What links ventilator driving pressure with survival in the acute respiratory distress syndrome? A computational study

Driving pressure in acute respiratory distress syndrome for developing a protective lung strategy: A systematic review

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a critical condition characterized by acute hypoxemia, non-cardiogenic pulmonary edema, and decreased lung compliance. The Berlin definition, updated in 2012, classifies ARDS severity based on the partial pressure of arterial oxygen/fractional inspired oxygen fraction ratio. Despite various treatment strategies, ARDS remains a significant public health concern with high mortality rates.

AIM

To evaluate the implications of driving pressure (DP) in ARDS management and its potential as a protective lung strategy.

METHODS

We conducted a systematic review using databases including EbscoHost, MEDLINE, CINAHL, PubMed, and Google Scholar. The search was limited to articles published between January 2015 and September 2024. Twenty-three peer-reviewed articles were selected based on inclusion criteria focusing on adult ARDS patients undergoing mechanical ventilation and DP strategies. The literature review was conducted and reported according to PRISMA 2020 guidelines.

RESULTS

DP, the difference between plateau pressure and positive end-expiratory pressure, is crucial in ARDS management. Studies indicate that lower DP levels are significantly associated with improved survival rates in ARDS patients. DP is a better predictor of mortality than tidal volume or positive end-expiratory pressure alone. Adjusting DP by optimizing lung compliance and minimizing overdistension and collapse can reduce ventilator-induced lung injury.

CONCLUSION

DP is a valuable parameter in ARDS management, offering a more precise measure of lung stress and strain than traditional metrics. Implementing DP as a threshold for safety can enhance protective ventilation strategies, potentially reducing mortality in ARDS patients. Further research is needed to refine DP measurement techniques and validate its clinical application in diverse patient populations.

The development of a C5.0 machine learning model in a limited data set to predict early mortality in patients with ARDS undergoing an initial session of prone positioning

BACKGROUND

Acute Respiratory Distress Syndrome (ARDS) has a high morbidity and mortality. One therapy that can decrease mortality is ventilation in the prone position (PP). Patients undergoing PP are amongst the sickest, and there is a need for early identification of patients at particularly high risk of death. These patients may benefit from an in-depth review of treatment or consideration of rescue therapies. We report the development of a machine learning model trained to predict early mortality in patients undergoing prone positioning as part of the management of their ARDS.

METHODS

Prospectively collected clinical data were analysed retrospectively from a single tertiary ICU. The records of patients who underwent an initial session of prone positioning whilst receiving invasive mechanical ventilation were identified (n = 131). The decision to perform prone positioning was based on the criteria in the PROSEVA study. A C5.0 classifier algorithm with adaptive boosting was trained on data gathered before, during, and after initial proning. Data was split between training (85% of data) and testing (15% of data). Hyperparameter tuning was achieved through a grid-search using a maximal entropy configuration. Predictions for 7-day mortality after initial proning session were made on the training and testing data.

RESULTS

The model demonstrated good performance in predicting 7-day mortality (AUROC: 0.89 training, 0.78 testing). Seven variables were used for prediction. Sensitivity was 0.80 and specificity was 0.67 on the testing data set. Patients predicted to survive had 13.3% mortality, while those predicted to die had 66.67% mortality. Among patients in whom the model predicted patient would survive to day 7 based on their response, mortality at day 7 was 13.3%. Conversely, if the model predicted the patient would not survive to day 7, mortality was 66.67%.

CONCLUSIONS

This proof-of-concept study shows that with a limited data set, a C5.0 classifier can predict 7-day mortality from a number of variables, including the response to initial proning, and identify a cohort at significantly higher risk of death. This can help identify patients failing conventional therapies who may benefit from a thorough review of their management, including consideration of rescue treatments, such as extracorporeal membrane oxygenation. This study shows the potential of a machine learning model to identify ARDS patients at high risk of early mortality following PP. This information can guide clinicians in tailoring treatment strategies and considering rescue therapies. Further validation in larger cohorts is needed.

Factors associated with decreased compliance after on-site extracorporeal membrane oxygenation cannulation for acute respiratory distress syndrome: A retrospective, observational cohort study

Background

Extracorporeal membrane oxygenation (ECMO) for acute respiratory distress syndrome (ARDS) is systematically associated with decreased respiratory system compliance (CRS). It remains unclear whether transportation to the referral ECMO center, changes in ventilatory mode or settings to achieve ultra-protective ventilation, or the natural evolution of ARDS drives this change in respiratory mechanics. Herein, we assessed the precise moment when CRS decreases after ECMO cannulation and identified factors associated with decreased CRS.

Methods

To rule out the effect of transportation and the different modes of ventilation on CRS, we conducted a retrospective, single-center, observational cohort study from January 2013 to May 2020, on 22 patients with severe ARDS requiring on-site ECMO and ventilated in pressure-controlled mode to achieve ultra-protective ventilation. CRS was assessed at different time points ranging from 12 h before ECMO cannulation to 72 h after ECMO cannulation. The primary outcome was the relative change in CRS between 3 h before and 3 h after ECMO cannulation. The secondary outcomes included variables associated with the relative changes in CRS within the first 3 h after ECMO cannulation and the relative changes in CRS at each time point.

Results

CRS decreased within the first 3 h after ECMO cannulation (-28.3%, 95% confidence interval [CI]: -38.8 to -17.9, P<0.001), while the decrease was mild before and after these first 3 h after ECMO cannulation. To achieve ultra-protective ventilation, respiratory rate decreased in the mean by -13 breaths/min (95% CI: -15 to -11) and driving pressure by -8.3 cmH2O (95% CI: -11.2 to -5.3), resulting in decreased tidal volume by -3.3 mL/kg of predicted body weight (95% CI: -3.9 to -2.6) as compared to before ECMO cannulation (P <0.001 for all). Plateau pressure reduction, driving pressure reduction, and tidal volume reduction were significantly associated with decreased CRS after ECMO cannulation, whereas neither respiratory rate, positive end-expiratory pressure, inspired fraction of oxygen, fluid balance, nor mean airway pressure was associated with decreased CRS.

Conclusions

Decreased driving pressure resulting in lower tidal volume to achieve ultra-protective ventilation after ECMO cannulation was associated with a marked decrease in CRS in ARDS patients with on-site ECMO cannulation.

Investigating the Association Between Dynamic Driving Pressure and Mortality in COVID-19-Related Acute Respiratory Distress Syndrome: A Joint Modeling Approach Using Real-Time Continuously-Monitored Ventilation Data

IMPORTANCE AND OBJECTIVES

COVID-19-related acute respiratory distress syndrome (ARDS) is associated with high mortality and often necessitates invasive mechanical ventilation (IMV). Previous studies on non-COVID-19 ARDS have shown driving pressure to be robustly associated with ICU mortality; however, those studies relied on "static" driving pressure measured periodically and manually. As "continuous" automatically monitored driving pressure is becoming increasingly available and reliable with more advanced mechanical ventilators, we aimed to examine the effect of this "dynamic" driving pressure in COVID-19 ARDS throughout the entire ventilation period.

DESIGN SETTING AND PARTICIPANTS

This retrospective, observational study cohort study evaluates the association between driving pressure and ICU mortality in patients with concurrent COVID-19 and ARDS using multivariate joint modeling. The study cohort (n = 544) included all adult patients (≥ 18 yr) with COVID-19 ARDS between March 1, 2020, and April 30, 2021, on volume-control mode IMV for 12 hours or more in a Mass General Brigham, Boston, MA ICU.

MEASUREMENTS AND MAIN RESULTS

Of 544 included patients, 171 (31.4%) died in the ICU. Increased dynamic ΔP was associated with increased risk in the hazard of ICU mortality (hazard ratio [HR] 1.035; 95% credible interval, 1.004-1.069) after adjusting for other relevant dynamic respiratory biomarkers. A significant increase in risk in the hazard of death was found for every hour of exposure to high intensities of driving pressure (≥ 15 cm H2O) (HR 1.002; 95% credible interval 1.001-1.003).

CONCLUSIONS

Limiting patients' exposure to high intensities of driving pressure even while under lung-protective ventilation may represent a critical step in improving ICU survival in patients with COVID-19 ARDS. Time-series IMV data could be leveraged to enhance real-time monitoring and decision support to optimize ventilation strategies at the bedside.

Changes in Driving Pressure vs Oxygenation as Predictor of Mortality in Moderate to Severe Acute Respiratory Distress Syndrome Patients Receiving Prone Position Ventilation

Background

Prone position ventilation (PPV) causes improvement in oxygenation, nevertheless, mortality in severe acute respiratory distress syndrome (ARDS) remains high. The changes in the driving pressure (DP) and its role in predicting mortality in moderate to severe ARDS patients receiving PPV is unexplored.

Methods

A prospective observational study, conducted between September 2020 and February 2023 on moderate-severe ARDS patients requiring PPV. The values of DP and oxygenation (ratio of partial pressure of arterial oxygen to fraction of inspired oxygen [PaO2/FiO2]) before, during, and after PPV were recorded. The aim was to compare the DP and oxygenation before, during and after PPV sessions among moderate- severe ARDS patients, and determine the best predictor of mortality.

Results

Total of 52 patients were included; 28-day mortality was 57%. Among the survivors, DP prior to PPV as compared to post-PPV session reduced significantly, from 16.36 ± 2.57 cmH2O to 13.91 ± 1.74 cmH2O (p-value < 0.001), whereas DP did not reduce in the non-survivors (19.43 ± 3.16 to 19.70 ± 3.15 cmH2O (p-value = 0.318)]. Significant improvement in PaO2/FiO2 before PPV to post-PPV among both the survivors [92.75 [67.5-117.75]) to [205.50 (116.25-244.50)], (p-value < 0.001) and also among the non-survivors [87.90 (67.75-100.75)] to [112 (88.00-146.50)], (p-value < 0.001) was noted. Logistic regression analysis showed DP after PPV session as best predictor of mortality (p-value = 0.044) and its AUROC to predict mortality was 0.939, cut-off ≥16 cmH2O, 90% sensitivity, 82% specificity. The Kaplan-Meier curve of DP after PPV ≥16 cmH2O and <16 cmH2O was significant (Log-rank Mantel-Cox p-value < 0.001).

Conclusion

Prone position ventilation-induced decrease in DP is prognostic marker of survival than the increase in PaO2/FiO2. There is a primacy of DP, rather than oxygenation, in predicting mortality in moderate-severe ARDS. Post-PPV session DP ≥16 cmH2O was an independent predictor of mortality.

How to cite this article

Todur P, Nileshwar A, Chaudhuri S, Shanbhag V, Cherisma C. Changes in Driving Pressure vs Oxygenation as Predictor of Mortality in Moderate to Severe Acute Respiratory Distress Syndrome Patients Receiving Prone Position Ventilation. Indian J Crit Care Med 2024;28(2):134-140.

The Impact of Mechanical Energy Assessment on Mechanical Ventilation: A Comprehensive Review and Practical Application

Mechanical ventilation (MV) provides basic organ support for patients who have acute hypoxemic respiratory failure, with acute respiratory distress syndrome as the most severe form. The use of excessive ventilation forces can exacerbate the lung condition and lead to ventilator-induced lung injury (VILI); mechanical energy (ME) or power can characterize such forces applied during MV. The ME metric combines all MV parameters affecting the respiratory system (ie, lungs, chest, and airways) into a single value. Besides evaluating the overall ME, this parameter can be also related to patient-specific characteristics, such as lung compliance or patient weight, which can further improve the value of ME for characterizing the aggressiveness of lung ventilation. High ME is associated with poor outcomes and could be used as a prognostic parameter and indicator of the risk of VILI. ME is rarely determined in everyday practice because the calculations are complicated and based on multiple equations. Although low ME does not conclusively prevent the possibility of VILI (eg, due to the lung inhomogeneity and preexisting damage), individualization of MV settings considering ME appears to improve outcomes. This article aims to review the roles of bedside assessment of mechanical power, its relevance in mechanical ventilation, and its associations with treatment outcomes. In addition, we discuss methods for ME determination, aiming to propose the most suitable method for bedside application of the ME concept in everyday practice.

The power of mechanical ventilation may predict mortality in critically ill patients

BACKGROUND

Mechanical power (MP) is the amount of energy transferred from the ventilator to the patient within a unit of time. It has been emphasized in ventilation-induced lung injury (VILI) and mortality. However, its measurement and use in clinical practice are challenging. "Electronic recording systems (ERS)" using mechanical ventilation parameters provided by the ventilator can be helpful to measure and record the MP. The MP (J/minutes) formula is 0.098 x tidal volume x respiratory rate x (Ppeak - ½ ∆P), in which ∆P is the driving pressure and Ppeak is the peak pressure. We aimed to define the association between MP values and ICU mortality, mechanical ventilation days, and intensive care unit length of stay (ICU-LOS). The secondary outcome was to determine the most potent or essential component of power in the equation that has a role in mortality.

METHODS

This retrospective study was performed in two centers (VKV American Hospital and Bakırköy Sadi Konuk Hospital ICUs) that used ERS (Metavision IMDsoft) between 2014 and 2018. We uploaded the power formula (MP (J/minutes)=0.098×VT×RR×(Ppeak - ½ ∆P) to ERS (METAvision, iMDsoft, and Consult Orion Health) and calculated the MP value by using MV parameters automatically sent from the ventilator. (∆P; driving pressure, VT; tidal volume, RR; respiratory rate and Ppeak; peak pressure).

RESULTS

A total of 3042 patients were included in the study. The median value of MP was 11.3 J/min. Mortality in MP<11.3 J/min was 35.4%, and 49.1% in MP>11.3J/min.; P<0.001. Mechanical ventilation days and ICU-LOS were also statistically longer in the MVP>11.3 J/min group.

CONCLUSIONS

The first 24 h MP maybe a predictive value for the ICU patients' prognosis. This implies that MP may be used as a decision-making system to define the clinical approach and as a scoring system to predict patient prognosis.

Developing an Artificial Intelligence-Based Representation of a Virtual Patient Model for Real-Time Diagnosis of Acute Respiratory Distress Syndrome

Acute Respiratory Distress Syndrome (ARDS) is a condition that endangers the lives of many Intensive Care Unit patients through gradual reduction of lung function. Due to its heterogeneity, this condition has been difficult to diagnose and treat, although it has been the subject of continuous research, leading to the development of several tools for modeling disease progression on the one hand, and guidelines for diagnosis on the other, mainly the "Berlin Definition". This paper describes the development of a deep learning-based surrogate model of one such tool for modeling ARDS onset in a virtual patient: the Nottingham Physiology Simulator. The model-development process takes advantage of current machine learning and data-analysis techniques, as well as efficient hyperparameter-tuning methods, within a high-performance computing-enabled data science platform. The lightweight models developed through this process present comparable accuracy to the original simulator (per-parameter R2 > 0.90). The experimental process described herein serves as a proof of concept for the rapid development and dissemination of specialised diagnosis support systems based on pre-existing generalised mechanistic models, making use of supercomputing infrastructure for the development and testing processes and supported by open-source software for streamlined implementation in clinical routines.

Computational Simulation of Virtual Patients Reduces Dataset Bias and Improves Machine Learning-Based Detection of ARDS from Noisy Heterogeneous ICU Datasets

Goal: Machine learning (ML) technologies that leverage large-scale patient data are promising tools predicting disease evolution in individual patients. However, the limited generalizability of ML models developed on single-center datasets, and their unproven performance in real-world settings, remain significant constraints to their widespread adoption in clinical practice. One approach to tackle this issue is to base learning on large multi-center datasets. However, such heterogeneous datasets can introduce further biases driven by data origin, as data structures and patient cohorts may differ between hospitals. Methods: In this paper, we demonstrate how mechanistic virtual patient (VP) modeling can be used to capture specific features of patients' states and dynamics, while reducing biases introduced by heterogeneous datasets. We show how VP modeling can be used for data augmentation through identification of individualized model parameters approximating disease states of patients with suspected acute respiratory distress syndrome (ARDS) from observational data of mixed origin. We compare the results of an unsupervised learning method (clustering) in two cases: where the learning is based on original patient data and on data derived in the matching procedure of the VP model to real patient data. Results: More robust cluster configurations were observed in clustering using the model-derived data. VP model-based clustering also reduced biases introduced by the inclusion of data from different hospitals and was able to discover an additional cluster with significant ARDS enrichment. Conclusions: Our results indicate that mechanistic VP modeling can be used to significantly reduce biases introduced by learning from heterogeneous datasets and to allow improved discovery of patient cohorts driven exclusively by medical conditions.

Extracorporeal Membrane Oxygenation Carbon Dioxide Removal

Protective lung ventilation is the mainstay ventilation strategy for patients on extracorporeal membrane oxygenation (ECMO), as prolonged mechanical ventilation increases morbidity and mortality; the technicalities of ventilation with ECMO have evolved in the last decade. ECMO on the other end of the spectrum is a complete or total extracorporeal support, which supplies complete physiological blood gas exchanges, normally performed by the native lungs and thus is capable of delivering oxygen (O2) and removing CO equal to the metabolic needs of the patient, it requires higher flows, is more complex, and uses bigger cannulas, higher dose of heparin and higher blood volume for priming. This review describes in detail carbon dioxide removal on ECMO.

Development and validation of a mathematical model to simulate human cardiovascular and respiratory responses to battlefield trauma

Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to generate synthetic data to train artificial intelligence (AI) clinical decision-support systems and assess closed-loop control technologies, for military medical applications. However, existing models are either complex, standalone systems that lack the interface to other applications or fail to capture the essential features of the physiological responses to the major causes of battlefield trauma (i.e., hemorrhage and airway compromise). To address these limitations, we developed the cardio-respiratory (CR) model by expanding and integrating two previously published models of the cardiovascular and respiratory systems. We compared the vital signs predicted by the CR model with those from three models, using experimental data from 27 subjects in five studies, involving hemorrhage, fluid resuscitation, and respiratory perturbations. Overall, the CR model yielded relatively small root mean square errors (RMSEs) for mean arterial pressure (MAP; 20.88 mm Hg), end-tidal CO₂ (ETCO₂ ; 3.50 mm Hg), O₂ saturation (SpO₂ ; 3.40%), and arterial O₂ pressure (PaO₂ ; 10.06 mm Hg), but a relatively large RMSE for heart rate (HR; 70.23 beats/min). In addition, the RMSEs for the CR model were 3% to 10% smaller than the three other models for HR, 11% to 15% for ETCO₂ , 0% to 33% for SpO₂ , and 10% to 64% for PaO₂ , while they were similar for MAP. In conclusion, the CR model balances simplicity and accuracy, while qualitatively and quantitatively capturing human physiological responses to battlefield trauma, supporting its use to train and assess emerging AI and control systems.

Mechanical power is associated with weaning outcome in critically ill mechanically ventilated patients

Several single-center studies have evaluated the predictive performance of mechanical power (MP) on weaning outcomes in prolonged invasive mechanical ventilation (IMV) patients. The relationship between MP and weaning outcomes in all IMV patients has rarely been studied. A retrospective study was conducted on MIMIC-IV patients with IMV for more than 24 h to investigate the correlation between MP and weaning outcome using logistic regression model and subgroup analysis. The discriminative ability of MP, MP normalized to dynamic lung compliance (C_dyn-MP) and MP normalized to predicted body weight (PBW-MP) on weaning outcome were evaluated by analyzing the area under the receiver-operating characteristic (AUROC). Following adjustment for confounding factors, compared with the reference group, the Odds Ratio of weaning failure in the maximum MP, C_dyn-MP, and PBW-MP groups increased to 3.33 [95%CI (2.04-4.53), P < 0.001], 3.58 [95%CI (2.27-5.56), P < 0.001] and 5.15 [95%CI (3.58-7.41), P < 0.001], respectively. The discriminative abilities of C_dyn-MP (AUROC 0.760 [95%CI 0.745-0.776]) and PBW-MP (AUROC 0.761 [95%CI 0.744-0.779]) were higher than MP (AUROC 0.745 [95%CI 0.730-0.761]) (P < 0.05). MP is associated with weaning outcomes in IMV patients and is an independent predictor of the risk of weaning failure. C_dyn-MP and PBW-MP showed higher ability in weaning failure prediction than MP.

A computational cardiopulmonary physiology simulator accurately predicts individual patient responses to changes in mechanical ventilator settings

We present new results validating the capability of a high-fidelity computational simulator to accurately predict the responses of individual patients with acute respiratory distress syndrome to changes in mechanical ventilator settings. 26 pairs of data-points comprising arterial blood gasses collected before and after changes in inspiratory pressure, PEEP, FiO₂, and I:E ratio from six mechanically ventilated patients were used for this study. Parallelized global optimization algorithms running on a high-performance computing cluster were used to match the simulator to each initial data point. Mean absolute percentage errors between the simulator predicted values of PaO₂ and PaCO₂ and the patient data after changing ventilator parameters were 10.3% and 12.6%, respectively. Decreasing the complexity of the simulator by reducing the number of independent alveolar compartments reduced the accuracy of its predictions. Clinical Relevance- These results provide further evidence that our computational simulator can accurately reproduce patient responses to mechanical ventilation, highlighting its usefulness as a clinical research tool.

Venovenous extracorporeal CO2 removal to support ultraprotective ventilation in moderate-severe acute respiratory distress syndrome: A systematic review and meta-analysis of the literature

BACKGROUND

A strategy that limits tidal volumes and inspiratory pressures, improves outcomes in patients with the acute respiratory distress syndrome (ARDS). Extracorporeal carbon dioxide removal (ECCO₂R) may facilitate ultra-protective ventilation. We conducted a systematic review and meta-analysis to evaluate the efficacy and safety of venovenous ECCO₂R in supporting ultra-protective ventilation in moderate-to-severe ARDS.

METHODS

MEDLINE and EMBASE were interrogated for studies (2000-2021) reporting venovenous ECCO₂R use in patients with moderate-to-severe ARDS. Studies reporting ≥10 adult patients in English language journals were included. Ventilatory parameters after 24 h of initiating ECCO₂R, device characteristics, and safety outcomes were collected. The primary outcome measure was the change in driving pressure at 24 h of ECCO₂R therapy in relation to baseline. Secondary outcomes included change in tidal volume, gas exchange, and safety data.

RESULTS

Ten studies reporting 421 patients (PaO₂:FiO₂ 141.03 mmHg) were included. Extracorporeal blood flow rates ranged from 0.35-1.5 L/min. Random effects modelling indicated a 3.56 cmH₂O reduction (95%-CI: 3.22-3.91) in driving pressure from baseline (p < .001) and a 1.89 mL/kg (95%-CI: 1.75-2.02, p < .001) reduction in tidal volume. Oxygenation, respiratory rate and PEEP remained unchanged. No significant interactions between driving pressure reduction and baseline driving pressure, partial pressure of arterial carbon dioxide or PaO₂:FiO₂ ratio were identified in metaregression analysis. Bleeding and haemolysis were the commonest complications of therapy.

CONCLUSIONS

Venovenous ECCO₂R permitted significant reductions in ∆P in patients with moderate-to-severe ARDS. Heterogeneity amongst studies and devices, a paucity of randomised controlled trials, and variable safety reporting calls for standardisation of outcome reporting. Prospective evaluation of optimal device operation and anticoagulation in high quality studies is required before further recommendations can be made.

Reduced survival in patients requiring chest tubes with COVID-19 acute respiratory distress syndrome

Background

Numerous complications requiring tube thoracostomy have been reported among critically ill patients with COVID-19; however, there has been a lack of evidence regarding outcomes following chest tube placement.

Methods

We developed a retrospective observational cohort of all patients admitted to an intensive care unit (ICU) with confirmed COVID-19 to describe the incidence of tube thoracostomy and factors associated with mortality following chest tube placement.

Results

In total, 1705 patients with laboratory confirmed COVID-19 patients were admitted to our ICUs from March 7, 2020, to March 1, 2021, with 69 out of 1705 patients (4.0%) receiving 130 chest tubes. Of these, 89 out of 130 (68%) chest tubes were indicated for pneumothorax. Patients receiving tube thoracostomy were much less likely to be alive 90 days post-ICU admission (52% vs 69%; P < .01), and had longer ICU (30 vs 5 days; P < .01) and hospital (37 vs 10 days; P < .01) lengths of stay compared with those without tube thoracostomy. Patients who received tube thoracostomy and survived at least 90 days post-ICU admission had shorter times to first chest tube insertion (8.5 vs 17.0 days; P = .01) and a nonsignificantly higher static compliance (20.0 vs 17.5 mL/cm H₂O; P = .052) at the time of chest tube placement than those who had expired. Logistic regression analysis demonstrated an association between time to first chest tube and decreased survival when adjusted for covariates.

Conclusions

Requiring a chest tube in COVID-19 is a negative prognostic end point. Delayed development of chest tube requirement was associated with a decreased survival and could reflect a poor healing phenotype.

Validation of at-the-bedside formulae for estimating ventilator driving pressure during airway pressure release ventilation using computer simulation

BACKGROUND

Airway pressure release ventilation (APRV) is widely available on mechanical ventilators and has been proposed as an early intervention to prevent lung injury or as a rescue therapy in the management of refractory hypoxemia. Driving pressure ([Formula: see text]) has been identified in numerous studies as a key indicator of ventilator-induced-lung-injury that needs to be carefully controlled. [Formula: see text] delivered by the ventilator in APRV is not directly measurable in dynamic conditions, and there is no "gold standard" method for its estimation.

METHODS

We used a computational simulator matched to data from 90 patients with acute respiratory distress syndrome (ARDS) to evaluate the accuracy of three "at-the-bedside" methods for estimating ventilator [Formula: see text] during APRV.

RESULTS

Levels of [Formula: see text] delivered by the ventilator in APRV were generally within safe limits, but in some cases exceeded levels specified by protective ventilation strategies. A formula based on estimating the intrinsic positive end expiratory pressure present at the end of the APRV release provided the most accurate estimates of [Formula: see text]. A second formula based on assuming that expiratory flow, volume and pressure decay mono-exponentially, and a third method that requires temporarily switching to volume-controlled ventilation, also provided accurate estimates of true [Formula: see text].

CONCLUSIONS

Levels of [Formula: see text] delivered by the ventilator during APRV can potentially exceed levels specified by standard protective ventilation strategies, highlighting the need for careful monitoring. Our results show that [Formula: see text] delivered by the ventilator during APRV can be accurately estimated at the bedside using simple formulae that are based on readily available measurements.

Modeling Mechanical Ventilation In Silico-Potential and Pitfalls

Computer simulation offers a fresh approach to traditional medical research that is particularly well suited to investigating issues related to mechanical ventilation. Patients receiving mechanical ventilation are routinely monitored in great detail, providing extensive high-quality data-streams for model design and configuration. Models based on such data can incorporate very complex system dynamics that can be validated against patient responses for use as investigational surrogates. Crucially, simulation offers the potential to "look inside" the patient, allowing unimpeded access to all variables of interest. In contrast to trials on both animal models and human patients, in silico models are completely configurable and reproducible; for example, different ventilator settings can be applied to an identical virtual patient, or the same settings applied to different patients, to understand their mode of action and quantitatively compare their effectiveness. Here, we review progress on the mathematical modeling and computer simulation of human anatomy, physiology, and pathophysiology in the context of mechanical ventilation, with an emphasis on the clinical applications of this approach in various disease states. We present new results highlighting the link between model complexity and predictive capability, using data on the responses of individual patients with acute respiratory distress syndrome to changes in multiple ventilator settings. The current limitations and potential of in silico modeling are discussed from a clinical perspective, and future challenges and research directions highlighted.

OLA strategy for ARDS: Its effect on mortality depends on achieved recruitment (PaO2/FiO2) and mechanical power. Systematic review and meta-analysis with meta-regression

OBJECTIVE

The "Open Lung Approach" (OLA), that includes high levels of positive end-expiratory pressure coupled with limited tidal volumes, is considered optimal for adult patients with ARDS. However, many previous meta-analyses have shown only marginal benefits of OLA on mortality but with statistical heterogeneity. It is crucial to identify the most likely moderators of this effect. To determine the effect of OLA strategy on mortality of ventilated ARDS patients. We hypothesized that the degree of recruitment achieved in the control group (PaO₂/FiO₂ ratio on day 3 of ventilation), and the difference in Mechanical Power (MP) or Driving Pressure (DP) between experimental and control groups will be the most likely sources of heterogeneity.

DESIGN

A Systematic Review and Meta-analysis was performed according to PRISMA statement and registered in PROSPERO database. We searched only for randomized controlled trials (RCTs). GRADE guidelines were used for rating the quality of evidence. Publication bias was assessed. For the Meta-analysis, we used a Random Effects Model. Sources of heterogeneity were explored with Meta-Regression, using a priori proposed set of possible moderators. For model comparison, Akaike's Information Criterion with the finite sample correction (AICc) was used.

SETTING

Not applicable.

PATIENTS

Fourteen RCTs were included in the study.

INTERVENTIONS

Not applicable.

MAIN VARIABLES OF INTEREST

Not applicable.

RESULTS

Evidence of publication bias was detected, and quality of evidence was downgraded. Pooled analysis did not show a significant difference in the 28-day mortality between OLA strategy and control groups. Overall risk of bias was low. The analysis detected statistical heterogeneity. The two "best" explicative meta-regression models were those that used control PaO₂/FiO₂ on day 3 and difference in MP between experimental and control groups. The DP and MP models were highly correlated.

CONCLUSIONS

There is no clear benefit of OLA strategy on mortality of ARDS patients, with significant heterogeneity among RCTs. Mortality effect of OLA is mediated by lung recruitment and mechanical power.

The Association between Mechanical Power and Mortality in Patients with Pneumonia Using Pressure-Targeted Ventilation

Recent studies have reported that mechanical power (MP) is associated with increased mortality in patients with acute respiratory distress syndrome (ARDS). We aimed to investigate the association between 28-day mortality and MP in patients with severe pneumonia. In total, the data of 313 patients with severe pneumonia were used for analysis. Serial MP was calculated daily for either 21 days or until ventilator support was no longer required. Compared with the non-ARDS group, the ARDS group (106 patients) demonstrated lower age, a higher Acute Physiology and Chronic Health Evaluation II score, lower history of diabetes mellitus, elevated incidences of shock and jaundice, higher MP and driving pressure on Day 1, and more deaths within 28 days. Regression analysis revealed that MP was an independent factor associated with 28-day mortality (odds ratio, 1.048; 95% confidence interval, 1.020-1.077). MP was persistently high in non-survivors and low in survivors among the ARDS group, the non-ARDS group, and all patients. These findings indicate that MP is associated with the 28-day mortality in ventilated patients with severe pneumonia, both in the ARDS and non-ARDS groups. MP had a better predicted value for the 28-day mortality than the driving pressure.

High risk of patient self-inflicted lung injury in COVID-19 with frequently encountered spontaneous breathing patterns: a computational modelling study

BACKGROUND

There is on-going controversy regarding the potential for increased respiratory effort to generate patient self-inflicted lung injury (P-SILI) in spontaneously breathing patients with COVID-19 acute hypoxaemic respiratory failure. However, direct clinical evidence linking increased inspiratory effort to lung injury is scarce. We adapted a computational simulator of cardiopulmonary pathophysiology to quantify the mechanical forces that could lead to P-SILI at different levels of respiratory effort. In accordance with recent data, the simulator parameters were manually adjusted to generate a population of 10 patients that recapitulate clinical features exhibited by certain COVID-19 patients, i.e., severe hypoxaemia combined with relatively well-preserved lung mechanics, being treated with supplemental oxygen.

RESULTS

Simulations were conducted at tidal volumes (VT) and respiratory rates (RR) of 7 ml/kg and 14 breaths/min (representing normal respiratory effort) and at VT/RR of 7/20, 7/30, 10/14, 10/20 and 10/30 ml/kg / breaths/min. While oxygenation improved with higher respiratory efforts, significant increases in multiple indicators of the potential for lung injury were observed at all higher VT/RR combinations tested. Pleural pressure swing increased from 12.0 ± 0.3 cmH2O at baseline to 33.8 ± 0.4 cmH2O at VT/RR of 7 ml/kg/30 breaths/min and to 46.2 ± 0.5 cmH2O at 10 ml/kg/30 breaths/min. Transpulmonary pressure swing increased from 4.7 ± 0.1 cmH2O at baseline to 17.9 ± 0.3 cmH2O at VT/RR of 7 ml/kg/30 breaths/min and to 24.2 ± 0.3 cmH2O at 10 ml/kg/30 breaths/min. Total lung strain increased from 0.29 ± 0.006 at baseline to 0.65 ± 0.016 at 10 ml/kg/30 breaths/min. Mechanical power increased from 1.6 ± 0.1 J/min at baseline to 12.9 ± 0.2 J/min at VT/RR of 7 ml/kg/30 breaths/min, and to 24.9 ± 0.3 J/min at 10 ml/kg/30 breaths/min. Driving pressure increased from 7.7 ± 0.2 cmH2O at baseline to 19.6 ± 0.2 cmH2O at VT/RR of 7 ml/kg/30 breaths/min, and to 26.9 ± 0.3 cmH2O at 10 ml/kg/30 breaths/min.

CONCLUSIONS

Our results suggest that the forces generated by increased inspiratory effort commonly seen in COVID-19 acute hypoxaemic respiratory failure are comparable with those that have been associated with ventilator-induced lung injury during mechanical ventilation. Respiratory efforts in these patients should be carefully monitored and controlled to minimise the risk of lung injury.

ECCO2R in 12 COVID-19 ARDS Patients With Extremely Low Compliance and Refractory Hypercapnia

Purpose: A phenotype of COVID-19 ARDS patients with extremely low compliance and refractory hypercapnia was found in our ICU. In the context of limited number of ECMO machines, feasibility of a low-flow extracorporeal carbon dioxide removal (ECCO₂R) based on the renal replacement therapy (RRT) platform in these patients was assessed. Methods: Single-center, prospective study. Refractory hypercapnia patients with COVID-19-associated ARDS were included and divided into the adjusted group and unadjusted group according to the level of PaCO₂ after the application of the ECCO₂R system. Ventilation parameters [tidal volume (VT), respiratory rate, and PEEP], platform pressure (Pplat) and driving pressure (DP), respiratory system compliance, arterial blood gases, and ECCO₂R system characteristics were collected. Results: Twelve patients with refractory hypercapnia were enrolled, and the PaCO₂ was 64.5 [56-88.75] mmHg. In the adjusted group, VT was significantly reduced from 5.90 ± 0.16 to 5.08 ± 0.43 ml/kg PBW; DP and Pplat were also significantly reduced from 23.5 ± 2.72 mmHg and 29.88 ± 3.04 mmHg to 18.5 ± 2.62 mmHg and 24.75 ± 3.41 mmHg, respectively. In the unadjusted group, PaCO₂ decreased from 94 [86.25, 100.3] mmHg to 80 [67.50, 85.25] mmHg but with no significant difference, and the DP and Pplat were not decreased after weighing the pros and cons. Conclusions: A low-flow ECCO₂R system based on the RRT platform enabled CO₂ removal and could also decrease the DP and Pplat significantly, which provided a new way to treat these COVID-19 ARDS patients with refractory hypercapnia and extremely low compliance. Clinical Trial Registration: https://www.clinicaltrials.gov/, identifier NCT04340414.

OLA strategy for ARDS: Its effect on mortality depends on achieved recruitment (PaO2/FiO2) and mechanical power. Systematic review and meta-analysis with meta-regression

OBJECTIVE

The "Open Lung Approach" (OLA), that includes high levels of positive end-expiratory pressure coupled with limited tidal volumes, is considered optimal for adult patients with ARDS. However, many previous meta-analyses have shown only marginal benefits of OLA on mortality but with statistical heterogeneity. It is crucial to identify the most likely moderators of this effect. To determine the effect of OLA strategy on mortality of ventilated ARDS patients. We hypothesized that the degree of recruitment achieved in the control group (PaO2/FiO2 ratio on day 3 of ventilation), and the difference in Mechanical Power (MP) or Driving Pressure (DP) between experimental and control groups will be the most likely sources of heterogeneity.

DESIGN

A Systematic Review and Meta-analysis was performed according to PRISMA statement and registered in PROSPERO database. We searched only for randomized controlled trials (RCTs). GRADE guidelines were used for rating the quality of evidence. Publication bias was assessed. For the Meta-analysis, we used a Random Effects Model. Sources of heterogeneity were explored with Meta-Regression, using a priori proposed set of possible moderators. For model comparison, Akaike's Information Criterion with the finite sample correction (AICc) was used.

SETTING

Not applicable.

PATIENTS

Fourteen RCTs were included in the study.

INTERVENTIONS

Not applicable.

MAIN VARIABLES OF INTEREST

Not applicable.

RESULTS

Evidence of publication bias was detected, and quality of evidence was downgraded. Pooled analysis did not show a significant difference in the 28-day mortality between OLA strategy and control groups. Overall risk of bias was low. The analysis detected statistical heterogeneity. The two "best" explicative meta-regression models were those that used control PaO2/FiO2 on day 3 and difference in MP between experimental and control groups. The DP and MP models were highly correlated.

CONCLUSIONS

There is no clear benefit of OLA strategy on mortality of ARDS patients, with significant heterogeneity among RCTs. Mortality effect of OLA is mediated by lung recruitment and mechanical power.

[Intraoperative Ventilation Approaches to One-lung Ventilation]

The management of thoracic surgery patients is challenging to the anesthetist, since one-lung ventilation (OLV) includes at least two major conditions: sufficient oxygenation and lung protection. The first is mainly because the ventilation of one lung is stopped while perfusion to that lung continues; the latter is related to the fact that the whole ventilation is applied to only a single lung. Recommendations for maintaining the oxygenation and methods of lung protection may contradict each other (e. g. high vs. low inspiratory oxygen fraction (FiO₂), high vs. low tidal volume, etc.). Therefore, a high degree of pathophysiological understanding and manual skills are required in the management of these patients.In light of recent clinical studies, this review focuses on a current protective strategy for OLV, which includes a possible decrease in FiO₂, lowered V_T, the application of positive end-expiratory pressure (PEEP) to the dependent and continuous positive airway pressure (CPAP) to the non-dependent lung and alveolar recruitment manoeuvres as well. Other approaches such as the choice of anaesthetics, remote ischemic preconditioning, fluid management and pain therapy can support the success of ventilatory strategy. The present work describes new developments that may change the classical approach in this respect.

Utility of Driving Pressure and Mechanical Power to Guide Protective Ventilator Settings in Two Cohorts of Adult and Pediatric Patients With Acute Respiratory Distress Syndrome: A Computational Investigation

OBJECTIVES

Mechanical power and driving pressure have been proposed as indicators, and possibly drivers, of ventilator-induced lung injury. We tested the utility of these different measures as targets to derive maximally protective ventilator settings.

DESIGN

A high-fidelity computational simulator was matched to individual patient data and used to identify strategies that minimize driving pressure, mechanical power, and a modified mechanical power that removes the direct linear, positive dependence between mechanical power and positive end-expiratory pressure.

SETTING

Interdisciplinary Collaboration in Systems Medicine Research Network.

SUBJECTS

Data were collected from a prospective observational cohort of pediatric acute respiratory distress syndrome from the Children's Hospital of Philadelphia (n = 77) and from the low tidal volume arm of the Acute Respiratory Distress Syndrome Network tidal volume trial (n = 100).

INTERVENTIONS

Global optimization algorithms evaluated more than 26.7 million changes to ventilator settings (approximately 150,000 per patient) to identify strategies that minimize driving pressure, mechanical power, or modified mechanical power.

MEASUREMENTS AND MAIN RESULTS

Large average reductions in driving pressure (pediatric: 23%, adult: 23%), mechanical power (pediatric: 44%, adult: 66%), and modified mechanical power (pediatric: 61%, adult: 67%) were achievable in both cohorts when oxygenation and ventilation were allowed to vary within prespecified ranges. Reductions in driving pressure (pediatric: 12%, adult: 2%), mechanical power (pediatric: 24%, adult: 46%), and modified mechanical power (pediatric: 44%, adult: 46%) were achievable even when no deterioration in gas exchange was allowed. Minimization of mechanical power and modified mechanical power was achieved by increasing tidal volume and decreasing respiratory rate. In the pediatric cohort, minimum driving pressure was achieved by reducing tidal volume and increasing respiratory rate and positive end-expiratory pressure. The Acute Respiratory Distress Syndrome Network dataset had limited scope for further reducing tidal volume, but driving pressure was still significantly reduced by increasing positive end-expiratory pressure.

CONCLUSIONS

Our analysis identified different strategies that minimized driving pressure or mechanical power consistently across pediatric and adult datasets. Minimizing standard and alternative formulations of mechanical power led to significant increases in tidal volume. Targeting driving pressure for minimization resulted in ventilator settings that also reduced mechanical power and modified mechanical power, but not vice versa.

Progress of mechanical power in the intensive care unit

Mechanical power of ventilation, currently defined as the energy delivered from the ventilator to the respiratory system over a period of time, has been recognized as a promising indicator to evaluate ventilator-induced lung injury and predict the prognosis of ventilated critically ill patients. Mechanical power can be accurately measured by the geometric method, while simplified equations allow an easy estimation of mechanical power at the bedside. There may exist a safety threshold of mechanical power above which lung injury is inevitable, and the assessment of mechanical power might be helpful to determine whether the extracorporeal respiratory support is needed in patients with acute respiratory distress syndrome. It should be noted that relatively low mechanical power does not exclude the possibility of lung injury. Lung size and inhomogeneity should also be taken into consideration. Problems regarding the safety limits of mechanical power and contribution of each component to lung injury have not been determined yet. Whether mechanical power-directed lung-protective ventilation strategy could improve clinical outcomes also needs further investigation. Therefore, this review discusses the algorithms, clinical relevance, optimization, and future directions of mechanical power in critically ill patients.

Volatile anesthetics versus intravenous anesthetics for noncardiac thoracic surgery: a systematic review and meta-analysis

INTRODUCTION

We performed this meta-analysis of randomised controlled trials (RCTs) to investigate two types of anesthetics for noncardiac thoracic surgery regarding their effects on clinical outcomes and the inflammatory response.

EVIDENCE ACQUISITION

We searched Cochrane Library, PubMed and EMBASE for RCTs comparing volatile anesthetics to intravenous anesthetics for noncardiac thoracic surgery.

EVIDENCE SYNTHESIS

This study reviewed 16 RCTs with 1467 patients. Volatile anesthetics reduced postoperative complications and the length of intensive care unit stay for lung surgery. They also lowered the concentrations of interleukin (IL)-1β, IL-6, IL-8 and tumour necrosis factor-α (TNF-α) in the airways of patients undergoing noncardiac thoracic surgery. However, there was no difference in short-term mortality; postoperative complications after esophagectomy; IL-1β, IL-6, IL-8 or TNF-α concentrations in the blood; IL-10 level in either the airway or the blood; overall monocyte chemoattractant protein-1.

CONCLUSIONS

In lung surgery, but not esophagectomy, volatile anesthetics may be a better choice than intravenous anesthetics, possibly because volatile anesthetics reduce airway inflammation.

In Silico Modeling of Coronavirus Disease 2019 Acute Respiratory Distress Syndrome: Pathophysiologic Insights and Potential Management Implications

Supplemental Digital Content is available in the text.

Objectives:

Patients with coronavirus disease 2019 acute respiratory distress syndrome appear to present with at least two distinct phenotypes: severe hypoxemia with relatively well-preserved lung compliance and lung gas volumes (type 1) and a more conventional acute respiratory distress syndrome phenotype, displaying the typical characteristics of the “baby lung” (type 2). We aimed to test plausible hypotheses regarding the pathophysiologic mechanisms underlying coronavirus disease 2019 acute respiratory distress syndrome and to evaluate the resulting implications for ventilatory management.

Design:

We adapted a high-fidelity computational simulator, previously validated in several studies of acute respiratory distress syndrome, to: 1) develop quantitative insights into the key pathophysiologic differences between the coronavirus disease 2019 acute respiratory distress syndrome and the conventional acute respiratory distress syndrome and 2) assess the impact of different positive end-expiratory pressure, Fio_2, and tidal volume settings.

Setting:

Interdisciplinary Collaboration in Systems Medicine Research Network.

Subjects:

The simulator was calibrated to represent coronavirus disease 2019 acute respiratory distress syndrome patients with both normal and elevated body mass indices undergoing invasive mechanical ventilation.

Interventions:

None.

Measurements and Main Results:

An acute respiratory distress syndrome model implementing disruption of hypoxic pulmonary vasoconstriction and vasodilation leading to hyperperfusion of collapsed lung regions failed to replicate clinical data on type 1 coronavirus disease 2019 acute respiratory distress syndrome patients. Adding mechanisms to reflect disruption of alveolar gas-exchange due to the effects of pneumonitis and heightened vascular resistance due to the emergence of microthrombi produced levels of ventilation perfusion mismatch and hypoxemia consistent with data from type 1 coronavirus disease 2019 acute respiratory distress syndrome patients, while preserving close-to-normal lung compliance and gas volumes. Atypical responses to positive end-expiratory pressure increments between 5 and 15 cm H₂O were observed for this type 1 coronavirus disease 2019 acute respiratory distress syndrome model across a range of measures: increasing positive end-expiratory pressure resulted in reduced lung compliance and no improvement in oxygenation, whereas mechanical power, driving pressure, and plateau pressure all increased. Fio₂ settings based on acute respiratory distress syndrome network protocols at different positive end-expiratory pressure levels were insufficient to achieve adequate oxygenation. Incrementing tidal volumes from 5 to 10 mL/kg produced similar increases in multiple indicators of ventilator-induced lung injury in the type 1 coronavirus disease 2019 acute respiratory distress syndrome model to those seen in a conventional acute respiratory distress syndrome model.

Conclusions:

Our model suggests that use of standard positive end-expiratory pressure/Fio₂ tables, higher positive end-expiratory pressure strategies, and higher tidal volumes may all be potentially deleterious in type 1 coronavirus disease 2019 acute respiratory distress syndrome patients, and that a highly personalized approach to treatment is advisable.

Management of primary blast lung injury: a comparison of airway pressure release versus low tidal volume ventilation

BACKGROUND

Primary blast lung injury (PBLI) presents as a syndrome of respiratory distress and haemoptysis resulting from explosive shock wave exposure and is a frequent cause of mortality and morbidity in both military conflicts and terrorist attacks. The optimal mode of mechanical ventilation for managing PBLI is not currently known, and clinical trials in humans are impossible due to the sporadic and violent nature of the disease.

METHODS

A high-fidelity multi-organ computational simulator of PBLI pathophysiology was configured to replicate data from 14 PBLI casualties from the conflict in Afghanistan. Adaptive and responsive ventilatory protocols implementing low tidal volume (LTV) ventilation and airway pressure release ventilation (APRV) were applied to each simulated patient for 24 h, allowing direct quantitative comparison of their effects on gas exchange, ventilatory parameters, haemodynamics, extravascular lung water and indices of ventilator-induced lung injury.

RESULTS

The simulated patients responded well to both ventilation strategies. Post 24-h investigation period, the APRV arm had similar PF ratios (137 mmHg vs 157 mmHg), lower sub-injury threshold levels of mechanical power (11.9 J/min vs 20.7 J/min) and lower levels of extravascular lung water (501 ml vs 600 ml) compared to conventional LTV. Driving pressure was higher in the APRV group (11.9 cmH₂O vs 8.6 cmH₂O), but still significantly less than levels associated with increased mortality.

CONCLUSIONS

Appropriate use of APRV may offer casualties with PBLI important mortality-related benefits and should be considered for management of this challenging patient group.

Risk factors for acute respiratory distress syndrome in severe burns: prospective cohort study

INTRODUCTION

Age and inhalation injury are important risk factors for acute respiratory distress syndrome (ARDS) in the burned patient; however, the impact of interventions such as mechanical ventilation, fluid balance (FB), and packed red blood cell transfusion remains unclear. The purpose of this study was to determine the incidence of moderate and severe ARDS and its risk factors among burn-related demographic variables and clinical interventions in mechanically ventilated burn patients. Risk factors for death within 28 days were also evaluated.

METHOD

A prospective longitudinal study was carried out over a period of 30 months between July 2015 and December 2017. Patients older than 18 years, with a burn injury and under mechanical ventilation were included. The outcomes of interest were diagnosis of ARDS up to seven days after admission and death within 28 days. The proportional Cox regression risk model was used to obtain the hazard ratio for each independent variable.

RESULTS

The cases of 61 patients were analyzed. Thirty-seven (60.66%) of the patients developed ARDS. The groups of patients with or without ARDS did not present differences regarding age, sex, burned body surface, or prognostic scores. Factors independently related to the occurrence of ARDS were age (hazard ratio [HR] = 1.04; 95% confidence interval [CI] 1.02-1.06; P < 0.001), inhalation injury (HR = 2.50; 95% CI 1.25-5.02; P = 0.01), and static compliance (HR = 0.97; 95% CI 0.94-0.99; P = 0.03). Tidal volume, driving pressure, acute renal injury, and FB between days 1 and 7 were similar in both groups. Accumulated FBs of 48, 72, 96, and 168 hours were also similar. Mortality at 28 days was 40.98% (25 patients). ARDS (HR = 3.63, 95% CI 1.36 to 9.68; P = 0.01) and burned body surface area (HR = 1.03, 95% CI 1.02 to 1.05; P < 0.001) were associated with death in 28 days.

CONCLUSION

ARDS was a frequent complication and a risk factor for death in patients under mechanical ventilation, with large burned areas. Age and inhalation injury were independent factors for ARDS. Current tidal volume, driving pressure, red blood cell transfusion, acute renal injury, and FB were not predictors of ARDS.

Effect of oxygen fraction on airway rescue: a computational modelling study

BACKGROUND

During induction of general anaesthesia, patients frequently experience apnoea, which can lead to dangerous hypoxaemia. An obstructed upper airway can impede attempts to provide ventilation. Although unrelieved apnoea is rare, it continues to cause deaths. Clinical investigation of management strategies for such scenarios is effectively impossible because of ethical and practical considerations.

METHODS

A population-representative cohort of 100 virtual (in silico) subjects was configured using a high-fidelity computational model of the pulmonary and cardiovascular systems. Each subject breathed 100% oxygen for 3 min and then became apnoeic, with an obstructed upper airway, during induction of general anaesthesia. Apnoea continued throughout the protocol. When arterial oxygen saturation (Sao₂) reached 20%, 40%, or 60%, airway obstruction was relieved. We examined the effect of varying supraglottic oxygen fraction (Fo₂) on the degree of passive re-oxygenation occurring without tidal ventilation.

RESULTS

Relief of airway obstruction during apnoea produced a single, passive inhalation (caused by intrathoracic hypobaric pressure) in all cases. The degree of re-oxygenation after airway opening was markedly influenced by the supraglottic Fo₂, with a supraglottic Fo₂ of 100% providing significant and sustained re-oxygenation (post-rescue Pao₂ 42.3 [4.4] kPa, when the airway rescue occurred after desaturation to Sao₂ 60%).

CONCLUSIONS

Supraglottic oxygen supplementation before relieving upper airway obstruction improves the effectiveness of simulated airway rescue. Management strategies should be implemented to assure a substantially increased pharyngeal Fo₂ during difficult airway management.

Comparative effects of open-lung positive end-expiratory pressure (PEEP) and fixed PEEP on respiratory system compliance in the isoflurane anaesthetised healthy dog

This study was performed to assess the effects of open-lung positive end-expiratory pressure (OL-PEEP) following stepwise recruitment manoeuvre (RM) and those of a fixed PEEP of 5 cm H₂O without previous RM on respiratory system compliance (Crs) and selected cardiovascular variables in healthy dogs under general anaesthesia. Forty-five healthy client-owned dogs undergoing surgery were anaesthetised and mechanically ventilated (tidal volume, VT = 10-12 mL/kg; PEEP = 0 cm H₂O) for 1 min (baseline) and randomly allocated into zero positive end-expiratory pressure (ZEEP), PEEP (5 cm H₂O) and OL-PEEP treatment groups. In the OL-PEEP group, a stepwise RM was performed and the individual OL-PEEP was subsequently applied. The Crs, heart rate (HR) and non-invasive mean arterial pressure (NIMAP) were registered at baseline and then every 10 min during 60 min. In the ZEEP group, Crs decreased from baseline. In the PEEP group, Crs was not different from either baseline or ZEEP group values. In the OL-PEEP group, Crs was higher than both baseline and ZEEP group values at all time points as well as of those in the PEEP group during at least 20 min after RM. There were no differences for HR and NIMAP between groups. A clinically relevant hypotension following RM was observed in 40% of dogs. Therefore, an individually set OL-PEEP following stepwise RM improved Crs in anaesthetised healthy dogs, although transient but clinically relevant hypotension was observed during RM in some dogs. Fixed PEEP of 5 cm H₂O without previous RM did not improve Crs, although it prevented it from decreasing.