# In Vitro Estimation of Relative Compliance during High-Frequency Oscillatory Ventilation

^{*}

## Abstract

**:**

## Featured Application

**Optimization of the mean pressure setting in high-frequency oscillatory ventilation.**

## Abstract

_{rs}) could be a promising parameter in the evaluation of respiratory system mechanics in HFOV. The aim of this study was to verify in vitro that a change in respiratory system mechanics during HFOV can be monitored by evaluating X

_{rs}. We built an experimental system consisting of a 3100B high-frequency oscillatory ventilator, a physical model of the respiratory system with constant compliance, and a system for pressure and flow measurements. During the experiment, models of different constant compliance were connected to HFOV, and X

_{rs}was derived from the impedance of the physical model that was calculated from the spectral density of airway opening pressure and spectral cross-power density of gas flow and airway opening pressure. The calculated X

_{rs}changed with the change of compliance of the physical model of the respiratory system. This method enabled monitoring of the trend in the respiratory system compliance during HFOV, and has the potential to optimize the mean pressure setting in HFOV in clinical practice.

## 1. Introduction

_{2}O [25]. Nevertheless, this way of setting CDP is quite questionable [25]. As shown in [29], the CDP directly influences the compliance of the lungs, which is also tied to the recruitment (volume) of the lungs [29,30,31]. However, monitoring of the ventilation parameters is very limited in HFOV. For example, the 3100B ventilator (Vyaire Medical, Mettawa, IL, USA), which is commonly used in clinical practice for HFOV, and which was used in this study as well, does not enable monitoring of tidal volume or parameters of lung mechanics, such as lung compliance. This lack of monitoring ability also exists in the 3100A ventilator (Vyaire Medical, Mettawa, IL, USA), which is suitable for the ventilation of neonatal and pediatric patients.

_{rs}) measured using the forced oscillation technique (FOT) is a promising tool for evaluation of the mechanics of the respiratory system in HFOV [20,28]. During FOT, reactance is found using high-frequency pressure oscillations applied at the entrance of the respiratory system, and using the induced flow. Reactance is tied to compliance (C), inertance (L), and frequency of the pressure oscillations (f) according to the equation:

_{rs}to the changes of the lung mechanics in different areas of the respiratory system [33]. The reactance X

_{rs}measured at f = 5 Hz is a sensitive indicator of the changes of the mechanics in peripheral areas of the lungs [33,34,35,36]. Assuming a constant ventilation frequency and proximal airways with constant dimensions and stable shape, we consider the changes of inertance L to be minimal. The first term of Equation (1) is therefore considered to be constant as well. On this assumption, the value of X

_{rs}defined by the equation (1) is inversely proportional to the negative of the value of compliance C of the ventilated system. A higher value of C also means a higher value of X

_{rs}, i.e., X

_{rs}is less negative, which is thus called relative compliance further in this study.

## 2. Materials and Methods

_{2}O, respectively. The measurements were realized in two phases: with and without additional parabolic resistor Rp5 (Michigan Instruments, Grand Rapids, MI, USA), which simulated an increase in the flow resistance of the airways. In the laboratory experiment, we used the following ventilatory parameters: bias flow = 30 L/min, inspiration to expiration time ratio I:E = 1:1, ventilatory frequency f = 5 Hz, CDP = 12 cmH

_{2}O, and amplitude of the pressure oscillations ΔP = 20 cmH

_{2}O. The ventilatory parameters were determined according to [37]. In clinical practice, the CDP and ΔP are titrated at the start of HFOV to reach physiological levels of P

_{a}O

_{2}and P

_{a}CO

_{2}. We did not titrate CDP and ΔP in the ventilation because there was no gas exchange in our in vitro laboratory experiment. Pressure p

_{aw}and flow q

_{aw}of the air were recorded at the entry of the model of the respiratory system using a measuring system designed for HFOV monitoring [38]. The flow was measured as a pressure difference across the orifice. Both p

_{aw}and q

_{aw}signals were recorded using a sampling frequency of 1000 Hz.

_{rs}was calculated based on the power-spectral density S

_{xx}of the pressure and the cross-spectral density S

_{yx}of flow and pressure. The spectral densities were calculated from p

_{aw}and q

_{aw}using windows with a width of 2 s that moved along the signals with a step of 1 s. In the windows, the average value of a signal in the time domain was subtracted from the signal to remove the DC component in the frequency domain. Both spectral densities S

_{xx}and S

_{yx}were calculated using Welch’s averaged modified periodogram method of spectral estimation [39]. When calculating the spectral densities, sections of both signals within the same window were split into eight segments, with a 50% overlap between the neighboring segments. In a particular 2-s window, an i-th sample y

_{K}(i) of the K-th segment of the p

_{aw}or q

_{aw}signal was thus acquired as:

_{aw}or q

_{aw}signal in the window, i has a range of 1 to 444, and K has a range of 1 to 8. Each segment y

_{K}was filtered in the time domain by a low-pass FIR filter using the Hamming window. Fourier transforms P

_{K}and Q

_{K}of y

_{K}were obtained for the pressure and flow signal segments, respectively. Modified periodograms I

_{K}of K-th segment were calculated from P

_{K}and Q

_{K}as:

_{xx}and as:

_{yx}. In equations (3) and (4), P

_{K}* represents a complex conjugate of P

_{K}, w is a column vector of coefficients of the previously used Hamming window, and w

^{T}represents the transpose of w. Finally, the spectral densities S

_{xx}and S

_{yx}were calculated as an average value of I

_{K}in a given window. In the S

_{xx}and S

_{yx}, the frequency f

_{max}corresponding to the maximal power was found. This frequency corresponds with the fundamental waveform (first harmonic frequency) of the oscillations generated by the ventilator, which was set in the study as a nominal frequency f = 5 Hz.

_{rs}was calculating the amplitude Z

_{mag}and the angle Z

_{ang}of the impedance of the respiratory system based on equations [40]:

_{rs}was then calculated by converting the respiratory system impedance from polar coordinates to Cartesian according to Equation (7):

## 3. Results

_{rs}is shown in Figure 2 during the measurement of the modeled respiratory system without (R = 0 cmH

_{2}O∙s/L) and with an added resistor (R = 5 cmH

_{2}O∙s/L), with three sizes of the glass container (54 L, 35 L, and 25 L). The relative compliance X

_{rs}determined from the pressure p

_{aw}and flow q

_{aw}in the respiratory circuit decreased with the value of the volume of the used rigid container, and therefore with decreasing compliance. When measuring with an additional resistor, we detected higher values of X

_{rs}compared to the corresponding measurements without the resistor.

_{rs}for each volume V of used rigid containers are summarized in Table 1 for measurements both with and without an additional resistor.

## 4. Discussion

_{rs}when compared to ventilation of the same rigid container in the model without the added Rp5 resistor. The inertance of a tube of a circular cross-section is inversely proportional to its cross-section. When we added the Rp5 resistor into the model of the respiratory system, we created a narrowing, which not only increased the flow resistance, but also led to an increase of inertance L, therefore increasing X

_{rs}, as shown by Equation (1). Nevertheless, in clinical practice, no major change in airway resistance in ventilated patients is likely to occur during short periods of titrating CDP. Under this assumption, the effect of resistance on the assessment of changes in respiratory system compliance from X

_{rs}can be neglected.

_{rs}analysis for the trend estimation of the respiratory system compliance under stable conditions. In previous studies, the analysis of the spectral density of pressure and flow in the ventilatory circuit was conducted within the experiment on small laboratory animals: rabbits and preterm lambs. Before applying the same method of X

_{rs}analysis on data from large subjects, we wished to evaluate the method on the data acquired under the condition of well-defined and stable lung compliance corresponding to the lung compliance of pediatric and adult patients. Our results were in concordance with [20,28], and suggested that the method of X

_{rs}analysis is also suitable for analysis of pulmonary mechanics of ventilated large laboratory animals.

_{rs}were very low (Table 1), which indicates a good robustness of the algorithm for X

_{rs}calculation. The oscillation of X

_{rs}around the average value was caused by the noise in the measured pressure and flow signals. Table 1 shows that the addition of the resistor into the ventilated system led to an increase in the value of the standard deviation of X

_{rs}. This was caused by an increased noise amplitude in the flow signal after the addition of the resistor, as shown in Figure 3, in which the flow signals without and with the added resistor during one breathing cycle are compared.

_{rs}during HFOV is simple enough to be used bedside. The single component added into the patient circuit is an orifice for pressure and flow measurement. In our study, we used a system that consists of the orifice, sensors, digitizing hardware, and a laptop with evaluation software [38]; in a clinical scenario, any standard monitoring device capable of proximal pressure and flow measurement and real-time data streaming would be feasible. A possible disadvantage of this method is an increase of the flow resistance, together with the dead space when the orifice (used for pressure and flow measurement) is added into the patient circuit. A limitation of our study is that the test used a single ventilator model with a frequency f = 5 Hz. This choice was based on previous studies [33,34,35,36], and we did not investigate the possible use of other ventilatory frequencies.

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

## References

- Meade, M.O.; Young, D.; Hanna, S.; Zhou, Q.; Bachman, T.E.; Bollen, C.; Slutsky, A.S.; Lamb, S.E.; Adhikari, N.K.; Mentzelopoulos, S.D.; et al. Severity of Hypoxemia and Effect of High-Frequency Oscillatory Ventilation in Acute Respiratory Distress Syndrome. Am. J. Respir. Crit. Care Med.
**2017**, 196, 727–733. [Google Scholar] [CrossRef] - Sud, S.; Sud, M.; Friedrich, J.O.; Meade, M.O.; Ferguson, N.D.; Wunsch, H.; Adhikari, N.K. High frequency oscillation in patients with acute lung injury and acute respiratory distress syndrome (ARDS): Systematic review and meta-analysis. BMJ
**2010**, 340, c2327. [Google Scholar] [CrossRef] [Green Version] - Sklar, M.C.; Fan, E.; Goligher, E.C. High-Frequency Oscillatory Ventilation in Adults With ARDS: Past, Present, and Future. Chest
**2017**, 152, 1306–1317. [Google Scholar] [CrossRef] - Ng, J.; Ferguson, N.D. High-frequency oscillatory ventilation: Still a role? Curr. Opin. Crit. Care
**2017**, 23, 175–179. [Google Scholar] [CrossRef] [PubMed] - Goligher, E.C.; Munshi, L.; Adhikari, N.K.; Meade, M.O.; Hodgson, C.L.; Wunsch, H.; Uleryk, E.; Gajic, O.; Amato, M.P.; Ferguson, N.D.; et al. High-Frequency Oscillation for Adult Patients with Acute Respiratory Distress Syndrome. A Systematic Review and Meta-Analysis. Ann. Am. Thorac. Soc.
**2017**, 14, S289–S296. [Google Scholar] [CrossRef] - Wong, J.J.; Liu, S.; Dang, H.; Anantasit, N.; Phan, P.H.; Phumeetham, S.; Qian, S.; Ong, J.S.; Gan, C.S.; Chor, Y.K.; et al. The impact of high frequency oscillatory ventilation on mortality in paediatric acute respiratory distress syndrome. Crit. Care
**2020**, 24, 31. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Angriman, F.; Ferreyro, B.L.; Donaldson, L.; Cuthbertson, B.H.; Ferguson, N.D.; Bollen, C.W.; Bachman, T.E.; Lamontagne, F.; Adhikari, N.K. The harm of high-frequency oscillatory ventilation (HFOV) in ARDS is not related to a high baseline risk of acute cor pulmonale or short-term changes in hemodynamics. Intensive Care Med.
**2020**, 46, 132–134. [Google Scholar] [CrossRef] [PubMed] - Ning, B.; Liang, L.; Lyu, Y.; Yu, Y.; Li, B. The effect of high-frequency oscillatory ventilation or airway pressure release ventilation on children with acute respiratory distress syndrome as a rescue therapy. Transl. Pediatr.
**2020**, 9, 213–220. [Google Scholar] [CrossRef] - Ferguson, N.D.; Cook, D.J.; Guyatt, G.H.; Mehta, S.; Hand, L.; Austin, P.; Zhou, Q.; Matte, A.; Walter, S.D.; Lamontagne, F.; et al. High-frequency oscillation in early acute respiratory distress syndrome. N. Engl. J. Med.
**2013**, 368, 795–805. [Google Scholar] [CrossRef] [Green Version] - Young, D.; Lamb, S.E.; Shah, S.; MacKenzie, I.; Tunnicliffe, W.; Lall, R.; Rowan, K.; Cuthbertson, B.H. High-frequency oscillation for acute respiratory distress syndrome. N. Engl. J. Med.
**2013**, 368, 806–813. [Google Scholar] [CrossRef] [Green Version] - Gu, X.L.; Wu, G.N.; Yao, Y.W.; Shi, D.H.; Song, Y. Is high-frequency oscillatory ventilation more effective and safer than conventional protective ventilation in adult acute respiratory distress syndrome patients? A meta-analysis of randomized controlled trials. Crit. Care
**2014**, 18, R111. [Google Scholar] [CrossRef] [Green Version] - Maitra, S.; Bhattacharjee, S.; Khanna, P.; Baidya, D.K. High-frequency ventilation does not provide mortality benefit in comparison with conventional lung-protective ventilation in acute respiratory distress syndrome: A meta-analysis of the randomized controlled trials. Anesthesiology
**2014**, 122, 841–851. [Google Scholar] [CrossRef] [PubMed] - de Jager, P.; Kamp, T.; Dijkstra, S.K.; Burgerhof, J.G.; Markhorst, D.G.; Curley, M.A.; Cheifetz, I.M.; Kneyber, M.C. Feasibility of an alternative, physiologic, individualized open-lung approach to high-frequency oscillatory ventilation in children. Ann. Intensive Care
**2019**, 9, 9. [Google Scholar] [CrossRef] [PubMed] - de Jager, P.; Burgerhof, J.G.; Koopman, A.A.; Markhorst, D.G.; Kneyber, M.C. Physiologic responses to a staircase lung volume optimization maneuver in pediatric high-frequency oscillatory ventilation. Ann. Intensive Care
**2020**, 10, 153. [Google Scholar] [CrossRef] - Liu, S.; Zhao, Z.; Tan, L.; Wang, L.; Möller, K.; Frerichs, I.; Yu, T.; Huang, Y.; Pan, C.; Yang, Y.; et al. Optimal mean airway pressure during high-frequency oscillatory ventilation in an experimental model of acute respiratory distress syndrome: EIT-based method. Ann. Intensive Care
**2020**, 10, 31. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Lista, G.; Bresesti, I.; Cavigioli, F.; Castoldi, F.; Lupo, E.; LoMauro, A.; Aliverti, A. Efficacy of lung volume optimization maneuver monitored by optoelectronic pletismography in the management of congenital diaphragmatic hernia. Respir. Med. Case Rep.
**2017**, 22, 133–136. [Google Scholar] [CrossRef] - Zannin, E.; Dellaca, R.L.; Dognini, G.; Marconi, L.; Perego, M.; Pillow, J.J.; Tagliabue, P.E.; Ventura, M.L. Effect of frequency on pressure cost of ventilation and gas exchange in newborns receiving high-frequency oscillatory ventilation. Pediatr. Res.
**2017**, 82, 994–999. [Google Scholar] [CrossRef] - Kneyber, M.C.; Markhorst, D.G. Do We Really Know How to Use High-Frequency Oscillatory Ventilation in Critically Ill Children? Am. J. Respir. Crit. Care Med.
**2016**, 193, 1067–1068. [Google Scholar] [CrossRef] - Kneyber, M.C.; Markhorst, D.G. Any trial can (almost) kill a good technique. Intensive Care Med.
**2016**, 42, 1092–1093. [Google Scholar] [CrossRef] - Dellacà, R.L.; Zannin, E.; Ventura, M.L.; Sancini, G.; Pedotti, A.; Tagliabue, P.; Miserocchi, G. Assessment of dynamic mechanical properties of the respiratory system during high-frequency oscillatory ventilation. Crit. Care Med.
**2013**, 41, 2502–2511. [Google Scholar] [CrossRef] - Casserly, B.; McCool, F.D.; Sethi, J.M.; Kawar, E.; Read, R.; Levy, M.M. A method for determining optimal mean airway pressure in high-frequency oscillatory ventilation. Lung
**2013**, 191, 69–76. [Google Scholar] [CrossRef] [PubMed] - van Genderingen, H.R.; van Vught, J.A.; Jansen, J.R.; Duval, E.L.; Markhorst, D.G.; Versprille, A. Oxygenation index, an indicator of optimal distending pressure during high-frequency oscillatory ventilation? Intensive Care Med.
**2002**, 28, 1151–1156. [Google Scholar] [CrossRef] - Goddon, S.; Fujino, Y.; Hromi, J.M.; Kacmarek, R.M. Optimal mean airway pressure during high-frequency oscillation: Predicted by the pressure-volume curve. Anesthesiology
**2001**, 94, 862–869. [Google Scholar] [CrossRef] [PubMed] - Habib, R.H.; Pyon, K.H.; Courtney, S.E. Optimal high-frequency oscillatory ventilation settings by nonlinear lung mechanics analysis. Am. J. Respir. Crit. Care Med.
**2002**, 166, 950–953. [Google Scholar] [CrossRef] [PubMed] - Klapsing, P.; Moerer, O.; Wende, C.; Herrmann, P.; Quintel, M.; Bleckmann, A.; Heuer, J.F. High-frequency oscillatory ventilation guided by transpulmonary pressure in acute respiratory syndrome: An experimental study in pigs. Crit. Care
**2018**, 22, 121. [Google Scholar] [CrossRef] [PubMed] - Klapsing, P.; Moerer, O.; Wende, C.; Herrmann, P.; Quintel, M.; Bleckmann, A.; Heuer, J.F. Setting mean airway pressure during high-frequency oscillatory ventilation according to the static pressure-volume curve in surfactant-deficient lung injury: A computed tomography study. Anesthesiology
**2003**, 99, 1313–1322. [Google Scholar] [CrossRef] [Green Version] - Tingay, D.G.; Mills, J.F.; Morley, C.J.; Pellicano, A.; Dargaville, P.A. Indicators of optimal lung volume during high-frequency oscillatory ventilation in infants. Crit. Care Med.
**2013**, 41, 237–244. [Google Scholar] [CrossRef] - Zannin, E.; Ventura, M.L.; Dellacà, R.L.; Natile, M.; Tagliabue, P.; Perkins, E.J.; Sourial, M.; Bhatia, R.; Dargaville, P.A.; Tingay, D.G. Optimal mean airway pressure during high-frequency oscillatory ventilation determined by measurement of respiratory system reactance. Pediatr. Res.
**2014**, 75, 493–499. [Google Scholar] [CrossRef] [Green Version] - Miedema, M.; de Jongh, F.H.; Frerichs, I.; van Veenendaal, M.B.; van Kaam, A.H. The effect of airway pressure and oscillation amplitude on ventilation in pre-term infants. Eur. Respir. J.
**2012**, 40, 479–484. [Google Scholar] [CrossRef] [Green Version] - Pillow, J.J. Tidal volume, recruitment and compliance in HFOV: Same principles, different frequency. Eur. Respir. J.
**2012**, 40, 291–293. [Google Scholar] [CrossRef] [Green Version] - Kung, S.C.; Hung, Y.L.; Chen, W.L.; Wang, C.M.; Chang, H.C.; Liu, W.L. Effects of Stepwise Lung Recruitment Maneuvers in Patients with Early Acute Respiratory Distress Syndrome: A Prospective, Randomized, Controlled Trial. J. Clin. Med.
**2019**, 8, 231. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Bates, J.H. The Role of Airway Shunt Elastance on the Compartmentalization of Respiratory System Impedance. J. Eng. Sci. Med. Diagn. Ther.
**2019**, 2, 110011–110018. [Google Scholar] [CrossRef] [PubMed] - Brashier, B.; Salvi, S. Measuring lung function using sound waves: Role of the forced oscillation technique and impulse oscillometry system. Breathe
**2015**, 11, 57–65. [Google Scholar] [CrossRef] [PubMed] - Shimoda, T.; Obase, Y.; Nagasaka, Y.; Kishikawa, R.; Mukae, H.; Iwanaga, T. Peripheral bronchial obstruction evaluation in patients with asthma by lung sound analysis and impulse oscillometry. Allergol. Int.
**2017**, 66, 132–138. [Google Scholar] [CrossRef] [PubMed] [Green Version] - Aronsson, D.; Hesselstrand, R.; Bozovic, G.; Wuttge, D.M.; Tufvesson, E. Airway resistance and reactance are affected in systemic sclerosis. Eur. Clin. Respir. J.
**2015**, 2, 28667. [Google Scholar] [CrossRef] [Green Version] - Bhattarai, P.; Myers, S.; Chia, C.; Weber, H.C.; Young, S.; Williams, A.D.; Sohal, S.S. Clinical Application of Forced Oscillation Technique (FOT) in Early Detection of Airway Changes in Smokers. J. Clin. Med.
**2020**, 9, 2778. [Google Scholar] [CrossRef] - Fessler, H.E.; Derdak, S.; Ferguson, N.D.; Hager, D.N.; Kacmarek, R.M.; Thompson, B.T.; Brower, R.G. A protocol for high-frequency oscillatory ventilation in adults: Results from a roundtable discussion. Crit. Care Med.
**2007**, 35, 1649–1654. [Google Scholar] [CrossRef] - Roubik, K. Measuring and evaluating system designed for high-frequency oscillatory ventilation monitoring. Biomed. Tech.
**2014**. [Google Scholar] [CrossRef] - Welch, P. The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Trans. Audio Electroacoust.
**1967**, 15, 70–73. [Google Scholar] [CrossRef] [Green Version] - Michaelson, E.D.; Grassman, E.D.; Wendell, R.P. Pulmonary mechanics by spectral analysis of forced random noise. J. Clin. Invest.
**1975**, 56, 1210–1230. [Google Scholar] [CrossRef] - Rožánek, M.; Horáková, Z.; Čadek, O.; Kučera, M.; Roubík, K. Damping of the dynamic pressure amplitude in the ventilatory circuit during high-frequency oscillatory ventilation. Biomed. Eng. Biomed. Tech.
**2012**, 57, 53–56. [Google Scholar] [CrossRef] [PubMed] - Laviola, M.; Rafl, J.; Rozanek, M.; Kudrna, P.; Roubik, K. Models of PaO2 response to the continuous distending pressure maneuver during high frequency oscillatory ventilation in healthy and ARDS lung model pigs. Exp. Lung Res.
**2016**, 42, 87–94. [Google Scholar] [CrossRef] [PubMed] - Suter, P.M.; Fairley, H.B.; Isenberg, M.D. Optimum endexpiratory airway pressure in patients with acute pulmonary failure. N. Engl. J. Med.
**1975**, 292, 284–289. [Google Scholar] [CrossRef] [PubMed] - Dargaville, P.A.; Rimensberger, P.C.; Frerichs, I. Regional tidal ventilation and compliance during a stepwise vital capacity manoeuvre. Intensive Care Med.
**2010**, 36, 1953–1961. [Google Scholar] [CrossRef] - Dellaca, R.L.; Veneroni, C. Trends in mechanical ventilation: Are we ventilating our patients in the best possible way? Breathe
**2017**, 13, 84–98. [Google Scholar] [CrossRef] - Roubík, K.; Ráfl, J.; van Heerde, M.; Markhorst, D.G. Design and control of a demand flow system assuring spontaneous breathing of a patient connected to an HFO ventilator. IEEE Trans. Biomed. Eng.
**2011**, 58, 3225–3233. [Google Scholar] [CrossRef] - Van Heerde, M.; Roubik, K.; Kopelent, V.; Plötz, F.B.; Markhorst, D.G. Demand flow facilitates spontaneous breathing during high-frequency oscillatory ventilation in a pig model. Crit. Care Med.
**2009**, 37, 1068–1073. [Google Scholar] [CrossRef]

**Figure 2.**The waveform of X

_{rs}when ventilating a model of the respiratory system without an additional resistor (R = 0 cmH

_{2}O∙s/L) and with an additional resistor (R = 5 cmH

_{2}O∙s/L). Three glass containers with different volumes (25, 35, and 54 L) were ventilated with and without the resistor to mimic various compliance of the respiratory system.

**Figure 3.**Comparison of the measured flow signal prior to and after the addition of the Rp5 resistor.

V (L) | X_{rs} with No Resistor | X_{rs} with Added Resistor | ||
---|---|---|---|---|

Mean | SD ^{1} | Mean | SD ^{1} | |

54 | −5.82 | 0.06 | −1.56 | 0.17 |

35 | −12.07 | 0.05 | −8.26 | 0.17 |

25 | −18.76 | 0.06 | −15.62 | 0.17 |

^{1}SD is an abbreviation for standard deviation.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Matejka, J.; Rozanek, M.; Rafl, J.; Kudrna, P.; Roubik, K.
In Vitro Estimation of Relative Compliance during High-Frequency Oscillatory Ventilation. *Appl. Sci.* **2021**, *11*, 899.
https://doi.org/10.3390/app11030899

**AMA Style**

Matejka J, Rozanek M, Rafl J, Kudrna P, Roubik K.
In Vitro Estimation of Relative Compliance during High-Frequency Oscillatory Ventilation. *Applied Sciences*. 2021; 11(3):899.
https://doi.org/10.3390/app11030899

**Chicago/Turabian Style**

Matejka, Jan, Martin Rozanek, Jakub Rafl, Petr Kudrna, and Karel Roubik.
2021. "In Vitro Estimation of Relative Compliance during High-Frequency Oscillatory Ventilation" *Applied Sciences* 11, no. 3: 899.
https://doi.org/10.3390/app11030899