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Frontiers in veterinary science2018; 5; 58; doi: 10.3389/fvets.2018.00058

Physiologic Factors Influencing the Arterial-To-End-Tidal CO2 Difference and the Alveolar Dead Space Fraction in Spontaneously Breathing Anesthetised Horses.

Abstract: The arterial to end-tidal CO difference (PCO) and alveolar dead space fraction (VDalv = PCO/PaCO), are used to estimate Enghoff's "pulmonary dead space" (V/Q), 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 CO indices in anesthetized spontaneously breathing horses. Six healthy adult horses were anesthetized in dorsal recumbency breathing spontaneously for 3 h. Data to calculate the CO 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 [Formula: see text], 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 CO indices before V/Q and the explanatory variables with rho were reported. Multiple linear regression analysis was performed on PCO and VDalv assessing which explanatory variables best explained the variance in each response. The simplest, best-fit model was selected based on the maximum adjusted and smallest Mallow's p (C). The 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 to alveolar tidal volume ratio for both, PCO ( = 0.899) and VDalv ( = 0.938). Venous admixture and CO best explained PCO ( = 0.752; C = 4.372) and VDalv ( = 0.711; C = 9.915). Adding MPP (PCO) and airway dead space (VDalv) 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 CO indices. PCO and VDalv were closely associated with the alveolar part of V/Q and as such, were also influenced by variables representing a dysfunctional pulmonary perfusion. Neither PCO nor VDalv should be considered pulmonary dead space, but used as global indices of V/Q mismatching under the described conditions.
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Publication Date: 2018-03-28 PubMed ID: 29644221PubMed Central: PMC5882784DOI: 10.3389/fvets.2018.00058Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research article focuses on the factors that affect the arterial to end-tidal CO2 difference (PCO) and the alveolar dead space fraction (VDalv) in anesthetized, spontaneously breathing horses. This research is significant as these factors are widely used to estimate Enghoff’s “pulmonary dead space” (V/Q).

Study Design and Methodology

  • The authors conducted an experimental study on six healthy adult horses. These horses were anesthetized in a dorsal recumbency position and left to breathe spontaneously for three hours.
  • Measurements for calculating both CO2 indices and dead space variables were taken every 30 minutes.
  • The explanatory variables evaluated included Bohr’s physiological and alveolar dead space variables, cardiac output (CO), mean pulmonary pressure (MPP), venous admixture, airway dead space, tidal volume, oxygen consumption, and slope III of the volumetric capnogram.
  • Data analysis included univariate Pearson correlation for both CO2 indices and multiple linear regression analysis assessing which explanatory variables explained the variation in each response.

Key Findings

  • The highest correlation was found with the alveolar part of V/Q to the alveolar tidal volume ratio, for both PCO and VDalv.
  • Venous admixture and cardiac output best explained PCO, while VDalv was best explained by the same two variables.
  • Adding mean pulmonary pressure to the PCO model and airway dead space to the VDalv model only marginally improved the models.
  • None of the real dead space variables from Bohr’s equation contributed to the explanation of the variance of the two CO2 indices.
  • PCO and VDalv were closely associated with the alveolar part of V/Q. As such, they are also influenced by variables representing a dysfunctional pulmonary perfusion.

Conclusion

  • Based on the study’s results, neither PCO nor VDalv should be considered as pulmonary dead space. Rather, they should be used as global indices of V/Q mismatching under the conditions described in the study.

Cite This Article

APA
Mosing M, Böhm SH, Rasis A, Hoosgood G, Auer U, Tusman G, Bettschart-Wolfensberger R, Schramel JP. (2018). Physiologic Factors Influencing the Arterial-To-End-Tidal CO2 Difference and the Alveolar Dead Space Fraction in Spontaneously Breathing Anesthetised Horses. Front Vet Sci, 5, 58. https://doi.org/10.3389/fvets.2018.00058

Publication

Frontiers in veterinary science
ISSN: 2297-1769
NlmUniqueID: 101666658
Country: Switzerland
Language: English
Volume: 5
Pages: 58
PII: 58

Researcher Affiliations

Mosing, Martina
  • College of Veterinary Medicine, Murdoch University, Perth, WA, Australia.
Böhm, Stephan H
  • Department of Anesthesiology and Intensive Care Medicine, Rostock University Medical Center, Rostock, Germany.
Rasis, Anthea
  • College of Veterinary Medicine, Murdoch University, Perth, WA, Australia.
Hoosgood, Giselle
  • College of Veterinary Medicine, Murdoch University, Perth, WA, Australia.
Auer, Ulrike
  • Anaesthesiology and Perioperative Intensive Care Medicine, Veterinary University Vienna, Vienna, Austria.
Tusman, Gerardo
  • Department of Anesthesiology, Hospital Privado de Comunidad, Mar del Plata, Argentina.
Bettschart-Wolfensberger, Regula
  • Division of Anaesthesiology, Vetsuisse Faculty, Zurich, Switzerland.
Schramel, Johannes P
  • Anaesthesiology and Perioperative Intensive Care Medicine, Veterinary University Vienna, Vienna, Austria.

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Citations

This article has been cited 9 times.
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