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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

Overview of attention for article published in Frontiers in Veterinary Science, March 2018
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Title
Physiologic Factors Influencing the Arterial-To-End-Tidal CO2 Difference and the Alveolar Dead Space Fraction in Spontaneously Breathing Anesthetised Horses
Published in
Frontiers in Veterinary Science, March 2018
DOI 10.3389/fvets.2018.00058
Pubmed ID
Authors

Martina Mosing, Stephan H. Böhm, Anthea Rasis, Giselle Hoosgood, Ulrike Auer, Gerardo Tusman, Regula Bettschart-Wolfensberger, Johannes P. Schramel

Abstract

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 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 [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 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 13%
Student > Master 3 10%
Student > Bachelor 2 6%
Student > Postgraduate 2 6%
Student > Doctoral Student 1 3%
Other 4 13%
Unknown 15 48%
Readers by discipline Count As %
Medicine and Dentistry 8 26%
Veterinary Science and Veterinary Medicine 7 23%
Nursing and Health Professions 1 3%
Unknown 15 48%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 28 March 2018.
All research outputs
#18,594,219
of 23,031,582 outputs
Outputs from Frontiers in Veterinary Science
#4,175
of 6,329 outputs
Outputs of similar age
#256,287
of 329,889 outputs
Outputs of similar age from Frontiers in Veterinary Science
#63
of 76 outputs
Altmetric has tracked 23,031,582 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,329 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,889 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.