin: the relationship of the binding of other adhesive proteins to heparin. Arch Biochem Biophys. 1993;303(1):27–31. https://doi.org/10.1006/abbi.1993.1251 .
doi: 10.1006/abbi.1993.1251
pubmed: 7683861
Yakovlev S, Gorlatov S, Ingham K, Medved L. Interaction of fibrin(ogen) with heparin: further characterization and localization of the heparin-binding site. Biochemistry. 2003;42(25):7709–16. https://doi.org/10.1021/bi0344073 .
doi: 10.1021/bi0344073
pubmed: 12820880
Mouton C, Calderon J, Janvier G, Vergnes MC. Dextran sulfate included in factor Xa assay reagent overestimates heparin activity in patients after heparin reversal by protamine. Thromb Res. 2003;111(4–5):273–9. https://doi.org/10.1016/j.thromres.2003.09.014 .
doi: 10.1016/j.thromres.2003.09.014
pubmed: 14693175
Ori A, Wilkinson MC, Fernig DG. A systems biology approach for the investigation of the heparin/heparan sulfate interactome. J Biol Chem. 2011;286(22):19892–904. https://doi.org/10.1074/jbc.M111.228114 . (Epub 2011 Mar 30).
doi: 10.1074/jbc.M111.228114
pubmed: 21454685
pmcid: 3103365
Levy JH, Connors JM. Heparin resistance: clinical perspectives and management strategies. N Engl J Med. 2021;385(9):826–32. https://doi.org/10.1056/NEJMra2104091 .
doi: 10.1056/NEJMra2104091
pubmed: 34437785
Giuliani R, Szwarcer E, Martinez Aquino E, Palumbo G. Fibrin-dependent fibrinolytic activity during extracorporeal circulation. Thromb Res. 1991;61(4):369–73. https://doi.org/10.1016/0049-3848(91)90650-l .
doi: 10.1016/0049-3848(91)90650-l
pubmed: 1905846
Despotis GJ, Joist JH. Anticoagulation and anticoagulation reversal with cardiac surgery involving cardiopulmonary bypass: an update. J Cardiothorac Vasc Anesth. 1999;13(4 Suppl. 1):18–29 (discussion 36–7).
doi: 10.1016/S1053-0770(21)00594-2
pubmed: 10468245
Cohen EJ. J Extra Corpor Technol. 1980;12:139.
doi: 10.1051/ject/1980126139
Amiral J, Amiral C, Dunois C. Optimization of heparin monitoring with anti-FXa assays and the impact of dextran sulfate for measuring all drug activity. Biomedicines. 2021;9(6):700. https://doi.org/10.3390/biomedicines9060700 .
doi: 10.3390/biomedicines9060700
pubmed: 34205548
pmcid: 8235539
Palmer K, Ridgway T, Al-Rawi O, Poullis M. Heparin therapy during extracorporeal circulation: deriving an optimal activated clotting time during cardiopulmonary bypass for isolated coronary artery bypass grafting. J Extra Corpor Technol. 2012;44(3):145–50.
doi: 10.1051/ject/201244145
pubmed: 23198395
pmcid: 4557526
Authors/Task Force Members; Kunst G, Milojevic M, Boer C, De Somer FMJJ, Gudbjartsson T, van den Goor J, et al.; EACTS/EACTA/EBCP Committee Reviewers; Alston P, Fitzgerald D, Nikolic A, Onorati F, Rasmussen BS, Svenmarker S. 2019 EACTS/EACTA/EBCP guidelines on cardiopulmonary bypass in adult cardiac surgery. Br J Anaesth. 2019;123(6):713–57. https://doi.org/10.1016/j.bja.2019.09.012 (Epub 2019 Oct 2).