Abstract: Featured is a method for assessing risk of a patient condition. Such a method includes providing criteria that relate predetermined parameters to each other, inputting observations into given criterion and relating observations of one or more acquired parameters, and converging the given criterion so as to provide an output representative of a patient condition. Such a method further includes translating the output into a visual form such as displaying the output on a display device.
Abstract: In terms of its soluble precursors, the coagulation proteome varies quantitatively among apparently healthy individuals. The significance of this variability remains obscure, in part because it is the backdrop against which the hemostatic consequences of more dramatic composition differences are studied. In this study we have defined the consequences of normal range variation of components of the coagulation proteome by using a mechanism-based computational approach that translates coagulation factor concentration data into a representation of an individual's thrombin generation potential. A novel graphical method is used to integrate standard measures that characterize thrombin generation in both empirical and computational models (e.g max rate, max level, total thrombin, time to 2 nM thrombin ('clot time')) to visualize how normal range variation in coagulation factors results in unique thrombin generation phenotypes. Unique ensembles of the 8 coagulation factors encompassing the limits of normal range variation were used as initial conditions for the computational modeling, each ensemble representing 'an individual' in a theoretical healthy population. These 'individuals' with unremarkable proteome composition was then compared to actual normal and 'abnormal' individuals, i.e. factor ensembles measured in apparently healthy individuals, actual coagulopathic individuals or artificially constructed factor ensembles representing individuals with specific factor deficiencies. A sensitivity analysis was performed to rank either individual factors or all possible pairs of factors in terms of their contribution to the overall distribution of thrombin generation phenotypes. Key findings of these analyses include: normal range variation of coagulation factors yields thrombin generation phenotypes indistinguishable from individuals with some, but not all, coagulopathies examined; coordinate variation of certain pairs of factors within their normal ranges disproportionately results in extreme thrombin generation phenotypes, implying that measurement of a smaller set of factors may be sufficient to identify individuals with aberrant thrombin generation potential despite normal coagulation proteome composition.
Abstract: The generation of proteolyzed prothrombin species by preassembled prothrombinase in phospholipid-coated glass capillaries was studied at physiologic shear rates (100–1000 s−1). The concentration of active thrombin species (α-thrombin and meizothrombin) reaches a steady state, which varies inversely with shear rate. When corrected for shear rate, steady-state levels of active thrombin species exhibit no variation and a Michaelis-Menten analysis reveals that chemistry of this reaction is invariant between open and closed systems; collectively, these data imply that variations with shear rate arise from dilutional effects. Significantly, the major products observed include nonreactive species arising from the loss of prothrombin's phospholipid binding domain (des F1 species). A numerical model developed to investigate the spatial and temporal distribution of active thrombin species within the capillary reasonably approximates the observed output of total thrombin species at different shears; it also predicts concentrations of active thrombin species in the wall region sufficient to account for observed levels of des FI species. The predominant feedback formation of nonreactive species and high levels of the primarily anticoagulant intermediate meizothrombin (∼40% of total active thrombin species) may provide a mechanism to prevent thrombus propagation downstream of a site of thrombosis or hemorrhage.
Abstract: The generation of thrombin by preassembled prothrombinase on phospholipid coated capillaries was studied under laminar flow at physiologic shear rates (100–1000 sec−1). When prothrombin (1.4μM) was perfused, thrombin levels reached a steady-state that decreased with increasing shear rate; however, generation was independent of shear rate when corrected for the velocity of the effluent. The ratio of α-thrombin to meizothrombin formed was 3:2 at shear rates of 250 and 500 sec−1. Kinetic constants determined at a shear rate of 250 sec−1 were in agreement with those obtained in closed systems, suggesting that the exchange between the bulk solution and the capillary wall region is limited by the competition between molecular diffusion of thrombin and flow convection. This results in the development of a diffusive boundary layer that spatially confines thrombin, yielding predicted concentrations of up to 1μM. The observation of extensive thrombin feedback cleavage of the phospholipid binding domain from prothrombin and meizothrombin is consistent with such high concentrations of thrombin. A flow transport model is presented for thrombin generation that estimates the development of the thrombin layer. Supported by NIH HL46703 and 5T32HL007594.
Abstract: Deterministic mathematical models of biochemical processes operate as if the empirically derived rate constants governing the dynamics are known with certainty. Our objective in this study was to explore the sensitivity of a deterministic model of blood coagulation to variations in the values of its 44 rate constants. This was accomplished for each rate constant at a given time by defining a normalized ensemble standard deviation that accounted for the sensitivity of the predicted concentration of each protein species to variation in that rate constant (from 10 to 1000% of the accepted value). A mean coefficient of variation derived from the normalized ensemble standard deviation values for all protein species was defined to quantify the overall variation introduced into the model's predictive capacity at that time by the assumed uncertainty in that rate constant. A time-average value of the coefficient of variation over the 20-min simulation for each rate constant was then used to rank rate constants. The model's predictive capacity is particularly sensitive (50% of the aggregate variation) to uncertainty in five rate constants involved in the regulation of the formation and function of the factor VIIa–tissue factor complex. Therefore, our analysis has identified specific rate constants to which the predictive capability of this model is most sensitive and thus where improvements in measurement accuracy will yield the greatest increase in predictive capability.