Understanding and Managing ventilator Asynchrony: A Comprehensive Clinical Review for Critical Care Practice

Dr Neeraj Manikath , claude.ai

Abstract

Background: Ventilator asynchrony affects 25-85% of mechanically ventilated patients and is associated with increased duration of mechanical ventilation, ICU length of stay, and mortality. Despite its clinical significance, asynchrony remains underrecognized and suboptimally managed in critical care practice.

Objective: To provide a comprehensive review of ventilator asynchrony types, pathophysiology, clinical consequences, and evidence-based management strategies for critical care practitioners.

Methods: This narrative review synthesizes current literature on ventilator asynchrony, focusing on practical clinical applications and management strategies.

Key Findings: The three major categories of asynchrony—trigger, flow, and cycle asynchrony—each require distinct diagnostic approaches and targeted interventions. Optimal management combines appropriate ventilator settings, sedation strategies, and systematic monitoring protocols.

Conclusions: Understanding and promptly addressing ventilator asynchrony is crucial for optimizing patient-ventilator interaction, reducing complications, and improving clinical outcomes in critically ill patients.

Keywords: Mechanical ventilation, Patient-ventilator asynchrony, Critical care, Respiratory failure, Ventilator management

Introduction

Mechanical ventilation represents one of the most fundamental interventions in critical care medicine, yet the interaction between patient and ventilator remains a complex physiological challenge. Ventilator asynchrony—defined as a mismatch between patient respiratory effort and ventilator assistance—occurs when the patient's respiratory drive conflicts with the ventilator's programmed parameters.¹

This phenomenon affects a substantial proportion of mechanically ventilated patients, with reported incidence rates ranging from 25% to 85% depending on the population studied and detection methods employed.² The clinical significance extends beyond mere discomfort, as asynchrony is independently associated with prolonged mechanical ventilation, increased ICU mortality, and higher healthcare costs.³

Despite technological advances in ventilator design and monitoring capabilities, asynchrony remains a persistent clinical challenge. This review provides a comprehensive framework for understanding, recognizing, and managing the various forms of ventilator asynchrony encountered in contemporary critical care practice.

Pathophysiology of Patient-Ventilator Interaction

Normal Ventilatory Mechanics

During spontaneous breathing, the respiratory control centers coordinate diaphragmatic contraction with accessory muscle recruitment to generate the pressure gradient necessary for airflow. In mechanically ventilated patients, this intrinsic respiratory drive must synchronize with the ventilator's assist mechanisms—a process that requires precise timing and appropriate response characteristics.⁴

The ventilator's ability to detect, respond to, and terminate patient respiratory effort depends on multiple factors including trigger sensitivity, flow delivery patterns, inspiratory termination criteria, and the underlying pathophysiology of respiratory failure. When these elements are mismatched with patient needs, asynchrony inevitably occurs.

Neurological Control and Ventilatory Drive

The respiratory control system continues to function during mechanical ventilation, with the medullary respiratory centers responding to chemical stimuli (CO₂, pH, O₂) and mechanical feedback from pulmonary stretch receptors. Understanding this continued neurological input is crucial for optimizing patient-ventilator synchrony, as attempts to completely suppress respiratory drive often prove counterproductive.⁵

Classification and Types of Ventilator Asynchrony

Ventilator asynchrony can be systematically classified into three primary categories based on the phase of the respiratory cycle affected: trigger asynchrony, flow asynchrony, and cycle asynchrony. Each category encompasses specific subtypes with distinct pathophysiological mechanisms and clinical manifestations.

Trigger Asynchrony

Trigger asynchrony occurs when there is a mismatch between patient inspiratory effort and ventilator triggering response. This category includes several distinct phenomena:

Ineffective Triggering (Wasted Efforts)

Definition and Pathophysiology: Ineffective triggering occurs when patient inspiratory efforts fail to initiate a ventilator-assisted breath. This phenomenon is characterized by detectable patient effort (evidenced by esophageal pressure deflection, diaphragmatic EMG activity, or subtle airway pressure changes) without corresponding ventilator response.⁶

Clinical Pearl: Look for small, sharp deflections in airway pressure tracings during expiration—these "notches" often represent ineffective triggering attempts.

Prevalence and Risk Factors: Ineffective triggering affects 5-50% of ventilated patients, with higher rates observed in patients with:

COPD and dynamic hyperinflation
High levels of PEEP
Deep sedation
Respiratory muscle weakness
Severe metabolic alkalosis

Auto-triggering

Definition and Mechanism: Auto-triggering represents the opposite extreme, where the ventilator initiates breaths without patient effort. This can result from:

Cardiac oscillations transmitted to the breathing circuit
Circuit leaks creating pressure fluctuations
Water condensation in ventilator tubing
Excessive trigger sensitivity settings⁷

Clinical Hack: In patients with suspected auto-triggering, temporarily increase trigger sensitivity (make it less sensitive) and observe whether the triggering episodes resolve.

Delayed Triggering

Definition and Clinical Significance: Delayed triggering occurs when there is an abnormally prolonged interval between patient effort initiation and ventilator response. This creates a temporal mismatch that can increase work of breathing and patient discomfort.⁸

Quantitative Assessment: Normal trigger delay should be <150 milliseconds; delays >300 milliseconds are clinically significant and require intervention.

Flow Asynchrony

Flow asynchrony manifests when the ventilator's flow delivery pattern fails to match patient inspiratory demand, resulting in continued respiratory muscle activity during mechanical inspiration.

Inadequate Flow Delivery

Pathophysiology: This occurs when peak inspiratory flow or flow acceleration is insufficient to meet patient demand. The patient continues inspiratory effort throughout the ventilator's inspiratory phase, leading to increased work of breathing and patient-ventilator fighting.⁹

Recognition: Key signs include:

Persistent negative deflection in airway pressure during inspiration
"Scooped out" appearance of the pressure-time curve
High respiratory rates with short inspiratory times
Patient appears to be "sucking" against the ventilator

Clinical Pearl: Calculate the patient's inspiratory flow demand using the formula: Peak flow demand = Minute ventilation × 4-6. Compare this to the set peak flow to identify potential mismatches.

Flow Pattern Mismatch

Square vs. Decelerating Flow: While most modern ventilators default to decelerating (descending ramp) flow patterns that generally provide better patient comfort, some patients may benefit from square wave or other flow patterns, particularly those with restrictive lung disease or high metabolic demands.¹⁰

Cycle Asynchrony

Cycle asynchrony occurs when there is a mismatch between patient neural inspiratory time and ventilator inspiratory termination, manifesting as either premature or delayed cycling.

Premature Cycling

Mechanism: The ventilator terminates inspiration before the patient's neural inspiratory time has ended, forcing the patient to continue inspiratory effort during early expiration. This is commonly seen in:

Patients with high respiratory drive
Those receiving excessive PEEP
Presence of significant air leaks¹¹

Oyster: Double-triggering is a specific form of premature cycling where the patient's continued inspiratory effort after ventilator cycling triggers an immediate second breath, potentially leading to dangerously high tidal volumes.

Delayed Cycling (Prolonged Inspiration)

Pathophysiology: The ventilator continues inspiration beyond the patient's neural inspiratory time, forcing passive inflation during the patient's neural expiratory phase. This is particularly problematic in pressure support ventilation, where cycling is flow-dependent.¹²

Clinical Consequences:

Increased work of breathing
Hemodynamic compromise due to prolonged positive pressure
Patient discomfort and agitation
Potential for barotrauma

Clinical Assessment and Monitoring

Bedside Recognition Techniques

Visual Assessment

Ventilator Graphics Analysis: Modern ventilators provide real-time pressure, flow, and volume waveforms that serve as the primary tools for asynchrony detection. Key patterns include:

Pressure-time curves: Look for irregularities, double-humping, or abnormal concavity
Flow-time curves: Assess for flow starvation patterns or premature flow termination
Volume-time curves: Evaluate for incomplete expiration or volume stacking

Clinical Hack: Use the "eyeball test"—if the waveforms look chaotic, irregular, or "fighting," asynchrony is likely present and requires systematic evaluation.

Physical Examination Findings

Patient Observation:

Use of accessory muscles during mechanical inspiration
Paradoxical chest wall movement
Visible distress or discomfort
Inability to synchronize speech with ventilator cycles¹³

Auscultation: Listen for:

Harsh breath sounds during inspiration
Prolonged expiratory phase sounds
Asymmetric breath sound timing

Advanced Monitoring Techniques

Esophageal Pressure Monitoring

Gold Standard Assessment: Esophageal pressure (Pes) monitoring provides the most accurate assessment of patient respiratory effort and asynchrony detection. The Pes waveform directly reflects diaphragmatic activity and allows quantification of:

Patient work of breathing
Ineffective triggering episodes
Optimal PEEP titration¹⁴

Practical Implementation: While not universally available, Pes monitoring should be considered in complex cases with persistent asynchrony despite conventional management.

Electrical Activity of the Diaphragm (EAdi)

Neurally Adjusted Ventilatory Assist (NAVA): EAdi monitoring provides real-time assessment of respiratory drive and can guide ventilator adjustments even in the absence of NAVA mode ventilation.¹⁵

Clinical Applications:

Quantification of respiratory drive
Optimal sedation titration
Weaning readiness assessment

Evidence-Based Management Strategies

Optimizing Ventilator Settings

Trigger Sensitivity Optimization

Pressure Triggering:

Start with -1 to -2 cmH₂O for most patients
Avoid excessive sensitivity (<-0.5 cmH₂O) to prevent auto-triggering
Consider less sensitive settings (-3 to -5 cmH₂O) in patients with dynamic hyperinflation¹⁶

Flow Triggering:

Generally more responsive than pressure triggering
Set at 2-3 L/min for most patients
May be preferred in patients with significant circuit leaks

Clinical Pearl: In COPD patients with dynamic hyperinflation, the trigger threshold may need to exceed the level of intrinsic PEEP for effective triggering to occur.

Flow Optimization Strategies

Peak Flow Adjustment:

Increase peak flow to 60-100 L/min in patients showing flow starvation
Use the patient's minute ventilation as a guide: Peak flow = VE × 4-6
Monitor for over-assistance, which can lead to respiratory alkalosis¹⁷

Rise Time Manipulation:

Faster rise times (shorter time to reach peak flow) may benefit patients with high flow demands
Slower rise times may improve comfort in patients with restrictive disease
Adjust based on patient response and comfort

Cycling Criteria Optimization

Pressure Support Ventilation:

Standard cycling at 25% of peak flow works for most patients
Increase cycling threshold (to 40-45%) in COPD patients to prevent delayed cycling
Decrease cycling threshold (to 10-15%) in restrictive disease to prevent premature cycling¹⁸

Volume Control Modes:

Ensure adequate inspiratory time (typically I:E ratio of 1:2 to 1:3)
Consider pressure-regulated volume control (PRVC) for better flow delivery

PEEP Optimization for Asynchrony Reduction

Managing Intrinsic PEEP

Pathophysiology: Dynamic hyperinflation creates intrinsic PEEP that must be overcome before effective triggering can occur. This is particularly problematic in COPD and asthma patients.¹⁹

Management Strategy:

Measure intrinsic PEEP using end-expiratory occlusion
Set external PEEP to 80-85% of intrinsic PEEP level
Monitor for improvement in triggering effectiveness
Avoid excessive PEEP that could worsen hyperinflation

Clinical Hack: In suspected dynamic hyperinflation, try the "squeeze test"—gently compress the chest at end-expiration. If additional flow is expelled, intrinsic PEEP is present.

PEEP Titration for Optimal Synchrony

Individualized Approach:

Use esophageal pressure monitoring when available for optimal PEEP titration
Consider decremental PEEP trials in patients with persistent asynchrony
Monitor multiple parameters: oxygenation, compliance, hemodynamics, and synchrony²⁰

Role of Sedation in Asynchrony Management

Sedation Strategy Framework

Targeted Approach: The goal is not to eliminate respiratory drive but to optimize patient-ventilator interaction while maintaining some level of patient participation in ventilation.²¹

Clinical Pearl: Light sedation with preserved respiratory drive often results in better synchrony than deep sedation, which can lead to ineffective triggering and delayed weaning.

Pharmacological Considerations

Propofol:

Rapid onset and offset
Dose-dependent respiratory depression
Useful for titrating to optimal sedation level
Consider in patients requiring frequent neurological assessments

Dexmedetomidine:

Minimal respiratory depression
Maintains some level of arousability
May be preferred in patients with significant asynchrony
Longer elimination half-life limits rapid titration²²

Opioid Considerations:

Morphine and fentanyl can suppress respiratory drive
May be necessary for comfort but should be titrated carefully
Consider remifentanil for rapid adjustability in complex cases

Sedation Monitoring and Titration

RASS Score Targets:

Aim for RASS -1 to 0 in most patients
Deeper sedation (RASS -2 to -3) may be necessary in severe ARDS
Avoid routine deep sedation (RASS -4 to -5) unless specifically indicated²³

Dynamic Assessment:

Regularly assess patient-ventilator interaction during sedation adjustments
Use objective measures (ventilator graphics) rather than subjective comfort alone
Consider sedation holidays to reassess underlying respiratory drive

Mode-Specific Considerations

Pressure Support Ventilation (PSV)

Advantages for Synchrony:

Patient-triggered and patient-cycled
Allows variable tidal volumes based on patient effort
Generally provides better synchrony than volume-controlled modes²⁴

Common Asynchrony Issues:

Delayed cycling in COPD patients
Inadequate pressure support leading to excessive work of breathing
Auto-cycling in the presence of leaks

Optimization Strategies:

Start with PS 10-15 cmH₂O and titrate based on tidal volume and patient comfort
Adjust cycling criteria based on underlying pathophysiology
Consider backup rate to prevent apnea in heavily sedated patients

Volume-Controlled Ventilation (VCV)

Synchrony Challenges:

Fixed flow pattern may not match patient demand
Time-cycled inspiration may not align with patient neural timing
Higher likelihood of flow asynchrony²⁵

Optimization Approaches:

Use decelerating flow patterns when available
Ensure adequate peak flow (60-100 L/min)
Consider dual-control modes (PRVC, AutoFlow) for better patient interaction

Airway Pressure Release Ventilation (APRV)

Synchrony Advantages:

Allows spontaneous breathing throughout the respiratory cycle
Minimal interference with patient respiratory pattern
May reduce need for deep sedation²⁶

Clinical Considerations:

Requires careful timing adjustment (T-high, T-low)
May not be suitable for patients with minimal respiratory drive
Monitoring can be more complex than conventional modes

Neurally Adjusted Ventilatory Assist (NAVA)

Theoretical Advantages:

Direct neural control of ventilator assistance
Eliminates most forms of asynchrony
Automatic adjustment to changing patient needs²⁷

Practical Limitations:

Requires specialized catheter placement
Limited availability in many centers
Learning curve for optimal NAVA level titration

Clinical Pearl: Even without using NAVA mode, EAdi monitoring can provide valuable insights into patient respiratory drive and guide conventional ventilator adjustments.

Special Populations and Clinical Scenarios

COPD and Asthma

Pathophysiological Considerations:

Dynamic hyperinflation and intrinsic PEEP
Prolonged expiratory time constants
High airway resistance affecting flow delivery²⁸

Specific Management Strategies:

Optimize external PEEP to counteract intrinsic PEEP
Use higher flow cycling thresholds (40-45% in PSV)
Consider longer expiratory times
Bronchodilator optimization

Oyster: In severe COPD exacerbations, permissive hypercapnia may reduce respiratory drive and improve synchrony, provided pH remains >7.25.

Acute Respiratory Distress Syndrome (ARDS)

Synchrony Challenges:

High respiratory drives due to hypoxemia and lung stiffness
Need for lung-protective ventilation strategies
Prone positioning effects on patient-ventilator interaction²⁹

Management Approach:

Balance lung protection with synchrony optimization
Consider APRV or other modes allowing spontaneous breathing
Neuromuscular blockade may be necessary in severe cases
Careful sedation titration to maintain some respiratory effort

Weaning and Liberation

Asynchrony During Weaning:

Increased respiratory drive as sedation is reduced
Changing respiratory mechanics as lung function improves
Psychological factors affecting patient-ventilator interaction³⁰

Optimization Strategies:

Gradual reduction in ventilator support
Maintain optimal synchrony throughout weaning process
Consider weaning protocols that incorporate synchrony assessment
Address patient anxiety and discomfort

Clinical Outcomes and Evidence

Impact on Patient Outcomes

Mortality and Morbidity

Multiple observational studies have demonstrated associations between ventilator asynchrony and adverse clinical outcomes. A large multicenter study by Blanch et al. found that patients with severe asynchrony (>10% of breaths) had significantly higher ICU mortality (34% vs. 21%, p<0.01) and longer duration of mechanical ventilation.³¹

Clinical Significance: The relationship appears dose-dependent, with greater degrees of asynchrony associated with progressively worse outcomes. This suggests that even moderate asynchrony warrants attention and intervention.

Duration of Mechanical Ventilation

Asynchrony consistently correlates with prolonged mechanical ventilation across multiple studies. Patients with significant asynchrony require an average of 2-4 additional days of mechanical ventilation, with corresponding increases in ICU length of stay and healthcare costs.³²

Economic Implications: The financial impact extends beyond ICU costs to include increased rates of ventilator-associated pneumonia, longer hospital stays, and higher rates of tracheostomy placement.

Quality of Life Considerations

Patient-Reported Outcomes: Studies incorporating patient perspectives reveal that asynchrony significantly impacts comfort, sleep quality, and psychological well-being. Patients describe the sensation as "fighting the machine" or "suffocating," contributing to ICU-related psychological trauma.³³

Practical Clinical Protocols

Systematic Asynchrony Assessment Protocol

Daily Evaluation Framework

Step 1: Visual Assessment (30 seconds)

Observe patient-ventilator interaction
Look for signs of distress or fighting
Check for use of accessory muscles

Step 2: Waveform Analysis (2 minutes)

Examine pressure-time curves for irregularities
Assess flow-time patterns for starvation or premature termination
Look for double-triggering or ineffective efforts

Step 3: Systematic Intervention (5 minutes)

Adjust trigger sensitivity if triggering problems identified
Modify flow settings for flow asynchrony
Optimize cycling criteria for cycle asynchrony

Clinical Hack: Use the "3-2-1 Rule"—Spend 3 minutes assessing, 2 minutes adjusting, and 1 minute re-evaluating the response to interventions.

Sedation-Ventilator Interaction Protocol

Integrated Assessment:

Assess current RASS score and sedation requirements
Evaluate patient-ventilator synchrony
Adjust sedation to optimize synchrony while maintaining comfort
Re-assess synchrony after sedation changes
Document findings and continue monitoring

Target Goals:

RASS score -1 to 0 when possible
<5% ineffective triggering
Minimal flow asynchrony
Appropriate cycling without fighting

Troubleshooting Guide for Common Scenarios

Scenario 1: Persistent High Respiratory Rate with Small Tidal Volumes

Likely Cause: Flow starvation or inadequate pressure support

Quick Assessment:

Check inspiratory flow rate and pattern
Assess pressure support level
Look for flow-time curve concavity

Immediate Interventions:

Increase peak flow to 80-100 L/min
Increase pressure support by 3-5 cmH₂O
Consider changing to decelerating flow pattern
Re-assess after 5 minutes

Scenario 2: Auto-triggering with High Respiratory Rate

Likely Causes: Excessive trigger sensitivity, circuit leak, or cardiac oscillations

Quick Assessment:

Check trigger sensitivity setting
Inspect circuit for leaks
Observe relationship between heart rate and triggered breaths

Immediate Interventions:

Decrease trigger sensitivity (make less sensitive)
Check and repair circuit connections
Consider switching from pressure to flow triggering
Evaluate need for sedation adjustment

Scenario 3: Patient Appears to be Fighting the Ventilator

Systematic Approach:

Immediate: Ensure adequate oxygenation and ventilation
Assessment: Perform rapid asynchrony evaluation
Intervention: Address most obvious asynchrony first
Escalation: Consider sedation if adjustments ineffective
Expert consultation: Involve respiratory therapy or critical care specialist

Clinical Pearl: Always rule out medical causes (pain, anxiety, hypoxemia, dynamic hyperinflation) before attributing fighting to ventilator settings alone.

Future Directions and Emerging Technologies

Artificial Intelligence and Machine Learning

Automated Asynchrony Detection: Machine learning algorithms are being developed to automatically detect and classify asynchrony types, potentially providing real-time alerts and adjustment recommendations.³⁴

Predictive Analytics: AI systems may eventually predict asynchrony development based on patient characteristics and ventilator trends, allowing for proactive management.

Advanced Monitoring Technologies

Non-invasive Respiratory Effort Monitoring: New technologies for measuring respiratory muscle activity without invasive procedures are in development, potentially making advanced asynchrony assessment more widely available.³⁵

Integrated Monitoring Systems: Future ventilators may incorporate multiple physiological signals (EAdi, respiratory mechanics, patient comfort scores) for comprehensive synchrony optimization.

Personalized Ventilation Strategies

Precision Medicine Approaches: Research is exploring patient-specific ventilation protocols based on individual pathophysiology, genetics, and response patterns.³⁶

Adaptive Control Systems: Next-generation ventilators may automatically adjust settings in real-time based on continuous asynchrony monitoring and patient response.

Key Clinical Pearls and Practical Tips

Assessment Pearls

"The Eyeball Test": If ventilator waveforms look chaotic or irregular, asynchrony is likely present
"Pressure Notching": Small deflections in airway pressure during expiration often indicate ineffective triggering
"Flow Starvation Sign": Scooped-out pressure curves during inspiration suggest inadequate flow delivery
"Double-Peak Pattern": Two peaks in a single pressure cycle usually indicate double-triggering

Management Pearls

"Start Simple": Address obvious trigger and flow issues before complex cycling adjustments
"Less is More": Light sedation often provides better synchrony than deep sedation
"PEEP Paradox": In COPD, optimal PEEP for synchrony may differ from optimal PEEP for oxygenation
"Patient First": Always consider patient comfort and clinical context when making ventilator adjustments

Troubleshooting Pearls

"The 5-Minute Rule": Allow at least 5 minutes for patient adaptation after ventilator changes
"One Change at a Time": Make single adjustments and assess response before additional changes
"When in Doubt, Sedate": If synchrony optimization fails, consider underlying patient factors requiring sedation
"Know When to Stop": Recognize when asynchrony may be unavoidable due to underlying pathophysiology

Conclusion

Ventilator asynchrony represents a complex but manageable challenge in contemporary critical care practice. Understanding the pathophysiology, recognition patterns, and systematic management approaches outlined in this review provides the foundation for optimizing patient-ventilator interaction and improving clinical outcomes.

The key to successful asynchrony management lies in systematic assessment, targeted interventions, and continuous monitoring. By integrating ventilator optimization with appropriate sedation strategies and considering individual patient factors, clinicians can significantly reduce asynchrony and its associated complications.

As technology continues to advance, automated detection systems and personalized ventilation strategies promise to further improve our ability to achieve optimal patient-ventilator synchrony. However, the fundamental principles of careful assessment, systematic intervention, and patient-centered care remain the cornerstones of effective asynchrony management.

The evidence clearly demonstrates that attention to patient-ventilator synchrony is not merely a comfort issue but a critical component of ventilator management that directly impacts patient survival, duration of mechanical ventilation, and overall outcomes. By incorporating these principles into daily practice, critical care practitioners can significantly improve the quality of care provided to mechanically ventilated patients.

References

Thille AW, Rodriguez P, Cabello B, et al. Patient-ventilator asynchrony during assisted mechanical ventilation. Intensive Care Med. 2006;32(10):1515-1522.
Blanch L, Villagra A, Sales B, et al. Asynchronies during mechanical ventilation are associated with mortality. Intensive Care Med. 2015;41(4):633-641.
Vaporidi K, Babalis D, Chytas A, et al. Clusters of ineffective efforts during mechanical ventilation: impact on outcome. Intensive Care Med. 2017;43(2):184-191.
Parthasarathy S, Jubran A, Tobin MJ. Assessment of neural inspiratory time in ventilator-supported patients. Am J Respir Crit Care Med. 2000;162(2 Pt 1):546-552.
Sinderby C, Navalesi P, Beck J, et al. Neural control of mechanical ventilation in respiratory failure. Nat Med. 1999;5(12):1433-1436.
Leung P, Jubran A, Tobin MJ. Comparison of assisted ventilator modes on triggering, patient effort, and dyspnea. Am J Respir Crit Care Med. 1997;155(6):1940-1948.
Imanaka H, Nishimura M, Takeuchi M, et al. Autotriggering caused by cardiogenic oscillation during flow-triggered mechanical ventilation. Crit Care Med. 2000;28(2):402-407.
Colombo D, Cammarota G, Bergamaschi V, et al. Physiologic response to varying levels of pressure support and neurally adjusted ventilatory assist in patients with acute respiratory failure. Intensive Care Med. 2008;34(11):2010-2018.
Marini JJ, Rodriguez RM, Lamb V. Bedside estimation of the inspiratory work of breathing during mechanical ventilation. Chest. 1986;89(1):56-63.
Laghi F, Segal J, Choe WK, et al. Effect of imposed inflation time on respiratory frequency and hyperinflation in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2001;163(6):1365-1370.
Nilsestuen JO, Hargett KD. Using ventilator graphics to identify patient-ventilator asynchrony. Respir Care. 2005;50(2):202-234.
Chao DC, Scheinhorn DJ, Stearn-Hassenpflug M. Patient-ventilator trigger asynchrony in prolonged mechanical ventilation. Chest. 1997;112(6):1592-1599.
Tobin MJ, Jubran A, Laghi F. Patient-ventilator interaction. Am J Respir Crit Care Med. 2001;163(5):1059-1063.
Akoumianaki E, Maggiore SM, Valenza F, et al. The application of esophageal pressure measurement in patients with respiratory failure. Am J Respir Crit Care Med. 2014;189(5):520-531.
Sinderby C, Beck J, Spahija J, et al. Voluntary activation of the human diaphragm in health and disease. J Appl Physiol. 1998;85(6):2146-2158.
Nava S, Bruschi C, Rubini F, et al. Respiratory response and inspiratory effort during pressure support ventilation in COPD patients. Intensive Care Med. 1995;21(11):871-879.
Bonmarchand G, Chevron V, Chopin C, et al. Increased initial flow rate reduces inspiratory work of breathing during pressure support ventilation in patients with exacerbation of chronic obstructive pulmonary disease. Intensive Care Med. 1996;22(11):1147-1154.
Tassaux D, Dalmas E, Gratadour P, et al. Patient-ventilator interactions during partial ventilatory support: a preliminary study comparing the effects of adaptive support ventilation with synchronized intermittent mandatory ventilation plus inspiratory pressure support. Crit Care Med. 2002;30(4):801-807.
Pepe PE, Marini JJ. Occult positive end-expiratory pressure in mechanically ventilated patients with airflow obstruction: the auto-PEEP effect. Am Rev Respir Dis. 1982;126(1):166-170.
Talmor D, Sarge T, Malhotra A, et al. Mechanical ventilation guided by esophageal pressure in acute lung injury. N Engl J Med. 2008;359(20):2095-2104.
Kress JP, Pohlman AS, O'Connor MF, et al. Daily interruption of sedative infusions in critically ill patients undergoing mechanical ventilation. N Engl J Med. 2000;342(20):1471-1477.
Pandharipande PP, Pun BT, Herr DL, et al. Effect of sedation with dexmedetomidine vs lorazepam on acute brain dysfunction in mechanically ventilated patients: the MENDS randomized controlled trial. JAMA. 2007;298(22):2644-2653.
Sessler CN, Gosnell MS, Grap MJ, et al. The Richmond Agitation-Sedation Scale: validity and reliability in adult intensive care unit patients. Am J Respir Crit Care Med. 2002;166(10):1338-1344.
Brochard L, Rauss A, Benito S, et al. Comparison of three methods of gradual withdrawal from ventilatory support during weaning from mechanical ventilation. Am J Respir Crit Care Med. 1994;150(4):896-903.
Jubran A, Van de Graaff WB, Tobin MJ. Variability of patient-ventilator interaction with pressure support ventilation in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 1995;152(1):129-136.
Putensen C, Zech S, Wrigge H, et al. Long-term effects of spontaneous breathing during ventilatory support in patients with acute lung injury. Am J Respir Crit Care Med. 2001;164(1):43-49.
Terzi N, Pelieu I, Guittet L, et al. Neurally adjusted ventilatory assist in patients recovering spontaneous breathing after acute respiratory distress syndrome: physiological evaluation. Crit Care Med. 2010;38(9):1830-1837.
Georgopoulos D, Mitrouska I, Bshouty Z, et al. Effects of non-invasive positive pressure ventilation on the inspiratory work

Sunday, August 10, 2025