Abstract
The standard clinical coagulation assays, activated partial thromboplastin time (aPTT) and prothrombin time (PT) cannot predict thrombotic or bleeding risk. Since thrombin generation is central to haemorrhage control and when unregulated, is the likely cause of thrombosis, thrombin generation assays (TGA) have gained acceptance as “global assays” of haemostasis. These assays generate an enormous amount of data including four key thrombin parameters (lag time, maximum rate, peak and total thrombin) that may change to varying degrees over time in longitudinal studies. Currently, each thrombin parameter is averaged and presented individually in a table, bar graph or box plot; no method exists to visualize comprehensive thrombin generation data over time. To address this need, we have created a method that visualizes all four thrombin parameters simultaneously and can be animated to evaluate how thrombin generation changes over time. This method uses all thrombin parameters to intrinsically rank individuals based on their haemostatic status. The thrombin generation parameters can be derived empirically using TGA or simulated using computational models (CM). To establish the utility and diverse applicability of our method we demonstrate how warfarin therapy (CM), factor VIII prophylaxis for haemophilia A (CM), and pregnancy (TGA) affects thrombin generation over time. The method is especially suited to evaluate an individual's thrombotic and bleeding risk during “normal” processes (e.g pregnancy or aging) or during therapeutic challenges to the haemostatic system. Ultimately, our method is designed to visualize individualized patient profiles which are becoming evermore important as personalized medicine strategies become routine clinical practice.
Highlights
Thrombin generation is central to haemorrhage control and when unregulated, is the most likely cause of thrombosis
Thrombin generation assays, thromboelastography and waveform analysis have gained in popularity and become accepted as useful tools to measure essential anticoagulant cofactor found on the vascular endothelium, which can be altered to represent the amount of TM
After 3 days on warfarin, subjects S1, S2 and S3 have reduced peak and total thrombin and a reduced maximal rate of thrombin generation compared to baseline
Summary
Thrombin generation is central to haemorrhage control and when unregulated, is the most likely cause of thrombosis. The minimal information required to simulate thrombin generation is the plasma concentrations of fII, fV, fVII/fVIIa, fVIII, fIX, fX, TFPI and AT (and protein C for the ‘‘Protein C’’ model). For both models, the starting concentration of fVIIa was set to 1% of the starting fVII concentration. The models are initiated by exposing the inputs to 0.5 pM tissue factor for haemophilia simulations (Base model only) or 5 pM tissue factor for warfarin anticoagulation simulations (Base and Protein C models) Using this approach, the concentration versus time profiles for all reactants, including thrombin are determined. Thrombin generation parameters such as the lag time (time to 2 nM thrombin), the maximum rate of thrombin generation (max rate), peak thrombin and total thrombin (area under the thrombin generation profile) can be determined from the time course of thrombin generation [31]
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