This paper proposes an algorithm that estimates blood viscosity during cardiopulmonary bypass (CPB) and validates its application in clinical cases. The proposed algorithm involves adjustable parameters based on the oxygenator and fluid types and estimates blood viscosity based on pressure-flow characteristics of the fluid perfusing through the oxygenator. This novel nonlinear model requires four parameters that were derived by in vitro experiments. The results estimated by the proposed method were then compared with a conventional linear model to demonstrate the former's optimal curve fitting. The viscosity (η) estimated using the proposed algorithm and the viscosity (η) measured using a viscometer were compared for 20 patients who underwent mildly hypothermic CPB. The developed system was applied to ten patients, and η was recorded for comparisons with hematocrit and blood temperature. The residual sum of squares between the two curve fittings confirmed the significant difference, with p < 0.001. η and η showed a very strong correlation with R = 0.9537 and p < 0.001. Regarding the mean coefficient of determination for all cases, the hematocrit and temperature showed weak correlations at 0.33 ± 0.14 and 0.22 ± 0.21, respectively. For CPB measurements of all cases, η was more than 98% distributed in the range from 1 to 3 mPa⋅s. This new system for estimating viscosity may be useful for detecting various viscosity-related effects that may occur during CPB.

During cardiopulmonary bypass (CPB), blood viscosity conspicuously increases and decreases due to changes in hematocrit and blood temperature. Nevertheless, blood viscosity is typically not evaluated, because there is no technology that can provide simple, continuous, noncontact monitoring. We modeled the pressure-flow characteristics of an oxygenator in a previous study, and in that study we quantified the influence of viscosity on oxygenator function. The pressure-flow monitoring information in the oxygenator is derived from our model and enables the estimation of viscosity. The viscosity estimation method was proposed and investigated in an in vitro experiment. Three samples of whole bovine blood with different hematocrit levels (21.8, 31.0, and 39.8%) were prepared and perfused into the oxygenator. As the temperature changed from 37°C to 27°C, the mean inlet pressure (P ) and outlet pressure (P ) of the oxygenator and the flow (Q) and viscosity of the blood were measured. The estimated viscosity was calculated from the pressure gradient (ΔP = P - P ) and Q and was compared to the measured blood viscosity. A strong correlation was found between the two methods for all samples. Bland-Altman analysis revealed a mean bias of -0.0263 mPa.s, a standard deviation of 0.071 mPa.s, limits of agreement of -0.114-0.166 mPa.s, and a percent error of 5%. Therefore, this method is considered compatible with the torsional oscillation viscometer that has plus or minus 5% measurement accuracy. Our study offers the possibility of continuously estimating blood viscosity during CPB.

The need for the estimation of the number of microbubbles (MBs) in cardiopulmonary bypass surgery has been recognized among surgeons to avoid postoperative neurological complications. MBs that exceed the diameter of human capillaries may cause endothelial disruption as well as microvascular obstructions that block posterior capillary blood flow. In this paper, we analyzed the relationship between the number of microbubbles generated and four circulation factors, i.e., intraoperative suction flow rate, venous reservoir level, continuous blood viscosity and perfusion flow rate in cardiopulmonary bypass, and proposed a neural-networked model to estimate the number of microbubbles with the factors. Model parameters were determined in a machine-learning manner using experimental data with bovine blood as the perfusate. The estimation accuracy of the model, assessed by tenfold cross-validation, demonstrated that the number of MBs can be estimated with a determinant coefficient R2 = 0.9328 (p < 0.001). A significant increase in the residual error was found when each of four factors was excluded from the contributory variables. The study demonstrated the importance of four circulation factors in the prediction of the number of MBs and its capacity to eliminate potential postsurgical complication risks.

No abstract

In this paper, we developed a model that uses pressure-flow monitoring information in the oxygenator to estimate viscosity of human blood. The comparison between estimated viscosity (ηe) and measured viscosity (η) was assessed in 16 patients who underwent cardiac surgery using mild hypothermia cardiopulmonary bypass (CPB). After initiation of CPB, ηe was recorded at three periods: post-establishment of total CPB, post-aortic cross-clamp, and post-declamp. During the same period, blood samples were collected from the circuit and η was measured with a torsional oscillation viscometer. The ηe was plotted as a function of η and the systematic errors and compatibility between two methods were assessed using Bland-Altman analysis. The parameters ηe and η were very strongly correlated at all points (R(2)=0.9616, p<;0.001). The Bland-Altman analysis revealed a mean bias of -0.001 mPas, a standard deviation of 0.03 mPas, limits of agreement of -0.06 mPas to 0.06 mPas, and a percent error of 3.3%. There was no fixed bias or proportion bias for the viscosity. As this method estimates blood viscosity with good precision during CPB continuously, it may be helpful for clinical perfusion management.

No abstract

We proposed a blood viscosity estimation method based on pressure-flow characteristics of oxygenators used during cardiopulmonary bypass (CPB) in a previous study that showed the estimated viscosity to correlate well with the measured viscosity. However, the determination of the parameters included in the method required the use of blood, thereby leading to high cost of calibration. Therefore, in this study we propose a new method to monitor blood viscosity, which approximates the pressure-flow characteristics of blood considered as a non-Newtonian fluid with characteristics of a Newtonian fluid by using the parameters derived from glycerin solution to enable ease of acquisition. Because parameters used in the estimation method are based on fluid types, bovine blood parameters were used to calculate estimated viscosity (ηe), and glycerin parameters were used to estimate deemed viscosity (ηdeem). Three samples of whole bovine blood with different hematocrit levels (21.8%, 31.0%, and 39.8%) were prepared and perfused into the oxygenator. As the temperature changed from 37 °C to 27 °C, the oxygenator mean inlet pressure and outlet pressure were recorded for flows of 2 L/min and 4 L/min, and the viscosity was estimated. The value of deemed viscosity calculated with the glycerin parameters was lower than estimated viscosity calculated with bovine blood parameters by 20-33% at 21.8% hematocrit, 12-27% at 31.0% hematocrit, and 10-15% at 39.8% hematocrit. Furthermore, deemed viscosity was lower than estimated viscosity by 10-30% at 2 L/min and 30-40% at 4 L/min. Nevertheless, estimated and deemed viscosities varied with a similar slope. Therefore, this shows that deemed viscosity achieved using glycerin parameters may be capable of successfully monitoring relative viscosity changes of blood in a perfusing oxygenator.

Distal perfusion during open distal anastomosis reduced kidney and liver injury after thoracic aortic surgery despite an increased body temperature of up to 28°C. This strategy may be useful to prevent AKI, liver dysfunction, the need for hemodialysis and multiple organ failure and could improve mid-term results.