Is pulmonary resistance constant, within the range of tidal volume ventilation, in patients with ARDS?

Effect of tidal volume and positive end-expiratory pressure on expiratory time constants in experimental lung injury

We utilized a multicompartment model to describe the effects of changes in tidal volume (V_T) and positive end‐expiratory pressure (PEEP) on lung emptying during passive deflation before and after experimental lung injury. Expiratory time constants (τ_E) were determined by partitioning the expiratory flow–volume (V˙_EV) curve into multiple discrete segments and individually calculating τ_E for each segment. Under all conditions of PEEP and V_T, τ_E increased throughout expiration both before and after injury. Segmented τ_E values increased throughout expiration with a slope that was different than zero (P < 0. 01). On average, τ_E increased by 45.08 msec per segment. When an interaction between injury status and τ_E segment was included in the model, it was significant (P < 0.05), indicating that later segments had higher τ_E values post injury than early τ_E segments. Higher PEEP and V_T values were associated with higher τ_E values. No evidence was found for an interaction between injury status and V_T, or PEEP. The current experiment confirms previous observations that τ_E values are smaller in subjects with injured lungs when compared to controls. We are the first to demonstrate changes in the pattern of τ_E before and after injury when examined with a multiple compartment model. Finally, increases in PEEP or V_T increased τ_E throughout expiration, but did not appear to have effects that differed between the uninjured and injured state.

Resistance in a non-linear autoregressive model of pulmonary mechanics

Respiratory system modelling can enable patient-specific mechanical ventilator settings to be found, and can thus reduce the incidence of ventilator induced lung injury in the intensive care unit. The resistance of a simple first order model (FOM) of pulmonary mechanics was compared with a flow dependent term of a non-linear autoregressive (NARX) model. Model parameters were identified for consecutive non-overlapping windows of length 20 breaths. The analysis was performed over recruitment manoeuvres for 25 sedated mechanically ventilated patients. The NARX model term, b1 , consistently decreased as positive end expiratory pressure (PEEP) increased, while the FOM resistance behaviour varied. Overall the NARX b1 behaviour is more in-line with expected trends in airway resistance as PEEP increases. This work has further verified the physiologically descriptive capability of the NARX model.

Simultaneous monitoring of intratidal compliance and resistance in mechanically ventilated piglets: A feasibility study in two different study groups

Compliance measures the force counteracting parenchymal lung distension. In mechanical ventilation, intratidal compliance-volume (C(V))-profiles therefore change depending on PEEP, tidal volume (VT), and underlying mechanical lung properties. Resistance counteracts gas flow through the airways. Due to anatomical linking between parenchyma and airways, intratidal resistance-volume (R(V))-profiles are hypothesised to change in a non-linear way as well. We analysed respiratory system mechanics in fifteen piglets with lavage-induced lung injury and nine healthy piglets ventilated at different PEEP/VT-settings. In healthy lungs, R(V)-profiles remained mostly constant and linear at all PEEP-settings whereas the shape of the C(V)-profiles showed an increase toward a maximum followed by a decrease (small PEEP) or volume-dependent decrease (large PEEP). In the lavage group, a large drop in resistance at small volumes and slow decrease toward larger volumes was found for small PEEP/VT-settings where C(V)-profiles revealed a volume-dependent increase (small PEEP) or a decrease (large PEEP and large VT). R(V)-profiles depend characteristically on PEEP, VT, and possibly whether lungs are healthy or not. Curved R(V)-profiles might indicate pathological changes in the underlying mechanical lung properties and/or might be a sign of derecruitment.

Comparing surrogates of oxygenation and ventilation between airway pressure release ventilation and biphasic airway pressure in a mechanical model of adult respiratory distress syndrome

BACKGROUND

No objective data directly comparing the 2 modes are available. Based on a simple mathematical model, APRV and BIPAP can presumably be set to achieve the same mean airway pressure (mPaw), end expiratory pressure, and tidal volume (V(T)). Herein, we tested this hypothesis when using a real ventilator and clinically relevant settings based on expiratory time constants.

METHODS

A spontaneously breathing acute respiratory distress syndrome patient was modeled with a lung simulator. Mode settings: P high and the number of releases were the same in both modes; T low=1 time constant in APRV (expected auto-positive end-expiratory pressure [PEEP], ≈9 cmH(2)O) and 5 time constants in BIPAP; P low, 0 cmH(2)O in APRV and 9 cmH(2)O in BIPAP (equal to the expected auto-PEEP in APRV). The mean mandatory release volumes, minute ventilation [V(E)], mPaw, and total PEEP were compared with t-tests using a P value of 0.05 to reject the null hypothesis.

RESULTS

APRV yielded significantly higher mPaw than did BIPAP. Minute ventilation was significantly higher in BIPAP. The total PEEP was significantly higher in APRV; the total PEEP was significantly higher than expected.

CONCLUSION

We found that neither mode was superior to the other, and that a real ventilator does not behave like a mathematical model. Extreme prolongation of T high generated a higher mPaw at the expense of V(E), and vice versa. The lower V(T) with APRV was due to the higher total PEEP, which was higher than expected. Setting the T low according to the respiratory system time constant for either mode resulted in an unpredictable total PEEP.

Visualisation of time-varying respiratory system elastance in experimental ARDS animal models

BACKGROUND

Patients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics. Model-based estimation of respiratory mechanics characterising patient-specific condition and response to treatment may be used to guide mechanical ventilation (MV). This study presents a model-based approach to monitor time-varying patient-ventilator interaction to guide positive end expiratory pressure (PEEP) selection.

METHODS

The single compartment lung model was extended to monitor dynamic time-varying respiratory system elastance, Edrs, within each breathing cycle. Two separate animal models were considered, each consisting of three fully sedated pure pietrain piglets (oleic acid ARDS and lavage ARDS). A staircase recruitment manoeuvre was performed on all six subjects after ARDS was induced. The Edrs was mapped across each breathing cycle for each subject.

RESULTS

Six time-varying, breath-specific Edrs maps were generated, one for each subject. Each Edrs map shows the subject-specific response to mechanical ventilation (MV), indicating the need for a model-based approach to guide MV. This method of visualisation provides high resolution insight into the time-varying respiratory mechanics to aid clinical decision making. Using the Edrs maps, minimal time-varying elastance was identified, which can be used to select optimal PEEP.

CONCLUSIONS

Real-time continuous monitoring of in-breath mechanics provides further insight into lung physiology. Therefore, there is potential for this new monitoring method to aid clinicians in guiding MV treatment. These are the first such maps generated and they thus show unique results in high resolution. The model is limited to a constant respiratory resistance throughout inspiration which may not be valid in some cases. However, trends match clinical expectation and the results highlight both the subject-specificity of the model, as well as significant inter-subject variability.

Monitoring of intratidal lung mechanics: a Graphical User Interface for a model-based decision support system for PEEP-titration in mechanical ventilation

In mechanical ventilation, a careful setting of the ventilation parameters in accordance with the current individual state of the lung is crucial to minimize ventilator induced lung injury. Positive end-expiratory pressure (PEEP) has to be set to prevent collapse of the alveoli, however at the same time overdistension should be avoided. Classic approaches of analyzing static respiratory system mechanics fail in particular if lung injury already prevails. A new approach of analyzing dynamic respiratory system mechanics to set PEEP uses the intratidal, volume-dependent compliance which is believed to stay relatively constant during one breath only if neither atelectasis nor overdistension occurs. To test the success of this dynamic approach systematically at bedside or in an animal study, automation of the computing steps is necessary. A decision support system for optimizing PEEP in form of a Graphical User Interface (GUI) was targeted. Respiratory system mechanics were analyzed using the gliding SLICE method. The resulting shapes of the intratidal compliance-volume curve were classified into one of six categories, each associated with a PEEP-suggestion. The GUI should include a graphical representation of the results as well as a quality check to judge the reliability of the suggestion. The implementation of a user-friendly GUI was successfully realized. The agreement between modelled and measured pressure data [expressed as root-mean-square (RMS)] tested during the implementation phase with real respiratory data from two patient studies was below 0.2 mbar for data taken in volume controlled mode and below 0.4 mbar for data taken in pressure controlled mode except for two cases with RMS < 0.6 mbar. Visual inspections showed, that good and medium quality data could be reliably identified. The new GUI allows visualization of intratidal compliance-volume curves on a breath-by-breath basis. The automatic categorisation of curve shape into one of six shape-categories provides the rational decision-making model for PEEP-titration.

Expiratory model-based method to monitor ARDS disease state

Introduction

Model-based methods can be used to characterise patient-specific condition and response to mechanical ventilation (MV) during treatment for acute respiratory distress syndrome (ARDS). Conventional metrics of respiratory mechanics are based on inspiration only, neglecting data from the expiration cycle. However, it is hypothesised that expiratory data can be used to determine an alternative metric, offering another means to track patient condition and guide positive end expiratory pressure (PEEP) selection.

Methods

Three fully sedated, oleic acid induced ARDS piglets underwent three experimental phases. Phase 1 was a healthy state recruitment manoeuvre. Phase 2 was a progression from a healthy state to an oleic acid induced ARDS state. Phase 3 was an ARDS state recruitment manoeuvre. The expiratory time-constant model parameter was determined for every breathing cycle for each subject. Trends were compared to estimates of lung elastance determined by means of an end-inspiratory pause method and an integral-based method. All experimental procedures, protocols and the use of data in this study were reviewed and approved by the Ethics Committee of the University of Liege Medical Faculty.

Results

The overall median absolute percentage fitting error for the expiratory time-constant model across all three phases was less than 10 %; for each subject, indicating the capability of the model to capture the mechanics of breathing during expiration. Provided the respiratory resistance was constant, the model was able to adequately identify trends and fundamental changes in respiratory mechanics.

Conclusion

Overall, this is a proof of concept study that shows the potential of continuous monitoring of respiratory mechanics in clinical practice. Respiratory system mechanics vary with disease state development and in response to MV settings. Therefore, titrating PEEP to minimal elastance theoretically results in optimal PEEP selection. Trends matched clinical expectation demonstrating robustness and potential for guiding MV therapy. However, further research is required to confirm the use of such real-time methods in actual ARDS patients, both sedated and spontaneously breathing.

Model-based PEEP optimisation in mechanical ventilation

BACKGROUND

Acute Respiratory Distress Syndrome (ARDS) patients require mechanical ventilation (MV) for breathing support. Patient-specific PEEP is encouraged for treating different patients but there is no well established method in optimal PEEP selection.

METHODS

A study of 10 patients diagnosed with ALI/ARDS whom underwent recruitment manoeuvre is carried out. Airway pressure and flow data are used to identify patient-specific constant lung elastance (E lung) and time-variant dynamic lung elastance (E drs) at each PEEP level (increments of 5 cm H2O), for a single compartment linear lung model using integral-based methods. Optimal PEEP is estimated using E lung versus PEEP, Edrs-Pressure curve and E drs Area at minimum elastance (maximum compliance) and the inflection of the curves (diminishing return). Results are compared to clinically selected PEEP values. The trials and use of the data were approved by the New Zealand South Island Regional Ethics Committee.

RESULTS

Median absolute percentage fitting error to the data when estimating time-variant E drs is 0.9% (IQR = 0.5-2.4) and 5.6% [IQR: 1.8-11.3] when estimating constant E lung. Both E lung and E drs decrease with PEEP to a minimum, before rising, and indicating potential over-inflation. Median E drs over all patients across all PEEP values was 32.2 cmH2O/l [IQR: 26.1-46.6], reflecting the heterogeneity of ALI/ARDS patients, and their response to PEEP, that complicates standard approaches to PEEP selection. All E drs-Pressure curves have a clear inflection point before minimum E drs, making PEEP selection straightforward. Model-based selected PEEP using the proposed metrics were higher than clinically selected values in 7/10 cases.

CONCLUSION

Continuous monitoring of the patient-specific E lung and E drs and minimally invasive PEEP titration provide a unique, patient-specific and physiologically relevant metric to optimize PEEP selection with minimal disruption of MV therapy.

[Monitoring airway pressure in pediatric anesthesia: an experimental model of intratracheal medication and pressure-volume loops]

BACKGROUND

In the monitoring of anesthesia, airway pressure is measured in the ventilator or at the closest possible connection to the endotracheal tube.

OBJECTIVE

To compare the airway pressures and pressure-volume loops obtained before connection to the endotracheal tube with those obtained in the trachea.

MATERIAL AND METHODS

We carried out a single-blind prospective observational study on ASA 1 patients between the ages of 7 and 12 years ventilated in volume-control mode with an inspiration-to-expiration ratio of 1:2. Intratracheal and extratracheal peak and plateau pressures and pressure-volume loops were recorded. A special device was designed to monitor intratracheal pressure. Both sensors were connected to the same spirometric analysis system. The variables were measured on intubation and 5, 10, 15, 20, 30, 40, 50, and 60 minutes after intubation. The recorded pressures were compared using the t test, the Pearson product moment correlation coefficient (r), and the Spearman rank correlation coefficient (p), and regression models were fit to the data.

RESULTS

Seventy-one patients were enrolled. The mean (SD) pressure difference between the 2 systems was 3.5 (0.35) cm H2O (P < .01) and no differences between the endotracheal peak pressures and the plateau pressures were observed. The intratracheal areas of the pressure-volume loops were 15% lower than the extratracheal areas. The value of r for the correlation between the intratracheal peak and plateau pressures was 0.998 (P < .01). The value of r for the correlation between the intratracheal and extratracheal peak pressures was 0.981 (P < .01). Analysis of variance confirmed the linear relationship.

CONCLUSIONS

The difference between the intratracheal and extratracheal pressure measurements is due to the different locations at which the measurements are taken.

Dynamic versus static respiratory mechanics in acute lung injury and acute respiratory distress syndrome

OBJECTIVES

It is not clear whether the mechanical properties of the respiratory system assessed under the dynamic condition of mechanical ventilation are equivalent to those assessed under static conditions. We hypothesized that the analyses of dynamic and static respiratory mechanics provide different information in acute respiratory failure.

DESIGN

Prospective multiple-center study.

SETTING

Intensive care units of eight German university hospitals.

PATIENTS

A total of 28 patients with acute lung injury and acute respiratory distress syndrome.

INTERVENTIONS

None.

MEASUREMENTS

Dynamic respiratory mechanics were determined during ongoing mechanical ventilation with an incremental positive end-expiratory pressure (PEEP) protocol with PEEP steps of 2 cm H2O every ten breaths. Static respiratory mechanics were determined using a low-flow inflation.

MAIN RESULTS

The dynamic compliance was lower than the static compliance. The difference between dynamic and static compliance was dependent on alveolar pressure. At an alveolar pressure of 25 cm H2O, dynamic compliance was 29.8 (17.1) mL/cm H2O and static compliance was 59.6 (39.8) mL/cm H2O (median [interquartile range], p < .05). End-inspiratory volumes during the incremental PEEP trial coincided with the static pressure-volume curve, whereas end-expiratory volumes significantly exceeded the static pressure-volume curve. The differences could be attributed to PEEP-related recruitment, accounting for 40.8% (10.3%) of the total volume gain of 1964 (1449) mL during the incremental PEEP trial. Recruited volume per PEEP step increased from 6.4 (46) mL at zero end-expiratory pressure to 145 (91) mL at a PEEP of 20 cm H2O (p < .001). Dynamic compliance decreased at low alveolar pressure while recruitment simultaneously increased. Static mechanics did not allow this differentiation. The decrease in static compliance occurred at higher alveolar pressures compared with the dynamic analysis.

CONCLUSIONS

Exploiting dynamic respiratory mechanics during incremental PEEP, both compliance and recruitment can be assessed simultaneously. Based on these findings, application of dynamic respiratory mechanics as a diagnostic tool in ventilated patients should be more appropriate than using static pressure-volume curves.

Respiratory load compensation during mechanical ventilation—proportional assist ventilation with load-adjustable gain factors versus pressure support

RATIONALE

In mechanically ventilated patients respiratory system impedance may vary from time to time, resulting, with pressure modalities of ventilator support, in changes in the level of assistance. Recently, implementation of a closed-loop adjustment to continuously adapt the level of assistance to changes in respiratory mechanics has been designed to operate with proportional assist ventilation (PAV+).

OBJECTIVES

The aim of this study was to assess, in critically ill patients, the short-term steady-state response of respiratory motor output to added mechanical respiratory load during PAV+ and during pressure support (PS).

PATIENTS AND INTERVENTIONS

In 10 patients respiratory workload was increased and the pattern of respiratory load compensation was examined during both modes of support.

MEASUREMENTS AND RESULTS

Airway and transdiaphragmatic pressures, volume and flow were measured breath by breath. Without load, both modes provided an equal support as indicated by a similar pressure-time product of the diaphragm per breath, per minute and per litre of ventilation. With load, these values were significantly lower (p<0.05) with PAV+ than those with PS (5.1+/-3.7 vs 6.1+/-3.4 cmH2O.s, 120.9+/-77.6 vs 165.6+/-77.5 cmH2O.s/min, and 18.7+/-15.1 vs 24.4+/-16.4 cmH2O.s/l, respectively). Contrary to PS, with PAV+ the ratio of tidal volume (VT) to pressure-time product of the diaphragm per breath (an index of neuroventilatory coupling) remained relatively independent of load. With PAV+ the magnitude of load-induced VT reduction and breathing frequency increase was significantly smaller than that during PS.

CONCLUSION

In critically ill patients the short-term respiratory load compensation is more efficient during proportional assist ventilation with adjustable gain factors than during pressure support.

Alveolar recruitment in acute lung injury

Alveolar recruitment is one of the primary goals of respiratory care for acute lung injury. It is aimed at improving pulmonary gas exchange and, even more important, at protecting the lungs from ventilator-induced trauma. This review addresses the concept of alveolar recruitment for lung protection in acute lung injury. It provides reasons for why atelectasis and atelectrauma should be avoided; it analyses current and future approaches on how to achieve and preserve alveolar recruitment; and it discusses the possibilities of detecting alveolar recruitment and derecruitment. The latter is of particular clinical relevance because interventions aimed at lung recruitment are often undertaken without simultaneous verification of their effectiveness.

Alveolar pressure monitoring: an evaluation in a lung model and in patients with acute lung injury

OBJECTIVES

We evaluated an algorithm for continuous on-line monitoring of alveolar pressure over time in a lung model with lower and upper inflection points and variable resistance ratios and in patients with acute lung injury. The algorithm is based on "static" pressure/volume curves obtained from tracheal pressure measurements under dynamic conditions.

DESIGN AND SETTING

Experimental and clinical evaluation of algorithm in a university hospital laboratory and intensive care unit.

PATIENTS

Ten patients undergoing postoperative respiratory therapy (feasibility of tracheal measurement) and ten patients with acute lung injury undergoing ventilator treatment (evaluation of algorithm).

MEASUREMENTS AND RESULTS

Direct tracheal pressure measurements with a catheter inserted through the endotracheal tube. Comparison of measured alveolar and the dynostatic alveolar pressure vs. time in a lung model with changes in five ventilatory parameters. Examples of clinical monitoring are reported. In the model there was excellent agreement between alveolar pressures obtained by the algorithm, the dynostatic alveolar pressure, and measured alveolar pressure at all ventilator settings. For inspiratory/expiratory resistance ratios between 1:2.1-2.1:1, the dynostatic alveolar pressure was within +/-1.5 cm H(2)O of measured alveolar pressure. In patients the technique for direct tracheal pressure measurement using a catheter inserted through the endotracheal tube functioned satisfactorily with intermittent air flushes for cleansing.

CONCLUSIONS

Using a thin tracheal pressure catheter inserted through the endotracheal tube alveolar pressure allows continuous bedside monitoring with ease and precision using the dynostatic algorithm. The method is unaffected by tube and connector geometry or by secretions.

Does the tube-compensation function of two modern mechanical ventilators provide effective work of breathing relief?

OBJECTIVE

An endotracheal tube (ETT) imposes work of breathing on mechanically ventilated patients. Using a bellows-in-a-box model lung, we compared the tube compensation (TC) performances of the Nellcor Puritan-Bennett 840 ventilator and of the Dräger Evita 4 ventilator.

MEASUREMENTS AND RESULTS

Each ventilator was connected to the model lung. The respiratory rate of the model lung was set at 10 breaths/min with 1 s inspiratory time. Inspiratory flows were 30 or 60 l/min. A full-length 8 mm bore ETT was inserted between the ventilator circuit and the model lung. The TC was set at 0%, 10%, 50%, and 100% for both ventilators. Pressure was monitored at the airway, the trachea, and the pleura, and the data were recorded on a computer for later analysis of the delay time, of the inspiratory trigger pressure, and of the pressure-time product (PTP). The delay time was calculated as the time between the start of inspiration and minimum airway pressure, and the inspiratory trigger pressure was defined as the most negative pressure level. The same measurements were performed under pressure support ventilation of 4 and 8 cmH2O. The PTP increased according to the magnitude of inspiratory flow. Even with 100% TC, neither ventilator could completely compensate for the PTP imposed by the ETT. At 0% TC the PTP tended to be less with the Nellcor Puritan-Bennett 840 ventilator, while at 100% TC the PTP tended to be less with the Dräger Evita 4 ventilator. A small amount of pressure support can be equally effective to reduce the inspiratory effort compared with the TC.

CONCLUSION

Although both ventilators provided effective TC, even when set to 100% TC they could not entirely compensate for a ventilator and ETT-imposed work of breathing. The effect of TC is less than that of pressure support ventilation. Physicians should be aware of this when using TC in weaning trials.