AUTHOR=Mosing Martina , Böhm Stephan H. , Rasis Anthea , Hoosgood Giselle , Auer Ulrike , Tusman Gerardo , Bettschart-Wolfensberger Regula , Schramel Johannes P. TITLE=Physiologic Factors Influencing the Arterial-To-End-Tidal CO2 Difference and the Alveolar Dead Space Fraction in Spontaneously Breathing Anesthetised Horses JOURNAL=Frontiers in Veterinary Science VOLUME=5 YEAR=2018 URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2018.00058 DOI=10.3389/fvets.2018.00058 ISSN=2297-1769 ABSTRACT=

The arterial to end-tidal CO₂ difference (P_(a-ET)CO₂) and alveolar dead space fraction (VDalv_frac = P_(a-ET)CO₂/PaCO₂), are used to estimate Enghoff’s “pulmonary dead space” (V/Q_Eng), a factor which is also influenced by venous admixture and other pulmonary perfusion abnormalities and thus is not just a measure of dead space as the name suggests. The aim of this experimental study was to evaluate which factors influence these CO₂ indices in anesthetized spontaneously breathing horses. Six healthy adult horses were anesthetized in dorsal recumbency breathing spontaneously for 3 h. Data to calculate the CO₂ indices (response variables) and dead space variables were measured every 30 min. Bohr’s physiological and alveolar dead space variables, cardiac output (CO), mean pulmonary pressure (MPP), venous admixture (Q˙s/Q˙t), airway dead space, tidal volume, oxygen consumption, and slope III of the volumetric capnogram were evaluated (explanatory variables). Univariate Pearson correlation was first explored for both CO₂ indices before V/Q_Eng and the explanatory variables with rho were reported. Multiple linear regression analysis was performed on P_(a-ET)CO₂ and VDalv_frac assessing which explanatory variables best explained the variance in each response. The simplest, best-fit model was selected based on the maximum adjusted R² and smallest Mallow’s p (C_p). The R² of the selected model, representing how much of the variance in the response could be explained by the selected variables, was reported. The highest correlation was found with the alveolar part of V/Q_Eng to alveolar tidal volume ratio for both, P_(a-ET)CO₂ (r = 0.899) and VDalv_frac (r = 0.938). Venous admixture and CO best explained P_(a-ET)CO₂ (R² = 0.752; C_p = 4.372) and VDalv_frac (R² = 0.711; C_p = 9.915). Adding MPP (P_(a-ET)CO₂) and airway dead space (VDalv_frac) to the models improved them only marginally. No “real” dead space variables from Bohr’s equation contributed to the explanation of the variance of the two CO₂ indices. P_(a-ET)CO₂ and VDalv_frac were closely associated with the alveolar part of V/Q_Eng and as such, were also influenced by variables representing a dysfunctional pulmonary perfusion. Neither P_(a-ET)CO₂ nor VDalv_frac should be considered pulmonary dead space, but used as global indices of V/Q mismatching under the described conditions.