Alexander Y Mitrophanov1, Fania Szlam, Roman M Sniecinski, Jerrold H Levy, Jaques Reifman. 1. From the *DoD Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, US Army Medical Research and Materiel Command, Fort Detrick, Maryland; †Department of Anesthesiology, Emory University School of Medicine, Atlanta, Georgia; and Departments of ‡ Anesthesiology and §Surgery, Duke University School of Medicine, Durham, North Carolina.
Abstract
BACKGROUND: The use of prothrombin complex concentrates in trauma- and surgery-induced coagulopathy is complicated by the possibility of thromboembolic events. To explore the effects of these agents on thrombin generation (TG), we investigated combinations of coagulation factors equivalent to 3- and 4-factor prothrombin complex concentrates with and without added antithrombin (AT), as well as recombinant factor VIIa (rFVIIa), in a dilutional model. These data were then used to develop a computational model to test whether such a model could predict the TG profiles of these agents used to treat dilutional coagulopathy. METHODS: We measured TG in plasma collected from 10 healthy volunteers using Calibrated Automated Thrombogram. TG measurements were performed in undiluted plasma, 3-fold saline-diluted plasma, and diluted plasma supplemented with the following factors: rFVIIa (group rFVIIa); factors (F)II, FIX, FX, and AT (group "combination of coagulation factors" [CCF]-AT); or FII, FVII, FIX, and FX (group CCF-FVII). We extended an existing computational model of TG to include additional reactions that impact the Calibrated Automated Thrombogram readout. We developed and applied a computational strategy to train the model using only a subset of the obtained TG data and used the remaining data for model validation. RESULTS: rFVIIa decreased lag time and the time to thrombin peak generation beyond their predilution levels (P < 0.001) but did not restore normal thrombin peak height (P < 0.001). CCF-FVII supplementation decreased lag time (P = 0.034) and thrombin peak time (P < 0.001) and increased both peak height (P < 0.001) and endogenous thrombin potential (P = 0.055) beyond their predilution levels. CCF-AT supplementation in diluted plasma resulted in an improvement in TG without causing the exaggerated effects of rFVIIa and CCF-FVII supplementation. The differences between the effects of CCF-AT and supplementation with rFVIIa and CCF-FVII were significant for lag time (P < 0.001 and P = 0.005, respectively), time to thrombin peak (P < 0.001 and P = 0.004, respectively), velocity index (P < 0.001 and P = 0.019, respectively), thrombin peak height (P < 0.001 for both comparisons), and endogenous thrombin potential (P = 0.034 and P = 0.019, respectively). The computational model generated subject-specific predictions and identified typical patterns of TG improvement. CONCLUSIONS: In this study of the effects of hemodilution, CCF-AT supplementation improved the dilution-impaired plasma TG potential in a more balanced way than either rFVIIa alone or CCF-FVII supplementation. Predictive computational modeling can guide plasma dilution/supplementation experiments.
BACKGROUND: The use of prothrombin complex concentrates in trauma- and surgery-induced coagulopathy is complicated by the possibility of thromboembolic events. To explore the effects of these agents on thrombin generation (TG), we investigated combinations of coagulation factors equivalent to 3- and 4-factor prothrombin complex concentrates with and without added antithrombin (AT), as well as recombinant factor VIIa (rFVIIa), in a dilutional model. These data were then used to develop a computational model to test whether such a model could predict the TG profiles of these agents used to treat dilutional coagulopathy. METHODS: We measured TG in plasma collected from 10 healthy volunteers using Calibrated Automated Thrombogram. TG measurements were performed in undiluted plasma, 3-fold saline-diluted plasma, and diluted plasma supplemented with the following factors: rFVIIa (group rFVIIa); factors (F)II, FIX, FX, and AT (group "combination of coagulation factors" [CCF]-AT); or FII, FVII, FIX, and FX (group CCF-FVII). We extended an existing computational model of TG to include additional reactions that impact the Calibrated Automated Thrombogram readout. We developed and applied a computational strategy to train the model using only a subset of the obtained TG data and used the remaining data for model validation. RESULTS: rFVIIa decreased lag time and the time to thrombin peak generation beyond their predilution levels (P < 0.001) but did not restore normal thrombin peak height (P < 0.001). CCF-FVII supplementation decreased lag time (P = 0.034) and thrombin peak time (P < 0.001) and increased both peak height (P < 0.001) and endogenous thrombin potential (P = 0.055) beyond their predilution levels. CCF-AT supplementation in diluted plasma resulted in an improvement in TG without causing the exaggerated effects of rFVIIa and CCF-FVII supplementation. The differences between the effects of CCF-AT and supplementation with rFVIIa and CCF-FVII were significant for lag time (P < 0.001 and P = 0.005, respectively), time to thrombin peak (P < 0.001 and P = 0.004, respectively), velocity index (P < 0.001 and P = 0.019, respectively), thrombin peak height (P < 0.001 for both comparisons), and endogenous thrombin potential (P = 0.034 and P = 0.019, respectively). The computational model generated subject-specific predictions and identified typical patterns of TG improvement. CONCLUSIONS: In this study of the effects of hemodilution, CCF-AT supplementation improved the dilution-impaired plasma TG potential in a more balanced way than either rFVIIa alone or CCF-FVII supplementation. Predictive computational modeling can guide plasma dilution/supplementation experiments.
Authors: Vijay Govindarajan; Shu Zhu; Ruizhi Li; Yichen Lu; Scott L Diamond; Jaques Reifman; Alexander Y Mitrophanov Journal: Biophys J Date: 2018-02-27 Impact factor: 4.033
Authors: Herbert Schöchl; Oliver Grottke; Ken Sutor; Kieron Dony; Martin Schreiber; Marco Ranucci; Peter W Collins Journal: Anesth Analg Date: 2017-11 Impact factor: 5.108