Abstract
Background
High drive and high effort during spontaneous breathing can generate patient self-inflicted lung injury (P-SILI) due to uncontrolled high transpulmonary and transvascular pressures, with deterioration of respiratory failure. P-SILI has been demonstrated in experimental studies and supported in recent computational models. Different treatment strategies have been proposed according to the phenotype of elastance of the respiratory system (Ers) for patients with COVID-19. This study aimed to investigate the effect of three spontaneous ventilation modes on respiratory drive and muscle effort in clinical practice and their relationship with different phenotypes. This was achieved by obtaining the following respiratory signals: airway pressure (Paw), flow (V´) and volume (V) and calculating muscle pressure (Pmus).
Methods
A physiologic observational study of a series of cases in a university medical-surgical ICU involving 11 mechanically ventilated patients with COVID-19 pneumonia at the initiation of spontaneous breathing was conducted. Three spontaneous ventilation modes were evaluated in each of the patients: pressure support ventilation (PSV), airway pressure release ventilation (APRV), and BiLevel positive airway pressure ventilation (BIPAP). Pmus was calculated through the equation of motion. For this purpose, we acquired the signals of Paw, V´ and V directly from the data transmission protocol of the ventilator (Dräger). The main physiological measurements were calculation of the respiratory drive (P0.1), muscle effort through the ΔPmus, pressure‒time product (PTP/min) and work of breathing of the patient in joules multiplied by respiratory frequency (WOBp, J/min).
Results
Ten mechanically ventilated patients with COVID-19 pneumonia at the initiation of spontaneous breathing were evaluated. Our results showed similar high drive and muscle effort in each of the spontaneous ventilatory modes tested, without significant differences between them: median (IQR): P0.1 6.28 (4.92–7.44) cm H2O, ∆Pmus 13.48 (11.09–17.81) cm H2O, PTP 166.29 (124.02–253.33) cm H2O*sec/min, and WOBp 12.76 (7.46–18.04) J/min. High drive and effort were found in patients even with low Ers. There was a significant relationship between respiratory drive and WOBp and Ers, though the coefficient of variation widely varied.
Conclusions
In our study, none of the spontaneous ventilatory methods tested succeeded in reducing high respiratory drive or muscle effort, regardless of the Ers, with subsequent risk of P-SILI.
Keywords: COVID-19 pneumonia, Muscle pressure, Respiratory drive, Muscle effort, Respiratory muscle monitoring, Mechanical ventilation, Respiratory mechanics, Patient self-inflicted lung injury (P-SILI)
Background
An increase in respiratory drive has been described for COVID-19 patients with moderate or severe respiratory failure [1]. The strong efforts of these patients are noteworthy and compatible with the development of potential patient self-inflicted lung injury (P-SILI) due to uncontrolled transpulmonary and transvascular pressures [2], such as deterioration and relapses of respiratory failure [1]. To induce hyperventilation in experimental settings, Mascheroni et al. [3] infused salicylate into the brainstem of spontaneously breathing sheep. The increase in minute ventilation produced lung injury, which was prevented by sedation and paralysis on controlled mechanical ventilation. In addition, two patterns of Ers have been described in such patients: high and low Ers [4]. Based on the P-SILI hypothesis and Ers, different authors have advocated for radical changes in respiratory management [4, 5]. However, the respiratory mechanics just before switching to spontaneous breathing or at the time of estimation of the respiratory drive, as well as the relationship between both, have not been sufficiently studied. P-SILI in COVID-19 has been evaluated in a computational model, which demonstrated that inspiratory effort is comparable with that associated with ventilator-induced injury [6].
Identifying strategies that can mitigate progression of lung injury is of interest for these patients. The aim of the present work was to evaluate the impact of different spontaneous ventilation modes on the respiratory response regarding respiratory drive, muscle effort, and WOBp in mechanically ventilated COVID-19 patients via direct acquisition of monitored respiratory signals from ventilators: Paw, V´ and V. The goal was to evaluate possible reduction in muscle effort, as well as its relationship with the Ers of the respiratory system (Ers). This study focused on inspiratory muscle activity by calculating muscle pressure (Pmus); we thus avoided more invasive manoeuvres with a risk of contamination and contagion, such as oesophageal catheters. Some of the results of this study have been previously reported in abstract form [7].
Methods
Design of the study
The present study was conceived as a case series of physiological analyses from a single centre in the medical-surgical intensive care unit (ICU). The study was included in the original project on muscle pressure approved by the local Ethics Committee of the Hospital Reina Sofía Córdoba, with reference PM-12. All patients and/or their surrogates were informed, and written consent was given prior to inclusion in the study.
Study population
We considered eligible for inclusion all consecutive patients older than 18 years admitted to the ICU with a confirmed diagnosis of COVID-19 (by real-time PCR) who were on assisted mechanical ventilation with pressure support ventilation (PSV) or suitable for PSV as per clinical decision. All patients were ventilated with an Evita 2D or XL ventilator (Dräger Medical, Lübeck, Germany). Sedation was titrated to achieve a level on the Richmond Agitation and Sedation Scale (RASS) of -2 to -3. All patients were admitted to the ICU from the hospitalization ward.
Study procedures
Data acquisition
We collected demographic data (age, sex, body mass index [BMI]), comorbidities, severity scores (APACHE II) upon ICU admission, chronology (time on ICU admission and mechanical ventilation), vital signs, laboratory parameters, and outcome.
Respiratory signals
Paw, V’ and V were recorded using the Medibus® protocol of the Evita 2D or XL® Dräger ventilator at a sampling rate of 125 Hz using personal software.
After clinical stabilization under assist-volume control mode (ACV), three spontaneous breathing trials were performed in random order for all patients. Ventilator settings during spontaneous breathing were as follows:
PSV 10 (5–15) cm H2O with PEEP 10 cm H2O.
APRV High pressure 20 cm H2O, time at inspiration for ≅ 90% of each respiratory cycle and the time at expiration set to finish at 75% of the peak expiratory flow; thus, the time low was sufficiently brief to maintain PEEP.
BiLevel (BIPAP®) 20 on 10 cm H2O, inspiratory/expiratory time ≅ 2.5/1.
In this way, the delta pressure (ΔP) was maintained at a safety threshold < 15 cm H2O [8]. Spontaneous ventilation modes were stopped if any sign of poor tolerance occurred, such as tachypnoea > 35 respiratory rate (RR), clinical signs of muscle fatigue, altered level of consciousness or SpO2 < 92%. Between each test, the patient was ventilated in the ACV for 20–30 min to achieve a cardiorespiratory status equivalent to baseline. The time period of recording was 60 min in each ventilatory mode.
Physiological measurements
The three components of the equation of motion (EM) for the respiratory system, elastance of the respiratory system (Ers), total resistances (Rrs) and total PEEP (PEEPt), were obtained in the passive mode using multiple linear regressions between Paw, V´ and V by the least square fitting method. In addition, in each of the spontaneous modes tested, Ers and Rrs were obtained for accurate calculation of Pmus. In spontaneous modes, we use the inspiratory and expiratory occlusion manoeuvres for Ers and measurement of the time constant (t), as the time required for 25–75% of the exhaled volume, to obtain Rrs [9]. PEEPt during spontaneous breathing modes was obtained by the end-inspiration occlusion method through the formula Pplat, aw = Elastic pressure (Pel) + PEEPt [10], Pel = V * Ers. In this way, the signals of Pmus and total distending pressure were obtained according to the formula PDist_EM = Ers*V + V’*Rrs + PEEPt. Pmus = Paw – PDist_EM. The mean PDist_EM was assumed to be an estimate of the total lung and chest wall stress. According to the standard elastance of the chest wall (Ecw), the main component of the distending pressure corresponds to the total lung stress.
Parameters related to the respiratory drive (P0.1), effort (ΔPmus, PTP/min), work of breathing (WOBp) as joules/min, and breathing pattern were calculated in each ventilatory mode, cycle by cycle, as computed according to the following formulas:
P0.1 = ∆Poccl cm H2O (100 ms),
,
.
The inspiratory period was obtained through the flow signal from the onset of the inspiratory flow to the cycling off at flow zero.
Measurements were repeated at least three times for the occlusion manoeuvre, inspiratory and expiratory, separated by at least 1 min, and the average values were recorded. The analysed period corresponded to an average of 500 ± 23 breath cycles in each mode and patient.
Statistical analysis
Continuous variables are expressed as the median and interquartile range (IQR). Data were compared by one-way repeated measure ANOVA with the rank sum test because of the small sample size. Linear regression was used to assess the relationship between respiratory drive and WOBp with respect to Ers. Basic calculations were performed in Excel v.2019. Sigmaplot v.14 was used for statistical analysis.
Results
Patients
Eleven mechanically ventilated patients with COVID-19 pneumonia admitted to the ICU over a 2-month period (April–May 2020), corresponding to the first wave in Spain, were considered for inclusion. One patient was excluded because he was on treatment with venovenous extracorporeal membrane oxygenation (VV-ECMO). A total of 10 patients were studied. A physiological study comparing the three ventilation modes was performed in each of the patients studied. The study protocol was successfully applied to all patients. The characteristics of the patients are displayed in Table 1. They had been in the clinical ward for a median of 4 (2–7) days, and they had received respiratory treatment with high nasal flow and/or noninvasive ventilation.
Table 1.
Patient (N) | Sex | Age (yr) | Apache II score | BMI (Kg/m2) | Comorbidities | Days on ventilator | pH | PaO2/FiO2 (mmHg) | FiO2 | PCO2 (mmHg) | Lactic mmol/L |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | M | 53 | 20 | 35 | Kidney transplantation | 10 | 7.48 | 198 | 0.4 | 35 | 0.60 |
2 | M | 57 | 18 | 32 | Hypertension | 10 | 7.14 | 193 | 0.4 | 70 | 1.72 |
3 | F | 76 | 17 | 26 | Hypertension | 5 | 7.25 | 273 | 0.4 | 62 | 1.10 |
4 | M | 60 | 15 | 28 | Hypertension | 24 | 7.25 | 185 | 0.4 | 54 | 0.70 |
5 | F | 66 | 19 | 35 | Diabetes | 22 | 7.39 | 167 | 0.6 | 63 | 1.81 |
6 | M | 52 | 21 | 30 | Lymphoma | 6 | 7.33 | 193 | 0.4 | 40 | 1.43 |
7 | F | 76 | 18 | 27 | Hypertension | 5 | 7.43 | 154 | 0.5 | 54 | 0.90 |
8 | M | 47 | 20 | 30 | COPD | 26 | 7.27 | 164 | 0.5 | 32 | 0.54 |
9 | M | 61 | 19 | 27 | Abdominal surgery | 14 | 7.43 | 266 | 0.35 | 47 | 1.21 |
10 | F | 69 | 21 | 28 | Abdominal surgery | 19 | 7.26 | 156 | 0.45 | 60 | 1.21 |
Median (IQR) | 61 (53–71) | 19 (18–20) | 29 (27–33) | 12 (6–23) | 7.30 (7.25–7.43) | 189 (162–267) | 0.40 (0.40–0.50) | 54 (39–62) | 1.15 (0.67–1.50) |
Results are presented as median and interquartile range (IRQ)
F Female, M Male, BMI body mass index, COPD Chronic obstructive pulmonary disease, FiO2 Fractional inspired oxygen tension
Respiratory parameters, respiratory drive and inspiratory muscle efforts
The results of the respiratory parameters of the applied ventilation modes are given in Table 2. There were no significant differences between the various strategy trials in terms of parameters related to respiratory drive (P0.1) and inspiratory effort (∆Pmus, PTP/min or WOBp J/L). It is particularly notable that the value of P0.1, as representative of the drive, was > 5 cm H2O in 7 (70%) patients, with a median > 6 cm H2O in each of the ventilatory trials. Additionally, the median ∆Pmus was > -14 cmH2O, and the WOBp was > 12 J/min. The median PDist_EM (mean pressure) was > 16 cm H2O. These parameters suggest high respiratory drive, inspiratory effort, and WOBp, which indicate lung stress.
Table 2.
ACV | PSV 10 (5–15 cmH2O) | APRV | BIPAP (20/10 cmH2O) | P | |
---|---|---|---|---|---|
Respiratory frequency (breaths/min) | 24.12 (23.31–26.42) | 19.26 (16.74–21.61) | 19.59 (12.14–29.35) | 20.11 (13.53–24.94) | 0.998 |
Tidal volume (ml/Kg) | 4.37 (4.02–5.95) | 7.65 (4.49–9.28) | 5.86 (3.78–6.03) | 4.58 (3.77–7.08) | 0.131 |
pH (units) | 7.33 (7.25–7.43) | 7.35 (7.31–7.44) | 7.33 (7.26–7.41) | 7.32 (7.26–7.38) | 0.965 |
PCO2 (mmHg) | 54 (44–62) | 43 (24–55) | 57 (42–65) | 53 (43–67) | 0.721 |
PO2 (mmHg) | 81 (77–95) | 80 (63–112) | 74 (64–103) | 79 (68–105) | 0.651 |
FiO2 (%) | 40 (40–50) | 40 (40–50) | 40 (40–50) | 40(40–50) | N/A |
Total PEEP (cmH2O) | 11.05 (10.31–11.55) | 10.05 (8.42–10.50) | 10.00 (4.45–10.81) | 10.04 (9.51–10.67) | N/A |
Ers (cmH2O/L) | 25.98 (20.17–37.78) | 22.24 (20.09–29.19) | 25.69 (18.96–29.50) | 24.75 (14.75–29.68) | 0.688 |
Rrs (cmH2O/L/s) | 12.15 (10.05–14.61) | 15.10 (11.50–18.58) | 14.76 (11.99–20.85) | 11.84 (10.06–12.67) | 0,117 |
P0.1 (cmH2O) | N/A | 6.12 (3.69–8.26) | 5.82 (4.13–10.89) | 5.80 (4.22–8.85) | 0.907 |
Delta Muscle Pressure (cmH2O) | N/A | 13.04 (10.06–17.35) | 15.77 (10.85–23.38) | 16.16 (6.92–17.76) | 0.556 |
PTPpmus (cmH2O.s/min) | N/A | 135.17 (96.55–175.27) | 148.74 (112.38–259.94) | 156.95 (84.18–335.11) | 0.716 |
WOB (Joule/min) | N/A | 13.52 (5.34–18.97) | 10.54 (4.87–24.75) | 14.39 (4.10–23.78) | 0.973 |
PDist_EM (cmH2O) | N/A | 14.81 (13.97–16.03)* | 20.74 (19.75–22.39) | 18.91 (17.72–23.65) | < 0.001 |
ACV Assist-control volume ventilation, PSV Pressure support ventilation (Inspiratory pressure), APRV Airway pressure release ventilation (High pressure 20 cmH2O, expiration limited to 75% expiratory flow), BIPAP biLevel mode, PEEP Positive end-expiratory pressure, Ers Elastance respiratory system, Rrs Resistance respiratory system, P0.1 Airway occlusion pressure generated at the airways during the first 100 ms of an inspiratory effort, PTPpmus Muscle pressure time product during the inspiratory period, WOB Patient work of breathing, PDist_EM Total distending pressure by equation motion, N/A Not applicable
*p < 0.05 between PSV versus APRV or BIPAP
There were no significant differences in ventilation among the ventilatory modes applied; however, there was a trend towards better PCO2 control during PSV (46 mmHg) vs. APRV (56 mmHg) and BiPAP (53 mmHg). Therefore, PSV might be better tolerated by the patients. We found significant differences in relation to mean PDist_EM in favour of PSV (14.81 cmH2O) vs. APRV (20.74 cm H2O) and BIPAP (18.91 cm H2O) (p < 0.001), which might be explained mainly by an extended time of inspiration (Table 2).
The relationships between respiratory drive, WOBp and Ers are shown in Fig. 1. Linear regression indicates a positive significant trend for both respiratory drive and work with respect to Ers. Thus, 41% of the increase in respiratory drive would be explained by the increase in the Ers and a 37.5% increase in the WOBp.
Table 3 shows the individual values of the respiratory components, ICU stay, and survival of the patients studied. Figure 2 shows the graphs of a representative patient with low Ers during the three ventilatory strategies tested. We found high respiratory drive, inspiratory effort, and WOBp, even with high assistance in PSV mode. The results indicate poor prognosis.
Table 3.
Patient | Ers cmH2O/L | Rrs cmH2O/L/s | P0.1 cmH2O | Delta Pmus cmH2O | PTPpmus cmH2O*s/min | WOB joules/min | Distending pressure cmH2O | ICU stay days | Survival |
---|---|---|---|---|---|---|---|---|---|
1 | 10.09 | 9.47 | 5.87 | 12.03 | 184.13 | 11.12 | 20.71 | 32 | Yes |
2 | 12.41 | 8.41 | 8.12 | 16.46 | 107.85 | 13.99 | 15.86 | 15 | No |
3 | 24.28 | 23.14 | 3.66 | 11.08 | 166.29 | 5.91 | 14.39 | 6 | Yes |
4 | 20.25 | 12.97 | 6.12 | 22.08 | 176.38 | 17.51 | 15.78 | 154 | Yes |
5 | 48.61 | 12.15 | 7.21 | 17.81 | 260.43 | 19.63 | 17.52 | 60 | No |
6 | 22.48 | 11.34 | 6.43 | 8.84 | 130.24 | 11,87 | 18.96 | 8 | No |
7 | 30.65 | 18.56 | 5.08 | 12.53 | 253.33 | 13.65 | 14.92 | 96 | Yes |
8 | 24.19 | 13.11 | 12.34 | 32.36 | 335.11 | 29.77 | 18.52 | 54 | No |
9 | 20.27 | 11.67 | 4.43 | 15.24 | 124.02 | 7.47 | 20.29 | 99 | No |
10 | 30.01 | 16.01 | 7.07 | 13.48 | 132.17 | 7.41 | 16.44 | 43 | Yes |
Median (IQR) | 22.74 (18.29–30.16) | 12.56 (10.87–16.64) | 6.28 (4.92–7.44) | 14.36 (11.91–18.88) | 180.26 (128.51–255.11) | 12.76 (7.46–18.04) | 16.97 (15.57–19.29) | 48.50 (13.25–96.75) | 5 (50%) |
Ers Elastance respiratory system, Rrs Resistance respiratory system, P0.1 Airway occlusion pressure generated at the airways during the first 100 ms of an inspiratory effort, PTPpmus Muscle pressure time product during inspiratory period, WOB Patient work of breathing
Discussion
The present study suggests that patients with pneumonia due to COVID-19 present an increase in respiratory drive and muscular effort compared to conventional values for patients under assisted mechanical ventilation [11, 12]. These results were obtained irrespective of any of the three ventilatory strategies applied. In our study, the ventilation modes chosen were based on protective strategies of assisted pressure in biphasic modes and maintaining ΔP below a safety threshold of 15 cm H2O [8]. We chose PSV as usual during spontaneous ventilation and two ventilation modes based on CPAP: APRV with a short exhalation period, similar to that proposed by Nieman et al. [13], a time-controlled adaptive ventilation protocol, and ventilation BiLevel (BIPAP) with extended inspiratory time.
The keystone for our study is obtaining the Pmus signal generated from flow, volume, and airway pressure using EM [14] by calculating Ers and Rrs both in ACV as in each spontaneous mode, and we did not find significant differences between the modes applied. Gattinoni and colleagues [4] reported patients with phenotypes with high and low compliance of the respiratory system, even on the days of mechanical ventilation on which they were included in the study. The accuracy of the Pmus calculation depends on the accuracy of the Ers and Rrs calculations, which did not show significant differences according to the applied ventilation mode. Therefore, we consider that Pmus is reliable.
The main finding of this study is that our patients had a high respiratory drive, P0.1 > 6 cm H2O; inspiratory effort, ΔPmus -12 to -19 cm H2O, PTP/min > 250 cm H2O.sec/min in the 3rd percentile; and WOBp > 12 J/min in all the ventilatory modes tested. High respiratory drive and inspiratory effort occur in both high and low elastance.
In the context of ARDS caused by COVID-19, a recent study by Esnault and colleagues [1] demonstrated an association between increased respiratory drive and worsening respiratory function during weaning from MV, which might be a consequence of P-SILI, myotrauma (diaphragm injury) and nonresolution of COVID-19 pneumonia. Therefore, it is important to monitor respiratory parameters related to drive and inspiratory effort. This study was also performed in patients in APRV and PSV modes.
The high drive might be caused by hypoxaemia and/or hypercapnia; however, high drive by itself has been shown in COVID-19 patients [1], as confirmed by our results. None of the patients studied had increased temperature or elevated lactic acid as sepsis markers (Table 1). The relationship between respiratory drive and WOBp with respect to Ers (Fig. 1) is significant; however, the increase in respiratory drive associated with Ers is explained in 41% of cases and associated with WOBp in only 37.5% of cases, with a wide coefficient of variation, which suggests the existence of other factors involved in addition to Ers. High respiratory drive and inspiratory effort can generate an increase in volume, especially in PSV mode (hidden volume), particularly in patients with low Ers. High volume per se can cause lung injury by strain, similar to ARDS of other aetiologies due to the relationship of volume to the functional residual capacity (FRC) [15]. Large tidal volume and transpulmonary pressure increase lung oedema. This is a manifestation of P-SILI, with worsening respiratory failure and a delay in the weaning process of MV, and it can affect length of stay [1].
The ΔPmus measurements were > -12 to -16 cm H2O (median) for the three spontaneous breathing tests, indicating excessive respiratory efforts. Indeed, Bertoni and colleagues suggest as a potential target that Pmus values similar to those of healthy subjects breathing at rest may be safe and may prevent diaphragm atrophy, a range between 5 and 10 cm H2O [5].
The normal value of WOBp expressed in joules/min in a healthy subject is approximately 2.4–7.5 J/min. Values of 12.8 (10–15.7) J/min have been reported for patients with ARDS during spontaneous breathing [16], and we found values close to these.
Although transpulmonary pressure by oesophageal pressure was not directly measured in our study, PDist_EM can be taken as an estimate of lung stress considering a standard Ecw. Therefore, the patients studied presented elevated PDist_EM with a significant difference in the APRV and BIPAP modes with respect to the PSV mode; therefore, they were at risk of lung injury associated with MV. This difference in PDist_EM can be explained by the extended inspiratory time.
Venovenous extracorporeal membrane oxygenation (VV-ECMO) in patients recovering from acute respiratory distress syndrome (ARDS) may influence spontaneous breathing for carbon dioxide removal and can be considered a lung and diaphragmatic protective strategy in patients with moderate-severe acute hypoxemic respiratory failure. In selected patients, this might be considered an alternative treatment to reduce respiratory drive and muscular effort [17, 18].
The prolonged ICU admission observed in our patients (median of 48.5 days) and poor prognosis (death 45.45%) may be the result of the development of P-SILI related more to inspiratory effort than directly to Ers; however, effort and Ers are related to each other (Fig. 1). None of the applied ventilator strategies were able to reduce inspiratory effort. COVID-19 can be considered a systemic disease, and therefore, respiratory drive, as a dependent variable, may be related to factors other than Ers that are still unclear.
Danti et al. [18] evaluated the role of sedation, PEEP, ECMO, and partial neuromuscular blockade in patients with moderate-severe hypoxemic respiratory failure as strategies to reduce inspiratory effort and provide diaphragmatic and lung protection. Inspiratory effort was evaluated using the delta of the oesophageal pressure. The study was stopped at the beginning of the COVID pandemic. We believe that our study can complement Danti´s study and provide interesting information using the Pmus signal. Overall, systematic monitoring that allows for control of muscular effort to use protective strategies to avoid diaphragmatic and lung injury during MV is important.
Experimentally, partial paralysis in severe lung injury seems to reduce P-SILi [19], and in some studies, such as Danti’s [18], it has been used to reduce elevated respiratory effort when other interventions fail. However, there is not enough evidence for clinical use, and it remains to be established.
Our study has several limitations. It represents an exploratory analysis with a limited number of patients because it is based on a case series in a monocentric design. However, we believe that this preliminary observation supports the implementation of continuous monitoring of inspiratory effort in these patients during episodes of hypoxemic ARF (AHRF) to avoid worsening respiratory function.
Conclusions
We found high respiratory drive, effort, and WOBpin all patients studied, regardless of ventilatory mode. Monitoring inspiratory effort is essential for assessing therapeutic decisions in clinical practice. The Pmus signal is key information.
Acknowledgements
We thank each of the authors for their contributions to the article.
«In memoriam» special mention for Dr. Benítez, who passed away on 2 June 2021, at 74 years, in full exercise of his functions, while the proofs of this article were being prepared. His kindness, love and inspiration and dedication to true working spirit, progress and responsibility have left a permanent imprint upon those of us who worked with him. The loss is irreparable, but his legacy will continue. Rest in peace.
Abbreviations
- P-SILI
Patient self-inflicted lung injury
- RASS
Richmond Agitation and Sedation Scale
- Ers
Elastance respiratory system
- Rrs
Total resistance of the respiratory system
- PEEP
Positive end-expiratory pressure
- PSV
Pressure support ventilation
- APRV
Airway pressure release ventilation
- BIPAP
BiLvel ventilation
- Pmus
Muscle Pressure
- Paw
Airway pressure
- V´
Flow
- V
Volume
- P0.1
Respiratory drive
- PTP_pmus
Muscle pressure time product during the inspiratory period
- WOBp (Joules/min)
Work of breathing of the patient
- VV-ECMO
Venovenous extracorporeal membrane oxygenation
- EM
Equation of motion
- PDist_EM
Total distending pressure by the equation of motion
- AHRF
Acute hypoxemic respiratory failure
- ARDS
Acute respiratory distress syndrome
- ICU
Intensive care unit
- IQR
Interquartile range
- FRC
Functional residual capacity
Authors’ contributions
JM SS designed the study, conducted the study, collected and analyzed the patient data, interpreted all data, and wrote the manuscript. C JM: revised, and corrected the manuscript. JF MC revised the manuscript. MJ DA revised the manuscript. J LC revised the manuscript. A RC: revised the manuscript. J CP interpreted the data and revised the manuscript. M RD: revised the manuscript. GBC interpreted the data and revised the manuscript. JA BL designed, conducted the study, interpreted all data, and make up the software.
Funding
The authors declare that the paper manuscript is not financially supported by the institution.
Availability of data and materials
The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
Approval for the study procedures and data collected for this report was obtained from the Ethics Committee of the University Hospital, Reina Sofia, Cordoba, Spain. To be included in the original study on muscle pressure under the number PM-12, all patients and/or their surrogates (family and legally responsible) were informed about the study with enough detail that the patients admitted that they understood the entire procedure. In addition, the patients were requested to sign a written informed consent form prior to inclusion in the study. All methods were performed in accordance with the guidelines and regulations of the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
José Antonio Benítez Lozano is deceased.
References
- 1.Esnault P, Hraiech S, Goutorbe P, Baumstrack K, Prud’homme E, Bordes J, Forel JM, Meaudre E, Papazian L. High respiratory drive and excessive respiratory efforts predict relapse of respiratory failure in critically patients with COVID-19. AJRCCM. 2020;202(8):1173–1178. doi: 10.1164/rccm.202005-1582LE. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Brochard L, Slutsky A, Pesenti A. Mechanical ventilation to minimize progression of lung injury in acute respiratory failure. Am J Respir Crit Care Med. 2017;195:438–442. doi: 10.1164/rccm.201605-1081CP. [DOI] [PubMed] [Google Scholar]
- 3.Mascheroni DE, Kolobow T, Fumagalli R, Moretti MP, Chen V, Buckhold D. Acute respiratory failure following pharmacologically induced hyperventilation an experimental animal study. Intensive Care Med. 1988;15(1):8–14. doi: 10.1007/BF00255628. [DOI] [PubMed] [Google Scholar]
- 4.Gattinoni L, Chiumello D, Caironi P, Busana M, Romiti F, Brazzi L, Camporota L. COVID-19 pneumonia: different respiratory treatments for different phenotypes? Intensive Care Med. 2020;46:1099–1102. doi: 10.1007/s00134-020-06033-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Bertoni M, Spadaro S, Goligher EC. Monitoring patient respiratory effort during mechanical ventilation: lung and diaphragm-protective ventilation. Crit Care. 2020;24:106–108. doi: 10.1186/s13054-020-2777-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Weaver L, Das A, Saffaran S, Yehya N, Scott TE, Chikhani M, Laffey JG, Hardman JG, Camporota L, Bates DG. High risk of patient self-inflicted lung injury in COVID-19 with frequently encountered spontaneous breathing patterns: a computational modelling study. Ann Intensive Care. 2021;11:109. doi: 10.1186/s13613-021-00904-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Benitez Lozano JA, Serrano Simon JM. Pneumonia in patients with Covid-19: strategies to decrease patient’s self-inflicted lung injury. Intensive Care Med Exp. 2020;8(2):000640. [Google Scholar]
- 8.Amato MB, Meade MO, Slutsky AS, Brochard L, Costa EL, Schoenfeld DA, Stewart TE, Briel M, Talmor D, Mercat A, Richard JC, Carvalho CR, Brower RG. Driving pressure and survival in the acute respiratory distress syndrome. N Engl J Med. 2015;372:747–755. doi: 10.1056/NEJMsa1410639. [DOI] [PubMed] [Google Scholar]
- 9.Al-Rawas N, Banner MJ, Euliano NR, Tams CG, Brown J, Martin AD, Gabrielli A. Expiratory time constant for determination of plateau pressure, respiratory system compliance, and total resistance. Crit Care. 2013;17:R23. doi: 10.1186/cc12500. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Giuseppe Natalini G, Buizza B, Granato A, Aniballi E, Luigi Pisani L, Gianni Ciabatti G, Lippolis V, Rosano A, Latronico N, Grasso S, Antonelli M, Bernardini A. Non invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end inspiration occlusion and least square fitting methods. J Clin Monit Comput. 2021;35:913–921. doi: 10.1007/s10877-020-00552-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Tobin MJ, Gardner W. Monitoring the control of breathing. In: Tobin M, editor. Principles and practice of intensive care monitoring. New York: MCGraw-Hill; 1988. pp. 415–464. [Google Scholar]
- 12.Calzia E, Lindner KH, Witt S, Schirmer U, Lange H, Stenz R, Georgieff M. Pressure-time product and work of breathing during biphasic continuous positive airway pressure and assisted spontaneous breathing. Am J Respir Crit Care Med. 1994;150:904–910. doi: 10.1164/ajrccm.150.4.7921461. [DOI] [PubMed] [Google Scholar]
- 13.Nieman GF, Gatto LA, Andrews P, Satalin J, Camporota L, Daxon B, Blair S, Al-Khailsy H, Madden M, Lollisch-Singule M, Aiash H, Habashi N. Prevention and treatment of acute lung injury with time–controlled adaptive ventilation: physiologically informed modification of airway pressure release ventilation. Ann Intensive Care. 2020;10(3):1–16. doi: 10.1186/s13613-019-0619-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Kondili E, Alexopoulou C, Xirouchaki N, Vaporidi K, Georgopoulos D. Estimation of inspiratory muscle pressure in critically ill patients. Intensive Care Med. 2010;36:648–635. doi: 10.1007/s00134-010-1753-4. [DOI] [PubMed] [Google Scholar]
- 15.Tonelli R, Busani S, Tabbì L, Fantini R, Castaniere I, Biagioni E, Mussini C, Girardis M, Clini E, Marchioni A. Inspiratory effort and lung mechanics in spontaneous breathing patients with acute respiratory failure due to COVID-19: a matched control study. Am J Respir Crit Care Med. 2021;204:725–728. doi: 10.1164/rccm.202104-1029LE. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Kallet RH, Hemphill JC, Dicker R, Alonso JA, Campbell AR, Mackersie RC, Katz JA. The spontaneous breathing pattern and work of breathing of patients with acute respiratory distress syndrome and acute lung injury. Respir Care. 2007;52(8):989–995. [PubMed] [Google Scholar]
- 17.Mauri T, Grasselli G, Suriano G, Eronia N, Spadaro S, Turrini C, Patroniti N, Bellani G, Pesenti A. control of respiratory drive and effort in extracorporeal membrane oxygenation patients recovering from severe acute respiratory distress syndrome. Anesthesiology. 2016;125(1):159–167. doi: 10.1097/ALN.0000000000001103. [DOI] [PubMed] [Google Scholar]
- 18.Dianti J, Fard S, Wong J, Chan TCY, Sorbo L, Fan E, Amato MB, Granton J, Burry L, Reid WD, Zhang B, Ratano D, Keshavjee S, Slutsky AS, Brochard LJ, Ferguson ND, Goligher EC. Strategies for lung- and diaphragm-protective ventilation in acute hypoxemic respiratory failure: a physiological trial. Crit Care. 2022;26:259. doi: 10.1186/s13054-022-04123-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Yoshida T, Uchiyama A, Nariaki Matsuura N, Mashimo T, Fujino Y. The comparison of spontaneous breathing and muscle paralysis in two different severities of experimental lung injury. Crit Care Med. 2013;41:536–545. doi: 10.1097/CCM.0b013e3182711972. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.