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Basic waveform capnography as a continuous monitoring tool during mechanical ventilation

Article

Author: Joe Hylton, MA, BSRT, RRT-ACCS/NPS, NRP, FAARC, FCCM, Clinical Applications Specialist, Hamilton Medical Inc.

Date of first publication: 15.07.2021

Waveform capnography is no stranger to intensive care/critical care medicine. It is a widely utilized airway management validation tool and is used extensively in the conscious sedation environment, as well as during interfacility transport of intubated patients requiring mechanical ventilation.  Waveform capnography can provide timely, valuable information to a well-trained caregiver.

Basic waveform capnography as a continuous monitoring tool during mechanical ventilation

Physiologic factors affecting end-tidal carbon dioxide (PetCO2)

There are many factors that may affect the amount of carbon dioxide in the end-tidal gas (PetCO2). For the elimination of CO2, there is a close, continuous balance between the production of CO2 in the tissues, its transport in the blood, diffusion into the alveoli, and elimination by ventilation (Kremeier P, Böhm SH, Tusman G. Clinical use of volumetric capnography in mechanically ventilated patients. J Clin Monit Comput. 2020;34(1):7-16. doi:10.1007/s10877-019-00325-91​). Capnography provides a graphical representation of expired CO2 and serves as a noninvasive means of displaying real-time information about the CO2 kinetics in mechanically ventilated patients.

An increase or decrease in the patient's metabolic rate will lead to a change in CO2 production and, therefore, CO2 elimination as well. If both circulation and ventilation are stable - a state which can only be achieved in passive mechanically ventilated patients - CO2 monitoring can be used as an indicator of CO2 production. Fever, sepsis, pain, and seizures are all conditions that increase metabolism, causing a corresponding increase in CO2 production and, in turn, an increase in PetCO2. A decrease in metabolism occurs in patients who are hypothermic, or sedated and paralyzed. This lowers the production of CO2 and may lead to a decrease in PetCO2 if the minute ventilation does not increase at the same time (Gravenstein, J., Jaffe, M., & Paulus, D. (2004). Capnography: Clinical Aspects. New York: Cambridge University Press.2​).

The transport of CO2 to the lungs relies on proper cardiovascular function; therefore, any factor that alters cardiovascular function may also influence CO2 transport to the lungs (Gravenstein, J., Jaffe, M., & Paulus, D. (2004). Capnography: Clinical Aspects. New York: Cambridge University Press.2​).

The removal of CO2 from the lungs to the environment is affected by changes in respiratory function. Obstructive lung diseases, pneumonia, neuromuscular disorders, and central nervous system disorders that result in impaired respiratory function will therefore effect a change in PetCO2 value (Gravenstein, J., Jaffe, M., & Paulus, D. (2004). Capnography: Clinical Aspects. New York: Cambridge University Press.2​).

Types of capnography

The measured CO2 signal can be recorded either as a function of time (time-based capnography) or expired volume (volumetric capnography). The amount of information potentially offered by these two different types of capnography varies significantly. Certain patterns in a time-based capnogram that are considered typical for specific clinical situations have been described in the literature. Some of the common ones are shown below in Figure 1.

However, time-based capnography also has limitations: It cannot provide an accurate estimate of the lung’s ventilation-perfusion status, nor can it be used to estimate the component of physiologic dead space. While not as simple and convenient as time-based capnography, volumetric capnography has the advantage of offering considerably more information.

Diagrams showing capnogram for common states
Figure 1
Diagrams showing capnogram for common states
Figure 1

The volumetric capnogram – shape and phases

The normal shape of a volumetric capnogram consists of three phases. It is important to remember that the capnogram is representative of exhalation.

  • Phase I represents the gas without CO2 from the airways (anatomical and instrument dead space).
  • Phase II is a transitional phase, where gas from the conductive airways is mixed with alveolar gas.
  • Phase III is a plateau phase, consisting of gas from alveoli and slow-emptying lung areas (Gravenstein, J., Jaffe, M., & Paulus, D. (2004). Capnography: Clinical Aspects. New York: Cambridge University Press.2​). A visual representation is shown below in Figure 2.
Diagram showing three phases
Figure 2
Diagram showing three phases
Figure 2

Capnography during transport

Capnography, whether time-based or volumetric, can provide valuable information to optimize monitoring and guide care in the patient requiring intrahospital/interhospital transport. It can be safely utilized with endotracheal tubes, tracheostomy tubes, and many supraglottic airways, provided an effective seal is present. Airway placement and patency, ventilation monitoring, and perfusion status are all areas where PetCO2 provides significant information. Another valuable parameter is the volume of carbon dioxide eliminated per minute (V'CO2), which allows caregivers to assess effective perfusion and volume resuscitative efforts (I-Gnaidy E., Abo El-Nasr, L., Ameen, S., & Abd El-Ghafar, M. (2019). Correlation between Cardon Dioxide Production and Mean Arterial Blood Pressure in Fluid Response in Mechanically Ventilated Patients. Medical Journal of Cairo University, 87(4), 2679-2684.3​).

Capnography in the ICU

In the intensive care unit, waveform capnography can continue monitoring of airway placement and patency, with various airway adjuncts. The dead space to tidal volume ratio (VD/Vt) is an important capnography measurement.  An increasing VD/Vt ratio can represent a potential increase in mortality, based on the level of increase (Kallet RH, Alonso JA, Pittet JF, Matthay MA. Prognostic value of the pulmonary dead-space fraction during the first 6 days of acute respiratory distress syndrome. Respir Care. 2004;49(9):1008-1014. 4​, Nuckton TJ, Alonso JA, Kallet RH, et al. Pulmonary dead-space fraction as a risk factor for death in the acute respiratory distress syndrome. N Engl J Med. 2002;346(17):1281-1286. doi:10.1056/NEJMoa0128355​). Caregivers may utilize the PetCO2 waveform and V’CO2 to optimize lung recruitment, to validate optimal PEEP adjustments, and to identify issues with perfusion (systemic and pulmonary) (Kallet RH, Alonso JA, Pittet JF, Matthay MA. Prognostic value of the pulmonary dead-space fraction during the first 6 days of acute respiratory distress syndrome. Respir Care. 2004;49(9):1008-1014. 4​, Nuckton TJ, Alonso JA, Kallet RH, et al. Pulmonary dead-space fraction as a risk factor for death in the acute respiratory distress syndrome. N Engl J Med. 2002;346(17):1281-1286. doi:10.1056/NEJMoa0128355​, Blankman P, Shono A, Hermans BJ, Wesselius T, Hasan D, Gommers D. Detection of optimal PEEP for equal distribution of tidal volume by volumetric capnography and electrical impedance tomography during decreasing levels of PEEP in post cardiac-surgery patients. Br J Anaesth. 2016;116(6):862-869. doi:10.1093/bja/aew1166​, Nguyen LS, Squara P. Non-Invasive Monitoring of Cardiac Output in Critical Care Medicine. Front Med (Lausanne). 2017;4:200. Published 2017 Nov 20. doi:10.3389/fmed.2017.002007​). V’CO2 can also be utilized during liberation of mechanical ventilation, allowing caregivers to identify potential patient tiring/failure (increasing dead space fraction, inadequate effort, and respiratory muscle tiring). Energy expenditure derived from V’CO2 is an accurate and precise method that caregivers can utilize to calculate nutritional requirements for mechanically ventilated patients (Stapel SN, de Grooth HJ, Alimohamad H, et al. Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept. Crit Care. 2015;19:370. Published 2015 Oct 22. doi:10.1186/s13054-015-1087-28​).

All Hamilton Medical ventilators provide volumetric capnography, either as a standard or optional feature (All models except HAMILTON-MR1A​). The CO2 measurement is performed using a CAPNOSTAT® 5 mainstream CO2 sensor at the patient‘s airway opening. In addition, they offer an overview of all relevant CO2-related values in the Monitoring CO2 window.

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Footnotes

  • A. All models except HAMILTON-MR1

References

  1. 1. Kremeier P, Böhm SH, Tusman G. Clinical use of volumetric capnography in mechanically ventilated patients. J Clin Monit Comput. 2020;34(1):7-16. doi:10.1007/s10877-019-00325-9
  2. 2. Gravenstein, J., Jaffe, M., & Paulus, D. (2004). Capnography: Clinical Aspects. New York: Cambridge University Press.
  3. 3. I-Gnaidy E., Abo El-Nasr, L., Ameen, S., & Abd El-Ghafar, M. (2019). Correlation between Cardon Dioxide Production and Mean Arterial Blood Pressure in Fluid Response in Mechanically Ventilated Patients. Medical Journal of Cairo University, 87(4), 2679-2684.
  4. 4. Kallet RH, Alonso JA, Pittet JF, Matthay MA. Prognostic value of the pulmonary dead-space fraction during the first 6 days of acute respiratory distress syndrome. Respir Care. 2004;49(9):1008-1014.
  5. 5. Nuckton TJ, Alonso JA, Kallet RH, et al. Pulmonary dead-space fraction as a risk factor for death in the acute respiratory distress syndrome. N Engl J Med. 2002;346(17):1281-1286. doi:10.1056/NEJMoa012835
  6. 6. Blankman P, Shono A, Hermans BJ, Wesselius T, Hasan D, Gommers D. Detection of optimal PEEP for equal distribution of tidal volume by volumetric capnography and electrical impedance tomography during decreasing levels of PEEP in post cardiac-surgery patients. Br J Anaesth. 2016;116(6):862-869. doi:10.1093/bja/aew116
  7. 7. Nguyen LS, Squara P. Non-Invasive Monitoring of Cardiac Output in Critical Care Medicine. Front Med (Lausanne). 2017;4:200. Published 2017 Nov 20. doi:10.3389/fmed.2017.00200
  8. 8. Stapel SN, de Grooth HJ, Alimohamad H, et al. Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept. Crit Care. 2015;19:370. Published 2015 Oct 22. doi:10.1186/s13054-015-1087-2

Clinical use of volumetric capnography in mechanically ventilated patients.

Kremeier P, Böhm SH, Tusman G. Clinical use of volumetric capnography in mechanically ventilated patients. J Clin Monit Comput. 2020;34(1):7-16. doi:10.1007/s10877-019-00325-9

Capnography is a first line monitoring system in mechanically ventilated patients. Volumetric capnography supports noninvasive and breath-by-breath information at the bedside using mainstream CO2 and flow sensors placed at the airways opening. This volume-based capnography provides information of important body functions related to the kinetics of carbon dioxide. Volumetric capnography goes one step forward standard respiratory mechanics and provides a new dimension for monitoring of mechanical ventilation. The article discusses the role of volumetric capnography for the clinical monitoring of mechanical ventilation.

Capnography: Clinical Aspects

Gravenstein, J., Jaffe, M., & Paulus, D. (2004). Capnography: Clinical Aspects. New York: Cambridge University Press.

Correlation between Carbon Dioxide Production and Mean Arterial Blood Pressure in Fluid Response in Mechanically Ventilated Patients

I-Gnaidy E., Abo El-Nasr, L., Ameen, S., & Abd El-Ghafar, M. (2019). Correlation between Cardon Dioxide Production and Mean Arterial Blood Pressure in Fluid Response in Mechanically Ventilated Patients. Medical Journal of Cairo University, 87(4), 2679-2684.

Prognostic value of the pulmonary dead-space fraction during the first 6 days of acute respiratory distress syndrome.

Kallet RH, Alonso JA, Pittet JF, Matthay MA. Prognostic value of the pulmonary dead-space fraction during the first 6 days of acute respiratory distress syndrome. Respir Care. 2004;49(9):1008-1014.



BACKGROUND

The ratio of pulmonary dead space to tidal volume (VD/VT) in acute respiratory distress syndrome (ARDS) is reported to be between 0.35 and 0.55. However, VD/VT has seldom been measured with consideration to the evolving pathophysiology of ARDS.

METHODS

We made serial VD/VT measurements with 59 patients who required mechanical ventilation for > or = 6 days. We measured VD/VT within 24 h of the point at which the patient met the American-European Consensus Conference criteria for ARDS, and we repeated the VD/VT measurement on ARDS days 2, 3, and 6 with a bedside metabolic monitor during volume-regulated ventilation. We analyzed the changes in VD/VT over the 6-day period to determine whether VD/VT has a significant association with mortality.

RESULTS

VD/VT was significantly higher in nonsurvivors on day 1 (0.61 +/- 0.09 vs 0.54 +/- 0.08, p < 0.05), day 2 (0.63 +/- 0.09 vs 0.53 +/- 0.09, p < 0.001), day 3 (0.64 +/- 0.09 vs 0.53 +/- 0.09, p < 0.001), and day 6 (0.66 +/- 0.09 vs 0.51 +/- 0.08, p < 0.001).

CONCLUSION

In ARDS a sustained VD/VT elevation is characteristic of nonsurvivors, so dead-space measurements made beyond the first 24 hours may have prognostic value.

Pulmonary dead-space fraction as a risk factor for death in the acute respiratory distress syndrome.

Nuckton TJ, Alonso JA, Kallet RH, et al. Pulmonary dead-space fraction as a risk factor for death in the acute respiratory distress syndrome. N Engl J Med. 2002;346(17):1281-1286. doi:10.1056/NEJMoa012835



BACKGROUND

No single pulmonary-specific variable, including the severity of hypoxemia, has been found to predict the risk of death independently when measured early in the course of the acute respiratory distress syndrome. Because an increase in the pulmonary dead-space fraction has been described in observational studies of the syndrome, we systematically measured the dead-space fraction early in the course of the illness and evaluated its potential association with the risk of death.

METHODS

The dead-space fraction was prospectively measured in 179 intubated patients, a mean (+/-SD) of 10.9+/-7.4 hours after the acute respiratory distress syndrome had developed. Additional clinical and physiological variables were analyzed with the use of multiple logistic regression. The study outcome was mortality before hospital discharge.

RESULTS

The mean dead-space fraction was markedly elevated (0.58+/-0.09) early in the course of the acute respiratory distress syndrome and was higher among patients who died than among those who survived (0.63+/-0.10 vs. 0.54+/-0.09, P<0.001). The dead-space fraction was an independent risk factor for death: for every 0.05 increase, the odds of death increased by 45 percent (odds ratio, 1.45; 95 percent confidence interval, 1.15 to 1.83; P=0.002). The only other independent predictors of an increased risk of death were the Simplified Acute Physiology Score II, an indicator of the severity of illness (odds ratio, 1.06; 95 percent confidence interval, 1.03 to 1.08; P<0.001) and quasistatic respiratory compliance (odds ratio, 1.06; 95 percent confidence interval, 1.01 to 1.10; P=0.01).

CONCLUSIONS

Increased dead-space fraction is a feature of the early phase of the acute respiratory distress syndrome. Elevated values are associated with an increased risk of death.

Detection of optimal PEEP for equal distribution of tidal volume by volumetric capnography and electrical impedance tomography during decreasing levels of PEEP in post cardiac-surgery patients.

Blankman P, Shono A, Hermans BJ, Wesselius T, Hasan D, Gommers D. Detection of optimal PEEP for equal distribution of tidal volume by volumetric capnography and electrical impedance tomography during decreasing levels of PEEP in post cardiac-surgery patients. Br J Anaesth. 2016;116(6):862-869. doi:10.1093/bja/aew116



BACKGROUND

Homogeneous ventilation is important for prevention of ventilator-induced lung injury. Electrical impedance tomography (EIT) has been used to identify optimal PEEP by detection of homogenous ventilation in non-dependent and dependent lung regions. We aimed to compare the ability of volumetric capnography and EIT in detecting homogenous ventilation between these lung regions.

METHODS

Fifteen mechanically-ventilated patients after cardiac surgery were studied. Ventilator settings were adjusted to volume-controlled mode with a fixed tidal volume (Vt) of 6-8 ml kg(-1) predicted body weight. Different PEEP levels were applied (14 to 0 cm H2O, in steps of 2 cm H2O) and blood gases, Vcap and EIT were measured.

RESULTS

Tidal impedance variation of the non-dependent region was highest at 6 cm H2O PEEP, and decreased significantly at 14 cm H2O PEEP indicating decrease in the fraction of Vt in this region. At 12 cm H2O PEEP, homogenous ventilation was seen between both lung regions. Bohr and Enghoff dead space calculations decreased from a PEEP of 10 cm H2O. Alveolar dead space divided by alveolar Vt decreased at PEEP levels ≤6 cm H2O. The normalized slope of phase III significantly changed at PEEP levels ≤4 cm H2O. Airway dead space was higher at higher PEEP levels and decreased at the lower PEEP levels.

CONCLUSIONS

In postoperative cardiac patients, calculated dead space agreed well with EIT to detect the optimal PEEP for an equal distribution of inspired volume, amongst non-dependent and dependent lung regions. Airway dead space reduces at decreasing PEEP levels.

Non-Invasive Monitoring of Cardiac Output in Critical Care Medicine.

Nguyen LS, Squara P. Non-Invasive Monitoring of Cardiac Output in Critical Care Medicine. Front Med (Lausanne). 2017;4:200. Published 2017 Nov 20. doi:10.3389/fmed.2017.00200

Critically ill patients require close hemodynamic monitoring to titrate treatment on a regular basis. It allows administering fluid with parsimony and adjusting inotropes and vasoactive drugs when necessary. Although invasive monitoring is considered as the reference method, non-invasive monitoring presents the obvious advantage of being associated with fewer complications, at the expanse of accuracy, precision, and step-response change. A great many methods and devices are now used over the world, and this article focuses on several of them, providing with a brief review of related underlying physical principles and validation articles analysis. Reviewed methods include electrical bioimpedance and bioreactance, respiratory-derived cardiac output (CO) monitoring technique, pulse wave transit time, ultrasound CO monitoring, multimodal algorithmic estimation, and inductance thoracocardiography. Quality criteria with which devices were reviewed included: accuracy (closeness of agreement between a measurement value and a true value of the measured), precision (closeness of agreement between replicate measurements on the same or similar objects under specified conditions), and step response change (delay between physiological change and its indication). Our conclusion is that the offer of non-invasive monitoring has improved in the past few years, even though further developments are needed to provide clinicians with sufficiently accurate devices for routine use, as alternative to invasive monitoring devices.

Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept.

Stapel SN, de Grooth HJ, Alimohamad H, et al. Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept. Crit Care. 2015;19:370. Published 2015 Oct 22. doi:10.1186/s13054-015-1087-2



INTRODUCTION

Measurement of energy expenditure (EE) is recommended to guide nutrition in critically ill patients. Availability of a gold standard indirect calorimetry is limited, and continuous measurement is unfeasible. Equations used to predict EE are inaccurate. The purpose of this study was to provide proof of concept that EE can be accurately assessed on the basis of ventilator-derived carbon dioxide production (VCO2) and to determine whether this method is more accurate than frequently used predictive equations.

METHODS

In 84 mechanically ventilated critically ill patients, we performed 24-h indirect calorimetry to obtain a gold standard EE. Simultaneously, we collected 24-h ventilator-derived VCO2, extracted the respiratory quotient of the administered nutrition, and calculated EE with a rewritten Weir formula. Bias, precision, and accuracy and inaccuracy rates were determined and compared with four predictive equations: the Harris-Benedict, Faisy, and Penn State University equations and the European Society for Clinical Nutrition and Metabolism (ESPEN) guideline equation of 25 kcal/kg/day.

RESULTS

Mean 24-h indirect calorimetry EE was 1823 ± 408 kcal. EE from ventilator-derived VCO2 was accurate (bias +141 ± 153 kcal/24 h; 7.7 % of gold standard) and more precise than the predictive equations (limits of agreement -166 to +447 kcal/24 h). The 10 % and 15 % accuracy rates were 61 % and 76 %, respectively, which were significantly higher than those of the Harris-Benedict, Faisy, and ESPEN guideline equations. Large errors of more than 30 % inaccuracy did not occur with EE derived from ventilator-derived VCO2. This 30 % inaccuracy rate was significantly lower than that of the predictive equations.

CONCLUSIONS

In critically ill mechanically ventilated patients, assessment of EE based on ventilator-derived VCO2 is accurate and more precise than frequently used predictive equations. It allows for continuous monitoring and is the best alternative to indirect calorimetry.

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