Calculation of venoarterial CO2 concentration difference

Abstract

Quantitative relationships in CO2 transport and exchange processes were combined for use as the basic components of an original mathematical model for the calculation of venoarterial blood CO2 concentration difference (v-aDCO2). This is calculated as the sum of the increment in CO2 concentration (CCO2) related to the increase in CO2 tension (delta P) from arterial to venous value at constant O2 saturation (delta CCO2/delta P) and of the increment in CO2 concentration related to the decrease in O2 saturation (delta S) from arterial to venous value at constant CO2 tension (delta CCO2/delta S). The newly developed relationships correlated well with the experimental data from which they were derived (r2 = 0.94-0.99). The results provided by the model compared remarkably well with the results of previously published measurements (r2 = 0.96-0.99). This new model allows one to overcome some of the limitations implicit in previously available methods and provides a useful tool for the assessment and monitoring of hemodynamic, metabolic, and O2-CO2 exchange patterns in whole body and regional vascular beds.

Jejunal luminal microdialysate lactate in cardiac tamponade – effect of low systemic blood flow on gut mucosa

“…These authors showed an abrupt increase in mucosal PCO 2 , dissociation of Dill-predicted venous %HbO 2 and, thereby, intestinal dysoxia at portal venous blood flow from 200 to 180 ml/min or lower, which is the same as our results. In addition, they estimated that the maximal aerobic mucosal-to-arterial PCO 2 gradient may be as high as 3.3-4.7 kPa (25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35). In the present experiment the mucosal-to-arterial PCO 2 gradient exceeded the higher estimated threshold at 30 min during the second stage of tamponade.…”

“…The mesenteric venous-arterial PCO 2 gradient (D (v-a) PCO 2 ) was calculated from corresponding blood samples for blood gas analysis (ABL 520 radiometer, Copenhagen, Denmark). We estimated regional CO 2 production by using an iterative procedure for regional arteriovenous CO 2 content difference [25] multiplied by superior mesenteric artery blood flow.…”

Computer-Assisted Analysis of the Impact of Respiratory Quotient on Blood CO2Tension and pH Changes

“…The model generated all the necessary data by simulating the progressive enrichment in CO 2 which takes place in arterial blood when it flows through the tissues and becomes venous. The Peters-Van Slyke equation for the buffer line of plasma of oxygenated blood (15), combined with the exponential Henderson-Hasselbalch equation for venous blood, was solved iteratively with a procedure related to the Newton-Raphson method for the ''root finding of a nonlinear equation'' (16,17). This made it possible to calculate the increase in plasma CO 2 concentration and the corresponding decrease in pH (ϪDpH 1 ) which were due to the increase in CO 2 tension from the arterial to the venous value.…”

“…Conversion of the increase in plasma CO 2 concentration into whole blood CO 2 concentration was allowed by the Gibbs-Donnan equilibrium relationships for combined CO 2 in blood (18). The contribution of the Haldane effect was then calculated by a complex polynomial developed from experimental data by Klocke (13,16) together with the total increase in blood CO 2 concentration. By continuing the iteration stepwise (19) it was possible to calculate the virtual values of DP and ϪDpH (DP EXP , ϪDpH EXP ) which should have been expected in the absence of the Haldane effect.…”

Proline metabolism in sepsis

“…Plasma clearances of AA were determined by using a previously described method (Clowes et al, 1980a(Clowes et al, , 1980bPearl et al, 1985;Pittiruti et al, 1985;Chiarla et al, 1988). As an additional measurement, plasma lactate was determined on a 24-hour basis together with the AA, and simultaneous arterial and mixed venous blood samples were collected for the determination of respiratory quotient (RQ) from blood gas analysis (Giovannini et al, 1993). The statistical analysis and validation of the results were performed by least-square regression analysis (Scheff6), with skewness and kurtosis control, analysis of residuals and use of a "best-fit" computer program selecting for each correlation the simplest possible regression yielding the best control of variability, based on Mallows' Cp criteria (Seber, 1977).…”