An Update on Management of Adult Patients with Acute Respiratory Distress Syndrome: An Official American Thoracic Society Clinical Practice Guideline.

Background: This document updates previously published Clinical Practice Guidelines for the management of patients with acute respiratory distress syndrome (ARDS), incorporating new evidence addressing the use of corticosteroids, venovenous extracorporeal membrane oxygenation, neuromuscular blocking agents, and positive end-expiratory pressure (PEEP). Methods: We summarized evidence addressing four "PICO questions" (patient, intervention, comparison, and outcome). A multidisciplinary panel with expertise in ARDS used the Grading of Recommendations, Assessment, Development, and Evaluation framework to develop clinical recommendations. Results: We suggest the use of: 1) corticosteroids for patients with ARDS (conditional recommendation, moderate certainty of evidence), 2) venovenous extracorporeal membrane oxygenation in selected patients with severe ARDS (conditional recommendation, low certainty of evidence), 3) neuromuscular blockers in patients with early severe ARDS (conditional recommendation, low certainty of evidence), and 4) higher PEEP without lung recruitment maneuvers as opposed to lower PEEP in patients with moderate to severe ARDS (conditional recommendation, low to moderate certainty), and 5) we recommend against using prolonged lung recruitment maneuvers in patients with moderate to severe ARDS (strong recommendation, moderate certainty). Conclusions: We provide updated evidence-based recommendations for the management of ARDS. Individual patient and illness characteristics should be factored into clinical decision making and implementation of these recommendations while additional evidence is generated from much-needed clinical trials.

Dyssynchronous diaphragm contractions impair diaphragm function in mechanically ventilated patients.

BACKGROUND: Pre-clinical studies suggest that dyssynchronous diaphragm contractions during mechanical ventilation may cause acute diaphragm dysfunction. We aimed to describe the variability in diaphragm contractile loading conditions during mechanical ventilation and to establish whether dyssynchronous diaphragm contractions are associated with the development of impaired diaphragm dysfunction. METHODS: In patients receiving invasive mechanical ventilation for pneumonia, septic shock, acute respiratory distress syndrome, or acute brain injury, airway flow and pressure and diaphragm electrical activity (Edi) were recorded hourly around the clock for up to 7 days. Dyssynchronous post-inspiratory diaphragm loading was defined based on the duration of neural inspiration after expiratory cycling of the ventilator. Diaphragm function was assessed on a daily basis by neuromuscular coupling (NMC, the ratio of transdiaphragmatic pressure to diaphragm electrical activity). RESULTS: A total of 4508 hourly recordings were collected in 45 patients. Edi was low or absent (≤ 5 µV) in 51% of study hours (median 71 h per patient, interquartile range 39-101 h). Dyssynchronous post-inspiratory loading was present in 13% of study hours (median 7 h per patient, interquartile range 2-22 h). The probability of dyssynchronous post-inspiratory loading was increased with reverse triggering (odds ratio 15, 95% CI 8-35) and premature cycling (odds ratio 8, 95% CI 6-10). The duration and magnitude of dyssynchronous post-inspiratory loading were associated with a progressive decline in diaphragm NMC (p < 0.01 for interaction with time). CONCLUSIONS: Dyssynchronous diaphragm contractions may impair diaphragm function during mechanical ventilation. TRIAL REGISTRATION: MYOTRAUMA, ClinicalTrials.gov NCT03108118. Registered 04 April 2017 (retrospectively registered).

Flow starvation during square-flow assisted ventilation detected by supervised deep learning techniques.

BACKGROUND: Flow starvation is a type of patient-ventilator asynchrony that occurs when gas delivery does not fully meet the patients' ventilatory demand due to an insufficient airflow and/or a high inspiratory effort, and it is usually identified by visual inspection of airway pressure waveform. Clinical diagnosis is cumbersome and prone to underdiagnosis, being an opportunity for artificial intelligence. Our objective is to develop a supervised artificial intelligence algorithm for identifying airway pressure deformation during square-flow assisted ventilation and patient-triggered breaths. METHODS: Multicenter, observational study. Adult critically ill patients under mechanical ventilation > 24 h on square-flow assisted ventilation were included. As the reference, 5 intensive care experts classified airway pressure deformation severity. Convolutional neural network and recurrent neural network models were trained and evaluated using accuracy, precision, recall and F1 score. In a subgroup of patients with esophageal pressure measurement (ΔPes), we analyzed the association between the intensity of the inspiratory effort and the airway pressure deformation. RESULTS: 6428 breaths from 28 patients were analyzed, 42% were classified as having normal-mild, 23% moderate, and 34% severe airway pressure deformation. The accuracy of recurrent neural network algorithm and convolutional neural network were 87.9% [87.6-88.3], and 86.8% [86.6-87.4], respectively. Double triggering appeared in 8.8% of breaths, always in the presence of severe airway pressure deformation. The subgroup analysis demonstrated that 74.4% of breaths classified as severe airway pressure deformation had a ΔPes > 10 cmH2O and 37.2% a ΔPes > 15 cmH2O. CONCLUSIONS: Recurrent neural network model appears excellent to identify airway pressure deformation due to flow starvation. It could be used as a real-time, 24-h bedside monitoring tool to minimize unrecognized periods of inappropriate patient-ventilator interaction.

Reverse Triggering during Controlled Ventilation: From Physiology to Clinical Management.

Reverse triggering dyssynchrony is a frequent phenomenon recently recognized in sedated critically ill patients under controlled ventilation. It occurs in at least 30-55% of these patients and often occurs in the transition from fully passive to assisted mechanical ventilation. During reverse triggering, patient inspiratory efforts start after the passive insufflation by mechanical breaths. The most often referred mechanism is the entrainment of the patient's intrinsic respiratory rhythm from the brainstem respiratory centers to periodic mechanical insufflations from the ventilator. However, reverse triggering might also occur because of local reflexes without involving the respiratory rhythm generator in the brainstem. Reverse triggering is observed during the acute phase of the disease, when patients may be susceptible to potential deleterious consequences of injurious or asynchronous efforts. Diagnosing reverse triggering might be challenging and can easily be missed. Inspection of ventilator waveforms or more sophisticated methods, such as the electrical activity of the diaphragm or esophageal pressure, can be used for diagnosis. The occurrence of reverse triggering might have clinical consequences. On the basis of physiological data, reverse triggering might be beneficial or injurious for the diaphragm and the lung, depending on the magnitude of the inspiratory effort. Reverse triggering can cause breath-stacking and loss of protective lung ventilation when triggering a second cycle. Little is known about how to manage patients with reverse triggering; however, available evidence can guide management on the basis of physiological principles.

Causes, Consequences, and Treatments of Sleep and Circadian Disruption in the ICU: An Official American Thoracic Society Research Statement.

Background: Sleep and circadian disruption (SCD) is common and severe in the ICU. On the basis of rigorous evidence in non-ICU populations and emerging evidence in ICU populations, SCD is likely to have a profound negative impact on patient outcomes. Thus, it is urgent that we establish research priorities to advance understanding of ICU SCD. Methods: We convened a multidisciplinary group with relevant expertise to participate in an American Thoracic Society Workshop. Workshop objectives included identifying ICU SCD subtopics of interest, key knowledge gaps, and research priorities. Members attended remote sessions from March to November 2021. Recorded presentations were prepared and viewed by members before Workshop sessions. Workshop discussion focused on key gaps and related research priorities. The priorities listed herein were selected on the basis of rank as established by a series of anonymous surveys. Results: We identified the following research priorities: establish an ICU SCD definition, further develop rigorous and feasible ICU SCD measures, test associations between ICU SCD domains and outcomes, promote the inclusion of mechanistic and patient-centered outcomes within large clinical studies, leverage implementation science strategies to maximize intervention fidelity and sustainability, and collaborate among investigators to harmonize methods and promote multisite investigation. Conclusions: ICU SCD is a complex and compelling potential target for improving ICU outcomes. Given the influence on all other research priorities, further development of rigorous, feasible ICU SCD measurement is a key next step in advancing the field.

Dyspnoea and respiratory muscle ultrasound to predict extubation failure.

BACKGROUND: This study investigated dyspnoea intensity and respiratory muscle ultrasound early after extubation to predict extubation failure. METHODS: The study was conducted prospectively in two intensive care units in France and Canada. Patients intubated for at least 48 h were studied within 2 h after an extubation following a successful spontaneous breathing trial. Dyspnoea was evaluated by a dyspnoea visual analogue scale (Dyspnoea-VAS) ranging from 0 to 10 and the Intensive Care Respiratory Distress Observational Scale (IC-RDOS). The ultrasound thickening fraction of the parasternal intercostal and the diaphragm was measured; limb muscle strength was evaluated using the Medical Research Council (MRC) score (range 0-60). RESULTS: Extubation failure occurred in 21 out of 122 enrolled patients (17%). The median (interquartile range (IQR)) Dyspnoea-VAS and IC-RDOS were higher in patients with extubation failure versus success: 7 (4-9) versus 3 (1-5) (p<0.001) and 3.7 (1.8-5.8) versus 1.7 (1.5-2.1) (p<0.001), respectively. The median (IQR) ratio of parasternal intercostal muscle to diaphragm thickening fraction was significantly higher and MRC was lower in patients with extubation failure compared with extubation success: 0.9 (0.4-2.1) versus 0.3 (0.2-0.5) (p<0.001) and 45 (36-50) versus 52 (44-60) (p=0.012), respectively. The thickening fraction of the parasternal intercostal and its ratio to diaphragm thickening showed the highest area under the receiver operating characteristic curve (AUC) for an early prediction of extubation failure (0.81). AUCs of Dyspnoea-VAS and IC-RDOS reached 0.78 and 0.74, respectively. CONCLUSIONS: Respiratory muscle ultrasound and dyspnoea measured within 2 h after extubation predict subsequent extubation failure.

Reverse Triggering Dyssynchrony 24 h after Initiation of Mechanical Ventilation.

BACKGROUND: Reverse triggering is a delayed asynchronous contraction of the diaphragm triggered by passive insufflation by the ventilator in sedated mechanically ventilated patients. The incidence of reverse triggering is unknown. This study aimed at determining the incidence of reverse triggering in critically ill patients under controlled ventilation. METHODS: In this ancillary study, patients were continuously monitored with a catheter measuring the electrical activity of the diaphragm. A method for automatic detection of reverse triggering using electrical activity of the diaphragm was developed in a derivation sample and validated in a subsequent sample. The authors assessed the predictive value of the software. In 39 recently intubated patients under assist-control ventilation, a 1-h recording obtained 24 h after intubation was used to determine the primary outcome of the study. The authors also compared patients' demographics, sedation depth, ventilation settings, and time to transition to assisted ventilation or extubation according to the median rate of reverse triggering. RESULTS: The positive and negative predictive value of the software for detecting reverse triggering were 0.74 (95% CI, 0.67 to 0.81) and 0.97 (95% CI, 0.96 to 0.98). Using a threshold of 1 µV of electrical activity to define diaphragm activation, median reverse triggering rate was 8% (range, 0.1 to 75), with 44% (17 of 39) of patients having greater than or equal to 10% of breaths with reverse triggering. Using a threshold of 3 µV, 26% (10 of 39) of patients had greater than or equal to 10% reverse triggering. Patients with more reverse triggering were more likely to progress to an assisted mode or extubation within the following 24 h (12 of 39 [68%]) vs. 7 of 20 [35%]; P = 0.039). CONCLUSIONS: Reverse triggering detection based on electrical activity of the diaphragm suggests that this asynchrony is highly prevalent at 24 h after intubation under assist-control ventilation. Reverse triggering seems to occur during the transition phase between deep sedation and the onset of patient triggering.

Automated detection and quantification of reverse triggering effort under mechanical ventilation.

BACKGROUND: Reverse triggering (RT) is a dyssynchrony defined by a respiratory muscle contraction following a passive mechanical insufflation. It is potentially harmful for the lung and the diaphragm, but its detection is challenging. Magnitude of effort generated by RT is currently unknown. Our objective was to validate supervised methods for automatic detection of RT using only airway pressure (Paw) and flow. A secondary objective was to describe the magnitude of the efforts generated during RT. METHODS: We developed algorithms for detection of RT using Paw and flow waveforms. Experts having Paw, flow and esophageal pressure (Pes) assessed automatic detection accuracy by comparison against visual assessment. Muscular pressure (Pmus) was measured from Pes during RT, triggered breaths and ineffective efforts. RESULTS: Tracings from 20 hypoxemic patients were used (mean age 65 ± 12 years, 65% male, ICU survival 75%). RT was present in 24% of the breaths ranging from 0 (patients paralyzed or in pressure support ventilation) to 93.3%. Automatic detection accuracy was 95.5%: sensitivity 83.1%, specificity 99.4%, positive predictive value 97.6%, negative predictive value 95.0% and kappa index of 0.87. Pmus of RT ranged from 1.3 to 36.8 cmH20, with a median of 8.7 cmH20. RT with breath stacking had the highest levels of Pmus, and RTs with no breath stacking were of similar magnitude than pressure support breaths. CONCLUSION: An automated detection tool using airway pressure and flow can diagnose reverse triggering with excellent accuracy. RT generates a median Pmus of 9 cmH2O with important variability between and within patients. TRIAL REGISTRATION: BEARDS, NCT03447288.

Duration of diaphragmatic inactivity after endotracheal intubation of critically ill patients.

BACKGROUND: In patients intubated for mechanical ventilation, prolonged diaphragm inactivity could lead to weakness and poor outcome. Time to resume a minimal diaphragm activity may be related to sedation practice and patient severity. METHODS: Prospective observational study in critically ill patients. Diaphragm electrical activity (EAdi) was continuously recorded after intubation looking for resumption of a minimal level of diaphragm activity (beginning of the first 24 h period with median EAdi > 7 µV, a threshold based on literature and correlations with diaphragm thickening fraction). Recordings were collected until full spontaneous breathing, extubation, death or 120 h. A 1 h waveform recording was collected daily to identify reverse triggering. RESULTS: Seventy-five patients were enrolled and 69 analyzed (mean age ± standard deviation 63 ± 16 years). Reasons for ventilation were respiratory (55%), hemodynamic (19%) and neurologic (20%). Eight catheter disconnections occurred. The median time for resumption of EAdi was 22 h (interquartile range 0-50 h); 35/69 (51%) of patients resumed activity within 24 h while 4 had no recovery after 5 days. Late recovery was associated with use of sedative agents, cumulative doses of propofol and fentanyl, controlled ventilation and age (older patients receiving less sedation). Severity of illness, oxygenation, renal and hepatic function, reason for intubation were not associated with EAdi resumption. At least 20% of patients initiated EAdi with reverse triggering. CONCLUSION: Low levels of diaphragm electrical activity are common in the early course of mechanical ventilation: 50% of patients do not recover diaphragmatic activity within one day. Sedatives are the main factors accounting for this delay independently from lung or general severity. Trial Registration ClinicalTrials.gov (NCT02434016). Registered on April 27, 2015. First patients enrolled June 2015.

Respiratory Drive in Critically Ill Patients. Pathophysiology and Clinical Implications.

Respiratory drive, the intensity of the respiratory center's output, determines the effort exerted in each breath. The increasing awareness of the adverse effects of both strong and weak respiratory efforts during mechanical ventilation on patient outcome brings attention to the respiratory drive of the critically ill patient. Critical illness can affect patients' respiratory drive through multiple pathways, mainly operating through three feedback systems: cortical, metabolic, and chemical. The chemical feedback system, defined as the response of the respiratory center's output to changes in arterial blood gases and pH, is one of the most important determinants of respiratory drive. The purpose of this state-of-the-art review is to describe the determinants of respiratory drive in critically ill patients, review the tools available to assess respiratory drive at the bedside, and discuss the implications of altered respiratory drive during mechanical ventilation. An analysis that relates arterial carbon dioxide levels with brain's response to this stimulus will be presented, contrasting the brain's responses to the patient's ability to generate effective alveolar ventilation, both during unassisted breathing and with different modes of ventilatory assist. This analysis may facilitate comprehension of the pathophysiology of respiratory drive in critically ill patients. As we aim to avoid both over- and under-assistance with mechanical ventilation, considering the patients' respiratory drive at the bedside may improve clinical assessment and management of the patient and the ventilator.

Airway Occlusion Pressure As an Estimate of Respiratory Drive and Inspiratory Effort during Assisted Ventilation.

Rationale: Monitoring and controlling respiratory drive and effort may help to minimize lung and diaphragm injury. Airway occlusion pressure (P0.1) is a noninvasive measure of respiratory drive.Objectives: To determine 1) the validity of "ventilator" P0.1 (P0.1vent) displayed on the screen as a measure of drive, 2) the ability of P0.1 to detect potentially injurious levels of effort, and 3) how P0.1vent displayed by different ventilators compares to a "reference" P0.1 (P0.1ref) measured from airway pressure recording during an occlusion.Methods: Analysis of three studies in patients, one in healthy subjects, under assisted ventilation, and a bench study with six ventilators. P0.1vent was validated against measures of drive (electrical activity of the diaphragm and muscular pressure over time) and P0.1ref. Performance of P0.1ref and P0.1vent to detect predefined potentially injurious effort was tested using derivation and validation datasets using esophageal pressure-time product as the reference standard.Measurements and Main Results: P0.1vent correlated well with measures of drive and with the esophageal pressure-time product (within-subjects R2 = 0.8). P0.1ref >3.5 cm H2O was 80% sensitive and 77% specific for detecting high effort (≥200 cm H2O ⋅ s ⋅ min-1); P0.1ref ≤1.0 cm H2O was 100% sensitive and 92% specific for low effort (≤50 cm H2O ⋅ s ⋅ min-1). The area under the receiver operating characteristics curve for P0.1vent to detect potentially high and low effort were 0.81 and 0.92, respectively. Bench experiments showed a low mean bias for P0.1vent compared with P0.1ref for most ventilators but precision varied; in patients, precision was lower. Ventilators estimating P0.1vent without occlusions could underestimate P0.1ref.Conclusions: P0.1 is a reliable bedside tool to assess respiratory drive and detect potentially injurious inspiratory effort.

Lung- and Diaphragm-Protective Ventilation.

Mechanical ventilation can cause acute diaphragm atrophy and injury, and this is associated with poor clinical outcomes. Although the importance and impact of lung-protective ventilation is widely appreciated and well established, the concept of diaphragm-protective ventilation has recently emerged as a potential complementary therapeutic strategy. This Perspective, developed from discussions at a meeting of international experts convened by PLUG (the Pleural Pressure Working Group) of the European Society of Intensive Care Medicine, outlines a conceptual framework for an integrated lung- and diaphragm-protective approach to mechanical ventilation on the basis of growing evidence about mechanisms of injury. We propose targets for diaphragm protection based on respiratory effort and patient-ventilator synchrony. The potential for conflict between diaphragm protection and lung protection under certain conditions is discussed; we emphasize that when conflicts arise, lung protection must be prioritized over diaphragm protection. Monitoring respiratory effort is essential to concomitantly protect both the diaphragm and the lung during mechanical ventilation. To implement lung- and diaphragm-protective ventilation, new approaches to monitoring, to setting the ventilator, and to titrating sedation will be required. Adjunctive interventions, including extracorporeal life support techniques, phrenic nerve stimulation, and clinical decision-support systems, may also play an important role in selected patients in the future. Evaluating the clinical impact of this new paradigm will be challenging, owing to the complexity of the intervention. The concept of lung- and diaphragm-protective ventilation presents a new opportunity to potentially improve clinical outcomes for critically ill patients.

A physiology-based mathematical model for the selection of appropriate ventilator controls for lung and diaphragm protection.

Mechanical ventilation is used to sustain respiratory function in patients with acute respiratory failure. To aid clinicians in consistently selecting lung- and diaphragm-protective ventilation settings, a physiology-based decision support system is needed. To form the foundation of such a system, a comprehensive physiological model which captures the dynamics of ventilation has been developed. The Lung and Diaphragm Protective Ventilation (LDPV) model centers around respiratory drive and incorporates respiratory system mechanics, ventilator mechanics, and blood acid-base balance. The model uses patient-specific parameters as inputs and outputs predictions of a patient's transpulmonary and esophageal driving pressures (outputs most clinically relevant to lung and diaphragm safety), as well as their blood pH, under various ventilator and sedation conditions. Model simulations and global optimization techniques were used to evaluate and characterize the model. The LDPV model is demonstrated to describe a CO2 respiratory response that is comparable to what is found in literature. Sensitivity analysis of the model indicate that the ventilator and sedation settings incorporated in the model have a significant impact on the target output parameters. Finally, the model is seen to be able to provide robust predictions of esophageal pressure, transpulmonary pressure and blood pH for patient parameters with realistic variability. The LDPV model is a robust physiological model which produces outputs which directly target and reflect the risk of ventilator-induced lung and diaphragm injury. Ventilation and sedation parameters are seen to modulate the model outputs in accordance with what is currently known in literature.

Techniques to monitor respiratory drive and inspiratory effort.

PURPOSE OF REVIEW: There is increased awareness that derangements of respiratory drive and inspiratory effort are frequent and can result in lung and diaphragm injury together with dyspnea and sleep disturbances. This review aims to describe available techniques to monitor drive and effort. RECENT FINDINGS: Measuring drive and effort is necessary to quantify risk and implement strategies to minimize lung and the diaphragm injury by modifying sedation and ventilation. Evidence on the efficacy of such strategies is yet to be elucidated, but physiological and epidemiological data support the need to avoid injurious patterns of breathing effort.Some techniques have been used in research for decades (e.g., esophageal pressure or airway occlusion pressure), evidence on their practical utility is growing, and technical advances have eased implementation. More novel techniques (e.g., electrical activity of the diaphragm and ultrasound) are being investigated providing new insights on their use and interpretation. SUMMARY: Available techniques provide reliable measures of the intensity and timing of drive and effort. Simple, noninvasive techniques might be implemented in most patients and the more invasive or time-consuming in more complex patients at higher risk. We encourage clinicians to become familiar with technical details and physiological rationale of each for optimal implementation.

Evidence Supporting Clinical Use of Proportional Assist Ventilation: A Systematic Review and Meta-Analysis of Clinical Trials.

BACKGROUND: While proportional assist ventilation (PAV), generates pressure in proportion to effort without a preselected target, proportional assist ventilation plus (PAV+) measures compliance and resistance, calculates work of breathing, and adjusts support to a preset assistance level. OBJECTIVE: To summarize randomized controlled trials (RCTs) comparing invasive or noninvasive PAV or PAV+ in critically ill patients. Data Sources: We searched multiple databases to April 2017 without language restrictions and conference proceedings from 5 meetings to identify randomized parallel-group and crossover RCTs that compared invasive or noninvasive PAV or PAV+ to another mode in critically ill adults or children and reported at least 1 clinically important outcome. RESULTS: We identified 14 RCTs (11 parallel group and 3 crossover) assessing PAV (n = 7) and PAV+ (n = 7) involving 931 adult patients. We found no effect of noninvasive PAV (vs noninvasive pressure support [PS]) on intubation (risk ratio 0.92 [0.59 to 1.43], I2 = 0%) or invasive PAV (vs invasive PS) on percentage rapid eye movement sleep (mean difference [MD] -2.93% [-14.20 to ±8.34], I2 = 43%). Compared to invasive PS, invasive PAV+ showed a nonsignificant increase in weaning time (MD +0.54 [-0.67 to +1.75] hours, I2 = 0%), but no effect on hospital mortality, reintubation, or tracheostomy. CONCLUSIONS: Current evidence does not support the use of invasive or noninvasive PAV or invasive PAV+ in critically ill adults. Amid low to moderate heterogeneity, we identified 3 promising areas for future research including assessing the role of noninvasive PAV as an initial support strategy in patients with acute respiratory failure, invasive PAV on sleep quality during invasive ventilation, and possibly invasive PAV+ for weaning.

Sleep and Pathological Wakefulness at the Time of Liberation from Mechanical Ventilation (SLEEWE). A Prospective Multicenter Physiological Study.

Rationale: Abnormal patterns of sleep and wakefulness exist in mechanically ventilated patients. Objectives: In this study (SLEEWE [Effect of Sleep Disruption on the Outcome of Weaning from Mechanical Ventilation]), we aimed to investigate polysomnographic indexes as well as a continuous index for evaluating sleep depth, the odds ratio product (ORP), to determine whether abnormal sleep or wakefulness is associated with the outcome of spontaneous breathing trials (SBTs). Methods: Mechanically ventilated patients from three sites were enrolled if an SBT was planned the following day. EEG was recorded using a portable sleep diagnostic device 15 hours before the SBT. The ORP was calculated from the power of four EEG frequency bands relative to each other, ranging from full wakefulness (2.5) to deep sleep (0). The correlation between the right and left hemispheres' ORP (R/L ORP) was calculated. Measurements and Main Results: Among 44 patients enrolled, 37 had technically adequate signals: 11 (30%) passed the SBT and were extubated, 8 (21%) passed the SBT but were not deemed to be clinically ready for extubation, and 18 (49%) failed the SBT. Pathological wakefulness or atypical sleep were highly prevalent, but the distribution of classical sleep stages was similar between groups. The mean ORP and the proportion of time in which the ORP was >2.2 were higher in extubated patients compared with the other groups (P < 0.05). R/L ORP was significantly lower in patients who failed the SBT, and the area under the receiver operating characteristic curve of R/L ORP to predict failure was 0.91 (95% confidence interval, 0.75-0.98). Conclusions: Patients who pass an SBT and are extubated reach higher levels of wakefulness as indicated by the ORP, suggesting abnormal wakefulness in others. The hemispheric ORP correlation is much poorer in patients who fail an SBT.

Intrathoracic Airway Closure Impacts CO2 Signal and Delivered Ventilation during Cardiopulmonary Resuscitation.

RATIONALE: End-tidal CO2 (EtCO2) is used to monitor cardiopulmonary resuscitation (CPR), but it can be affected by intrathoracic airway closure. Chest compressions induce oscillations in expired CO2, and this could reflect variable degrees of airway patency. OBJECTIVES: To understand the impact of airway closure during CPR, and the relationship between the capnogram shape, airway closure, and delivered ventilation. METHODS: This study had three parts: 1) a clinical study analyzing capnograms after intubation in patients with out-of-hospital cardiac arrest receiving continuous chest compressions, 2) a bench model, and 3) experiments with human cadavers. For 2 and 3, a constant CO2 flow was added in the lung to simulate CO2 production. Capnograms similar to clinical recordings were obtained and different ventilator settings tested. EtCO2 was compared with alveolar CO2 (bench). An airway opening index was used to quantify chest compression-induced expired CO2 oscillations in all three clinical and experimental settings. MEASUREMENTS AND MAIN RESULTS: A total of 89 patients were analyzed (mean age, 69 ± 15 yr; 23% female; 12% of hospital admission survival): capnograms exhibited various degrees of oscillations, quantified by the opening index. CO2 value varied considerably across oscillations related to consecutive chest compressions. In bench and cadavers, similar capnograms were reproduced with different degrees of airway closure. Differences in airway patency were associated with huge changes in delivered ventilation. The opening index and delivered ventilation increased with positive end-expiratory pressure, without affecting intrathoracic pressure. Maximal EtCO2 recorded between ventilator breaths reflected alveolar CO2 (bench). CONCLUSIONS: During chest compressions, intrathoracic airway patency greatly affects the delivered ventilation. The expired CO2 signal can reflect CPR effectiveness but is also dependent on airway patency. The maximal EtCO2 recorded between consecutive ventilator breaths best reflects alveolar CO2.