Literature DB >> 33078367

Effects of the Lower Airway Secretions on Airway Opening Pressures and Suction Pressures in Critically Ill COVID-19 Patients: A Computational Simulation.

Zhenglong Chen1, Ming Zhong2, Li Jiang3, Nanshan Chen4, Shengjin Tu4, Yuan Wei4, Ling Sang5, Xia Zheng6, Chunyuan Zhang7, Jiale Tao8, Linhong Deng9, Yuanlin Song10.   

Abstract

In patients with critically ill COVID-19 pneumonia, lower airways are filled with plenty of highly viscous exudates or mucus, leading to airway occlusion. The estimation of airway opening pressures and effective mucus clearance are therefore two issues that clinicians are most concerned about during mechanical ventilation. In this study we retrospectively analyzed respiratory data from 24 critically ill patients with COVID-19 who received invasive mechanical ventilation and recruitment maneuver at Jinyintan Hospital in Wuhan, China. Among 24 patients, the mean inspiratory plateau pressure was 52.4 ± 4.4 cmH2O (mean ± [SD]). Particularly, the capnograms presented an upward slope during the expiratory plateau, indicting the existence of airway obstruction. A computational model of airway opening was subsequently introduced to investigate possible fluid dynamic mechanisms for the extraordinarily high inspiratory plateau pressures among these patients. Our simulation results showed that the predicted airway opening pressures could be as high as 40-50 cmH2O and the suction pressure could exceed 20 kPa as the surface tension and viscosity of secretion simulants markedly increased, likely causing the closures of the distal airways. We concluded that, in some critically ill patients with COVID-19, limiting plateau pressure to 30 cmH2O may not guarantee the opening of airways due to the presence of highly viscous lower airway secretions, not to mention spontaneous inspiratory efforts. Active airway humidification and effective expectorant drugs are therefore strongly recommended during airway management.

Entities:  

Keywords:  Airway mucus; Airway opening pressure; Coronavirus disease 2019; Endotracheal suctioning; Respiratory mechanics

Mesh:

Year:  2020        PMID: 33078367      PMCID: PMC7571532          DOI: 10.1007/s10439-020-02648-0

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


Introduction

The coronavirus disease 2019 (COVID-19) is an infectious respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).2,9,13,32 The World Health Organization (WHO) has declared COVID-19 pandemic a major public health emergency. As of July 2, 2020, a total of 216 countries and regions have reported more than 10.5 million confirmed cases of COVID-19 to WHO, and more than 512,000 people have lost their lives.25 Pathological findings from autopsy or lung biopsy showed that COVID-19 mainly involved injuries at the small airways and alveoli, manifested as: partial detachment of bronchial epithelium, gelatinous mucus attachment in the bronchial lumen, and large amount of sticky mucus and sputum plugs in small airways; jelly-like inflammatory exudates filling in the alveoli, significant proliferation of alveolar epithelial type II cells, desquamation of part pneumocytes, over-inflation of a small number of alveoli, rupture of alveolar septa and cysts formation.20,29,31 These pathological changes were consistent with the main radiological features of patients with COVID 19, such as ground glass opacities, lung consolidation, air bronchograms and white lung appearance. A particularly life-threatening problem for critically ill COVID-19 patients is the presence of excessive airway mucus and jelly-like alveolar exudates that lead to airway obstruction and decreased alveolar gas-exchange function. In such cases, the patients usually require mechanical ventilation at a high level of positive end expiratory pressure (PEEP), and a greater than 50% fraction of inspiratory oxygen (FiO2) to help them breathe, as seen in a large portion of COVID-19 patients admitted to intensive care units (ICUs) in Lombardy, Italy.8 Therefore, how to clear sticky airway mucus and alveolar exudates (hereafter referred to as lower airway secretions) and maintain airway patency has become currently the most urgent issue in the ventilatory management of patients with severe COVID-19. In particular, the clinicians are most concerned with: (1) whether the opening of airways can be guaranteed with limitation of plateau pressure to 30 cmH2O; and (2) whether lower airway secretions can be suctioned out by a fiberoptic bronchoscope (FOB), and if possible, how much negative pressure is needed? Unfortunately, current technology limitations prevent in situ real-time observation and study of the dynamic events of opening in small airways and alveoli during mechanical ventilation. Instead, we used simulated lower airway secretions in a computational model to investigate the effects of changes in surface tension and rheological properties of lower airway mucus on the airway opening pressure and aspiration pressure in both healthy and diseased conditions similar to COVID-19. It is expected that results from this computational simulation could provide a theoretical reference for mechanical ventilation in severe COVID-19 patients, such as those admitted to the ICU at Jinyintan Hospital in Wuhan, China, as reviewed for respiratory data in this report.

Materials and Methods

Study Design and Participants

A single-center, retrospective observational study was performed in a 30-bed ICU at Jinyintan Hospital in Wuhan, China. We retrospectively analyzed patients with laboratory-confirmed SARS-COV-2 infection from Feb 1, 2020, to Mar 15, 2020, who were critically ill, and received invasive mechanical ventilation and lung recruitment maneuver. The Ethics Committee of Jinyintan Hospital approved the study (KY-2020-56.01). Written informed consent was waived due to the retrospective manner of this study.

Interventions

All intubated patients were managed with the lung protective ventilation strategy, setting driving pressure between 15 and 18 cmH2O, and titrating optimal PEEP according to maximal lung compliance.1,16 Once PaO2/FiO2 ratio was lower than 150 mmHg, a lung recruitment maneuver was performed except in patients with unstable hemodynamics or pneumothorax or mediastinal emphysema. To establish a stable hemodynamics, we titrated FiO2 to maintain an oxygen saturation (SpO2) of 88%. If SpO2 could not achieve a target value of 88% or above at a 100% FiO2, a lung recruitment maneuver was initiated with FiO2 set at 100%. During lung recruitment, mechanical ventilation mode was pressure control ventilation at a driving pressure of 15 cmH2O and PEEP of 30–45 cmH2O depending on the patient’s response. PEEP was initially set at 30 cmH2O for 1 min, then returned to 15 cmH2O for a 4-min observational period to check whether there was a response to recruitment maneuver. If no response occurred, we repeated the above recruitment maneuver with an increased PEEP in 5 cmH2O steps until a response emerged. A response to recruitment maneuver was defined as SpO2 no less than 96% or a more than 8% increase in SpO2. And if the maximum PEEP of 45 cmH2O was reached and still there was no response present, recruitment maneuver was terminated to avoid barotrauma and the patient was deemed as a non-responder.

Data Collection

Respiratory system mechanics, end-tidal partial pressure of carbon dioxide (PETCO2), blood gas analysis, and hemodynamic parameters were recorded for each patient immediately before and after lung recruitment maneuver. Subsequent to the lung recruitment maneuver, the patient was examined on chest radiography to rule out possible barotrauma.

Theory and Model of Airway Reopening

Closure of the distal airways at low lung volumes can occur through two mechanisms, namely, “liquid bridge formation” and “compliant collapse”. In the former case, the unstable lining fluid leads to a fluid plug formation spanning the lumen of an undeformed airway. In the latter case, the deformed airway wall bends inward and the lining fluid adheres to the wall. In general, airway closure occurs in terminal bronchioles with the diameters of airways to be as small as 0.25 mm and as large as 2–4 mm.7,14,33 Among several models to describe the fluid dynamics of airway reopening, the most relevant to the clinical observations of the airway opening process is the one developed by Gaver et al. as shown in Fig. 1.4,6,24 In this model, the peripheral airway collapses in a ribbon-like configuration. The open region of a cylindrical airway has radius R, and the lining fluid in the closed portion has thickness H.
Figure 1

Airway reopening model. R is the radius of the flexible-walled tube. H is the thickness of upstream film, and T is imposed axial wall tension. Positive pressure is applied to gas phase, peeling apart the tube at velocity U and opening angle .

Airway reopening model. R is the radius of the flexible-walled tube. H is the thickness of upstream film, and T is imposed axial wall tension. Positive pressure is applied to gas phase, peeling apart the tube at velocity U and opening angle . To reopen this collapsed airway a finger of air must progress through the structure and separate the walls in a peeling motion. From the viewpoint of fluid mechanics, the total pressure () required to displace the viscous lining fluid by the air-liquid meniscus interface mainly includes two components: the capillary pressure and the viscous pressure. Gaver and coworkers further showed that the total pressure can be expressed aswhere and are the surface tension and viscosity of the lining fluid, U represents the velocity of the air finger, and and are the dimensionless capillary and viscous pressures. The dimensionless quantity is defined as the capillary number (or dimensionless velocity), Ca, that represents the relative importance of viscous to surface tension effects on airway reopening. The Eq. (1) clearly shows that: (1) the smaller the airway radius is, the higher ; (2) the faster the airway reopening is, the higher needed; and (3) increases with increasing the surface tension or fluid viscosity. Utilizing in-vitro models of the pulmonary airway reopening, the effects of surface tension and flow properties (viscosity, viscoelasticity, and yield stress) of both Newtonian and non-Newtonian fluids on the airway reopening have been investigated.6,12,21 A typical study by Low at al. tested simulated lining fluids with surface tensions and rheological properties in the range as reported for both healthy and diseased human sputum, and a set of regression equations were obtained that show how the characteristics of the lining fluid and the airway radius influence the opening pressure-velocity relationship (see Table 1).21 These equations were used to roughly estimate the airway reopening pressures in both healthy and diseased conditions in the next section.
Table 1

The dimensionless airway reopening pressure-velocity relationship with various lining fluids.21

Lining fluidThe dimensionless pressure–velocity relationshipCapillary number
Newtonian fluids

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{PR}}/\gamma = 4.39 + 21.96{\text{Ca}}^{0.5} \quad {\text{Ca}} \le 0.75$$\end{document}PR/γ=4.39+21.96Ca0.5Ca0.75 (2a)

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{PR}}/\gamma = 21.29 + 4.81\;{\text{Ca}}\quad 0.75 \le {\text{Ca}} \le 86.56$$\end{document}PR/γ=21.29+4.81Ca0.75Ca86.56 (2b)

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{Ca}} \equiv \mu U/\gamma$$\end{document}CaμU/γ
Shear-Thinning Fluids\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{PR}}/\gamma = 3.42 + 19.06\,{\text{Ca}}_{\text{s}} \quad 0.02 \le {\text{Ca}}_{\text{s}} \le 2.0$$\end{document}PR/γ=3.42+19.06Cas0.02Cas2.0 (3)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{Ca}}_{\text{s}} \equiv \frac{m}{\gamma } \frac{{U^{n} }}{{\left( {0.5H} \right)^{n - 1} }}$$\end{document}CasmγUn0.5Hn-1
Yield stress fluids\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{P}{{\tau_{\text{y}} }} \cdot \frac{R}{H} = 39.06 + 5.66\,{\text{Ca}}_{\text{y}}$$\end{document}Pτy·RH=39.06+5.66Cay (4)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{Ca}}_{\text{y}} \equiv \frac{m}{{\tau_{\text{y}} }} \frac{{U^{n} }}{{\left( {0.5H} \right)^{n} }}$$\end{document}CaymτyUn0.5Hn

dimensionless velocity for Newtonian Fluids, represents the relative magnitudes of the viscous and capillary pressures, dimensionless velocity for shear thinning fluids, dimensionless velocity for yield stress fluids21, H lining fluid film thickness, m consistency parameter, n power-law index, P air finger pressure, R tube radius, , surface tension of lining fluid, , yield stress of lining fluid

The dimensionless airway reopening pressure-velocity relationship with various lining fluids.21 (2a) (2b) dimensionless velocity for Newtonian Fluids, represents the relative magnitudes of the viscous and capillary pressures, dimensionless velocity for shear thinning fluids, dimensionless velocity for yield stress fluids21, H lining fluid film thickness, m consistency parameter, n power-law index, P air finger pressure, R tube radius, , surface tension of lining fluid, , yield stress of lining fluid

Model Parameters

As described above, airway closure might take place at the levels of small bronchi to terminal bronchioles. Thus, we will accordingly calculate the pressures to open 8–14 generation airways according to a Weibel lung geometry. Considering the typical ventilator settings, for example, tidal volume 400 mL and inspiratory time 1 s, and assuming all generations of airways to be in the critical opening state, the average opening velocity Un (n = 8–14) in each generation could be roughly estimated by the total cross-sectional area of the each airway generation. Various types of simulated lower airway secretions are listed in Table 2, including both Newtonian and non-Newtonian fluids. The properties of these simulated lower airway secretions are comparable with those of healthy and diseased respiratory secretions.3,18 One type of secretion simulants, such as sodium carboxymethyl cellulose (SCMC) and polyethylene oxide (PEO),21 behaved like a pseudoplastic fluid and was therefore described by the power-law relationship, , where and m are the shear stress and the consistency of fluid, is the shear rate, and n is a measure of the degree of shear-thinning; the other type of secretion simulants, for example ghee, grease, peanut butter and mayonnaise, showed the behavior of a yield pseudoplastic fluid and was described by the Hershcel-Buckley model, , where is the yield stress.
Table 2

Properties of the simulated lower airway secretions.

Types of secretion simulantsSurface tension (dyn/cm)Consistency parameter (dyn/cm2) snYield stress (dyn/cm2)Power-law index(n)
Newtonian fluids
 Simulated fluid ①25 or 500.0101
 Simulated fluid ②25 or 500.101
 Simulated fluid ③20 or 50101
 Simulated fluid ④20 or 501001
Non-Newtonian fluidsa
 SCMC 1%70.624.900.560
 PEO 3.2%66.741.900.567
 SCMC 2%68.0255.100.375
 Gheeb3.71640.840
 Grease98.12350.618
 Peanut Butter130.84000.705
 Mayonnaise104.16000.471

All the fluid properties were measured at a temperature of 29 °C

aThe rheological parameters of non-Newtonian fluids obtained from Ref. 21, bFor yield pseudoplastic fluids the surface tension was assumed relatively insignificant

Properties of the simulated lower airway secretions. All the fluid properties were measured at a temperature of 29 °C aThe rheological parameters of non-Newtonian fluids obtained from Ref. 21, bFor yield pseudoplastic fluids the surface tension was assumed relatively insignificant

Results

Demographics and Characteristics

A total of 24 patients with COVID-19 were included in this retrospective study (Table 3). The average age was 59.5 ± 11.8 years, and 16 (66.7%) were male. Among those patients responded to lung recruitment maneuver, the minimal and maximal inspiratory plateau pressures were 45 cmH2O and 60 cmH2O, respectively, and the mean was 52.4 ± 4.4 cmH2O (the mean value of PEEP plus a driving pressure of 15 cmH2O). Of note, the alveolar-dead space was calculated as the difference between PaCO2 and PETCO2 divided by PaCO2, the average of which was 45% of tidal volume among patients studied.
Table 3

Demographic and clinical characteristics.

Patient No.Age (year)Sex (M/F)PETCO2 (mmHg)PaCO2 (mmHg)PaO2/FiO2 (mmHg)Cstat (mL/cmH2O)PEEP (cmH2O)FVD (% of VT)
158F691158613350.40
229M367114628300.49
352M43797618450.46
471F48868226350.44
564M377513232350.51
665M28599437350.53
765F265713525400.54
850F366310111450.43
957M488811431400.45
1064M507312319350.32
1150F345215637300.35
1263M376114818350.39
1364M58938628400.38
1453M358312620350.58
1591M37686312450.46
1677M29639421400.54
1769M497211026350.32
1851F36676522400.46
1952M38769029350.50
2061M62916219NA0.32
2147M25595215NA0.58
2255F36775927350.53
2359M34726122NA0.53
2461F57815418400.30
Mean ± SD59.5 ± 11.816M/8F41.2 ± 11.674.2 ± 14.196.5 ± 32.423.1 ± 7.337.4 ± 4.40.45 ± 0.09

PCO end-tidal partial pressure of carbon dioxide, PaCO arterial partial pressure of carbon dioxide, PaO arterial partial pressure of oxygen, FiO inspired oxygen fraction, Cstat static compliance of the respiratory system, PEEP positive end-expiratory pressure, FV alveolar dead space fraction (percent of tidal volume), which is calculated as the ratio of the difference between PaCO2 and PETCO2 to PaCO2, V tidal volume, NA not available

Demographic and clinical characteristics. PCO end-tidal partial pressure of carbon dioxide, PaCO arterial partial pressure of carbon dioxide, PaO arterial partial pressure of oxygen, FiO inspired oxygen fraction, Cstat static compliance of the respiratory system, PEEP positive end-expiratory pressure, FV alveolar dead space fraction (percent of tidal volume), which is calculated as the ratio of the difference between PaCO2 and PETCO2 to PaCO2, V tidal volume, NA not available Figure 2 shows capnograms derived from six critically ill patients with COVID-19. Patients a and c had a relatively normal capnogram shape, the elevation angle of the alveolar plateau was about 31 and 19.5° respectively; whereas in patients b, d, e and f, the CO2 waveform presented a “shark’s fin”27 or spike-like appearance, the elevation angle of the alveolar plateau was approximately 48.5, 66, 59.5, and 72°, respectively. The peak end-tidal carbon dioxide (ETCO2) was 28 and 26 mmHg in patients b and c respectively, slightly lower than normal levels of 35–45 mmHg; whereas the peak was 69 mmHg in patient d, obviously higher than normal values.
Figure 2

Graphic recording of end-tidal CO2 curves in six critically ill patients with COVID-19.

Graphic recording of end-tidal CO2 curves in six critically ill patients with COVID-19.

Airway Reopening Pressures

In a normal lung with the equilibrium surface tension and the viscosity of airway mucus similar to that of water (), the airway reopening pressures of generations 8–14 ranged from 2.1 to 3.8 cmH2O (star in Fig. 3), relatively smaller than the minimal PEEP of 5 cmH2O recommended by the ARDSnet protective ventilatory strategy. However, as the surface tension or viscositiy of the simulated airway secretions increased, the airway reopening pressure increased correspondingly. In particular, if in diseased lung the viscosity of secretions rose to 10 poise (similar to that of medicinal glycerin), the airway reopening pressure of generation 8 may increase to about 36 cmH2O, appreciably exceeding the plateau pressure limitation of 30 cmH2O; if the surface tension simultaneously increased to 50 dyn/cm, the airway reopening pressures of generations 8–14 may be all greater than 35 cmH2O (inverted triangles in Fig. 4), with the maximum reopening pressure of 41.8 cmH2O occurring at generation 8.
Figure 3

Effects of surface tension and viscosity of Newtonian lining liquids on airway reopening pressures. It is assumed that in a normal lung the equilibrium surface tension and viscosity of airway lining fluid are 25 dyn/cm and 0.01 poise, respectively. In a diseased lung, the values of viscosity are assumed to increase to 0.1, 1 or 10 poise. Note that the airway reopening pressures of generations 8–14 are less than 5 cmH2O in a normal lung and that the airway reopening pressure of generation 8 may rise to as high as 36 cmH2O if the value of viscosity increases to 10 poise in a diseased lung. ; .

Figure 4

Effects of surface tension and viscosity of Newtonian lining liquids on airway reopening pressures. It is assumed that in a diseased lung the equilibrium surface tension airway lining fluid increases to 50 dyn/cm and that the viscosity increase from a normal value of 0.01 poise to 0.1, 1 or 10 poise respectively. Note that as compared with Fig. 3, an increased surface tension leads to an increasing in the airway reopening pressures. As the surface tension and viscosity elevates to 50 dyn/cm and 10 poise respectively, the airway reopening pressure of generation 8 may reach 41.8 cmH2O. ; .

Effects of surface tension and viscosity of Newtonian lining liquids on airway reopening pressures. It is assumed that in a normal lung the equilibrium surface tension and viscosity of airway lining fluid are 25 dyn/cm and 0.01 poise, respectively. In a diseased lung, the values of viscosity are assumed to increase to 0.1, 1 or 10 poise. Note that the airway reopening pressures of generations 8–14 are less than 5 cmH2O in a normal lung and that the airway reopening pressure of generation 8 may rise to as high as 36 cmH2O if the value of viscosity increases to 10 poise in a diseased lung. ; . Effects of surface tension and viscosity of Newtonian lining liquids on airway reopening pressures. It is assumed that in a diseased lung the equilibrium surface tension airway lining fluid increases to 50 dyn/cm and that the viscosity increase from a normal value of 0.01 poise to 0.1, 1 or 10 poise respectively. Note that as compared with Fig. 3, an increased surface tension leads to an increasing in the airway reopening pressures. As the surface tension and viscosity elevates to 50 dyn/cm and 10 poise respectively, the airway reopening pressure of generation 8 may reach 41.8 cmH2O. ; . It is interesting to note that although the values of surface tension and consistency of SCMC 2% were all greater than those of simulated fluid ④ (surface tension 68 vs. 50 dyn/cm; consistency 255.1 vs. 10 dyn/cm2 s, see Table 2), the airway reopening pressures of generations 8–14 lining with SCMC 2% were all less than 13 cmH2O in all cases (Fig. 5), apparently lower than those of generations 8–14 lining with simulated fluid ④ (> 35 cmH2O, inverted triangles in Fig. 4). This finding indicated that shear thinning effect may reduce the airway reopening pressure. In addition, Fig. 5 also shows that the airway reopening pressure increased with an increase in the thickness of lining fluid.
Figure 5

The airway reopening pressures of generations 8–14 for non-Newtonian lining liquids (pseudoplastic fluids). Solid line and dash line show the thickness of lining liquids . Of note, although the values of surface tension and consistency of three pseudoplastic fluids were all greater than those of simulated fluid ④ (Table 2), the airway reopening pressures are less than 13 cmH2O, which are appreciably lower than those for simulated fluid ④ (> 35 cmH2O, inverted triangles in Fig. 4), indicating that shear thinning effect may reduce the airway reopening pressure.

The airway reopening pressures of generations 8–14 for non-Newtonian lining liquids (pseudoplastic fluids). Solid line and dash line show the thickness of lining liquids . Of note, although the values of surface tension and consistency of three pseudoplastic fluids were all greater than those of simulated fluid ④ (Table 2), the airway reopening pressures are less than 13 cmH2O, which are appreciably lower than those for simulated fluid ④ (> 35 cmH2O, inverted triangles in Fig. 4), indicating that shear thinning effect may reduce the airway reopening pressure. When the airways were filled with yield stress fluids such as ghee (low consistency) or mayonnaise (small power-law index), the corresponding airway reopening pressures were smaller than 6.5 cmH2O (star and inverted triangle in Fig. 6). But when they were filled with fluids like peanut butter (, and ), the airway reopening pressures may be as high as 30.1 cmH2O or even 48.9 cmH2O (triangle Fig. 6), depending on the thickness of fluid.
Figure 6

The airway reopening pressures of generations 8–14 for non-Newtonian lining liquids (yield pseudoplastic fluids). Solid line and dash line show the thickness of lining liquids . Note that the airway reopening pressures may be as high as 48.9 cmH2O when the airway is filled with peanut butter-like liquid (, and , Table 2). Although mayonnaise has the highest yield stress (, Table 2), the corresponding airway reopening pressures are lower than 6.5 cmH2O due to its strong shear thinning effect (, Table 2).

The airway reopening pressures of generations 8–14 for non-Newtonian lining liquids (yield pseudoplastic fluids). Solid line and dash line show the thickness of lining liquids . Note that the airway reopening pressures may be as high as 48.9 cmH2O when the airway is filled with peanut butter-like liquid (, and , Table 2). Although mayonnaise has the highest yield stress (, Table 2), the corresponding airway reopening pressures are lower than 6.5 cmH2O due to its strong shear thinning effect (, Table 2).

Suction Pressures

The FOB used for the removal of airway secretions generally has an effective length of 550–600 mm and a 3.5–5 mm tip diameter. It can be inserted down to segmental or small bronchi (generations 4–5) at most. In each endotracheal suctioning procedure, the suctioning time is generally not more than 15 s, and negative pressure applied is usually 7–10 kPa, allowing a maximal pressure of 13 kPa.19 When performing suction of airway secretions, the patient are normally in the supine position, and therefore the gravity has an insignificant effect on the movement of secretions along the catheter. Unless 5 to 4 generations of airways are completely occluded by secretions, there is always an air-liquid interface between the tip of FOB and secretions. Therefore, the suction pressure must overcome the capillary force generated by the surface tension of the air-liquid interface and the viscous friction in the fluid. Theoretical and experimental studies by Gaver and Yap showed that an apparent “yield pressure” must be exceeded before airway occlusion fluids started to flow.6,33 This yield pressure is determined by the equation, where K is the geometric parameter that relates the airway radius (R) to the radius of curvature of the meniscal air-liquid, . As such, we made a rough estimation of yield pressures for airway generations 8 to 14 in the case of secretions to be Newtonian fluids (Table 2). These results are shown in Fig. 7. Of note, cartilage disappears anatomically from the airway wall beyond the eleventh generation and air passages are directly embedded in the lung parenchyma. Yap et al.33 found that the critical transmural pressure () required to prevent compliant collapse of noncartilaginous 2- to 3-mm airways was approximately 7.5 cmH2O. However, it can be seen from Fig. 7 that when the surface tension increased to in diseased conditions, yield pressure needed to begin occlusion fluids motion is already higher than the critical transmural pressure of 7.5 cmH2O. This means that before occlusion fluids flow, compliant collapse of the airway has very likely taken place, which hence impedes an effective removal of lower airway secretions.
Figure 7

The yield pressures of 8 to 14 generations of airways with surface tension of occlusion fluids . The dash line indicates the critical transmural pressure needed to prevent compliant collapse of airways.

The yield pressures of 8 to 14 generations of airways with surface tension of occlusion fluids . The dash line indicates the critical transmural pressure needed to prevent compliant collapse of airways. Next, we calculate the pressure drop when the secretions pass through the suction catheter in the FOB. Let the working length (L) and the inner diameter of the suction catheter (d) be 60 cm and 2 mm, respectively. If the duration of suctioning is 15 s, then the movement speed of secretions (U) must be greater than 4 cm/s. As a relatively conservative estimation, we consider the volume of secretions aspirated into the FOB just to be 0.2 mL, which corresponds an approximately 6.4 cm-long secretions column. Then, the loss of pressure head can be calculated by Poiseuille’s Lawwhere is the viscosity of secretions. Substituting the corresponding values into Eq. (5), we obtained the relationship between the loss of pressure head and the viscosity of secretions shown in Table 4.
Table 4

Relationship between pressure loss and viscosity of secretions.

Type of secretionsViscosity (poise)Movement speed (cm/s)Pressure loss (kPa)
Purified water at 20 °C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim 0.01$$\end{document}0.0140.020
Cocoa butter at 45 °C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim 0.1$$\end{document}0.140.204
Cream 50% fat content at 16 °C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim 1$$\end{document}142.037
Medicinal glycerin at 25 °C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim 10$$\end{document}10420.37
Relationship between pressure loss and viscosity of secretions.

Discussion

Based on the computational and experimental models of pulmonary airway opening, this study examined the effects of physical properties of lower airway secretions on airway reopening pressures and suction pressures. Our results showed that the airway reopening pressure was dependent on surface tension of the air–liquid interface, consistency and yield stress of secretions, the volume of secretions, airway radius as well as airway opening velocity. In a healthy lung with and poise, the predicted airway reopening pressures for generations 8–14 range between 2.1 and 3.8 cmH2O; however, if in diseases like COVID-19 the viscosity of lower airway secretions increased by three orders of magnitude to 10 poise, similar to that of medicinal glycerin, the predicted airway reopening pressure may reach as high as 35–42 cmH2O, even 30–49 cmH2O if lower airway secretions become like peanut butter. Accordingly, the loss of pressure head during endotracheal suctioning may exceed 20 kPa, making it almost impossible to remove sticky secretions. For some critically ill patients with COVID-19, limiting plateau pressure to 30 cmH2O under a lung-protective ventilation strategy might not guarantee a complete opening of the pulmonary airways and an improved oxygenation, leading to the failure of mechanical ventilation.

Validity of the Computational Model

We first discussed the possible ranges of surface tension and rheological parameters of lower airway secretions in COVID-19 patients. Due to a lack of direct measurement of surface properties of alveolar exudates and airway mucus in patients with COVID-19, surface tension and rheology of the simulated lower airway secretions in this simulation study were referred to reported literature values of human mucus in patients with chronic bronchitis, bronchiectasis, pneumonia, cystic fibrosis and ARDS. But considering the fact that a portion of patients with relatively severe COVID-19 pneumonia progress to ARDS and that COVID-19 pneumonia is essentially a lung inflammation caused by viral infections,30 we therefore speculate that the composition of pulmonary secretions is basically similar across diseases mentioned above, mainly including mucins, plasma proteins, inflammatory cells, DNA, actin, bacteria, viruses and so on.15 As such, the real values of surface tension and rheological parameters should fall within the range discussed in this study. Macklem et al. found the airway opening pressure for 0.5-mm-diameter airways ranged from 5–9 cmH2O when pulmonary surfactant were present.23 If we assume the equilibrium surface tension to be , this opening pressure correspond to 5–9 , in good agreement with capillary pressure term  in equation (2a). Using this regression relationship, we can further obtain the opening pressure to be about 5.6 cmH2O for airways 0.5 mm in diameter. Crotti et al. studied threshold opening pressures (TOPs) for lung recruitment in five ALI/ARDS patients and found that in three patients, the maximal frequency of estimated TOPs was around 20 cmH2O, and in the other two patients, this maximal frequency occurred at 30–35 cmH2O.5 Among 24 critically ill patients with COVID-19 pneumonia in our study, the average of inspiratory plateau pressure applied in lung recruitment maneuver was 52.4 ± 4.4 cmH2O, very close to the maximum estimate of the airway reopening pressure 49 cmH2O under the condition that small airways were occluded by fluids like peanut butter (Fig. 6). This suggests that the changes in properties of lower airway secretions might be a mechanism responsible for high airway opening pressures in a majority of severe patients with COVID-19. This speculation can be further supported by low static compliance (mean ± [SD], 23.1 ± 7.3 mL/cmH2O, Table 3), high alveolar dead space fraction (45 ± 9 percent of tidal volume, Table 3), and particularly the CO2 waveform, whose shape relates to the airflow and emptying characteristics of the lung during each breath (Fig. 2).17 A decreased slope of the initial expiratory phase or a greater elevation angle of the expiratory plateau in capnograms indicate the existence of airway obstruction in patients with COVID-19 (panel d–f in Fig. 2), while in some other patients, ETCO2 level reduced likely due to an increase in ventilation of dead space (panel b and c in Fig. 2). Finally, it can be seen from Table 3 that despite a plateau pressure of 45–60 cmH2O, oxygen saturation of blood in these patients did not improve. These study data and clinical findings justify the present computational model.

Limitations

Our study has several limitations. First, estimation of the shear rates in Eqs. (2)–(4) may deviate from the real values at airway opening. In vitro model experiments have shown that the shear rates at airway opening are dependent on the type and thickness of the lining fluid as well as airway radius; second, we are unable to measure in situ the surface tension and viscosity of lower airway secretions in patients with COVID-19 for the time being because of the lack of a suitable measuring instrument, even data from in vitro measurement of the viscosity of secretions have not been reported due to barely accessible secretions samples. Third, in estimating the critical opening velocity in each generation, we assumed that lung was homogenous and all airways of each generation were in the critical opening state. Actually, lungs of COVID-19 patients should be highly heterogeneous, and therefore the opening time and velocity in each generation must be different. Suki et al.28 demonstrated that airway openings occur in a series of avalanches whose magnitudes follow power-law distributions. The triggering of the avalanche process depends on the magnitude and timing of pressure excursions applied at the airway entrance during mechanical ventilation. On one hand, it should be noted that the real human bronchial tree is anatomically asymmetrical, that is, the number of divisions from the trachea to end branches varies along the different branch pathways. Under these circumstances flow in any branch is proportional the number of end branches for that branch, as described in the Horsfield model.10,11 This asymmetry of flow distribution among bronchial tree would lead to the difference in the airway opening velocities, which may in turn give rise to the different airway opening pressures even between daughter branches of a given generation. On the other hand, the current model of the airway reopening is static. In fact, the reopening of the collapsed airway is a dynamic process. Studies4,6,12 found that airway opening times range from tens to hundreds of milliseconds depending on inflation pressure, and particularly on physical properties of airway surface liquid in the patients with COVID-19. If the time course of the airway opening is long in a given airway opening pressure, so that the airway remains closed for a significant portion of inhalation, the improvements in oxygenation will still be small. As a result, a dynamic model taking the asymmetry of airway structure and airway opening time into account awaits further research. Finally, we only considered the loss of pressure along the suction catheter caused by a very small amount of secretions (0.2 mL). In fact, the pressure loss from the alveoli upward to the tip of FOB is relatively greater due to smaller radii of these airways and bigger total length of airways (> 5.5 cm) in Eq. (5). Taken together, we actually underestimated to a large extent the pressure loss during endotracheal suctioning.

Conclusions

The results of current computational simulations provided a possible explanation for what we have observed in the clinical treatment of patients with COVID-19 pneumonia—patients died suddenly in their activities of daily life such as defecating, eating or holding their breath. It was very likely that an acute increase of intrathoracic pressure in these activities resulted in massive atelectasis. The maximal transpulmonary pressure is approximately 25–30 cmH2O in a healthy adult during spontaneous respiration,22 which is considerably less than the predicted airway opening pressures, probably 30–49 cmH2O, in the presence of sticky lower airway secretions. As a result patients could not open their lungs and eventually died from suffocation like drowning. So can we suction these sticky secretions out of the distal airways? The current simulation data showed clearly that if the viscosity of mucus or secretions rose to the order of magnitude of about 10 poise, similar to that of medicinal glycerin at room temperature, it was impossible to pump mucus or secretions out of the deep airways by a FOB at the routine negative pressure of 7–13 kPa. Active airway humidification is therefore suggested during airway management in critically ill patients with COVID-19. We also recommend using effective expectorant drugs to dissolve mucus plugs and reduce mucus or secretion viscosity. During the subsequent mechanical ventilation, the settings of personalized plateau pressure or PEEP should be based on the apparent viscosity of mucus or secretions suctioned. For those who have a relatively high-viscosity lower airway secretions, other treatment regimens such as lung recruitment or extracorporeal membrane oxygenation (ECMO) should be considered as early as possible.26
  30 in total

1.  Recruitment and derecruitment during acute respiratory failure: a clinical study.

Authors:  S Crotti; D Mascheroni; P Caironi; P Pelosi; G Ronzoni; M Mondino; J J Marini; L Gattinoni
Journal:  Am J Respir Crit Care Med       Date:  2001-07-01       Impact factor: 21.405

2.  Role of viscoelasticity in the tube model of airway reopening. II. Non-Newtonian gels and airway simulation.

Authors:  S H Hsu; K P Strohl; M A Haxhiu; A M Jamieson
Journal:  J Appl Physiol (1985)       Date:  1996-05

3.  Site of airway closure in excised dog lungs: histologic demonstration.

Authors:  J M Hughes; D Y Rosenzweig; P B Kivitz
Journal:  J Appl Physiol       Date:  1970-09       Impact factor: 3.531

4.  Management of Critically Ill Adults With COVID-19.

Authors:  Jason T Poston; Bhakti K Patel; Andrew M Davis
Journal:  JAMA       Date:  2020-03-26       Impact factor: 56.272

5.  Role of pulmonary surfactant in airway closure: a computational study.

Authors:  D R Otis; M Johnson; T J Pedley; R D Kamm
Journal:  J Appl Physiol (1985)       Date:  1993-09

6.  Baseline Characteristics and Outcomes of 1591 Patients Infected With SARS-CoV-2 Admitted to ICUs of the Lombardy Region, Italy.

Authors:  Giacomo Grasselli; Alberto Zangrillo; Alberto Zanella; Massimo Antonelli; Luca Cabrini; Antonio Castelli; Danilo Cereda; Antonio Coluccello; Giuseppe Foti; Roberto Fumagalli; Giorgio Iotti; Nicola Latronico; Luca Lorini; Stefano Merler; Giuseppe Natalini; Alessandra Piatti; Marco Vito Ranieri; Anna Mara Scandroglio; Enrico Storti; Maurizio Cecconi; Antonio Pesenti
Journal:  JAMA       Date:  2020-04-28       Impact factor: 56.272

Review 7.  Micro- and macrorheology of mucus.

Authors:  Samuel K Lai; Ying-Ying Wang; Denis Wirtz; Justin Hanes
Journal:  Adv Drug Deliv Rev       Date:  2009-01-03       Impact factor: 15.470

8.  Effectiveness and side effects of closed and open suctioning: an experimental evaluation.

Authors:  Sophie Lindgren; Birgitta Almgren; Marieann Högman; Sven Lethvall; Erik Houltz; Stefan Lundin; Ola Stenqvist
Journal:  Intensive Care Med       Date:  2004-02-24       Impact factor: 17.440

9.  Gross examination report of a COVID-19 death autopsy.

Authors:  Q Liu; R S Wang; G Q Qu; Y Y Wang; P Liu; Y Z Zhu; G Fei; L Ren; Y W Zhou; L Liu
Journal:  Fa Yi Xue Za Zhi       Date:  2020-02-25

10.  Pathological findings of COVID-19 associated with acute respiratory distress syndrome.

Authors:  Zhe Xu; Lei Shi; Yijin Wang; Jiyuan Zhang; Lei Huang; Chao Zhang; Shuhong Liu; Peng Zhao; Hongxia Liu; Li Zhu; Yanhong Tai; Changqing Bai; Tingting Gao; Jinwen Song; Peng Xia; Jinghui Dong; Jingmin Zhao; Fu-Sheng Wang
Journal:  Lancet Respir Med       Date:  2020-02-18       Impact factor: 30.700

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  5 in total

1.  Publications About COVID-19 Research by the BME Community.

Authors:  Carly Norris
Journal:  Ann Biomed Eng       Date:  2022-09-06       Impact factor: 4.219

Review 2.  A Tribute to Ajit Yoganathan's Cardiovascular Fluid Mechanics Lab: A Survey of Its Contributions to Our Understanding of the Physiology and Management of Single-Ventricle Patients.

Authors:  Peter E Hammer; David M Hoganson; Pedro J Del Nido
Journal:  Cardiovasc Eng Technol       Date:  2021-05-20       Impact factor: 2.495

3.  Detection of COVID-19 from CT and Chest X-ray Images Using Deep Learning Models.

Authors:  Wassim Zouch; Dhouha Sagga; Amira Echtioui; Rafik Khemakhem; Mohamed Ghorbel; Chokri Mhiri; Ahmed Ben Hamida
Journal:  Ann Biomed Eng       Date:  2022-04-12       Impact factor: 3.934

4.  Active Versus Passive Flow Control in UVC FILTERs for COVID-19 Containment.

Authors:  E Moreno; G Klochok; S García
Journal:  Ann Biomed Eng       Date:  2021-06-30       Impact factor: 3.934

5.  A Fully-Automated Method to Evaluate Coronavirus Disease Progression with COVID-19 Cough Sounds Using Minimal Phase Information.

Authors:  Farook Sattar
Journal:  Ann Biomed Eng       Date:  2021-06-03       Impact factor: 3.934

  5 in total

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