Determination of 'recruited volume' following a PEEP step is not a measure of lung recruitability

Correlation between normally aerated lung and respiratory system compliance at clinical high positive end-expiratory pressure in patients with COVID-19

Normally aerated lung tissue on computed tomography (CT) is correlated with static respiratory system compliance (Crs) at zero end-expiratory pressure. In clinical practice, however, patients with acute respiratory failure are often managed using elevated PEEP levels. No study has validated the relationship between lung volume and tissue and Crs at the applied positive end-expiratory pressure (PEEP). Therefore, this study aimed to demonstrate the relationship between lung volume and tissue on CT and Crs during the application of PEEP for the clinical management of patients with acute respiratory distress syndrome due to COVID-19. Additionally, as a secondary outcome, the study aimed to evaluate the relationship between CT characteristics and Crs, considering recruitability using the recruitment-to-inflation ratio (R/I ratio). We analyzed the CT and respiratory mechanics data of 30 patients with COVID-19 who were mechanically ventilated. The CT images were acquired during mechanical ventilation at PEEP level of 15 cmH2O and were quantitatively analyzed using Synapse Vincent system version 6.4 (Fujifilm Corporation, Tokyo, Japan). Recruitability was stratified into two groups, high and low recruitability, based on the median R/I ratio of our study population. Thirty patients were included in the analysis with the median R/I ratio of 0.71. A significant correlation was observed between Crs at the applied PEEP (median 15 [interquartile range (IQR) 12.2, 15.8]) and the normally aerated lung volume (r = 0.70 [95% CI 0.46-0.85], P < 0.001) and tissue (r = 0.70 [95% CI 0.46-0.85], P < 0.001). Multivariable linear regression revealed that recruitability (Coefficient = - 390.9 [95% CI - 725.0 to - 56.8], P = 0.024) and Crs (Coefficient = 48.9 [95% CI 32.6-65.2], P < 0.001) were significantly associated with normally aerated lung volume (R-squared: 0.58). In this study, Crs at the applied PEEP was significantly correlated with normally aerated lung volume and tissue on CT. Moreover, recruitability indicated by the R/I ratio and Crs were significantly associated with the normally aerated lung volume. This research underscores the significance of Crs at the applied PEEP as a bedside-measurable parameter and sheds new light on the link between recruitability and normally aerated lung.

Gas distribution by EIT during PEEP inflation: PEEP response and optimal PEEP with lowest trans-pulmonary driving pressure can be determined without esophageal pressure during a rapid PEEP trial in patients with acute respiratory failure

Objective. Protective ventilation should be based onlungmechanics and transpulmonary driving pressure (ΔPTP), as this 'hits' the lung directly.Approach. The change in end-expiratory lung volume (ΔEELV) is determined by the size of the PEEP step and the elastic properties of the lung (EL), ΔEELV/ΔPEEP. Consequently, EL can be determined as ΔPEEP/ΔEELV. By calibration of tidal inspiratory impedance change with ventilator inspiratory tidal volume, end-expiratory lung impedance changes were converted to volume changes and lung P/V curves were obtained during a PEEP trial in ten patients with acute respiratory failure. The PEEP level where ΔPTP was lowest (optimal PEEP) was determined as the steepest point of the lung P/V curve.Main results. Over-all EL ranged between 7.0-23.2 cmH₂O/L. Optimal PEEP was 12.9 cmH₂O (10-16) with ΔPTP of 4.1 cmH₂O (2.8-7.6). Patients with highest EL were PEEP non-responders, where EL increased in non-dependent and dependent lung at high PEEP, indicating over-distension in all lung. Patients with lower EL were PEEP responders with decreasing EL in dependent lung when increasing PEEP.Significance. PEEP non-responders could be identified by regional lung P/V curves derived from ventilator calibrated EIT. Optimal PEEP could be determined from the equation for the lung P/V curve.

Pulmonary pathophysiology development of COVID-19 assessed by serial Electrical Impedance Tomography in the MaastrICCht cohort

Patients with SARS-CoV-2 infection present with different lung compliance and progression of disease differs. Measures of lung mechanics in SARS-CoV-2 patients may unravel different pathophysiologic mechanisms during mechanical ventilation. The objective of this prospective observational study is to describe whether Electrical Impedance Tomography (EIT) guided positive end-expiratory pressure (PEEP) levels unravel changes in EIT-derived parameters over time and whether the changes differ between survivors and non-survivors. Serial EIT-measurements of alveolar overdistension, collapse, and compliance change in ventilated SARS-CoV-2 patients were analysed. In 80 out of 94 patients, we took 283 EIT measurements (93 from day 1-3 after intubation, 66 from day 4-6, and 124 from day 7 and beyond). Fifty-one patients (64%) survived the ICU. At admission mean PaO₂/FiO₂-ratio was 184.3 (SD 61.4) vs. 151.3 (SD 54.4) mmHg, (p = 0.017) and PEEP was 11.8 (SD 2.8) cmH₂O vs. 11.3 (SD 3.4) cmH₂O, (p = 0.475), for ICU survivors and non-survivors. At day 1-3, compliance was ~ 55 mL/cmH₂O vs. ~ 45 mL/cmH₂O in survivors vs. non-survivors. The intersection of overdistension and collapse curves appeared similar at a PEEP of ~ 12-13 cmH₂O. At day 4-6 compliance changed to ~ 50 mL/cmH₂O vs. ~ 38 mL/cmH₂O. At day 7 and beyond, compliance was ~ 38 mL/cmH₂O with the intersection at a PEEP of ~ 9 cmH₂O vs. ~ 25 mL/cmH₂O with overdistension intersecting at collapse curves at a PEEP of ~ 7 cmH₂O. Surviving SARS-CoV-2 patients show more favourable EIT-derived parameters and a higher compliance compared to non-survivors over time. This knowledge is valuable for discovering the different groups.

Positive end-expiratory pressure-induced recruited lung volume measured by volume-pressure curves in acute respiratory distress syndrome: a physiologic systematic review and meta-analysis

PURPOSE

Recruitment of lung volume is often cited as the reason for using positive end-expiratory pressure (PEEP) in acute respiratory distress syndrome (ARDS) patients. We performed a systematic review on PEEP-induced recruited lung volume measured from inspiratory volume-pressure (VP) curves in ARDS patients to assess the prevalence of patients with PEEP-induced recruited lung volume and the mortality in recruiters and non-recruiters.

METHODS

We conducted a systematic search of PubMed to identify studies including ARDS patients in which the intervention of an increase in PEEP was accompanied by measurement of the recruited volume (V_rec increase versus no increase) using the VP curve in order to assess the relation between V_rec and mortality at ICU discharge. We first analysed the pooled data from the papers identified and then analysed individual patient level data received from the authors via personal contact. The risk of bias of the included papers was assessed using the quality in prognosis studies tool and the certainty of the evidence regarding the relationship of mortality to V_rec by the GRADE approach. Recruiters were defined as patients with a V_rec > 150 ml. A random effects model was used for the pooled data. Multivariable logistic regression analysis was used for individual patient data.

RESULTS

We identified 16 papers with a total of 308 patients for the pooled data meta-analysis and 14 papers with a total of 384 patients for the individual data analysis. The quality of the articles was moderate. In the pooled data, the prevalence of recruiters was 74% and the mortality was not significantly different between recruiters and non-recruiters (relative risk 1.20 [95% confidence intervals 0.88-1.63]). The certainty of the evidence regarding this association was very low and publication bias evident. In the individual data, the prevalence of recruiters was 70%. In the multivariable logistic regression, V_rec was not associated with mortality but Simplified Acute Physiology Score II and driving pressure at PEEP of 5 cmH₂O were.

CONCLUSION

After a PEEP increment, most patients are recruiters. V_rec was not associated with ICU mortality. The presence of similar findings in the individual patient level analysis and the driving pressure at PEEP of 5 cmH₂O was associated with mortality as previously reported validate our findings. Publication bias and the lack of prospective studies suggest more research is required.

Can we estimate transpulmonary pressure without an esophageal balloon?-yes

A protective ventilation strategy is based on separation of lung and chest wall mechanics and determination of transpulmonary pressure. So far, this has required esophageal pressure measurement, which is cumbersome, rarely used clinically and associated with lack of consensus on the interpretation of measurements. We have developed an alternative method based on a positive end expiratory pressure (PEEP) step procedure where the PEEP-induced change in end-expiratory lung volume is determined by the ventilator pneumotachograph. In pigs, lung healthy patients and acute lung injury (ALI) patients, it has been verified that the determinants of the change in end-expiratory lung volume following a PEEP change are the size of the PEEP step and the elastic properties of the lung, ∆PEEP × Clung. As a consequence, lung compliance can be calculated as the change in end-expiratory lung volume divided by the change in PEEP and esophageal pressure measurements are not needed. When lung compliance is determined in this way, transpulmonary driving pressure can be calculated on a breath-by-breath basis. As the end-expiratory transpulmonary pressure increases as much as PEEP is increased, it is also possible to determine the end-inspiratory transpulmonary pressure at any PEEP level. Thus, the most crucial factors of ventilator induced lung injury can be determined by a simple PEEP step procedure. The measurement procedure can be repeated with short intervals, which makes it possible to follow the course of the lung disease closely. By the PEEP step procedure we may also obtain information (decision support) on the mechanical consequences of changes in PEEP and tidal volume performed to improve oxygenation and/or carbon dioxide removal.

Chest wall effect on the monitoring of respiratory mechanics in acute respiratory distress syndrome

The respiratory system mechanics depend on the characteristics of the lung and chest wall and their interaction. In patients with acute respiratory distress syndrome under mechanical ventilation, the monitoring of airway plateau pressure is fundamental given its prognostic value and its capacity to assess pulmonary stress. However, its validity can be affected by changes in mechanical characteristics of the chest wall, and it provides no data to correctly titrate positive end-expiratory pressure by restoring lung volume. The chest wall effect on respiratory mechanics in acute respiratory distress syndrome has not been completely described, and it has likely been overestimated, which may lead to erroneous decision making. The load imposed by the chest wall is negligible when the respiratory system is insufflated with positive end-expiratory pressure. Under dynamic conditions, moving this structure demands a pressure change whose magnitude is related to its mechanical characteristics, and this load remains constant regardless of the volume from which it is insufflated. Thus, changes in airway pressure reflect changes in the lung mechanical conditions. Advanced monitoring could be reserved for patients with increased intra-abdominal pressure in whom a protective mechanical ventilation strategy cannot be implemented. The estimates of alveolar recruitment based on respiratory system mechanics could reflect differences in chest wall response to insufflation and not actual alveolar recruitment.

Lung volumes, respiratory mechanics and dynamic strain during general anaesthesia

BACKGROUND

Driving pressure (ΔP) represents tidal volume normalised to respiratory system compliance (C_RS) and is a novel parameter to target ventilator settings. We conducted a study to determine whether C_RS and ΔP reflect aerated lung volume and dynamic strain during general anaesthesia.

METHODS

Twenty non-obese patients undergoing open abdominal surgery received three PEEP levels (2, 7, or 12 cm H₂O) in random order with constant tidal volume ventilation. Respiratory mechanics, lung volumes, and alveolar recruitment were measured to assess end-expiratory aerated volume, which was compared with the patient's individual predicted functional residual capacity in supine position (FRCp).

RESULTS

C_RS was linearly related to aerated volume and ΔP to dynamic strain at PEEP of 2 cm H₂O (intraoperative FRC) (r=0.72 and r=0.73, both P<0.001). These relationships were maintained with higher PEEP only when aerated volume did not overcome FRCp (r=0.73, P<0.001; r=0.54, P=0.004), with 100 ml lung volume increases accompanied by 1.8 ml cm H₂O^-1 (95% confidence interval [1.1-2.5]) increases in C_RS. When aerated volume was greater or equal to FRCp (35% of patients at PEEP 2 cm H₂O, 55% at PEEP 7 cm H₂O, and 75% at PEEP 12 cm H₂O), C_RS and ΔP were independent from aerated volume and dynamic strain, with C_RS weakly but significantly inversely related to alveolar dead space fraction (r=-0.47, P=0.001). PEEP-induced alveolar recruitment yielded higher C_RS and reduced ΔP only at aerated volumes below FRCp (P=0.015 and 0.008, respectively).

CONCLUSIONS

During general anaesthesia, respiratory system compliance and driving pressure reflect aerated lung volume and dynamic strain, respectively, only if aerated volume does not exceed functional residual capacity in supine position, which is a frequent event when PEEP is used in this setting.

Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.