Journal articles: 'Respiratory Gas Analysis'

1

Langton, J. A., and A. Hutton. "Respiratory gas analysis." Continuing Education in Anaesthesia Critical Care & Pain 9, no. 1 (February 2009): 19–23. http://dx.doi.org/10.1093/bjaceaccp/mkn048.

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Jaffe, Michael B. "Respiratory Gas Analysis—Technical Aspects." Anesthesia & Analgesia 126, no. 3 (March 2018): 839–45. http://dx.doi.org/10.1213/ane.0000000000002384.

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3

Hamilton, Lyle H. "GAS CHROMATOGRAPHY FOR RESPIRATORY AND BLOOD GAS ANALYSIS*." Annals of the New York Academy of Sciences 102, no. 1 (December 15, 2006): 15–28. http://dx.doi.org/10.1111/j.1749-6632.1962.tb13622.x.

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4

VanWagenen, Richard, Dwayne R. Westenskow, and Robert Benner. "RESPIRATORY GAS ANALYSIS BY RAMAN SCATTERING." Anesthesiology 63, Supplement (September 1985): A163. http://dx.doi.org/10.1097/00000542-198509001-00163.

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5

Fraser, R. B., and S. Z. Turney. "New method of respiratory gas analysis: light spectrometer." Journal of Applied Physiology 59, no. 3 (September 1, 1985): 1001–7. http://dx.doi.org/10.1152/jappl.1985.59.3.1001.

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A multigas concentration analyzer particularly suited for respiratory gas analysis has been developed using a new principle based on the measurement of the intensity of light emitted by excited atoms or ions in a direct current glow discharge. This glow discharge spectral emission gas analyzer (GDSEA), or light spectrometer, simultaneously measures O2, N2, CO2, He, and N2O gas concentrations with a 0–90% response time of 100 ms and a sample rate of less than 20 ml/min in a short gas sample line configuration. Mole accuracy and resolution of the GDSEA using a short sample line were determined in the laboratory to be +/- 0.15 to +/- 0.7% and 0.02–0.05%, respectively. In the clinical setting a comparative evaluation was made with a mass spectrometer in a long sample line, computerized, multibed, respiratory monitoring system. Results indicate a close agreement between the two instruments with differences in mixed inspiratory or expiratory O2 and CO2 concentrations of less than 2% and of derived variables, such as O2 consumption, CO2 production, and respiratory exchange ratio, of less than 5%.

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6

Kim, Jinkyu, Masaaki Kawahashi, and Hiroyuki Hirahara. "Analysis of airway gas dynamics in a micro-channel of bronchiole model(3C1 Cardiopulmonary & Respiratory Mechanics)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2007.3 (2007): S202. http://dx.doi.org/10.1299/jsmeapbio.2007.3.s202.

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7

Tompuri, Tuomo T., Niina Lintu, Sonja Soininen, Tomi Laitinen, and Timo Antero Lakka. "Comparison between parameters from maximal cycle ergometer test first without respiratory gas analysis and thereafter with respiratory gas analysis among healthy prepubertal children." Applied Physiology, Nutrition, and Metabolism 41, no. 6 (June 2016): 624–30. http://dx.doi.org/10.1139/apnm-2015-0355.

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It is important to distinguish true and clinically relevant changes and methodological noise from measure to measure. In the clinical practice, maximal cycle ergometer tests are typically performed first without respiratory gas analysis and thereafter, if needed, with respiratory gas analysis. Therefore, we report a comparison of parameters from maximal cycle ergometer exercise tests that were done first without respiratory gas analysis and thereafter with it in 38 prepubertal and healthy children (20 girls, 18 boys). The Bland–Altman method was used to assess agreement in maximal workload (WMAX), heart rate (HR), and systolic blood pressure (SBP) between rest and maximum. Girls achieved higher WMAX in the exercise tests with respiratory gas analysis compared with exercise tests without respiratory gas analysis (p = 0.016), whereas WMAX was similar in the tests among boys. Maximal HR (proportional offset, –1%; coefficients of variation, 3.3%) and highest SBP (proportional offset, 3%; coefficients of variation, 10.6%) were similar in the tests among children. Precision and agreement for HR improved and precision for SBP worsened with increasing exercise intensity. Heteroscedasticity was not observed for WMAX, HR, or SBP. We conclude that maximal cycle ergometer tests without and with respiratory gas analysis can be used consecutively because measurement of respiratory gases did not impair performance or have a significant effect on the maximality of the exercise tests. Our results suggest that similar references can be used for children who accept or refuse using a mask during a maximal exercise test.

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8

Turner, M. J., and S. Culbert. "Apparatus to measure the step and frequency responses of gas analysis instruments (respiratory gas analysis)." Physiological Measurement 14, no. 3 (August 1, 1993): 317–26. http://dx.doi.org/10.1088/0967-3334/14/3/010.

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9

de JONGSTE, JOHAN C, and KJELL ALVING. "Gas Analysis." American Journal of Respiratory and Critical Care Medicine 162, supplement_1 (August 2000): S23—S27. http://dx.doi.org/10.1164/ajrccm.162.supplement_1.maic-6.

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10

Hahn, G., and M. Meyer. "Sample-hold technique for analysis of respiratory gas composition at high breathing frequencies." Journal of Applied Physiology 64, no. 6 (June 1, 1988): 2684–91. http://dx.doi.org/10.1152/jappl.1988.64.6.2684.

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A gas sampling device is described for continuous monitoring of respiratory gas composition that is applicable to experimental conditions when the breathing frequency is very high (greater than 2 Hz) and the response time of conventional gas analyzers becomes a critical limiting factor. The system utilizes the principle of discontinuous gas collection at any selected point of the respiratory cycle facilitated by ultraspeed piezoelectric valves and includes provision for sample-hold characteristics. Two distinct modes of operation are supported. In phase-locked mode gas sampling is synchronous with breathing frequency. In scanning mode gas collection is asynchronous with breathing frequency. Phase-locked mode may be used for continuous monitoring of end-tidal gas concentrations, whereas scanning mode is intended for assessing the gas concentration profile throughout the respiratory cycle. The system may be applied to steady breathing encountered in mechanical ventilation at high frequency or during quasi-steady breathing observed in panting animals. Combined with a respiratory mass spectrometer, the system has been used for measurement of gas concentrations in alveolar gas mixtures at breathing frequencies ranging from 3 to 30 Hz that were otherwise not amenable to rapid measuring techniques.

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11

Borodulina, Elena A., G. Yu Chernogayeva, B. E. Borodulin, E. S. Vdoushkina, L. V. Povalyaeva, and L. F. Abubakirova. "Optimization of choice of respiratory support the intensive care severe community-acquired pneumonia." Clinical Medicine (Russian Journal) 96, no. 2 (April 27, 2018): 152–57. http://dx.doi.org/10.18821/0023-2149-2018-96-2-152-157.

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The purpose of study is the optimization of the choice of method of respiratory support in patients with severe community-acquired pneumonia (CAP) on admission to intensive care unit (ICU) on the basis of acid-alkaline indicators and arterial blood gas analysis. Material and methods. Depending on the method of the choice of respiratory support two groups of 350 people were formed. The first group (n = 350) - by the results of pulse oximetry (SatO2). The second group (n = 350) - in terms of acid-base and arterial blood gas analysis (pH, PO2, PCO2). To determine hypoxemia, pulse oximetry (heart monitor GOLDWAY G40), acid-alkali and gas composition of arterial blood (gas analyzer «MEDICA EasyStat») were used. In the ICU there were conducted three types of respiratory support: 1) oxygen therapy via orinasal mask 2) non-invasive mechanical ventilation (respirators «VENTimotion 2» and «Bipap Vision») 3) mechanical ventilation («Engstrom Carestation»). The criterion of effectiveness: recovery performance pulse oximetry, acid-base balance, and arterial blood gas analysis, the presence of positive clinical dynamics. Results. Choice of method of respiratory support in the gas composition of blood allowed to expand the indications for use NIV as a method of respiratory support in the treatment of patients with severe CAP, to ensure timely transfer and reduce the time finding patients on mechanical ventilation, to avoid damage due to hypoxia bodies - «target» with the development of multiple organ failure, and thus 4.3 times to reduce mortality and length of stay in the ICU of 1.7.

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12

Hirano, Masami, Yosuke Yamada, Masanobu Hibi, Mitsuhiro Katashima, Yasuki Higaki, Akira Kiyonaga, and Hiroaki Tanaka. "Simultaneous multiple-subject analysis of respiratory gas exchange in humans." Journal of Physical Fitness and Sports Medicine 3, no. 2 (2014): 269–79. http://dx.doi.org/10.7600/jpfsm.3.269.

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13

Tomizawa, Giichi, Isao Nishi, Akinori Nagano, Hiromichi Oiwa, Akio Hashimoto, Kuniaki Okonogi, and Shinya Suzuki. "Continuous measurements of respiratory gas analysis in hyperbaric heliox environment." Journal of the Mass Spectrometry Society of Japan 36, no. 2 (1988): 35–48. http://dx.doi.org/10.5702/massspec.36.35.

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14

Hahn, C. E. "Oxygen respiratory gas analysis by sine-wave measurement: a theoretical model." Journal of Applied Physiology 81, no. 2 (August 1, 1996): 985–97. http://dx.doi.org/10.1152/jappl.1996.81.2.985.

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A sinusoidal forcing function inert-gas-exchange model (C. E. W. Hahn, A. M. S. Black, S. A. Barton, and I. Scott. J. Appl. Physiol. 75: 1863–1876, 1993) is modified by replacing the inspired inert gas with oxygen, which then behaves mathematically in the gas phase as if it were an inert gas. A simple perturbation theory is developed that relates the ratios of the amplitudes of the inspired, end-expired, and mixed-expired oxygen sine-wave oscillations to the airways' dead space volume and lung alveolar volume. These relationships are independent of oxygen consumption, the gas-exchange ratio, and the mean fractional inspired (FIO2) and expired oxygen partial pressures. The model also predicts that blood flow shunt fraction (Qs/QT) is directly related to the oxygen sine-wave amplitude perturbations transmitted to end-expired air and arterial and mixed-venous blood through two simple equations. When the mean FIO2 is sufficiently high for arterial hemoglobin to be fully saturated, oxygen behaves mathematically in the blood like a low-solubility inert gas, and the amplitudes of the arterial and end-expired sine-wave perturbations are directly related to Qs/QT. This relationship is independent of the mean arterial and mixed-venous oxygen partial pressures and is also free from mixed-venous perturbation effects at high forcing frequencies. When arterial blood is not fully saturated, the theory predicts that QS/QT is directly related to the ratio of the amplitudes of the induced-saturation sinusoids in arterial and mixed-venous blood. The model therefore predicts that 1) on-line calculation of airway dead space and end-expired lung volume can be made by the addition of an oxygen sine-wave perturbation component to the mean FIO2; and (2) QS/QT can be measured from the resultant oxygen perturbation sine-wave amplitudes in the expired gas and in arterial and mixed-venous blood and is independent of the mean blood oxygen partial pressure and oxyhemoglobin saturation values. These calculations can be updated at the sine-wave forcing period, typically 2–4 min.

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15

Röpcke, Jürgen, and Mario Hannemann. "Special section on Breath Gas Analysis." Journal of Breath Research 5, no. 2 (June 1, 2011): 020201. http://dx.doi.org/10.1088/1752-7155/5/2/020201.

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16

Northey, D. R., R. L. Hughson, and J. E. Cochrane. "BREATH-BY-BREATH ANALYSIS OF RESPIRATORY GAS EXCHANGE: EFFECT OF MATCHING VENTILATION AND GAS FRACTION." Medicine and Science in Sports and Exercise 21, Supplement (April 1989): S20. http://dx.doi.org/10.1249/00005768-198904001-00120.

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17

Boutellier, U., T. Kundig, U. Gomez, P. Pietsch, and E. A. Koller. "Respiratory phase detection and delay determination for breath-by-breath analysis." Journal of Applied Physiology 62, no. 2 (February 1, 1987): 837–43. http://dx.doi.org/10.1152/jappl.1987.62.2.837.

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The delay between air flow and gas concentration signals is generally assumed to be constant within a breath as well as from breath to breath, but it was not possible to examine the constancy of the delay with the delay determination techniques so far available. Thus we developed new methods for respiratory phase detection and delay determination. The presented algorithm for the detection of the start of inspiration and expiration (phase detection) replaces the generally used valve assembly with two pneumotachographs. Now, the pneumotachograph is used in a bidirectional mode, but with a volume criterion for phase detection replacing the less reliable threshold criterion. To measure the delay between flow and gas concentration signals, a test gas is periodically injected as a marker. This test gas contains less N2 than ambient air. Therefore, the delay is determined as time between the moment of injection and the drop of N2. These two methods rendered it possible to examine delay variations and their consequences. The investigation of various breathing patterns demonstrated that the usually assumed errors caused by delay uncertainty are underestimated. We suggest reliance on a breath-by-breath delay determination to account for delay variations.

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18

İlhan, Sami, Rafet Günay, Sevil Özkan, Tolga Sinan Güvenç, and Nurgül Yurtsever. "Arterial Blood Gas Analysis in Chronic Obstructive Pulmonary Disease Patients Undergoing Coronary Artery Bypass Surgery." Turkish Thoracic Journal 17, no. 3 (September 10, 2016): 93–99. http://dx.doi.org/10.5578/ttj.30503.

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19

Varene, P., and C. Kays. "A graphic analysis of respiratory heat exchange." Journal of Applied Physiology 63, no. 4 (October 1, 1987): 1374–80. http://dx.doi.org/10.1152/jappl.1987.63.4.1374.

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A new graphic representation of respiratory heat exchange is proposed using the concept of equivalent temperatures directly related to enthalpy values. On such a diagram it is possible to 1) compute the value of the heat exchange (delta H) knowing the inspired temperature (TI) and the partial pressure of water vapor (PIH2O) [or the relative humidity (rhI)] of inspired gas; 2) estimate the variation in delta H following a given variation in TI and PIH2O or, inversely, to choose the variation in TI and PIH2O necessary to obtain a given variation in delta H; 3) dissociate inspiratory and expiratory exchanges and to evaluate the efficiency of the respiratory heat exchange process in different environmental situations; and 4) easily compare the results of different studies published on respiratory heat exchanges in humans or other animal species.

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20

Proulx, Jeffrey. "Respiratory monitoring: Arterial blood gas analysis, pulse oximetry, and end-tidal carbon dioxide analysis." Clinical Techniques in Small Animal Practice 14, no. 4 (November 1999): 227–30. http://dx.doi.org/10.1016/s1096-2867(99)80015-2.

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21

Shaffer, Thomas H., Raymond Foust, Marla R. Wolfson, and Thomas F. Miller. "Analysis of perfluorochemical elimination from the respiratory system." Journal of Applied Physiology 83, no. 3 (September 1, 1997): 1033. http://dx.doi.org/10.1152/jappl.1997.83.3.1033.

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Shaffer, Thomas H., Raymond Foust IIII, Marla R. Wolfson, and Thomas F. Miller, Jr. Analysis of perfluorochemical elimination from the respiratory system. J. Appl. Physiol. 83(3): 1033–1040, 1997.—We describe a simple apparatus for analysis of perfluorochemicals (PFC) in expired gas and thus a means for determining PFC vapor and liquid elimination from the respiratory system. The apparatus and data analysis are based on thermal conduction and mass transfer principles of gases. In vitro studies were conducted with the PFC vapor analyzer to determine calibration curves for output voltage as a function of individual respiratory gases, respiratory gases saturated with PFC vapor, and volume percent standards for percent PFC saturation (%PFC-Sat) in air. Voltage-concentration data for %PFC-Sat of the vapor from the in vitro tests were accurate to within 2.0% from 0 to 100% PFC-Sat, linear ( r = 0.99, P < 0.001), and highly reproducible. Calculated volume loss of PFC liquid over time correlated well with actual loss by weight ( r = 0.99, P < 0.001). In vivo studies with neonatal lambs demonstrated that PFC volume loss and evaporation rates decreased nonlinearly as a function of time. These relationships were modulated by changes in PFC physical properties, minute ventilation, and postural repositioning. The results of this study demonstrate the sensitivity and accuracy of an on-line method for PFC analysis of expired gas and describe how it may be useful in liquid-assisted ventilation procedures for determining PFC volume loss, evaporation rate, and optimum dosing and ventilation strategy.

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22

Han, Dong-Hun, Sin-Woong Choi, and So Yun Lee. "Hazardous Gas Analysis during Fire Investigation." Fire Science and Engineering 34, no. 6 (December 31, 2020): 94–103. http://dx.doi.org/10.7731/kifse.26c6d4ab.

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Various types of hazardous substances are generated at fire scenes. Firefighters usually use the self-contained breathing apparatus (SCBA) during firefighting; however, SCBA is very inconvenient to use in other works (e.g., fire investigation and fire scene commands). Therefore, firefighters can be exposed to numerous chemicals. In this study, concentrations of hazardous gases were measured by utilizing gas analyzers with seven sensors during fire investigations. Six fire investigators measured the concentrations of hazardous gases directly as they worked. This included capturing the maximum concentrations of SO2 at seven places, HCHO at 29 places, NO2 at one place, HCN at 13 places, and CO at two places where the concentration exceeded the short-term exposure limit (STEL). When reconstruction experiments were performed, the maximum allowable concentrations for most hazardous chemicals fell below the STEL approximately 90 min after the fire occurrence. Therefore, we determined that fire investigators should wear proper respiratory protective equipment when working.

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23

Paiva, M., and L. A. Engel. "Model analysis of intra-acinar gas exchange." Respiration Physiology 62, no. 2 (November 1985): 257–72. http://dx.doi.org/10.1016/0034-5687(85)90119-7.

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24

Scholz, Alexander-Wigbert, Ursula Wolf, Michael Fabel, Norbert Weiler, Claus P. Heussel, Balthasar Eberle, Matthias David, and Wolfgang G. Schreiber. "Comparison of magnetic resonance imaging of inhaled SF6 with respiratory gas analysis." Magnetic Resonance Imaging 27, no. 4 (May 2009): 549–56. http://dx.doi.org/10.1016/j.mri.2008.08.010.

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25

Gan, K., I. Nishi, I. Chin, and A. S. Slutsky. "On-line determination of pulmonary blood flow using respiratory inert gas analysis." IEEE Transactions on Biomedical Engineering 40, no. 12 (1993): 1250–59. http://dx.doi.org/10.1109/10.250579.

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26

Chinn, D. J., Y. Naruse, and J. E. Cotes. "Accuracy of gas analysis in lung function laboratories." Thorax 41, no. 2 (February 1, 1986): 133–37. http://dx.doi.org/10.1136/thx.41.2.133.

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27

Pitkin, A. D., C. M. Roberts, and J. A. Wedzicha. "Arterialised earlobe blood gas analysis: an underused technique." Thorax 49, no. 4 (April 1, 1994): 364–66. http://dx.doi.org/10.1136/thx.49.4.364.

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28

Nikki, P., M. Bahr, and M. P. J. Paloheimo. "Comparison of non-invasive respiratory and arterial blood gas analysis. A recovery room study on acute respiratory depression." Scandinavian Journal of Clinical and Laboratory Investigation 50, sup203 (January 1990): 213–16. http://dx.doi.org/10.3109/00365519009087512.

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29

Scheid, Peter, and Johanes Piiper. "Inert gas wash-out from tissue: Model analysis." Respiration Physiology 63, no. 1 (January 1986): 1–18. http://dx.doi.org/10.1016/0034-5687(86)90026-5.

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30

Baraldi, E., F. Pasquale, G. Bonetto, S. Carraro, and S. Zanconat. "Exhaled gas analysis and airway inflammation." Pediatric Pulmonology 37, S26 (2004): 16–19. http://dx.doi.org/10.1002/ppul.70035.

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31

Fernandez, Ramiro, and Ankit Bharat. "Pleural gas analysis for the identification of alveolopleural fistulae." Current Opinion in Pulmonary Medicine 22, no. 4 (July 2016): 362–66. http://dx.doi.org/10.1097/mcp.0000000000000282.

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32

Herbig, Jens, and Jonathan Beauchamp. "Towards standardization in the analysis of breath gas volatiles." Journal of Breath Research 8, no. 3 (September 4, 2014): 037101. http://dx.doi.org/10.1088/1752-7155/8/3/037101.

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33

Arbak, Peri, İlknur Başer, Özlem Ozdemir Kumbasar, Füsun Ülger, Zeki Kılıçaslan, and Fatma Evyapan. "Long Term Effects of Tear Gases on Respiratory System: Analysis of 93 Cases." Scientific World Journal 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/963638.

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Aim. This study aimed to assess the long-term respiratory effects of tear gases among the subjects with history of frequent exposure.Materials and Methods. A questionnaire by NIOSH and pulmonary function tests was performed in 93 males exposed to the tear gases frequently and 55 nonexposed subjects.Results. The mean numbers of total exposure and last 2 years exposure were8.4±6.4times,5.6±5.8times, respectively. Tear gas exposed subjects were presented with a higher rate for cough and phlegm more than 3 months (24.7% versus 11.3%,P>0.05). Mean FEV1/FVC and % predicted MMFR in smoker exposed subjects are significantly lower than those in smoker controls (81.7% versus 84.1%,P=0.046and 89.9% versus 109.6%,P=0.0004, resp.). % predicted MMFR in nonsmoker exposed subjects is significantly lower than that in nonsmoker controls (99.4% versus 113.1%,P=0.05). Odds ratios for chest tightness, exercise dyspnea, dyspnea on level ground, winter morning cough, phlegm, and daily phlegm were increased almost 2 to 2.5 folds among tear gas exposed subjects.Conclusion. The rates for respiratory complaints were high in the case of the exposure to the tear gases previously. Tears gas exposed subjects were found to be under the risk for chronic bronchitis.

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34

Keskinen, Kari L., Ferran A. Rodríguez, and Ossi P. Keskinen. "Respiratory snorkel and valve system for breath-by-breath gas analysis in swimming." Scandinavian Journal of Medicine & Science in Sports 13, no. 5 (September 26, 2003): 322–29. http://dx.doi.org/10.1034/j.1600-0838.2003.00319.x.

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35

Peake, Michael J., and Graham H. White. "Arterial Blood Gas Analysis: Selecting the Clinically Appropriate Option for Calculating Base Excess." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 39, no. 6 (November 2002): 614–15. http://dx.doi.org/10.1177/000456320203900614.

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As part of arterial blood gas analysis, base excess is often reported as a measure of non-respiratory acid-base disturbance. Most blood gas analysers offer the option of calculating either the base excess of the blood sample or the base excess of the extracellular fluid (ECF). We report a case that illustrates that selecting the physiologically appropriate parameter avoids the potential for misinterpretation of acid-base data. We recommend that the base excess of the ECF is the appropriate metabolic blood gas parameter for clinical use.

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Tisch, Ulrike, and Hossam Haick. "Chemical sensors for breath gas analysis: the latest developments at the Breath Analysis Summit 2013." Journal of Breath Research 8, no. 2 (March 28, 2014): 027103. http://dx.doi.org/10.1088/1752-7155/8/2/027103.

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37

Whiteside, Garth T., Michele Hummel, Jamie Boulet, Jessica D. Beyenhof, Bryan Strenkowski, Janet Dell John, Terri Knappenberger, Harry Maselli, and Lee Koetzner. "Robustness of arterial blood gas analysis for assessment of respiratory safety pharmacology in rats." Journal of Pharmacological and Toxicological Methods 78 (March 2016): 32–41. http://dx.doi.org/10.1016/j.vascn.2015.11.001.

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38

Manera, Umberto, Maria Claudia Torrieri, Cristina Moglia, Margherita Viglione, Margherita Anna Rosa Daviddi, Enrico Matteoni, Luca Solero, et al. "The role of arterial blood gas analysis (ABG) in amyotrophic lateral sclerosis respiratory monitoring." Journal of Neurology, Neurosurgery & Psychiatry 91, no. 9 (June 30, 2020): 999–1000. http://dx.doi.org/10.1136/jnnp-2020-323810.

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39

YASUMI, Takashi, Takanori MATSUKI, Si Chen, Ichiro YAMADA, and Shin'ichi WARISAWA. "J212034 Fabrication and evaluation of a micro sensor for respiratory gas analysis using graphene." Proceedings of Mechanical Engineering Congress, Japan 2013 (2013): _J212034–1—_J212034–4. http://dx.doi.org/10.1299/jsmemecj.2013._j212034-1.

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SEVERINGHAUS, JOHN W, POUL ASTRUP, and JOHN F MURRAY. "Blood Gas Analysis and Critical Care Medicine." American Journal of Respiratory and Critical Care Medicine 157, no. 4 (April 1998): S114—S122. http://dx.doi.org/10.1164/ajrccm.157.4.nhlb1-9.

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41

Anisimov, Dmitry Alexandrovich, Lyudmila Nikitichna Goncharov, and Anna Albertovna Dyachkova. "ANALYSIS OF DIAGNOSTIC PARAMETERS OF RESPIRATORY FAILURE IN PATIENTS WITH BRONCHIAL ASTHMA." Samara Journal of Science 4, no. 2 (June 15, 2015): 10–12. http://dx.doi.org/10.17816/snv20152102.

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Respiratory failure (NAM)-a pathological condition in which there is provided the maintenance of normal blood gas or it is achieved through more intensive operation of external respiration and heart, resulting in decreased functional capacity of the organism [1,2]. The main method of diagnosis of DN is the study of the gas composition of the arterial blood, but because of the complexity of the analysis, which involves complex invasive techniques for obtaining arterial blood by puncture of a major artery in the therapeutic Department is not carried out [1,3]. A plurality of classifications days, the lack of clear criteria for diagnosis was to analyze assessment days by a combination of clinical, laboratory and instrumental methods patient days. As a model of acute respiratory failure were selected from patients with mild intermittent and persistent severity of asthma, which bore a slight aggravation, burdened days 1 severity, number of 30 people. SatO2 blood was the criterion for assessing the severity of DN. In the evaluation of clinical parameters, such as shortness of breath and respiratory rate, it was revealed that the values of these parameters increase is inversely proportional to the drop SatO2 blood. In assessing such clinical parameters as the rate of breathing and instrumental measure FEV1 did not find such dependence. Thus, to assess the severity of DN in patients with bronchial asthma it is necessary to conduct a comprehensive analysis of the clinical and instrumental methods.

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42

Palange, P., and A. M. Ferrazza. "A simplified approach to the interpretation of arterial blood gas analysis." Breathe 6, no. 1 (September 1, 2009): 14–22. http://dx.doi.org/10.1183/18106838.0601.014.

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43

Cap, P. "Gas chromatography/mass spectrometry analysis of exhaled leukotrienes in asthmatic patients." Thorax 59, no. 6 (June 1, 2004): 465–70. http://dx.doi.org/10.1136/thx.2003.011866.

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44

Federspiel, W. J., and J. J. Fredberg. "Axial dispersion in respiratory bronchioles and alveolar ducts." Journal of Applied Physiology 64, no. 6 (June 1, 1988): 2614–21. http://dx.doi.org/10.1152/jappl.1988.64.6.2614.

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The mixing of gases in the pulmonary acinus was characterized by analyzing axial gas dispersion during steady flow in models of respiratory bronchioles and alveolar ducts. An analysis (method of moments) developed for addressing dispersion in porous media was used to derive an integral expression for the axial dispersion coefficient (D*). Evaluation of D* required solving the Navier-Stokes equations for the flow field and a convection-diffusion type equation arising from the analysis. D* was strongly dependent on alveolar volume per central duct volume, the aperture size through which the alveoli communicate with the central duct, and the Peclet number (Pe). At smaller Pe (flow rate) D* was substantially smaller than the molecular diffusion coefficient, whereas at larger Pe (flow rate) D* was much greater than the Taylor-Aris result for flow-enhanced dispersion in straight tubes. Also, flow-enhanced dispersion became appreciable at smaller Pe than indicated by the Taylor-Aris result. These behaviors transcend both the lower and upper limits established previously for gas mixing in the pulmonary acinus.

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Larach, D. R., H. G. Schuler, T. M. Skeehan, and J. A. Derr. "Mass spectrometry for monitoring respiratory and anesthetic gas waveforms in rats." Journal of Applied Physiology 65, no. 2 (August 1, 1988): 955–63. http://dx.doi.org/10.1152/jappl.1988.65.2.955.

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A method is presented for real-time monitoring of airway gas concentration waveforms in rats and other small animals. Gas is drawn from the tracheal tube, analyzed by a mass spectrometer, and presented as concentration vs. time waveforms simultaneously for CO2, halothane, and other respiratory gases and anesthetics. By use of a respiratory simulation device, the accuracy of mass spectrometric end-tidal CO2 analysis was compared with both the actual gas composition and infrared spectrophotometry. The effects of various ventilator rates and inspiration-to-expiration ratios on sampling accuracy were also examined. The technique was validated in male Sprague-Dawley rats being ventilated mechanically. The difference between the arterial PCO2 (PaCO2) and the end-tidal PCO2 (PETCO2) was not significantly different from zero, and the correlation between PETCO2 and PaCO2 was strong (r = 0.97, P less than 0.0001). Continuous gas sampling for periods up to 5 min did not affect PaCO2, PETCO2, or airway pressures. By use of this new method for measuring end-tidal halothane concentrations in rats approximately 6.5 mo of age, the minimum alveolar concentration of halothane that prevented reflex movement in response to tail clamping was 0.97 +/- 0.04% atmospheric (n = 14). This mass spectrometric technique can be used in small laboratory animals, such as rats, weighing as little as 250 g. Gas monitoring did not distort either PETCO2 or PaCO2. Under the defined conditions of this study, accurate and simultaneous measurements of phasic respiratory concentrations of anesthetic and respiratory gases can be achieved.

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Dantas, Gabriela N., Bianca P. Santarosa, Fernando J. Benesi, Vitor Hugo Santos, and Roberto C. Gonçalves. "Clinical and blood gas analysis of calves conceived by artificial insemination, in vitro fertilization and animal cloning." Pesquisa Veterinária Brasileira 39, no. 7 (July 2019): 485–91. http://dx.doi.org/10.1590/1678-5150-pvb-5971.

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ABSTRACT: In order for successful extra-uterine adaptation to occur, it is necessary for the neonate to be able to establish its respiratory functions effectively, guaranteeing efficient oxygenation and good vitality. Respiratory disorders are the major cause of death during the neonatal period in cattle, and this mortality is even more significant when it comes to calves originated by in vitro fertilization (FIV) or animal cloning (CA). Blood gas analysis assesses acid-base balance changes effectively, and when associated with the neonate’s clinical examination, provides subsidies for accurate diagnosis and early treatment of neonatal maladaptation. The objective of this study was to study neonates born from artificial insemination (IA) and to compare them to calves conceived by FIV and CA, regarding blood gas and clinical examination. For that, 20 AI calves, 15 FIV calves, and 15 cloned calves were evaluated immediately after calving and at 6, 12, 24 and 48 hours of life. At all experimental times, venous blood samples were collected for blood gas and clinical examination was performed. In the postpartum evaluation, Apgar score and column length and respiratory amplitude measurements were used. IVF animals showed no alterations, resembling Group IA calves. The calves from CA showed more pronounced acidosis postpartum than expected physiological acidosis mixed for neonates, with decreasing values of bicarbonate (HCO3-), and base excess (BE) and the increase in carbon dioxide pressure (PCO2) when compared to the other groups. This disorder may have reflected lower mean values of Apgar scores and increased heart and respiratory rates. Intensive follow-up of these neonates is suggested, with monitoring by clinical and hemogasometric examination for early diagnosis of this condition and treatment based on oxygen therapy and bicarbonate replacement.

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Al-Ani, M., A. S. Forkins, J. N. Townend, and J. H. Coote. "Respiratory Sinus Arrhythmia and Central Respiratory Drive in Humans." Clinical Science 90, no. 3 (March 1, 1996): 235–41. http://dx.doi.org/10.1042/cs0900235.

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1. The influence of central inspiratory drive on heart rate variability was investigated in young human subjects using power spectral analysis of R—R intervals. 2. The area of the high-frequency component occurring at the respiratory frequency (0.2–0.25 Hz) in the power spectral density curves was used as an index of respiratory sinus arrhythmia. 3. Central inspiratory drive was increased by breathing a CO2-enriched (5%) gas mixture and this condition was compared with a similar degree of ventilation produced voluntarily. 4. Tests were conducted on eight young subjects with and without low-dose scopolamine (scopoderm TTS) in a double-blind cross-over trial. 5. Scopolamine decreased heart rate and increased the high-frequency peak, suggesting that its main action on the cardiac vagal pathway was a peripheral one, possibly increasing the efficacy of vagal impulses on the cardiac pacemaker. 6. With scopolamine, CO2 breathing increased the area of the high-frequency component significantly more than a similar degree of ventilatory movements produced by voluntary hyperventilation. 7. It is concluded that respiratory sinus arrhythmia in humans is at least partly dependent on a central respiratory—cardiac coupling, most probably similar to that shown in animal studies.

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Seo, Hyo-Chang, Daehyeon Shin, Chae Hun Leem, and Segyeong Joo. "Development of a Portable Respiratory Gas Analyzer for Measuring Indirect Resting Energy Expenditure (REE)." Journal of Healthcare Engineering 2021 (February 17, 2021): 1–10. http://dx.doi.org/10.1155/2021/8870749.

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Objective. A rapidly growing home healthcare market has resulted in the development of many portable or wearable products. Most of these products measure, estimate, or calculate physiologic signals or parameters, such as step counts, blood pressure, or electrocardiogram. One of the most important applications in home healthcare is monitoring one’s metabolic state since the change of metabolic state could reveal minor or major changes in one’s health condition. A simple and noninvasive way to measure metabolism is through breath monitoring. With breath monitoring by breath gas analysis, two important indicators like the respiratory quotient (RQ) and resting energy exposure (REE) can be calculated. Therefore, we developed a portable respiratory gas analyzer for breath monitoring to monitor metabolic state, and the performance of the developed device was tested in a clinical trial. Approach. The subjects consisted of 40 healthy men and women. Subjects begin to measure exhalation gas using Vmax 29 for 15 minutes. After that, subjects begin to measure exhalation gas via the developed respiratory gas analyzer. Finally, the recorded data on the volume of oxygen (VO2), volume of carbon dioxide (VCO2), RQ, and REE were used to validate correlations between Vmax 29 and the developed respiratory gas analyzer. Results. The results showed that the root-mean-square errors (RMSE) values of VCO2, VO2, RQ, and REE are 0.0315, 0.0417, 0.504, and 0.127. Bland-Altman plots showed that most of the VCO2, VO2, RQ, and REE values are within 95% of the significance level. Conclusions. We have successfully developed and tested a portable respiratory gas analyzer for home healthcare. However, there are limitations of the clinical trial; the number of subjects is small in size, and the age and race of subjects are confined. The developed portable respiratory gas analyzer is a cost-efficient method for measuring metabolic state and a new application of home healthcare.

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Chernov, Vladimir I., Evgeniy L. Choynzonov, Denis E. Kulbakin, Elena V. Obkhodskaya, Artem V. Obkhodskiy, Aleksandr S. Popov, Victor I. Sachkov, and Anna S. Sachkova. "Cancer Diagnosis by Neural Network Analysis of Data from Semiconductor Sensors." Diagnostics 10, no. 9 (September 5, 2020): 677. http://dx.doi.org/10.3390/diagnostics10090677.

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“Electronic nose” technology, including technical and software tools to analyze gas mixtures, is promising regarding the diagnosis of malignant neoplasms. This paper presents the research results of breath samples analysis from 59 people, including patients with a confirmed diagnosis of respiratory tract cancer. The research was carried out using a gas analytical system including a sampling device with 14 metal oxide sensors and a computer for data analysis. After digitization and preprocessing, the data were analyzed by a neural network with perceptron architecture. As a result, the accuracy of determining oncological disease was 81.85%, the sensitivity was 90.73%, and the specificity was 61.39%.

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Stolecka, Katarzyna. "Analysis of the Accidental Release of Chlorine." System Safety: Human - Technical Facility - Environment 1, no. 1 (March 1, 2019): 149–55. http://dx.doi.org/10.2478/czoto-2019-0019.

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AbstractDue to its properties, chlorine is one of the highly toxic substances used by humans. This gas attacks the respiratory system, eyes and skin. In higher concentrations, its inhalation leads to death. It is mainly used in water treatment plants where it guarantees a bacteriologically safe water in water supply systems. It is also used as a disinfectant and bleaching agent.The use, transport and storage of chlorine may pose serious hazard associated with its uncontrolled release from technological installations or tanks. The level of this threat will depend on the run of the release scenario or meteorological conditions. The article presents an analysis of the hazards associated with the uncontrolled release of chlorine. The ranges of zones with dangerous level of gas concentration are presented as a result of its instantaneous and continuous release.

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Journal articles on the topic 'Respiratory Gas Analysis'

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