Patient-ventilator Interaction Research Articles

Clusters of ineffective efforts during mechanical ventilation: impact on outcome.

The aim of this study was to investigate the role of ineffective efforts (IEs), specifically clusters of IEs, during mechanical ventilation on the outcome of critically ill patients. In a prospective observational study, 24-h recordings were obtained in 110 patients on the 1stday of assisted ventilation (pressure support or proportional assist), using a prototype monitor validated to identify IEs. Patients remaining on assisted ventilation were studied again on the 3rdday (n=37) and on the 6thday (n=13). To describe the clusters of IEs, the concept of an IEs event was developed, defined as a 3-min period of time containing more than 30 IEs. Along with all patient data, to minimize selection bias by time of recording, analysis was performed only on 1stday data of patients with ≥16h of recording (1stday group). The analysis included 2931h of assisted ventilation and 4,456,537 breaths. Neither the IEs index (IEs as a percentage of total breaths) in general nor a value above 10% was correlated with patient outcome. Overall, IEs events were identified in 38% of patients. In multivariate analysis, the presence of events in the 1stday group (n=79) was associated with the risk of being on mechanical ventilation ≥8days after first recording [odds ratio 6.4, 95% confidence interval (1.1-38.30)] and hospital mortality [20 (2.3-175)]. Analysis of the data for all patients revealed similarly increased risks for prolonged ventilation [3.4 (1.1-10.7)] and mortality [4.9 (1.3-18)]. Clusters of IEs are often present in mechanically ventilated critically ill patients and are associated with prolonged mechanical ventilation and increased mortality. Studies to find ways of improving patient-ventilator interaction are warranted.

The influence of condensate in the piezometric tube on patient ventilator interaction during noninvasive positive pressure ventilation

To study the effects of condensate in the piezometric tube on patient ventilator interaction during noninvasive positive pressure ventilation. Eleven healthy adults volunteered to receive noninvasive positive pressure ventilation. Different capacity of physiological saline was injected gradually into the piezometric tube until the volunteers could not trigger the ventilator or the total volume of the water reached 1.5 ml. The dynamic changes of the pressure of mask(Pmask), piezometric tube near mask (Ppro), piezometric tube near breathing machine(Pdis), and the flow were observed. With increasing volume of saline injected, the trigger time TItri(Pmask) increased from 0.09(0.07-0.11) to 0.31(0.22-0.39)s, the trigger pressure TPtri(Pmask) increased from 0.26(0.15-0.33) to 2.29(1.76-3.09)cmH2O, and the pressure-time product PTP (Pmask) increased from 0.02(0.01-0.03) to 0.55(0.41-0.68) cmH2O·s. Ineffective triggering rate increased from 0 up to 9 times/min, and spurious triggering rate increased from 0 up to 33 times/min. The plateau pressure of Pmask and Ppro exceeded the preset parameters, increased significantly as compared with 0 ml, from (9.74±0.34)to (15.79±3.10) cmH2O and from(9.80±0.31) to(15.44±3.47) cmH2O. The change of plateau pressure of Pdis was not significant [from (9.85±0.29)to (12.58±2.64)cmH2O]. The baseline pressure of Pmask, Ppro and Pdis changed from (3.67±0.36) to (8.40±3.22) cmH2O, from (3.71±0.32) to (8.13±3.55) cmH2O and from( 3.77±0.32) to (5.36±1.25) cmH2O, respectively. The pressure fluctuation of platform of Pmask increased significantly compare with 0 ml, from 0.60(0.48-0.71) to 7.94(7.11-8.63)cmH2O. The frequency of fluctuation of platform increased as many as 7 times during a single respiratory period. The time when the pressure of the Pdis began to change was delayed to Pmask and Ppro, 0.11(0.08-0.12)s compared with 0 ml. Condensate in the piezometric tube during noninvasive positive pressure ventilation could influence patient-ventilator synchrony. To improve patient ventilator interaction in noninvasive positive pressure ventilation, condensate in the piezometric tube should be avoided.

Measurement of pleural pressure swings with a fluid-filled esophageal catheter vs pulmonary artery occlusion pressure

PurposePleural pressure measured with esophageal balloon catheters (Peso) can guide ventilator management and help with the interpretation of hemodynamic measurements, but these catheters are not readily available or easy to use. We tested the utility of an inexpensive, fluid-filled esophageal catheter (Peso) by comparing respiratory-induced changes in pulmonary artery occlusion (Ppao), central venous (CVP), and Peso pressures. MethodsWe studied 30 patients undergoing elective cardiac surgery who had pulmonary artery and esophageal catheters in place. Proper placement was confirmed by chest compression with airway occlusion. Measurements were made during pressure-regulated volume control (VC) and pressure support (PS) ventilation. ResultsThe fluid-filled esophageal catheter provided a high-quality signal. During VC and PS, change in Ppao (∆Ppao) was greater than ∆Peso (bias = −2 mm Hg) indicating an inspiratory increase in cardiac filling. During VC, ∆CVP bias was 0 indicating no change in right heart filling, but during PS, CVP fell less than Peso indicating an inspiratory increase in filling. Peso measurements detected activation of expiratory muscles, development of non–west zone 3 lung conditions during inspiration, and ventilator-triggered inspiratory efforts. ConclusionsA fluid-filled esophageal catheter provides a high-quality, easily accessible, and inexpensive measure of change in pleural pressure and provided insights into patient-ventilator interactions.

Estimating the true respiratory mechanics during asynchronous pressure controlled ventilation

Abstract Mechanical ventilation (MV) therapy partially or fully replaces the work of breathing in patients with respiratory failure. Respiratory mechanics during pressure controlled (PC) or pressure support (PS) are often not estimated due to variability induced by patient’s spontaneous breathing effort (SB) or asynchronous events (AEs). Thus for non-invasive model-based MV with PC/PS, there is a need for improved estimation of respiratory mechanics. An algorithm is proposed that allows for the improvement of respiratory system mechanics estimation during pressure controlled ventilation, while providing a means of quantifying AE magnitude as one indicator of patient-ventilator interaction, which may be valuable to clinicians to monitor patient response to care. For testing, 10 retrospective airway pressure and flow data samples were obtained from 6 MV patients, with each data sample containing 450–500 breaths. All data samples with AE present experienced a decrease in 5th to 95th range (Range90) and mean absolute deviation (MAD) for the estimated respiratory system elastance after reconstruction. These results suggested improved in respiratory mechanics estimation during pressure controlled ventilation. The median [maximum (max), minimum (min)] decrease in MAD was 29.4% (51%, 18.6%), and the median (max, min) decrease in Range90 divided by median respiratory system elastance was 30.7% (48.8%, 6.4%). The algorithm is robust to many different spontaneous breathing efforts, asynchrony shapes and types. The proposed algorithm demonstrates the potential to effectively improve respiratory mechanics and quantify the magnitude of AEs.

Effects of dexmedetomidine and propofol on patient-ventilator interaction in difficult-to-wean, mechanically ventilated patients: a prospective, open-label, randomised, multicentre study.

BackgroundDexmedetomidine can be used for sedation of mechanically ventilated patients and has minor respiratory effects. The aim of this study was to compare the incidence of patient-ventilator dyssynchronies during sedation with dexmedetomidine or propofol.MethodsWe conducted a multicentre, prospective, open-label, randomised clinical trial, comparing dexmedetomidine with standard propofol sedation at three intensive care units of university hospitals in Italy. Twenty difficult-to-wean patients for whom the first weaning trial had failed and who were on pressure support ventilation were randomised to receive sedation with either dexmedetomidine or propofol at a similar level of sedation (Richmond Agitation-Sedation Scale [RASS] score +1 to −2). The asynchrony index (AI) was calculated using tracings of airflow, airway pressure and electrical activity of the diaphragm sampled at 0, 0.5, 1, 2, 6, 12, 18 and 24 h.ResultsThe mean AI was lower with dexmedetomidine than with propofol from 2 h onwards, although the two groups significantly differed only at 12 h (2.68 % vs 9.10 %, p < 0.05). No further difference was observed at 18 and 24 h.ConclusionsWhen sedation with propofol and dexmedetomidine was compared at similar RASS scores of patients in whom first weaning trial had failed, the AI was lower with dexmedetomidine than with propofol, and this difference was statistically significant at 12 h. These results suggest that sedation with dexmedetomidine may offer some advantages in terms of patient-ventilator synchrony.

A randomized clinical trial of neurally adjusted ventilatory assist versus conventional weaning mode in patients with COPD and prolonged mechanical ventilation.

BackgroundPatient-ventilator asynchrony is a common problem in mechanically ventilated patients; the problem is especially obvious in COPD. Neutrally adjusted ventilatory assist (NAVA) can improve patient-ventilator asynchrony; however, the effect in COPD patients with prolonged mechanical ventilation is still unknown. The goals of this study are to evaluate the effect of NAVA and conventional weaning mode in patients with COPD during prolonged mechanical ventilation.MethodsThe study enrolled a total of 33 COPD patients with ventilator dependency for more than 21 days in the weaning center. A diaphragm electrical activity (Edi) catheter was inserted in patients within 24 hours after admission to the respiratory care center, and patients were randomly allocated to NAVA or conventional group. A spontaneous breathing trial was performed every 24 hours. The results correlated with the clinical parameters.ResultsThere were significantly higher asynchrony incidence rates in the whole group after using Edi catheter (before vs post-Edi catheter insertion =60.6% vs 87.9%, P<0.001). Asynchrony index: before vs post-Edi catheter insertion =7.4%±8.5% vs 13.2%±13.5%, P<0.01. Asynchrony incidence: NAVA vs conventional =0% vs 84.2%, P<0.001. Asynchrony index: NAVA vs conventional =0 vs 11.9±11.2 (breath %), P<0.001. The most common asynchrony events were ineffective trigger and delayed trigger.ConclusionCompared to conventional mode, NAVA mode can significantly enhance respiratory monitoring and improve patient-ventilator interaction in COPD patients with prolonged mechanical ventilation in respiratory care center.

Assisted Ventilation in Patients With Acute Respiratory Distress Syndrome

BACKGROUND: In patients with acute respiratory distress syndrome (ARDS), the use of assisted mechanical ventilation is a subject of debate. Assisted ventilation has benefits over controlled ventilation, such as preserved diaphragm function and improved oxygenation. Therefore, higher level of patient of ventilator assist may be preferable in ARDS. However, assisted modes may also increase the risk of high tidal volumes and lung-distending pressures. The current study aims to quantify how differences in freedom to control the ventilator affect lung-protective ventilation, breathing pattern variability, and patient-ventilator interaction. METHODS: Twelve patients with ARDS were ventilated in a randomized order with assist pressure control ventilation (PCV), pressure support ventilation (PSV), and neurally adjusted ventilatory assist (NAVA). Transpulmonary pressure, tidal volume, diaphragm electrical activity, and patient-ventilator interaction were measured. Respiratory variability was assessed using the coefficient of variation of tidal volume. RESULTS: During inspiration, transpulmonary pressure was slightly lower with NAVA (10.3 +/- 0.7, 11.2 +/- 0.7, and 9.4 +/- 0.7 cm H2O for PCV, PSV, and NAVA, respectively; P < 0.01). Tidal volume was similar between modes (6.6 [5.7 to 7.0], 6.4 [5.8 to 7.0], and 6.0 [5.6 to 7.3] ml/kg for PCV, PSV, and NAVA, respectively), but respiratory variability was higher with NAVA (8.0 [6.4 to 10.0], 7.1 [5.9 to 9.0], and 17.0 [12.0 to 36.1] % for PCV, PSV, and NAVA, respectively; P < 0.001). Patient-ventilator interaction improved with NAVA (6 [5 to 8] % error) compared with PCV (29 [14 to 52] % error) and PSV (12 [9 to 27] % error); P < 0.0001. CONCLUSION: In patients with mild-to-moderate ARDS, increasing freedom to control the ventilator maintains lung-protective ventilation in terms of tidal volume and lung-distending pressure, but it improves patient-ventilator interaction and preserves respiratory variability.

The Influence of Condensate in the Piezometric Tube on Patient Ventilator Interaction During Noninvasive Positive Pressure Ventilation

The Influence of Condensate in the Piezometric Tube on Patient Ventilator Interaction During Noninvasive Positive Pressure Ventilation

Bedside detection of patient-ventilation asynchrony

Patient-ventilator asynchrony is common but under-recognized and under-reported. The frequency of PAV is reported around 23%, but up to 93% of patients have at least one episode of PVA. While sporadic asyn-chronies may have uncertain clinical im-pact, when they amount to more than 10% of the total breaths, PVA can increase the need for sedation and reduce sleep quality. In addition, they can impact on outcome by prolonging mechanical ventilation and increasing both ICU and hospital mortal-ity.&nbsp;The purpose of this review is threefold: 1) to characterise different types of patient-ventilator interaction; 2) to describe mech-anisms leading to asynchrony; and 3) to describe ventilator modification to reduce patient-ventilation asynchrony.

Patient-Ventilator Interaction During Noninvasive Ventilation in Simulated COPD.

During noninvasive ventilation (NIV) of COPD patients, delayed off-cycling of pressure support can cause patient ventilator mismatch and NIV failure. This systematic experimental study analyzes the effects of varying cycling criteria on patient-ventilator interaction. A lung simulator with COPD settings was connected to an ICU ventilator via helmet or face mask. Cycling was varied between 10 and 70% of peak inspiratory flow at different breathing frequencies (15 and 30 breaths/min) and pressure support levels (5 and 15 cm H2O) using the ventilator's invasive and NIV mode with and without an applied leakage. Low cycling criteria led to severe expiratory cycle latency. Augmenting off-cycling reduced expiratory cycle latency (P < .001), decreased intrinsic PEEP, and avoided non-supported breaths. Setting cycling to 50% of peak inspiratory flow achieved best synchronization. Overall, using the helmet interface increased expiratory cycle latency in almost all settings (P < .001). Augmenting cycling from 10 to 40% progressively decreased expiratory pressure load (P < .001). NIV mode decreased expiratory cycle latency compared with the invasive mode (P < .001). Augmenting the cycling criterion above the default setting (20-30% peak inspiratory flow) improved patient ventilator synchrony in a simulated COPD model. This suggests that an individual approach to cycling should be considered, since interface, level of pressure support, breathing frequency, and leakage influence patient-ventilator interaction and thus need to be considered.

Automated Mechanical Ventilator Waveform Analysis of Patient-Ventilator Asynchrony

AUTOMATED MECHANICAL VENTILATOR WAVEFORM ANALYSIS OF PATIENT-VENTILATOR ASYNCHRONY MAS , MD , Lieng , Jason Adams, MD, Brooks Kuhn, Monica BS, Jean-Pierre Delplanque, PhD , Edward Guo , Sean Peisert, PhD , Nick Anderson, PhD 1 UC Davis Medical Center, Department of Pulmonary and Critical Care Medicine 2 UC Davis School of Medicine 3 UC Davis, Department of Engineering 4 UC Davis, Department of Computer Science 5 UC Davis, Department of Pathology Figure 1: Bedside to Cloud mechanical ventilator waveform pipeline Purpose Simulation Center Mechanical ventilation is a life-saving intervention but is also associated with adverse effects including ventilator-induced lung injury (VILI). Patient-ventilator asynchrony (PVA) is thought to contribute to VILI, but the study of PVA has been hampered by limited access to the high frequency, large volume data streams produced by modern ventilators and a lack of robust PVA analytics. To address these limitations, we developed an automated pipeline for breath-by-breath analysis of mechanical ventilator waveform data. Wireless Micro- Computer Attached to Ventilator Wireless Server Secure Analytic Environment ANALYTICS: • TDAP • Python • Machine Learning • R/SAS • Tableau Critical Care Registry ASCEII Medical ICU Methods Double Trigger Ventilator Data Asynchrony Meta-Data Data Acquisition >>>>>>>>>>>>>>>>>> Storage >>>>>>>>>>>>>>>>>>>>>>> Analysis>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Figure 3: Charted tidal volumes compared to continuously recorded tidal volumes of a subject with ARDS, subsequently treated with neuromuscular blockade Cisatracurium started 8 ml/kg PBW 6 ml/kg PBW Recorded Tidal Volumes Suction Common Patient-Ventilator Asynchronies and “Artifacts” Breath Flow Ventilator Stacking Asynchrony Cough Disconnect Waveform Reconstitution Virtual Desktop Access Tidal Volume (mL) Simulated pressure and flow time series data representing normal breaths and common forms of PVA were generated on mechanical ventilators, collected unobtrusively using wireless peripheral devices, and transmitted to a networked server for storage and analysis. Two critical care physicians reviewed waveforms to generate gold standard data sets of PVA events. Rule-based algorithms were developed to quantify inspiratory and expiratory tidal volumes (TV) and identify common PVA subtypes including double trigger and delayed termination asynchrony. Data were split randomly into derivation and validation sets. Algorithm performance was compared with ventilator reported values and clinician annotation. Raw Waveform Data (CSV File) Results The mean difference between algorithm-determined and ventilator- reported TVs was 3.1% (99% CI ± 1.36%). Algorithm agreement with clinician annotation was excellent for double trigger PVA and moderate for delayed termination PVA, with Kappa statistics of 0.85 and 0.58, respectively. In the validation data set (n = 492 breaths), double trigger asynchrony was detected with an overall accuracy of 94.1%, a sensitivity of 100%, and a specificity of 92.8%. Conclusions Tidal Volume (mL) Figure 2: Derivation and validation of double trigger algorithm n=214 n=139 n=492 Rater 1 Rater 2 Algorithm Rater 1 Scan QR code for access to references via Dropbox.com Rater 2 Delayed Termination Algorithm 8 ml/kg PBW 6 ml/kg PBW Double Trigger Delayed Termination Double Trigger Sensitivity Specificity n=90 Charted Tidal Volumes n=179 Validation Breath Number Figure 4: PVA frequency pre and post cisatracurium. Severe breath stacking is defined as TVe:TVi 10 to 33%. Moderate breath stacking defined as as TVe:TVi 33 to 67%. % Asynchronous Breaths Derivation Double trigger dbl_trig A pipeline combining wireless ventilator data acquisition and rule-based signal analysis algorithms informed by the principles of bedside ventilator waveform analysis allows for accurate, automated, quantitative breath-by- breath analysis of patient-ventilator interactions. Clinical Impact Severe breath stacking bs_severe Moderate breath stacking bs_moderate Composite composite_dbl_bs Total (%) Pre-Cisatra (%) During Cisatra (%) Post-Cisatra (%) Phase of Mechanical Ventilation Improved classification and automated identification of double triggers, tidal volume, and other common types of PVA allowing more robust analysis of injurious patient-ventilator interactions Future plans include: • Expansion to all mechanically ventilated patients at UCDMC, including the emergency department • Comparison of rules-based algorithms to machine based learning algorithms • Outcomes correlation to PVA/TV metadata

Automated logging of inspiratory and expiratory non-synchronized breathing (ALIEN) for mechanical ventilation.

Asynchronous Events (AEs) during mechanical ventilation (MV) result in increased work of breathing and potential poor patient outcomes. Thus, it is important to automate AE detection. In this study, an AE detection method, Automated Logging of Inspiratory and Expiratory Non-synchronized breathing (ALIEN) was developed and compared between standard manual detection in 11 MV patients. A total of 5701 breaths were analyzed (median [IQR]: 500 [469-573] per patient). The Asynchrony Index (AI) was 51% [28-78]%. The AE detection yielded sensitivity of 90.3% and specificity of 88.3%. Automated AE detection methods can potentially provide clinicians with real-time information on patient-ventilator interaction.

Ventilator triggering.

Allowing spontaneous respiration during mechanical ventilation requires that the ventilator system can interpret a trigger signal from the patient and then deliver a synchronous breath. The majority of current ventilators are triggered by preset changes in pressure or flow detected in the system as a patient is initiating a breath. However, other triggers such as chest wall motion, waveform alteration, and diaphragmatic electromyograms have also been utilized. The time between initiation of a breath by a patient and delivery of a breath by the ventilator is known as trigger delay. Most trigger delay is inherent in the mechanics of the patient-ventilator interaction. However, recent advances in technology have captured a neural signal from the diaphragm to trigger the ventilator to deliver a breath, reducing trigger delay. Understanding trigger delay is important as it may lead to increased work of breathing and patient-ventilator asynchrony. Types of asynchrony related to the triggering phase are ineffective triggering, double triggering, and autotriggering. The presence of asynchrony has been shown to have deleterious effects on patients, including duration of mechanical ventilation and increased length of hospital stay. Recognizing asynchrony and understanding how to manipulate the trigger variable will reduce adverse effects on patients.

Non-invasive neurally adjusted ventilatory assist in preterm infants: a randomised phase II crossover trial

ObjectiveTo compare non-invasive ventilation neurally adjusted ventilatory assist (NIV-NAVA) and non-invasive pressure support (NIV-PS) in preterm infants on patient–ventilator synchrony.DesignA randomised phase II crossover trial.SettingNeonatal intensive care units of two...

Assisted Ventilation in Patients with Acute Respiratory Distress Syndrome: Lung-distending Pressure and Patient-Ventilator Interaction.

In patients with acute respiratory distress syndrome (ARDS), the use of assisted mechanical ventilation is a subject of debate. Assisted ventilation has benefits over controlled ventilation, such as preserved diaphragm function and improved oxygenation. Therefore, higher level of "patient control" of ventilator assist may be preferable in ARDS. However, assisted modes may also increase the risk of high tidal volumes and lung-distending pressures. The current study aims to quantify how differences in freedom to control the ventilator affect lung-protective ventilation, breathing pattern variability, and patient-ventilator interaction. Twelve patients with ARDS were ventilated in a randomized order with assist pressure control ventilation (PCV), pressure support ventilation (PSV), and neurally adjusted ventilatory assist (NAVA). Transpulmonary pressure, tidal volume, diaphragm electrical activity, and patient-ventilator interaction were measured. Respiratory variability was assessed using the coefficient of variation of tidal volume. During inspiration, transpulmonary pressure was slightly lower with NAVA (10.3 ± 0.7, 11.2 ± 0.7, and 9.4 ± 0.7 cm H2O for PCV, PSV, and NAVA, respectively; P < 0.01). Tidal volume was similar between modes (6.6 [5.7 to 7.0], 6.4 [5.8 to 7.0], and 6.0 [5.6 to 7.3] ml/kg for PCV, PSV, and NAVA, respectively), but respiratory variability was higher with NAVA (8.0 [6.4 to 10.0], 7.1 [5.9 to 9.0], and 17.0 [12.0 to 36.1] % for PCV, PSV, and NAVA, respectively; P < 0.001). Patient-ventilator interaction improved with NAVA (6 [5 to 8] % error) compared with PCV (29 [14 to 52] % error) and PSV (12 [9 to 27] % error); P < 0.0001. In patients with mild-to-moderate ARDS, increasing freedom to control the ventilator maintains lung-protective ventilation in terms of tidal volume and lung-distending pressure, but it improves patient-ventilator interaction and preserves respiratory variability.

Update in Mechanical Ventilation, Sedation, and Outcomes 2014.

Novel approaches to the management of acute respiratory distress syndrome include strategies to enhance alveolar liquid clearance, promote epithelial cell growth and recovery after acute lung injury, and individualize ventilator care on the basis of physiological responses. The use of extracorporeal membrane oxygenation (ECMO) is growing rapidly, and centers providing ECMO must strive to meet stringent quality standards such as those set out by the ECMONet working group. Prognostic tools such as the RESP score can assist clinicians in predicting outcomes for patients with severe acute respiratory failure but do not predict whether ECMO will enhance survival. Evidence continues to grow that novel modes of mechanical ventilation such as neurally adjusted ventilatory assist are feasible and improve patient physiology and patient-ventilator interaction; data on clinical outcomes are limited but supportive. Critical illness causes long-term psychological and function sequelae: the risk of a new psychiatric diagnosis and severe physical impairment is significantly increased in the months after discharge from the intensive care unit. These long-term effects might be amenable to changes in sedation practice and increased early mobilization. Daily sedation discontinuation enhances the validity of routine delirium assessment. Many critically ill patients merit assessment by palliative care clinicians; the demand for palliative care services among critically ill patients is expected to grow. Future trials to test therapies for critical illness must ensure that study designs are adequately powered to detect benefit using realistic event rates. Integrating "big data" approaches into treatment decisions and trial designs offers a potential means of individualizing care to enhance outcomes for critically ill patients.

Influence of different interfaces on synchrony during pressure support ventilation in a pediatric setting: a bench study.

In adults and children, patient-ventilator synchrony is strongly dependent on both the ventilator settings and interface used in applying positive pressure to the airway. The aim of this bench study was to determine whether different interfaces and ventilator settings may influence patient-ventilator interaction in pediatric models of normal and mixed obstructive and restrictive respiratory conditions. A test lung, connected to a pediatric mannequin using different interfaces (endotracheal tube [ETT], face mask, and helmet), was ventilated in pressure support ventilation mode testing 2 ventilator settings (pressurization time [Timepress]50%/cycling-off flow threshold [Trexp]25%, Timepress80%/Trexp60%), randomly applied. The test lung was set to simulate one pediatric patient with a healthy respiratory system and another with a mixed obstructive and restricted respiratory condition, at different breathing frequencies (f) (30, 40, and 50 breaths/min). We measured inspiratory trigger delay, pressurization time, expiratory trigger delay, and time of synchrony. At each breathing frequency, the helmet showed the longest inspiratory trigger delay compared with the ETT and face mask. At f30, the ETT had a reduced Tpress. The helmet had the shortest Tpress in the simulated child with a mixed obstructive and restricted respiratory condition, at f40 during Timepress50%/Trexp25% and at f50 during Timepress80%/Trexp60%. In the simulated child with a normal respiratory condition, the ETT presented the shortest Tpress value at f50 during Timepress80%/Trexp60%. Concerning the expiratory trigger delay, the helmet showed the best interaction at f30, but the worst at f40 and at f50. The helmet showed the shortest time of synchrony during all ventilator settings. The choice of the interface can influence patient-ventilator synchrony in a pediatric model breathing at increased f, thus making it more difficult to set the ventilator, particularly during noninvasive ventilation. The helmet demonstrated the worst interaction, suggesting that the face mask should be considered as the first choice for delivering noninvasive ventilation in a pediatric model.

Impact of ventilatory modes on the breathing variability in mechanically ventilated infants: a commentary.

Neurally adjusted ventilator assist (NAVA) ventilation is a mode of ventilation that is triggered and cycled by a signal from the electrical activity of the diaphragm (EAdi) to provide a positive pressure breath. The EAdi signal is obtained from an esophageal catheter that is positioned at the level of the diaphragm. The rational of this mode of ventilation is to improve patient–ventilator interaction by matching ventilator support to patient’s demand and therefore avoiding hyperventilation and air trapping, and impairment of cardiac output (1). Several studies have shown that NAVA is better tolerated than other modes of mechanical ventilation in infants and children. For instance, premature infants require a lower peak inspiratory pressure (PiP) and a lower fraction of inspired oxygen (FiO2) and they have a better blood gas regulation at a lower respiratory rate when ventilated with NAVA instead of pressure control (PC) (2). Furthermore, premature infants have a reduction in their respiratory muscle load and a lower PiP when ventilated with NAVA instead of synchronized intermittent mandatory ventilation (SIMV) with pressure support (PS) (3). Also, critically ill children are more comfortable when ventilated with NAVA instead of PS. They have a better synchronization with the ventilator, a reduction in their ventilatory drive, and an increase in breath to breath variability while on NAVA (4).

Is the gastric tube a burden for the noninvasive ventilation?

The application of noninvasive ventilation (NIV) in ICUs has spread widely during the years. It is used in the treatment of different forms of acute respiratory failure and COPD exacerbations. Although NIV is thought to be more comfortable for patients than invasive mechanical ventilation, its failure rates in the ICUs range between 10 and 40%. Except for the interface-related problems, there are some specific considerations for the patient-ventilator interaction and the applied mechanical forces. During NIV there is a predisposition for the stomach to be inflated with gas, which could cause severe respiratory complications, especially in COPD patients, and thus prolong the mechanical ventilation and the weaning process. This remains one of the major causes for NIV failure. Although a lot of face masks with different interfaces are available on the market, just a few have additional ports for a NGT. They are characterized by higher price and a complex setup. In order to perform NIV in patients, requiring NGT placement, without additional air leaks and to be able to ensure their enteral nutrition and/or stomach drainage, we installed a port for a NGT on a standard face mask.

Neurally adjusted non-invasive ventilation in patients with chronic obstructive pulmonary disease: does patient-ventilator synchrony matter?

Patient–ventilator interaction represents an important clinical challenge during non-invasive ventilation (NIV). Doorduin and colleagues’ study shows that non-invasive neurally adjusted ventilatory assist (NAVA) improves patient–ventilator interaction compared with pressure support ventilation in patients with chronic obstructive pulmonary disease. There is no doubt nowadays that NAVA is the most effective mode of improving the synchrony between patient and machine, but the key question for the clinicians is whether or not this will make a difference to the patient’s outcome. The results of the study still do not clarify this issue because of the very low clinically important dyssynchrony, like wasted efforts, in the population studied. Air leaks play an important role in determining patient–ventilator interaction and therefore NIV success or failure. Apart from the use of a dedicated NIV ventilator or specific modes of ventilation like NAVA, the clinicians should be aware that the choice of interface, the humidification system and the appropriate sedation are key factors in improving patient–ventilator synchrony.