A new theoretical model of apparent blood viscosity with the Fåhræus-Lindqvist effect using informational entropy-based approach.

The behavior of blood viscosity is influenced by several physical factors, particularly hematocrit levels and vessel diameter. For a fixed hematocrit, apparent blood viscosity decreases with tube diameters in the range of 9μm to 1000μm, a phenomenon known as the Fåhræus-Lindqvist (FL) effect. Almost all existing models of the apparent blood viscosity are empirically proposed describing that viscosity exponentially increases with hematocrit. To predict apparent blood viscosity, this study proposes a new model derived from an iterative approach based on Einstein's complete formula by considering different blood samples with varying RBC levels. To predict model parameters, this work proposes the informational entropy approach based on a probabilistic concept, which is new in this field. The model generalizes several existing models and successfully predicts the FL effects. We validate its accuracy against a wide range of experimental data sets (from infants to adults, along with the original data set of Fåhræus-Lindqvist) and perform a comparative analysis with existing models. To illustrate the model performance the error analysis has been carried out. The results show that our model offers a better prediction across a wide range of considered data sets and existing models. The model is tested for predicting RBC transport efficiency and analyzing vessel oxygen transport rates and the results are found satisfactory. Apart from these, a new entropy theory based computational methodology is proposed allowing flexibility in adapting the model to different data sets. The suggested hybrid methodology can be used for future similar research.