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首页> 外文期刊>Frontiers in Veterinary Science >Physiologic Factors Influencing the Arterial-To-End-Tidal CO2 Difference and the Alveolar Dead Space Fraction in Spontaneously Breathing Anesthetised Horses
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Physiologic Factors Influencing the Arterial-To-End-Tidal CO2 Difference and the Alveolar Dead Space Fraction in Spontaneously Breathing Anesthetised Horses

机译:自发呼吸麻醉马的动脉潮气末CO2差异和肺泡死区分数的生理因素

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The arterial to end-tidal CO2 difference (P(a-ET)CO2) and alveolar dead space fraction (VDalvfrac=P(a-ET)CO2/PaCO2), are used to estimate Enghoff’s ‘pulmonary dead space’ (V/QEng), 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 anaesthetised spontaneously breathing horses. Six healthy adult horses were anaesthetised in dorsal recumbency breathing spontaneously for 3 hours. Data to calculate the CO2 indices (response variables) and dead space variables were measured every 30 minutes. 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/QEng and the explanatory variables with rho were reported. Multiple linear regression analysis was performed on P(a-ET)CO2 and VDalvfrac 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 (Cp). 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/QEng to alveolar tidal volume ratio for both, P(a-ET)CO2 (r = 0.899) and VDalvfrac (r = 0.938). Venous admixture and CO best explained P(a-ET)CO2 (R2 = 0.752; Cp = 4.372) and VDalvfrac (R2 = 0.711; Cp = 9.915). Adding MPP (P(a-ET)CO2) and airway dead space (VDalvfrac) 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 VDalvfrac were closely associated with the alveolar part of V/QEng and as such, were also influenced by variables representing a dysfunctional pulmonary perfusion. Neither P(a-ET)CO2 nor VDalvfrac should be considered pulmonary dead space, but used as global indices of V/Q mismatching under the described conditions.
机译:动脉到潮气末的CO2差(P(a-ET)CO2)和肺泡死腔分数(VDalvfrac = P(a-ET)CO2 / PaCO2)用于估计Enghoff的“肺死腔”(V / QEng ),这也是受静脉混合气体和其他肺灌注异常影响的因素,因此,顾名思义,它不仅是死腔的量度。本实验研究的目的是评估哪些因素影响麻醉的自发呼吸马中的这些CO2指数。六只健康的成年马在背卧位自发麻醉3小时。每30分钟测量一次用于计算CO2指数(响应变量)和死区变量的数据。玻尔的生理和肺泡死腔变量,心输出量(CO),平均肺压(MPP),静脉混合气(“ Q”?s /“ Q”?t),气道死腔,潮气量,耗氧量和斜率III评估了容积二氧化碳图(解释变量)。在V / QEng和报道有rho的解释变量之前,首先探索了两个CO2指数的单变量Pearson相关性。对P(a-ET)CO2和VDalvfrac进行了多元线性回归分析,评估了哪些解释变量最能解释每个响应的方差。根据最大的调整R2和最小的Mallow p(Cp)选择了最简单,最合适的模型。报告了所选模型的R2,该R2表示可以通过所选变量解释响应中的多少方差。对于P(a-ET)CO2(r = 0.899)和VDalvfrac(r = 0.938)而言,V / QEng的肺泡部分与肺泡潮气量之比的相关性最高。静脉混合剂和CO可以最好地解释P(a-ET)CO2(R2 = 0.752; Cp = 4.372)和VDalvfrac(R2 = 0.711; Cp = 9.915)。在模型中添加MPP(P(a-ET)CO2)和气道死角(VDalvfrac)只能稍微改善它们。玻尔方程式中没有“真实”死区变量有助于解释两个CO2指数的方差。 P(a-ET)CO2和VDalvfrac与V / QEng的肺泡部分密切相关,因此也受到代表肺灌注异常的变量的影响。 P(a-ET)CO2和VDalvfrac均不应被视为肺部死腔,而是在所述条件下用作V / Q不匹配的整体指标。

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