Information

What does FETCO2(end-tidal fraction CO2 concentration) represent?

What does FETCO2(end-tidal fraction CO2 concentration) represent?



We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

What is end-tidal fractional CO2 concentration? I have searched online and found little actually explaining what this measurement is. Thanks again.


I'm not sure if you're asking about the procedure or the underlying concepts of CO2 concentration or how a capnometer works. But in brief, it is measured at the end of an exhaled breath, which is least 'contaminated' by inhaled but unused air from the conduction zone (trachea, etc.). The measurement is done by looking at the blockage of light from an infrared light to a sensor by the CO2 - exactly the same mechanism by which global warming works. And the way it's reported is, in this case, as a fraction from 0 to 1. It could be reported as a percentage by multiplying by 100, or as a partial pressure by multiplying by the total atmospheric pressure (often 760 torr at sea level).


Reduction of Carbon Dioxide in Filtering Facepiece Respirators with an Active-Venting System: A Computational Study

During expiration, the carbon dioxide (CO2) levels inside the dead space of a filtering facepiece respirator (FFR) increase significantly above the ambient concentration. To reduce the CO2 concentration inside the dead space, we attach an active lightweight venting system (AVS) comprising a one-way valve, a blower and a battery in a housing to a FFR. The achieved reduction is quantified with a computational-fluid-dynamics model that considers conservation of mass, momentum and the dilute species, CO2, inside the FFR with and without the AVS. The results suggest that the AVS can reduce the CO2 levels inside the dead space at the end of expiration to around 0.4% as compared to a standard FFR, for which the CO2 levels during expiration reach the same concentration as that of the expired alveolar air at around 5%. In particular, during inspiration, the average CO2 volume fraction drops to near-to ambient levels of around 0.08% with the AVS. Overall, the time-averaged CO2 volume fractions inside the dead space for the standard FFR and the one with AVS are around 3% and 0.3% respectively. Further, the ability of the AVS to vent the dead-space air in the form of a jet into the ambient – similar to the jets arising from natural expiration without a FFR – ensures that the expired air is removed and diluted more efficiently than a standard FFR.

Citation: Birgersson E, Tang EH, Lee WLJ, Sak KJ (2015) Reduction of Carbon Dioxide in Filtering Facepiece Respirators with an Active-Venting System: A Computational Study. PLoS ONE 10(6): e0130306. https://doi.org/10.1371/journal.pone.0130306

Editor: Gongnan Xie, Northwestern Polytechnical University, CHINA

Received: September 26, 2014 Accepted: May 19, 2015 Published: June 26, 2015

Copyright: © 2015 Birgersson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Data Availability: All relevant data are within the paper.

Funding: The financial support of ST Dynamics and National University of Singapore is gratefully acknowledged. ST Dynamics provided support in the form of salaries for authors EHT, WLJL, KJS, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: EHT, WLJL, KJS are employees ST Dynamics, whose company partly funded this study. At the time of this study, ST Dynamics is developing a product and has applied for patents for the active venting system. International Patent name "An Active Venting System and Devices Incorporating Active Venting System" (Application Number: PCT/SG2014/000498) and International Patent name "Respiratory device with unidirectional valve for attaching active venting system" (Application Number: PCT/SG2014/000228). There are no further patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.


Introduction

High concentration oxygen (O2) therapy is an important early first aid treatment for injured divers. Complete relief or improvement of the symptoms of decompression illness (DCI) has been seen in divers receiving pre-hospital normobaric O2 therapy.[ 1] The current pre-hospital care recommendation for divers with symptoms and signs of DCI is for O2 delivery at the highest possible inspired fraction (close to 100%).[ 2] However, there are many factors that need to be considered when choosing the most appropriate O2 delivery system for a dive operation.[ 3 , 4]

A variety of portable O2 delivery units have been designed to provide divers with pre-hospital O2.[ 3 , 5] These units incorporate one of two basic operating configurations: (1) a constant O2 flow configuration used with a non-rebreather mask (NRB), medical O2 rebreathing system (MORS) or other constant flow delivery devices and (2) a patient triggered demand valve configuration. The recommended initial O2 flow rate with the NRB mask for divers with suspected DCI has long been 15 L∙min -1 .[ 6] Divers Alert Network (DAN) America reduced its recommended O2 flow rate to between 10 to 15 L∙min -1 , to extend the duration of often limited O2 supplies in the field, while still providing high levels of oxygenation.[ 7] However, the effect of lower flow rates on tissue oxygenation is unknown. A previous study comparing tissue oxygenation found that the NRB at 15 L·min -1 performed better than the demand valve with an oronasal mask.[ 8] However, a subsequent study showed that the demand valve provided the best tissue oxygenation when used with an intraoral mask and nose clip (NC)[ 9] almost certainly because the intraoral mask eliminated leaks that were occurring with the oronasal mask.

The present study used transcutaneous oximetry measurement (TCOM) to determine tissue oxygenation at multiple standardised sites in participants breathing O2 from a demand valve using an intraoral mask with a NC a MORS with an oronasal mask and with an intraoral mask and a NRB at 15 and 10 L·min -1 . The primary null hypothesis was that there would be no clinically significant difference in the partial pressure of transcutaneous tissue O2 (PtcO2) achieved after 10 min of breathing O2 with any of the different O2 delivery devices or flow rates.


Extremity Tourniquets

Hypercapnia.

End-tidal carbon dioxide (ETCO2) increases after tourniquet release owing to the efflux of hypercapnic venous blood from the ischemic limb into the systemic circulation. The peak ETCO2 increase occurs by 1 minute, and it returns to baseline by 10 to 13 minutes. Spontaneously breathing patients compensate by increasing their respiratory rate. However, those with controlled ventilation require a transient increase in minute ventilation by 50% for about 5 minutes to maintain normocapnia. Hyperventilation can prevent the associated increase in cerebral blood volume and intracranial pressure that might otherwise be detrimental to a patient with a severe head injury.


How would you calculate the partial pressure of CO2, given an atmospheric pressure of 760 mm Hg and a 0.04% concentration?

The key to this problem is the fact that each component of a gaseous mixture will contribute to the total pressure exerted by the mixture proportionally to the number of molecules in has in the mixture.

More often than not, you will see the partial pressure of a gas being expresses in terms of its mole fraction.

This is exactly what proportionally to the number of molecules means.

As you know, one mole of any substance is equal to exactly #6.022 * 10^(23)# molecules of that substance - this is known as Avogadro's number, #N_A# .

This means that you an express the number of moles of a gas by using the number of molecules, let's say #x# , and Avogadro's number

#color(blue)("no. of moles" = "no. of molecules" xx N_A)#

Now, the percent composition of a gaseous mixture tells you how many molecules each gas contributes in #100# molecules of mixture.

In this case, air is said to be #0.04%# carbon dioxide. This means that in every #100# molecules of air, #0.04# will be #"CO"_2# molecules.

For example, the number of moles of carbon dioxide in #100# molecules of air will be

#n_(CO_2) = "0.04 molecules" xx N_A = 0.04 * N_A#

The total number of moles in this sample of air will be

#n_"total" = "100 molecules" xx N_A = 100 * N_A#

This means that the mole fraction of carbon dioxide in the mixture will be

#chi_(CO_2) = (0.4 color(red)(cancel(color(black)(N_A))))/(100color(red)(cancel(color(black)(N_A)))) = 0.00004#

Carbon dioxide's partial pressure in air will thus be

Rounded to one sig fig, the number of sig figs you have for the percent composition of #"CO"_2# , the answer will be


Control of respiration in the chicken: Effects of venous CO2 loading

To determine if ventilation in unanesthetized chickens is adjusted sufficiently to prevent alterations in the partial pressure of carbon dioxide in arterial blood (PaCO2) when the CO2 content of mixed venous blood is changed, hypercapnic (PCO2 about 533 Torr) and hypocapnic (PCO2 less than 10 Torr) blood was infused into the left jugular vein of decerebrate chickens at 38 ml β min −1 for 30 sec. Ventilation and PaCO2 were assessed by determining respiratory frequency (f), tidal volune (VT), and the end-tidal CO2 fraction while serial samples of arterial blood were withdrawn from the sciatic artery.

Infusion of hypercapnic blood resulted in an increase in VT and minute ventilation (VE) as well as an increase in PaCO2. Infusion of hypocapnic blood resulted in a decrease in VT and VE and a small, transient decrease in PaCO2 the PaCO2 often returned to control levels before the end of the infusion period. The respiratory control system in the chicken appears to be better able to maintain a constant PaCO2 when perturbed by a reduced venous CO2 load reaching the lung than when perturbed by an increase CO2 load.

These results are consistent with the hypothesis that intrapulmonary CO2 receptors, whose sensitivity to PCO2 is highest at low PCO2, are involved in the breath-to-breath control of breathing in birds


Results

Oxygen Studies

(Figure 1) shows the recording of a step transition from hyperoxia to hypoxia and back to normoxia. It took several breaths before the target hypoxic P ET O 2 was reached. The ventilatory response shows nearly no overshoot. The transition from hypoxia to normoxia occurs within two or three breaths. Nevertheless, the ventilatory response is relatively slow and shows a slight undershoot. Not all cats respond with a clear over- or undershoot in the response. In this sample of cats, we found a manifest over- or undershoot in two cats. In Figure 2, the ensemble average of the responses from hypoxia to normoxia and to hyperoxia is shown. It shows that although the step out of hypoxia occurs in about 6 s, the ventilatory response is relatively slow. The control responses show a slight undershoot, which was no longer visible after administration of morphine.

Figure 1. Recording of part of an oxygen study. Plotted against time are ventilation (V with dot I ), tidal volume (V T ), breathing frequency (f), and oxygen and carbon dioxide concentrations (FO 2 and FCO 2 , respectively) in tracheal gas.

Figure 1. Recording of part of an oxygen study. Plotted against time are ventilation (V with dot I ), tidal volume (V T ), breathing frequency (f), and oxygen and carbon dioxide concentrations (FO 2 and FCO 2 , respectively) in tracheal gas.

Figure 2. Ensemble average of ventilation (V with dot I ) and end-tidal oxygen tension (P ET O 2 ) of control and morphine studies for the transitions from hypoxia (52 mmHg) to normoxia (lower) and from hypoxia (42 mmHg) to moderate hyperoxia (upper).

Figure 2. Ensemble average of ventilation (V with dot I ) and end-tidal oxygen tension (P ET O 2 ) of control and morphine studies for the transitions from hypoxia (52 mmHg) to normoxia (lower) and from hypoxia (42 mmHg) to moderate hyperoxia (upper).

(Figure 3) shows a representative example of the steady-state ventilatory response curves to oxygen of one cat. It illustrates the general finding that after morphine administration, hyperoxic ventilation is significantly depressed. However, the increase in ventilation by hypoxia is about the same, so that the response is approximately parallel and displaced to lower ventilation levels. This is also illustrated by Figure 4, which shows the difference in ventilation (Delta V I ) between control and morphine experiments at each oxygen level of all cats. Analysis of variance revealed that Delta V I was not significantly different at each P ET O 2 level (P = 0.65). The mean steady-state ventilation and its components tidal volume and breathing frequency are shown in Table 1. In Figure 5, scatter diagrams of the hypoxic sensitivity (A), the shape parameter (B), and the ventilation at hyperoxia (C) are shown. The mean of the estimated parameters of the fits to Equation 1are summarized in Table 2. Only the ventilation at hyperoxia (parameter A) decreased significantly from 1,260 +/- 140 ml/min to 530 +/- 110 ml/min.

Figure 3. Steady-state hypoxic ventilatory response curves during control (solid square) and after administration of morphine (delta) of one cat. The drawn lines are the exponentials fitted to the data according to the function V with dot I = G.exp(-D.P ET O 2 )+ A, with G = 1.807 l/min, D = 0.0204 mmHg sup -1, and A = 1.032 l/min for control and G = 2.697 l/min, D = 0.0291 mmHg sup -1, and A = 0.474 l/min for morphine.

Figure 3. Steady-state hypoxic ventilatory response curves during control (solid square) and after administration of morphine (delta) of one cat. The drawn lines are the exponentials fitted to the data according to the function V with dot I = G.exp(-D.P ET O 2 )+ A, with G = 1.807 l/min, D = 0.0204 mmHg sup -1, and A = 1.032 l/min for control and G = 2.697 l/min, D = 0.0291 mmHg sup -1, and A = 0.474 l/min for morphine.

Figure 4. Semilog plot of the difference in ventilation (Delta V with dot I ) between control and morphine experiments of each cat against end-tidal oxygen tension. Mean values are indicated by closed circles connected with a dotted line.

Figure 4. Semilog plot of the difference in ventilation (Delta V with dot I ) between control and morphine experiments of each cat against end-tidal oxygen tension. Mean values are indicated by closed circles connected with a dotted line.

Table 1. Mean Values of Ventilatory Parameters at Different PET O sub 2, Levels of Eight Cats

RdV2Yw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" />

Table 2. Parameters for Control and Morphine O 2 Experiments

6ynuo5wdie094aq-jOXAhtQh8Er2smvbucE04806gU3096qwO66FNu4nAHUotyY1wnqPzXdUAb6MnbHAImxQe0K2UvgBnYF6Qcg1-5ECozK0XH5f15D80Y923aES55uoyq-X49tznvw1XcM0kIpR2ZZ2vAf68mkw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" />

Figure 5. Scatter diagrams of the parameters of the oxygen response curves. (A) Hypoxic sensitivity G. (B) Shape parameter D. (C) Ventilation at hyperoxia A. The dotted lines represent the lines of identity.

Figure 5. Scatter diagrams of the parameters of the oxygen response curves. (A) Hypoxic sensitivity G. (B) Shape parameter D. (C) Ventilation at hyperoxia A. The dotted lines represent the lines of identity.

Carbon Dioxide Studies

Twenty-two control studies and 21 morphine studies were obtained. Administration of morphine shifted the carbon dioxide response curve to higher end-tidal carbon dioxide values and decreased the slope (i.e., total ventilatory carbon dioxide sensitivity [S TOT ]). The value of parameter B increased significantly after morphine by approximately 6 mmHg (Table 3). The central (S c ) and peripheral (S sub p) carbon dioxide sensitivities decreased by about 30%, causing the ratio of S p to S c not to differ between treatments. Mean values of the parameters are collected in Table 3.

Table 3. Parameters for Control and Morphine CO 2 Experiments in Eight Cats

sHZQf8xUyWUYyT6zSsOpdP5kIanRBCaGejh-ffaZsYZqj6h2fNgiTh4TQ8iy0tCePiuzke-fw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA" />


Physiological dead space in an abnormal lung

In contrast to the simple compartmental models of tables 1 and 2, abnormal lungs ordinarily have combinations of factors that contribute to the physiological dead space measurement. Figure 2 illustrates a distribution of VA/Q′ units typical for an abnormal lung that includes increased ventilation/perfusion heterogeneity, shunt and anatomical dead space. Note that a normal lung would have the same bell-shaped distribution of VA/Q′ units centred on the overall mean VA/Q′ of 1.0, but the lung units would be contained within a VA/Q′ range between 0.5 and 2.0. To quantitatively characterise the relative roles of combinations of physiological abnormalities on the physiological dead space measurement requires some familiarity with features of the multiple inert gas elimination technique (MIGET).

Allocation of ventilation and blood flow in an abnormal lung that includes shunt, increased alveolar ventilation/perfusion ratio (VA/Q′) heterogeneity and increased anatomical dead space. The lung has an overall VA/Q′ of 1.0 and has the component lung units sorted according to their individual VA/Q′ ratios. The broad base of the bell-shaped curve reflects substantial overall VA/Q′ heterogeneity. The bar on the left represents the frequency of lung units compromising shunt, and the bar on the right represents lung units receiving ventilation but no pulmonary artery blood flow. Figure reproduced courtesy of R.W. Glenny (Division of Pulmonary and Critical Care Medicine, University of Washington, Seattle, WA, USA).

To employ MIGET, partial pressures of six intravenously infused inert gases are measured in arterial and mixed venous blood and mixed expired gas to provide the data required for the mathematical model that describes the distribution of ventilation and perfusion in the lung [14, 15]. The infusion technique with its associated model provides a quantitative estimate of the allocation of pulmonary blood flow to shunt, to regions with VA/Q′ ratios ranging between .001 and 100, and ventilation to inert gas dead space, a parameter that correlates well with anatomical dead space [16]. While this technique provides a unique means of fully characterising gas exchange abnormalities in humans, useful insights into the physiological dead space calculation in disease can be obtained from examining the basic inert gas data itself [17, 18].

In a publication that provided the insights crucial to the subsequent development of MIGET, F arhi [17] demonstrated that the alveolar or arterial partial pressure of an intravenously infused inert gas could be predicted based on the solubility of the gas in blood and the VA/Q′ ratio of the lung unit. For any given VA/Q′ value, the predicted arterial (or alveolar) partial pressures of infused inert gases covering a wide range of solubility in blood form a sigmoid curve when plotted against the log of gas solubilities. The single solid line in figure 3 illustrates this retention–solubility diagram for a homogenous lung. If lung units including a distribution of different VA/Q′ ratios are combined, the arterial and alveolar lines on the diagram diverge (dashed lines in fig. 3). The vertical line on figure 3 labelled λG represents the solubility appropriate for CO2, ranging between 2 and 4 mL of gas per mL of blood, depending on the influence of the Haldane effect [20]. The intersection of the λG line with the arterial and alveolar curves identifies the two partial pressures needed to make an alveolar dead space calculation for the gas with the solubility λG:

Arterial (Pa) (retention) and alveolar (PA) (excretion) partial pressures for intravenously infused inert gases spanning a very large range of solubility in blood. The single solid curved line represents the arterial and alveolar curves of a perfectly homogenous lung (PaHOMO = PAHOMO), and the two dashed lines represent the influence of ventilation/perfusion heterogeneity that creates an arterial–alveolar partial pressure difference for both respiratory and inert gases. Pv: mixed venous partial pressure λG: represents the solubility appropriate for CO2. # : solubility is expressed as mL of gas per mL of blood at 1 Atm. Reproduced from [19] with permission from the publisher.

Applying this graphical inert gas analysis to lung models representing different combinations of abnormal lung physiology, H lastala and R obertson [19] examined the influence of different degrees of VA/Q′ heterogeneity, shunt and anatomical dead space to illustrate the influence of these abnormalities on a physiological dead space calculation, examined over a wide range of inert (and respiratory) gas solubility [19]. Figure 4 illustrates the physiological dead space calculation made over the range of different gas solubilities in three different abnormal lungs, all containing 20% shunt and 20% anatomical dead space, in combination with no VA/Q′ heterogeneity (fig. 4a), normal VA/Q′ heterogeneity (fig. 4b) and increased VA/Q′ heterogeneity (fig. 4c). Note that the physiological dead space in the CO2 solubility range, ∼3 mL of gas per mL of blood, is most sensitive to the extent of VA/Q′ heterogeneity, with a secondary sensitivity to shunt. In the recent context of investigating the mechanisms responsible for dead space abnormalities in ARDS, W agner [21] compared the influence of different degrees of shunt and VA/Q′ heterogeneity on physiological dead space, and emphasised the relatively greater influence of VA/Q′ heterogeneity on the measurement. A final insight gained from the application of inert gas retention–solubility curves to the understanding of physiological dead space in disease is that any increase the overall VA/Q′ ratio (a change that would shift the bell-shaped distribution in fig. 2 to the right on the VA/Q′ axis) will also shift all of the curves on the retention–solubility diagram to the right [17, 18]. Hence a five-fold increase in overall VA/Q′ ratio will shift all of the figure 4 curves five units to the right along the solubility axis. As gas solubility in blood is fixed, any increase in the mean VA/Q′ value by increased ventilation and/or decreased perfusion will also increase the calculated physiological dead space. Of note, the influence of a substantial increase in the mean VA/Q′ ratio on the physiological dead space measurement was first described by John West, based on calculations utilising his initial computer model of ventilation/perfusion interactions in the lung [22].

Plots based on inert gas retention and excretion values for three model lungs that have 20% shunt and 20% anatomical dead space, illustrating the influence of a) no alveolar ventilation/perfusion ratio (VA/Q′) heterogeneity, b) normal VA/Q′ heterogeneity, and c) a high extent of VA/Q′ heterogeneity. The dashed lines identify the physiological dead space calculation for the entire range of inert gas solubility. The solid lines represent the inert gas arterial–alveolar differences and the dotted lines represent the venous admixture calculation for the inert gases. # : solubility is expressed as mL of gas per mL of blood at 1 Atm. Reproduced from [19] with permission from the publisher.


A simple method to clamp end-tidal carbon dioxide during rest and exercise

Carbon dioxide regulates ventilation and cerebral blood flow during exercise. There are significant limitations in breathing systems designed to control end-tidal gas concentrations when used during high-intensity exercise. We designed a simple, inexpensive breathing system which controls end-tidal carbon dioxide ( ( < ext>_<<< ext>_ <2>>> ) ) during exercise from rest to peak work capacity (W max). The system is operated by an investigator who, in response to breath-by-breath ( < ext>_<<< ext>_ <2>>> ) , titrates flow of a 10 % CO2, 21 % O2 mixture into an open-ended 5-L inspiratory reservoir. To demonstrate system efficacy, nine fit male subjects performed two maximal, incremental exercise tests (25 W min −1 ramp) on a cycle ergometer: a poikilocapnic control trial in which ( < ext>_<<< ext>_ <2>>> ) varied with work intensity, and an experimental trial, in which we planned to clamp ( < ext>_<<< ext>_ <2>>> ) at 50 mmHg. With our breathing system, we maintained ( < ext>_<<< ext>_ <2>>> ) at 51 ± 2 mmHg throughout exercise (rest, 50 ± 2 W max, 52 ± 5 mmHg mean ± SD) despite large changes in ventilation (range 27–65 at rest, 134–185 L min −1 BTPS at W max) and carbon dioxide production (range 0.3–0.7 at rest, 4.5–5.5 L min −1 at W max). This simple, inexpensive system achieves ( < ext>_<<< ext>_ <2>>> ) control at rest and throughout exercise.

This is a preview of subscription content, access via your institution.


Materials and Methods

Experimental Protocol

The design of this pharmacokinetic study entailed 16 individual experiments. Four purpose-bred male coonhounds, weighing 24–37 kg (28.4 ± 5.9 kg see table 1), were studied on four occasions each in this Institutional Animal Care and Use Committee–approved study. Approximately 1 month before being studied, a Vascular-Access-Port (Access Technologies, Skokie, IL) was implanted with its catheter tip positioned near the aortic bifurcation via a femoral artery of each dog to facilitate frequent percutaneous arterial blood sampling. 16

All dogs were studied while awake (0% isoflurane, control) and while anesthetized with isoflurane at end-tidal concentrations of 1.7%, 2.6%, and 3.5%, which correspond to 1.15, 1.7, and 2.3 minimum alveolar concentration. 17,18The order in which these studies were conducted in each dog was randomized using a Latin square experimental design. The details of the preparation and conduct of the individual studies have been described in detail previously. 14

In the isoflurane studies, anesthesia was induced with methohexital (10–15 mg/kg intravenously), the trachea was intubated, and the animal was placed in the left lateral decubitus position. Mechanical ventilation was instituted to control end-tidal carbon dioxide tension at 30 ± 5 mmHg. Anesthesia was maintained with 1.7%, 2.6%, or 3.5% isoflurane in oxygen, and end-tidal concentrations were monitored with a side-stream infrared analyzer.

A flow-directed thermal dilution pulmonary artery catheter was inserted through a right external jugular vein sheath introducer in both awake and anesthetized dogs. The pulmonary artery catheter was subsequently used to determine thermal dilution CO as well as to facilitate right atrial administration of the physiologic markers.

The study was not begun until the dog was hemodynamically stable (approximately 1 h) after the targeted end-tidal isoflurane concentration had been reached. This was defined as less than 10% variation of CO and pulmonary and systemic arterial blood pressures over a 30-min period when heart rate and blood pressures were measured continuously and CO was determined at least every 15 min.

Indocyanine green (ICG Cardio-Green Hynson, Westcott, and Dunning, Baltimore, MD), 5 mg in 1 ml of ICG diluent, [ 14 C]-inulin (DuPont NEN, Boston, MA), 30 μCi in 1.5 ml of ICG diluent, and antipyrine (Sigma, St. Louis, MO), 25 mg in 1 ml of ICG diluent, were placed sequentially in a 76-cm-long intravenous tubing (4.25 ml priming volume) and connected to the proximal injection port of the pulmonary artery catheter. At the onset of the study (time t = 0 min), the markers were flushed into the right atrium within 4 s using 10 ml of 5% dextrose in water, allowing the simultaneous determination of dye and thermal dilution COs. Arterial blood samples were collected via the Vascular-Access-Port every 0.03 min for the first 0.48 min and every 0.06 min for the next 0.54 min using a computer-controlled roller pump (Masterflex Cole-Parmer, Chicago, IL). Subsequently, 35 3-ml arterial blood samples were drawn manually at 0.2-min intervals to 2 min, at 0.5-min intervals to 4 min, at 5 and 6 min, every 2 min to 20 min, at 25 and 30 min, every 10 min to 60 min, every 15 min to 120 min, and every 30 min to 360 min.

Analytical Methods

Plasma ICG concentrations of all samples obtained up to 20 min were measured on the study day by the high-performance liquid chromatography technique of Grasela et al. 19as modified in our laboratory. 10Plasma [ 14 C]-inulin concentrations of all samples were determined by liquid scintillation counting, using an external standard method for quench correction. 20Plasma antipyrine concentrations were measured in all samples using a modification of a high-performance liquid chromatography technique developed in our laboratory. 10,21

To interpret antipyrine intercompartmental clearances in relation to blood flow, the recirculatory models were constructed on the basis of whole blood marker concentrations. Plasma ICG and inulin concentrations were converted to blood concentrations by multiplying them by one minus the hematocrit, as neither ICG nor inulin partitions into erythrocytes. Plasma antipyrine concentrations were converted to blood concentrations using an in vivo technique that corrects for antipyrine partitioning into erythrocytes by calculating its apparent dose assuming an erythrocyte:plasma partition coefficient of one the product of CO and AUC first-pass for the plasma antipyrine concentration versus time curve equals dose when its erythrocyte:plasma partitioning is one. 10,22

Pharmacokinetic Model

The pharmacokinetic modeling methodology (fig. 1) has been described in detail previously. 10,14It is based on the approach described by Jacquez for obtaining information from outflow concentration histories, the so-called inverse problem. 23Inulin and antipyrine distributions were analyzed as the convolution of their intravascular behavior, determined by the pharmacokinetics of concomitantly administered ICG, and tissue distribution kinetics. 10

Fig. 1. The general model for the recirculatory pharmacokinetics of indocyanine green (ICG), inulin, and antipyrine. The central circulation of all three markers, defined by the central delay elements (V C ), receives all of cardiac output (CO). The delay elements are represented generically by rectangles surrounding four compartments, although the actual number of compartments needed varied between 2 and 30 in any given delay. Beyond the central circulation, the CO distributes to numerous circulatory and tissue pathways that lump, on the basis of their blood volume to blood flow ratios or tissue volume to distribution clearance ratios (MTTs), into fast (Cl ND-F , V ND-F ) and slow (Cl ND-S , V ND-S ) peripheral-blood circuits (ICG) or nondistributive peripheral pathways (inulin and antipyrine) and fast (Cl T-F , V T-F ) and slow (Cl T-S , V T-S ) tissue volume groups. ICG, which distributes only within the intravascular space, does not have fast and slow tissue volumes. Antipyrine does not have an identifiable second nondistributive peripheral circuit. The elimination clearance (Cl E ) of all three markers are modeled from the arterial sampling site without being associated with any particular peripheral circuit.

Fig. 1. The general model for the recirculatory pharmacokinetics of indocyanine green (ICG), inulin, and antipyrine. The central circulation of all three markers, defined by the central delay elements (V C ), receives all of cardiac output (CO). The delay elements are represented generically by rectangles surrounding four compartments, although the actual number of compartments needed varied between 2 and 30 in any given delay. Beyond the central circulation, the CO distributes to numerous circulatory and tissue pathways that lump, on the basis of their blood volume to blood flow ratios or tissue volume to distribution clearance ratios (MTTs), into fast (Cl ND-F , V ND-F ) and slow (Cl ND-S , V ND-S ) peripheral-blood circuits (ICG) or nondistributive peripheral pathways (inulin and antipyrine) and fast (Cl T-F , V T-F ) and slow (Cl T-S , V T-S ) tissue volume groups. ICG, which distributes only within the intravascular space, does not have fast and slow tissue volumes. Antipyrine does not have an identifiable second nondistributive peripheral circuit. The elimination clearance (Cl E ) of all three markers are modeled from the arterial sampling site without being associated with any particular peripheral circuit.

Arterial ICG, inulin, and antipyrine concentration versus time data before evidence of recirculation (i.e. , first-pass data) were weighted uniformly and fit to the sum of two Erlang distribution functions using TableCurve2D (ver 3.0 Jandel Scientific, San Rafael, CA) on a Pentium-based personal computer (Gateway 2000, North Sioux City, SD) two parallel, lumped pathways with different transit characteristics reflect the heterogeneity in the distribution of transit times in the pulmonary circulation. 22Because neither ICG nor inulin distribute beyond the intravascular space before recirculation, they were modeled simultaneously to improve the confidence in the model parameters of the central (first-pass) circulation. Antipyrine has measurable pulmonary tissue distribution during this time and was modeled independently the antipyrine pulmonary tissue volume (V T-P ) is the difference between the antipyrine central volume (MTT antipyrine · CO) and the central intravascular volume codetermined by ICG and inulin (MTT ICG,inulin · CO).

In subsequent pharmacokinetic analysis, these descriptions of the central circulation were incorporated as parallel linear chains, or delay elements, into independent recirculatory models for the individual markers using SAAM II (SAAM Institute, Seattle, WA) implemented on a Pentium-based personal computer. 22,24The concentration–time data were weighted, assuming a proportional variance model, in proportion to the inverse of the square of the observed value. Possible systematic deviations of the observed data from the calculated values were sought 25using the one-tailed one-sample runs test, 26with P < 0.05, corrected for multiple applications of the runs test, as the criterion for rejection of the null hypothesis. Possible model misspecification was sought by visual inspection of the measured and predicted marker concentrations versus time relationships.

In general, peripheral drug distribution can be lumped into identifiable volumes and clearances: a fast nondistributive peripheral pathway (V ND-F and Cl ND-F ) a slow nondistributive peripheral pathway (V ND-S and Cl ND-S ) rapidly (fast) equilibrating tissues (V T-F and Cl T-F ) and slowly equilibrating tissues (V T-S and Cl T-S ). The fast and slow nondistributive peripheral pathways (delay elements) represent intravascular circuits in the ICG and inulin models the only identifiable nondistributive peripheral pathway in the antipyrine model, determined by the recirculation peak, represents blood flow that quickly returns the lipophilic marker to the central circulation after minimal apparent tissue distribution (i.e. , a pharmacokinetic shunt). 10,14In the inulin and antipyrine models, the parallel rapidly and slowly equilibrating tissues are the fast and slow compartments of traditional three-compartment pharmacokinetic models, respectively therefore, the central circulation and nondistributive peripheral pathway(s) are detailed representations of the ideal central volume of the three-compartment model. 21Because of the direct correspondence between the recirculatory model and three-compartment models, Cl E was modeled from the arterial (sampling) compartment to enable comparison of these results with previous ones.

The AUC was determined for both the first-pass fit (AUC first-pass , calculated for the sum of two parallel Erlang functions) and for the full recirculatory model. 12The AUCs for the full model were calculated for the interval 0–3 min (AUC 0-3 min ) because most intravenous drugs used in the practice of anesthesia (e.g. , hypnotics and muscle relaxants) have demonstrable onset within this time. AUC 0-3 min is the sum of AUC first-pass , which is determined by CO (i.e. , AUC first-pass = dose/CO), and the AUC resulting from marker recirculation (AUC recirc ). To resolve the factors influencing AUC 0-3 min , both AUC first-pass and AUC recirc were determined.

Statistical Analysis

The effects of treatment as well as the order of treatment on observed pharmacokinetic parameters were assessed using a general linear model analysis of variance for a Latin square experimental design (NCSS 6.0.2 Statistical System for Windows Number Cruncher Statistical Systems, Kaysville, UT). Post hoc analysis was conducted using Scheffé multiple comparison test. The relationship of the pharmacokinetic parameters to CO and end-tidal isoflurane concentration was sought using standard least squares linear regression and the Spearman rank order correlation, respectively, (SigmaStat SPSS, Chicago, IL) using the Bonferroni correction of the criterion for rejection of the null hypothesis. The criterion for rejection of the null hypothesis was P < 0.05.


Methods

Animals

The study was approved by the Ethics Committee for Animal Experiments of Lower Saxony, Germany, number 33.14-42,502-04- 14/1547. Twelve experimental horses (six mares, three geldings and three stallions) with a body weight of 540 ± 41 kg (mean ± SD) and an age of 7 ± 6 years were used for this study. All horses were systemically healthy based on physical examination and routine haematological and biochemical blood work. They were part of an additional anesthesia study and a terminal, experimental surgery study and were euthanized for tissue sampling at the end of anesthesia using pentobarbital (60 mg/kg i.v.).

Anesthesia

Horses were sedated with xylazine (0.5 mg/kg, Xylavet, CP-Pharma, Burgdorf, Germany) or dexmedetomidine (3.5 μg/kg, Dexdomitor, Pfizer Tiergesundheit GmbH, Germany). Induction of anesthesia with midazolam (0.05 mg/kg, Midazolam-ratiopharm, ratiopharm, Ulm, Germany) and ketamine (2.2 mg/kg, Narketan, Vetoquinol, Ravensburg, Germany) was identical in all horses. Anesthesia was maintained with isoflurane (IsofluranCP, CP-Pharma, Burgdorf, Germany) in pure oxygen in combination with a constant rate infusion of 1 mg/kg/h xylazine or 7 μg/kg/h dexmedetomidine. The end tidal isoflurane concentration was maintained between 1.1 and 1.2 Vol.% and kept constant during the experimental procedure and horses received lactated Ringer’s solution (B. Braun, Melsungen, Germany) at a rate of 10 ml/kg/h. After induction and intubation horses were positioned on a surgical table in dorsal recumbency. Controlled mechanical ventilation was performed with a pressure cycled large animal ventilator (Model JAVC 2000 J.D. Medical Distributing Company Phoenix, USA) using intermittent positive pressure ventilation with an inspiratory pressure of 25 cm H2O. Respiratory rate was adjusted to maintain arterial partial carbon dioxide pressure (PaCO2) between 40 and 45 mmHg.

Instrumentation

Before anesthesia the skin over the right and left jugular vein was clipped and subcutaneously infiltrated with mepivacaine (Scandicain 2%, AstraZeneca GmbH, Germany). One 12 G catheter (EquiCathTM Fastflow®, Brau, Melsungen, Germany) was placed into the left jugular veins and two 8F catheter (BD CritiCath BD Critical Care Systems, USA) introducers in the right jugular vein to facilitate the placement of two balloon tipped catheters. A Swan-Ganz standard thermodilution pulmonary artery catheter (BD CritiCath BD Critical Care Systems, USA) with a length a 110 cm was placed into the pulmonary artery and a second balloon tipped catheter (Arrow 5 Fr 110 cm Balloon Wedge Pressure Catheter, Teleflex, Germany) was placed into the right atrium. Correct placement was confirmed by visual inspection of the pressure waveforms and by transthoracic ultrasonography.

During anesthesia, the transverse facial artery was cannulated with a 20 G catheter (VenocanTM IV Catheter, Kruuse, Langeskov, Denmark) for invasive blood pressure monitoring and arterial blood sampling. The catheters were connected to calibrated pressure transducers (Gould Statham Transducer, PD 23 ID, USA) via fluid-filled extension lines. The pressure transducers were positioned at the level of the sternal manubrium. A combined spectrophotometry and laser-doppler flow probe of the micro-lightguide spectrophotometer O2C (Oxygen to See, LEA Medizintechnik) was placed via median laparotomy on the serosal surface of the stomach, the jejunum and the pelvic flexion of the colon.

Measured variables

Recording and evaluation of the data started 180 min after induction of anesthesia and after finishing another conducted study. MAP, PAP, heart rate (HR), respiratory rate, end tidal isoflurane concentration (ETIso) and FiO2 were measured continuously with a standard anesthesia monitor o and recorded.

For cardiac output measurements, the bolus thermodilution (BTD) technique was used. Therefore iced 5% dextrose solution (one mL per 15 kg bodyweight) was injected into the right atrium and the temperature change was measured via an inline temperature probe positioned in the pulmonary artery. Five injections were performed and the average of the closest three values was used. The CO was measured and the CI was calculated.

Arterial and mixed venous blood samples were taken and arterial pH, PaO2, PV̄̀O2 and PaCO2 as well as arterial and mixed venous hemoglobin concentrations and arterial and mixed venous oxygen saturation (SaO2, SV̄̀O2) and measured immediately after sampling (AVL995, AVL Medizintechnik, Germany).

Oxygen delivery to the tissue was calculated using the standard formula:

Oxygen extraction ratio was calculated using the standard formula:

With CaO2 = 1.34 × [hemoglobin concentration] × SaO2) + (0.0031 × PaO2).

And with CV̄̀O2 = 1.34 × [hemoglobin concentration] × SV̄̀O2) + (0.0031 × PV̄̀O2)

Tissue oxygenation and blood flow

Gastrointestinal tissue oxygenation (sO2 in %) and blood flow (flow) were measured by the micro-lightguide spectrophotometer O2C as described previously [42]. This device uses the laser Doppler shift to measure tissue blood flow and white light spectroscopy for measuring the tissue oxygenation (sO2). A probe with a penetration depth of 2.5 mm was used for all measurements. The surface of this probe was placed on the mucosa of the stomach, the jejunem (about 3 m orally from the ileum) and the pelvic flexure of the large colon. Flow and saturation were recorded for at least 30 s at every measuring time point. Before each recording, quality of the laser Doppler signal was evaluated on a monitor so that identification of incorrect probe positioning or movement artefacts was possible.

Experimental protocol

Part A: Hypoxemia

After equilibration and instrumentation two baseline measurements were performed at a stable plane of anesthesia with an inspiratory oxygen concentration of >95%. Thereafter FiO2 (constant fresh gas flow of 8 l per minute) was stepwise decreased to 75%, 55%, 40%, 30%, 20%, 15% and 10% by mixing inspiratory oxygen with nitrogen up stream of the vaporizer. Measurements were performed 10 min after reaching the new inspiratory oxygen concentration. Decreasing inspiratory oxygen concentration was terminated when a horse had SaO2 of 65% or less. About 10 min after reaching the targeted FiO2 the MAP and CI as well as the sO2 were measured and arterial and central venous blood samples were taken.

For comparison of global oxygenation (SaO2) and peripheral oxygenation (tissue oxygenation) SaO2 values were grouped as follows: 95 ± 2%, 90 ± 2%, 85 ± 2%, 80 ± 2%, 75 ± 2%, 70 ± 2% and 65 ± 2% independent from FiO2.

After completion of hypoxic measurements, nitrogen flow was stopped and pure oxygen was used. After 30 min inspiratory oxygen concentration was 90% or higher and no horse showed signs of hypoxemia (SaO2 > 95%). Gastrointestinal oxygenation recovered back to baseline values.

Part B: Hypovolemia

Surgical preparation of the carotid artery was performed and an 8G catheter was placed into the artery. The catheter was connected to a roller pump (IP 65, Ismatec, Germany) to ensure controlled and continuous exsanguination and Ringer-Lactate-Infusion was stopped.

Total blood volume of the horses was estimated being about 7.6% of the total body weight (bwt) or 76 mL/kg bwt [43]. After calculation total blood volume of each horse pumping rate was set to get an exsanguination rate of 50% total blood volume loss per hour (38 mL/kg bwt/h).

The HR, MAP, PAP and CI as well as the intestinal blood flow were measured every 15 min starting at baseline blood volume and at 88%, 75%, 63%, 50% and less than 45% of that value. Central and peripheral perfusion parameters measurements were continued until horses had no detectable pulse or cardiac output.

Statistical analysis

Statistical significance was attributed when p < 0.05. Analyses were carried out with the statistical software SAS, version 9.1.3 (SAS Institute, Cary, NY, USA) and GraphPad Prism 5 (GraphPad Software, Inc., USA). For the analysis of the linear model, the procedure MIXED was used. The parameters sO2 and flow were sampled with 2 Hz. Measurements were performed over at least 25 to 30 s resulting in 50 to 60 values for each parameter and time point. The mean of these single measurements was calculated and used for this set time point. Normal distribution of model residuals of dependent variables was confirmed by Shapiro-Wilks-Test. Data is presented as mean ± standard deviation. A two way analysis of variance and Tukey’s post hoc test were used for comparing the measured parameters by period of time (repeated measurements). The non-linear curve fitting was used to construct the curve that has the best fit to the data points in Figs. 1, 2, 4 and 5.


Watch the video: Respiratory Therapy - End Tidal CO2 Monitoring ETCO2 Part 13 - Physiology of Carbon Dioxide (August 2022).