Gas Exchange during Exercise in Healthy People: I. the Physiological Dead-Space Volume

1976 ◽  
Vol 51 (4) ◽  
pp. 323-333 ◽  
Author(s):  
Christine A. Bradley ◽  
E. A. Harris ◽  
Eve R. Seelye ◽  
R. M. L. Whitlock
Keyword(s):  
Carbon Dioxide ◽  
Dead Space ◽  
Confidence Limit ◽  
Carbon Dioxide Tension ◽  
Physiological Dead Space ◽  
Carbon Dioxide Output ◽  
Pulmonary Capillary ◽  
Dead Space Volume ◽  
Capillary Temperature ◽  
Space Volume

1. Physiological dead-space volume (VD) was measured in twenty-four healthy men and women aged from 20 to 71 years, at rest and at two rates of work on a treadmill, whilst breathing air and breathing oxygen. 2. The effect of correction of arterial carbon dioxide tension (Pa,co2) to pulmonary capillary temperature on the resulting value for VD was investigated. We find that the effect is substantial and that a correction should be made. 3. Equations have been derived for the prediction of normal VD during exercise. The best prediction was given by a regression on height, age, carbon dioxide output, ventilation and respiratory frequency, with an upper 95% confidence limit of +81 ml.

scholarly journals Reductions in dead space ventilation with nasal high flow depend on physiological dead space volume: metabolic hood measurements during sleep in patients with COPD and controls

2018 ◽  
Vol 51 (5) ◽  
pp. 1702251 ◽  
Author(s):  
Paolo Biselli ◽  
Kathrin Fricke ◽  
Ludger Grote ◽  
Andrew T. Braun ◽  
Jason Kirkness ◽  
...  
Keyword(s):  
Respiratory Rate ◽  
Dead Space ◽  
Minute Ventilation ◽  
High Flow ◽  
Physiological Dead Space ◽  
Copd Patients ◽  
Dead Space Volume ◽  
Anatomical Dead Space ◽  
Dead Space Ventilation ◽  
Space Volume

Nasal high flow (NHF) reduces minute ventilation and ventilatory loads during sleep but the mechanisms are not clear. We hypothesised NHF reduces ventilation in proportion to physiological but not anatomical dead space.11 subjects (five controls and six chronic obstructive pulmonary disease (COPD) patients) underwent polysomnography with transcutaneous carbon dioxide (CO2) monitoring under a metabolic hood. During stable non-rapid eye movement stage 2 sleep, subjects received NHF (20 L·min−1) intermittently for periods of 5–10 min. We measured CO2 production and calculated dead space ventilation.Controls and COPD patients responded similarly to NHF. NHF reduced minute ventilation (from 5.6±0.4 to 4.8±0.4 L·min−1; p<0.05) and tidal volume (from 0.34±0.03 to 0.3±0.03 L; p<0.05) without a change in energy expenditure, transcutaneous CO2 or alveolar ventilation. There was a significant decrease in dead space ventilation (from 2.5±0.4 to 1.6±0.4 L·min−1; p<0.05), but not in respiratory rate. The reduction in dead space ventilation correlated with baseline physiological dead space fraction (r2=0.36; p<0.05), but not with respiratory rate or anatomical dead space volume.During sleep, NHF decreases minute ventilation due to an overall reduction in dead space ventilation in proportion to the extent of baseline physiological dead space fraction.

Labeled carbon dioxide (C18O2): an indicator gas for phase II in expirograms

2004 ◽  
Vol 97 (5) ◽  
pp. 1755-1762 ◽  
Author(s):  
Holger Schulz ◽  
Anne Schulz ◽  
Gunter Eder ◽  
Joachim Heyder
Keyword(s):  
Carbon Dioxide ◽  
Phase Ii ◽  
Dead Space ◽  
Moment Analysis ◽  
Cumulative Distribution ◽  
Breath Holding ◽  
Power Moment ◽  
Single Breath ◽  
Dead Space Volume ◽  
Space Volume

Carbon dioxide labeled with 18O (C18O2) was used as a tracer gas for single-breath measurements in six anesthetized, mechanically ventilated beagle dogs. C18O2 is taken up quasi-instantaneously in the gas-exchanging region of the lungs but much less so in the conducting airways. Its use allows a clear separation of phase II in an expirogram even from diseased individuals and excludes the influence of alveolar concentration differences. Phase II of a C18O2 expirogram mathematically corresponds to the cumulative distribution of bronchial pathways to be traversed completely in the course of exhalation. The derivative of this cumulative distribution with respect to respired volume was submitted to a power moment analysis to characterize volumetric mean (position), standard deviation (broadness), and skewness (asymmetry) of phase II. Position is an estimate of dead space volume, whereas broadness and skewness are measures of the range and asymmetry of functional airway pathway lengths. The effects of changing ventilatory patterns and of changes in airway size (via carbachol-induced bronchoconstriction) were studied. Increasing inspiratory or expiratory flow rates or tidal volume had only minor influence on position and shape of phase II. With the introduction of a postinspiratory breath hold, phase II was continually shifted toward the airway opening (maximum 45% at 16 s) and became steeper by up to 16%, whereas skewness showed a biphasic response with a moderate decrease at short breath holding and a significant increase at longer breath holds. Stepwise bronchoconstriction decreased position up to 45 ± 2% and broadness of phase II up to 43 ± 4%, whereas skewness was increased up to twofold at high-carbachol concentrations. Under all circumstances, position of phase II by power moment analysis and dead space volume by the Fowler technique agreed closely in our healthy dogs. Overall, power moment analysis provides a more comprehensive view on phase II of single-breath expirograms than conventional dead space volume determinations and may be useful for respiratory physiology studies as well as for the study of diseased lungs.

Revised Standards for Normal Resting Dead-Space Volume and Venous Admixture in Men and Women

1978 ◽  
Vol 55 (1) ◽  
pp. 125-128 ◽  
Author(s):  
E. A. Harris ◽  
Eve R. Seelye ◽  
R.M.L. Whitlock
Keyword(s):  
Oxygen Tension ◽  
Dead Space ◽  
Arterial Oxygen Tension ◽  
Arterial Oxygen ◽  
Venous Admixture ◽  
Men And Women ◽  
Physiological Dead Space ◽  
Dead Space Volume ◽  
Previous Series ◽  
Space Volume

1. Data have been combined from three previous series to provide revised standards for the prediction of physiological dead-space volume (VD), arterial oxygen tension (Pa,o2), alveolar-to-arterial oxygen-tension difference (Pa,o2 - Pa,o2) and venous admixture fraction (Q̇va/Q̇t) in the sitting position. 2. These standards, based on measurements in 96 healthy men and women aged from 20 to 74 years, largely confirm conclusions drawn from the first series of 48 subjects. 3. VD is best predicted on age, height, tidal volume and the reciprocal of respiratory frequency. Pa,o2, (Pa,o2 - Pa,o2) and Q̇va/Q̇t are adequately predicted on age alone.

Negative arterial-mixed expired PC02 gradient during acute and chronic hypercapnia

1975 ◽  
Vol 38 (3) ◽  
pp. 382-388 ◽  
Author(s):  
D. B. Jennings ◽  
C. C. Chen
Keyword(s):  
Carbon Dioxide ◽  
Dead Space ◽  
Carbon Dioxide Tension ◽  
Passive Diffusion ◽  
Conscious Dogs ◽  
Low Oxygen ◽  
Physiological Dead Space ◽  
Oxygen Concentrations

In resting conscious dogs physiological dead space was calculated using the Bohr equation and measurements of arterial and mixed expired carbon dioxide tension. Whenever dogs inhaled carbon dioxide mixtures (5–10%) that had normal or low oxygen concentrations, the calculated dead space became negative. This paradox was based on the fact that the mixed expired carbon dioxide tension in resting hypercapnic dogs. Under these circumstances carbon dioxide was produced from the lung as measured by gas analyses and blood analyses. By the lung as measured by gas analyses and blood analyses. By reasoning this implies that “alveolar” carbon dioxide tension was higher than pulmonary venous carbon dioxide tension. The negative carbon dioxide gradient persisted at 14 days of chronic hypercapnia and reverted to normal within 10 min of breathing air after chronic hypercapnia. These findings suggest that the exchange of carbon dioxide in the lung cannot be explained solely on the basis of passive diffusion.

Prediction of the Physiological Dead-Space in Resting Normal Subjects

1973 ◽  
Vol 45 (3) ◽  
pp. 375-386 ◽  
Author(s):  
E. A. Harris ◽  
Mary E. Hunter ◽  
Eve R. Seelye ◽  
Margaret Vedder ◽  
R. M. L. Whitlock
Keyword(s):  
Tidal Volume ◽  
Multiple Regression ◽  
Dead Space ◽  
Predictive Accuracy ◽  
Volume Ratio ◽  
Normal Subjects ◽  
Physiological Dead Space ◽  
Dead Space Volume ◽  
Made In ◽  
Space Volume

1. Two-hundred and forty duplicate estimations of physiological dead-space volume (VD) were made in forty-eight healthy subjects (twenty-four men and twenty-four women) aged from 20 to 74 years, to assess the predictive accuracy of various standards. 2. The VD/VT (physiological dead-space volume/tidal volume) ratio standard was least precise, but could be improved by allowing for sex and age. 3. The best prediction could be made by multiple regression of VD on age, height, tidal volume (VT) and the reciprocal of respiratory frequency (f), which gave an estimate with a standard deviation of 24·7 ml. 4. Theoretical and practical arguments favour the abandonment of the VD/VT ratio standard. Simple regression of VD on VT also is unsatisfactory, giving a much less precise estimate of VD than a multiple regression on VT and other variables.

scholarly journals MEASUREMENT OF LUNG DEAD SPACE VOLUME BY CAPNOVOLUMETRY

2020 ◽  
pp. 471-477
Author(s):  
T.A. MIROSHKINA ◽  
◽  
S.A. SHUSTOVA ◽  
Keyword(s):  
Dead Space ◽  
Alveolar Dead Space ◽  
Volumetric Capnography ◽  
Equal Area ◽  
Physiological Dead Space ◽  
Dead Space Volume ◽  
Anatomical Dead Space ◽  
The Difference ◽  
Space Volume

The article provides information on the lung dead space – a part of the respiratory volume that does not participate in gas exchange. The anatomical and alveolar dead spaces jointly together form the physiological dead space. The article describes methods for determining the volume of dead spaces using the capnovolumetry. The volume of physiological dead space is calculated using the C. Bohr equation. The volume of anatomical dead space can be determined using the equal area method proposed by W.S. Fowler. The volume of the alveolar dead space is the difference of volumes of the physiological and anatomical dead spaces. In pathology, the volume of the alveolar space and, consequently, physiological dead space can increase significantly. Determination of the volume of dead space is the significant criterion for diagnostic and predicting the outcome of a number of diseases. Keywords: Physiological dead space , anatomical dead space , alveolar dead space , capnovolumetry, volumetric capnography.

Respiration

2021 ◽  
pp. 261-291
Author(s):  
Graham Mitchell
Keyword(s):  
Carbon Dioxide ◽  
Gas Exchange ◽  
Respiratory System ◽  
Dead Space ◽  
Ventilation Rate ◽  
Alveolar Ventilation ◽  
Laryngeal Muscles ◽  
Dead Space Volume ◽  
Recurrent Laryngeal Nerves ◽  
Space Volume

This chapter discusses the respiratory system of giraffes. The respiratory system supplies oxygen, removes of carbon dioxide and produces the airflow needed to make sounds. Giraffes do not have the velocity of airflow through the airways to vibrate vocal cords sufficiently to generate sounds able to be heard by humans but can produce sounds able to be heard by giraffes. Air reaches alveoli for gas exchange through a long trachea, which is relatively narrow (~4 cm in diameter). Dead space volume is large. A short trunk and rigid chest wall reduce the capacity of the thorax and consequently lung volume is small. Respiratory rate is low (~10 min-1), but tidal volume is relatively big, and alveolar ventilation rate (VA; ~60 L min-1) delivers sufficient air despite the large dead space volume. Laryngeal muscles act to prevent food from entering the trachea a process controlled by the (short) superior and (long) inferior (recurrent) laryngeal nerves. Air that has been delivered to alveoli comes into contact with pulmonary artery blood (=cardiac output, Q; ~40 L min-1). The VA: Q ratio is ~1.5 (cf 0.8 in humans). Gas exchange occurs by diffusion. The surface area for diffusion is related to the number of alveoli which increase in number during growth from ~1 billion in a newborn giraffe to 11 billion in an adult. Gas carriage of oxygen and carbon dioxide is a function of erythrocytes which are small (MCV = 12 fL) but numerous (12 × 1012 L-1) and each liter of blood contains ~150 g of hemoglobin.

Dead Space Volume in N95 Masks

2020 ◽  
Author(s):  
Santiago C. Arce ◽  
Fernando Chiodetti ◽  
Eduardo L. De Vito
Keyword(s):  
Dead Space ◽  
Dead Space Volume ◽  
Space Volume

PULMONARY FUNCTION IN THE NEWBORN INFANT

PEDIATRICS ◽  
1962 ◽  
Vol 30 (6) ◽  
pp. 975-989
Author(s):  
N. M. Nelson ◽  
L. S. Prod'hom ◽  
R. B. Cherry ◽  
P. J. Lipsitz ◽  
C. A. Smith
Keyword(s):  
Pulmonary Function ◽  
Respiratory Distress ◽  
Newborn Infant ◽  
Dead Space ◽  
Clinical Course ◽  
Average Difference ◽  
Alveolar Dead Space ◽  
Physiological Dead Space ◽  
New Born ◽  
Pulmonary Capillary

The arterial-alveolar tension gradient for CO2 has been investigated in 17 normal new born infants and in 15 with some degree of respiratory distress. Whereas the normal infants had virtually no Pco2 gradient from pulmonary capillary to alveolus, an average difference of 13.9 mm Hg was detected in sick infants. This gradient for Pco2 is caused by increased alveolar (and total physiological dead space, the relative amount of which closely parallels the clinical course of the disease. The data obtained indicate the increase in alveolar dead space to be largely due to poor perfusion of ventilated alveoli. In severely ill infants more than 60% of ventilated alveoli appear to be under-perfused.

High-frequency ventilation

1984 ◽  
Vol 64 (2) ◽  
pp. 505-543 ◽  
Author(s):  
J. M. Drazen ◽  
R. D. Kamm ◽  
A. S. Slutsky
Keyword(s):  
Experimental Data ◽  
Gas Exchange ◽  
Dead Space ◽  
Gas Transport ◽  
Physical Models ◽  
High Frequency Ventilation ◽  
General Description ◽  
Wide Range ◽  
Dead Space Volume ◽  
Space Volume

Complete physiological understanding of HFV requires knowledge of four general classes of information: 1) the distribution of airflow within the lung over a wide range of frequencies and VT (sect. IVA), 2) an understanding of the basic mechanisms whereby the local airflows lead to gas transport (sect. IVB), 3) a computational or theoretical model in which transport mechanisms are cast in such a form that they can be used to predict overall gas transport rates (sect. IVC), and 4) an experimental data base (sect. VI) that can be compared to model predictions. When compared with available experimental data, it becomes clear that none of the proposed models adequately describes all the experimental findings. Although the model of Kamm et al. is the only one capable of simulating the transition from small to large VT (as compared to dead-space volume), it fails to predict the gas transport observed experimentally with VT less than equipment dead space. The Fredberg model is not capable of predicting the observed tendency for VT to be a more important determinant of gas exchange than is frequency. The remaining models predict a greater influence of VT than frequency on gas transport (consistent with experimental observations) but in their current form cannot simulate the additional gas exchange associated with VT in excess of the dead-space volume nor the decreased efficacy of HFV above certain critical frequencies observed in both animals and humans. Thus all of these models are probably inadequate in detail. One important aspect of these various models is that some are based on transport experiments done in appropriately scaled physical models, whereas others are entirely theoretical. The experimental models are probably most useful in the prediction of pulmonary gas transport rates, whereas the physical models are of greater value in identifying the specific transport mechanism(s) responsible for gas exchange. However, both classes require a knowledge of the factors governing the distribution of airflow under the circumstances of study as well as requiring detail about lung anatomy and airway physical properties. Only when such factors are fully understood and incorporated into a general description of gas exchange by HFV will it be possible to predict or explain all experimental or clinical findings.

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