Performance of noninvasive ventilation algorithms on ICU ventilators during pressure support: a clinical study

Patient-ventilator synchrony under non-invasive ventilation is improved by an automated real time waveform analysis algorithm: a bench study

BACKGROUND

Because of inherent leaks, obtaining good patient-ventilator synchrony during non-invasive ventilation (NIV) is challenging. The IntelliSync + ® software (Hamilton medical, Bonaduz, CH), that can be used together with the NIV mode, performs real-time automated analysis of airway pressure- and flow-time curves to detect the transition between inspiration and expiration. It then controls the ventilator inspiratory and expiratory valves to improve patient-ventilator synchrony. The main goal of this NIV bench study was to evaluate the impact of IntelliSync + ® on synchrony in the presence of leaks of 9 and 20 L/min in the tested ventilator circuit (no face mask used), with normal, obstructive and restrictive respiratory mechanics and two levels of NIV pressure support (PS 8 and 14 cmH2O). For this, the time needed to trigger the ventilator (Td) and the difference between the end of the simulated breath and the termination of pressurization (Tiex) were measured. The number of classical asynchronies and the ventilator pressurization capacity were also assessed.

RESULTS

Compared to NIV delivered with the classical NIV mode (compensating leaks and limiting inspiratory time to 2 s), activating IntelliSync + ® improved Tiex and, to a lesser extent, Td in clinically relevant setups. IntelliSync + ® also showed a trend towards reducing classical asynchronies, particularly directly after leak flow increase. The impact of the system was most significant with high PS levels and pathological respiratory mechanics. Especially, in the obstructive model, in the presence of large leak (20 L/min) and PS 14 cmH2O, Tiex decreased from 0.61 [0.56-0.64] to 0.16 [0.07-0.18] s and Td from 0.07 [0.06-0.08] to 0.06 [0.06-0.08] s. In less challenging situations, IntelliSync + ® was less beneficial. Overall, ventilator pressurization was improved when IntelliSync + ® was activated.

CONCLUSIONS

In this NIV bench model, IntelliSync + ®, used in addition to NIV-PS, improved both expiratory and inspiratory synchrony. It was particularly efficient in the presence of obstructive and restrictive respiratory mechanics and high-pressure support levels. These pre-clinical results tend to support the ability of IntelliSync + ® to improve patient-ventilator synchrony in the presence of leaks and provide pre-clinical data supporting a clinical evaluation of the automated algorithm during NIV.

Ventilator performances for non-invasive ventilation: a bench study

INTRODUCTION

A wide range of recent ventilators, dedicated or not, is available for non-invasive ventilation (NIV) in respiratory or intensive care units (ICU). We conducted a bench study to compare their technical performances.

METHODS

Ventilators, including five ICU ventilators with NIV mode on, two dedicated NIV ventilators and one transport ventilator, were evaluated on a test bench for NIV, consisting of a 3D manikin head connected to an ASL 5000 lung model via a non-vented mask. Ventilators were tested according to three simulated lung profiles (normal, obstructive, restrictive), three levels of simulated air leakage (0, 15, 30 L/min), two levels of pressure support (8, 14 cmH2O) and two respiratory rates (15, 25 cycles/min).

RESULTS

The global median Asynchrony Index (AI) was higher with ICU ventilators than with dedicated NIV ventilators (4% (0; 76) vs 0% (0; 15), respectively; p<0.05) and different between all ventilators (p<0.001). The AI was higher with ICU ventilators for the normal and restrictive profiles (p<0.01) and not different between ventilators for the obstructive profile. Auto-triggering represented 43% of all patient-ventilator asynchrony. Triggering delay, cycling delay, inspiratory pressure-time product, pressure rise time and pressure at mask were different between all ventilators (p<0.01). Dedicated NIV ventilators induced a lower pressure-time product than ICU and transport ventilators (p<0.01). There was no difference between ventilators for minute ventilation and peak flow.

CONCLUSION

Despite the integration of NIV algorithms, most recent ICU ventilators appear to be less efficient than dedicated NIV ventilators. Technical performances could change, however, according to the underlying respiratory disease and the level of air leakage.

[Non-invasive Mechanical Ventilation in Acute Respiratory Failure. Clinical Practice Guidelines - on behalf of the German Society of Pneumology and Ventilatory Medicine]

The guideline update outlines the advantages as well as the limitations of NIV in the treatment of acute respiratory failure in daily clinical practice and in different indications.Non-invasive ventilation (NIV) has a high value in therapy of hypercapnic acute respiratory failure, as it significantly reduces the length of ICU stay and hospitalization as well as mortality.Patients with cardiopulmonary edema and acute respiratory failure should be treated with continuous positive airway pressure (CPAP) and oxygen in addition to necessary cardiological interventions. This should be done already prehospital and in the emergency department.In case of other forms of acute hypoxaemic respiratory failure with only mild or moderately disturbed gas exchange (PaO2/FiO2 > 150 mmHg) there is no significant advantage or disadvantage compared to high flow nasal oxygen (HFNO). In severe forms of ARDS NIV is associated with high rates of treatment failure and mortality, especially in cases with NIV-failure and delayed intubation.NIV should be used for preoxygenation before intubation. In patients at risk, NIV is recommended to reduce extubation failure. In the weaning process from invasive ventilation NIV essentially reduces the risk of reintubation in hypercapnic patients. NIV is regarded useful within palliative care for reduction of dyspnea and improving quality of life, but here in concurrence to HFNO, which is regarded as more comfortable. Meanwhile NIV is also recommended in prehospital setting, especially in hypercapnic respiratory failure and pulmonary edema.With appropriate monitoring in an intensive care unit NIV can also be successfully applied in pediatric patients with acute respiratory insufficiency.

Are all ventilators for NIV performing the same? A bench analysis

Global pandemic due to COVID-19 has increased the interest for ventilators´ use worldwide. New devices have been developed and older ones have undergone a renewed interest, but we lack robust evidence about performance of each ventilator to match appropriate device to a given patient and care environment. The aim of this bench study was to investigate the performance of six devices for noninvasive ventilation, and to compare them in terms of volume delivered, trigger response, pressurization capacity and synchronization in volume assisted controlled and pressure support ventilation. All ventilators were tested under thirty-six experimental conditions by using the lung model ASL5000® (IngMar Medical, Pittsburgh, PA). Two leak levels, two muscle inspiratory efforts and three mechanical patterns were combined for simulation. Trigger function was assessed by measurement of trigger-delay time. Pressurization capacity was evaluated as area under the pressure-time curve over the first 500 ms after inspiratory effort onset. Synchronization was evaluated by the asynchrony index and by incidence and type of asynchronies in each condition. All ventilators showed a good performance, even if pressurization capacity was worse than expected. Leak level did not affect their function. Differences were found during low muscle effort and obstructive pattern. In general, Philips Trilogy Evo/EV300 and Hamilton C3 showed the best results. NIV devices successfully compensate air leaks but still underperform with low muscle effort and obstructive lungs. Clinicians´ must have a clear understanding of the goals of NIV both for devices´ choice and set main parameters to achieve therapy success.

Mechanical Ventilation: Negative to Positive and Back Again

Critical care and mechanical ventilation have a relatively brief history in medicine. Premises existed through the seventeenth to nineteenth centuries but modern mechanical ventilation started in the twentieth century. Noninvasive ventilation techniques had started both in the intensive care unit and for home ventilation at the end of the 1980s and the 1990s. The need for mechanical ventilation is increasingly influenced worldwide by the spread of respiratory viruses, and the last coronavirus disease 2019 pandemic has seen a massive successful use of noninvasive ventilation.

Monitoring the patient-ventilator asynchrony during non-invasive ventilation

Patient-ventilator asynchrony is a major issue during non-invasive ventilation and may lead to discomfort and treatment failure. Therefore, the identification and prompt management of asynchronies are of paramount importance during non-invasive ventilation (NIV), in both pediatric and adult populations. In this review, we first define the different forms of asynchronies, their classification, and the method of quantification. We, therefore, describe the technique to properly detect patient-ventilator asynchronies during NIV in pediatric and adult patients with acute respiratory failure, separately. Then, we describe the actions that can be implemented in an attempt to reduce the occurrence of asynchronies, including the use of non-conventional modes of ventilation. In the end, we analyzed what the literature reports on the impact of asynchronies on the clinical outcomes of infants, children, and adults.

Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System

Background: Patient-ventilator synchronization during non-invasive ventilation (NIV) can be assessed by visual inspection of flow and pressure waveforms but it remains time consuming and there is a large inter-rater variability, even among expert physicians. SyncSmart™ software developed by Breas Medical (Mölnycke, Sweden) provides an automatic detection and scoring of patient-ventilator asynchrony to help physicians in their daily clinical practice. This study was designed to assess performance of the automatic scoring by the SyncSmart software using expert clinicians as a reference in patient with chronic respiratory failure receiving NIV.

Methods: From nine patients, 20 min data sets were analyzed automatically by SyncSmart software and reviewed by nine expert physicians who were asked to score auto-triggering (AT), double-triggering (DT), and ineffective efforts (IE). The study procedure was similar to the one commonly used for validating the automatic sleep scoring technique. For each patient, the asynchrony index was computed by automatic scoring and each expert, respectively. Considering successively each expert scoring as a reference, sensitivity, specificity, positive predictive value (PPV), κ-coefficients, and agreement were calculated.

Results: The asynchrony index assessed by SynSmart was not significantly different from the one assessed by the experts (18.9 ± 17.7 vs. 12.8 ± 9.4, p = 0.19). When compared to an expert, the sensitivity and specificity provided by SyncSmart for DT, AT, and IE were significantly greater than those provided by an expert when compared to another expert.

Conclusions:SyncSmart software is able to score asynchrony events within the inter-rater variability. When the breathing frequency is not too high (<24), it therefore provides a reliable assessment of patient-ventilator asynchrony; AT is over detected otherwise.

Refractory ineffective triggering during pressure support ventilation: effect of proportional assist ventilation with load-adjustable gain factors

Background

Ineffective triggering is frequent during pressure support ventilation (PSV) and may persist despite ventilator adjustment, leading to refractory asynchrony. We aimed to assess the effect of proportional assist ventilation with load-adjustable gain factors (PAV+) on the occurrence of refractory ineffective triggering.

Design

Observational assessment followed by prospective cross-over physiological study.

Setting

Academic medical ICU.

Patients

Ineffective triggering was detected during PSV by a twice-daily inspection of the ventilator’s screen. The impact of pressure support level (PSL) adjustments on the occurrence of asynchrony was recorded. Patients experiencing refractory ineffective triggering, defined as persisting asynchrony at the lowest tolerated PSL, were included in the physiological study.

Interventions

Physiological study: Flow, airway, and esophageal pressures were continuously recorded during 10 min under PSV with the lowest tolerated PSL, and then under PAV+ with the gain adjusted to target a muscle pressure between 5 and 10 cmH₂O.

Measurements

Primary endpoint was the comparison of asynchrony index between PSV and PAV+ after PSL and gain adjustments.

Results

Among 36 patients identified having ineffective triggering under PSV, 21 (58%) exhibited refractory ineffective triggering. The lowest tolerated PSL was higher in patients with refractory asynchrony as compared to patients with non-refractory ineffective triggering. Twelve out of the 21 patients with refractory ineffective triggering were included in the physiological study. The median lowest tolerated PSL was 17 cmH₂O [12–18] with a PEEP of 7 cmH₂O [5–8] and FiO₂ of 40% [39–42]. The median gain during PAV+ was 73% [65–80]. The asynchrony index was significantly lower during PAV+ than PSV (2.7% [1.0–5.4] vs. 22.7% [10.3–40.1], p < 0.001) and consistently decreased in every patient with PAV+. Esophageal pressure–time product (PTPes) did not significantly differ between the two modes (107 cmH₂O/s/min [79–131] under PSV vs. 149 cmH₂O/s/min [129–170] under PAV+, p = 0.092), but the proportion of PTPes lost in ineffective triggering was significantly lower with PAV+ (2 cmH₂O/s/min [1–6] vs. 8 cmH₂O/s/min [3–30], p = 0.012).

Conclusions

Among patients with ineffective triggering under PSV, PSL adjustment failed to eliminate asynchrony in 58% of them (21 of 36 patients). In these patients with refractory ineffective triggering, switching from PSV to PAV+ significantly reduced or even suppressed the incidence of asynchrony.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00935-0.

Diagnostic Accuracy of Diaphragm Ultrasound in Detecting and Characterizing Patient-Ventilator Asynchronies during Noninvasive Ventilation

BACKGROUND

Management of acute respiratory failure by noninvasive ventilation is often associated with asynchronies, like autotriggering or delayed cycling, incurred by leaks from the interface. These events are likely to impair patient's tolerance and to compromise noninvasive ventilation. The development of methods for easy detection and monitoring of asynchronies is therefore necessary. The authors describe two new methods to detect patient-ventilator asynchronies, based on ultrasound analysis of diaphragm excursion or thickening combined with airway pressure. The authors tested these methods in a diagnostic accuracy study.

METHODS

Fifteen healthy subjects were placed under noninvasive ventilation and subjected to artificially induced leaks in order to generate the main asynchronies (autotriggering or delayed cycling) at event-appropriate times of the respiratory cycle. Asynchronies were identified and characterized by conjoint assessment of ultrasound records and airway pressure waveforms; both were visualized on the ultrasound screen. The performance and accuracy of diaphragm excursion and thickening to detect each asynchrony were compared with a "control method" of flow/pressure tracings alone, and a "working standard method" combining flow, airway pressure, and diaphragm electromyography signals analyses.

RESULTS

Ultrasound recordings were performed for the 15 volunteers, unlike electromyography recordings which could be collected in only 9 of 15 patients (60%). Autotriggering was correctly identified by continuous recording of electromyography, excursion, thickening, and flow/pressure tracings with sensitivity of 93% (95% CI, 89-97%), 94% (95% CI, 91-98%), 91% (95% CI, 87-96%), and 79% (95% CI, 75-84%), respectively. Delayed cycling was detected by electromyography, excursion, thickening, and flow/pressure tracings with sensitivity of 84% (95% CI, 77-90%), 86% (95% CI, 80-93%), 89% (95% CI, 83-94%), and 67% (95% CI, 61-73%), respectively.

CONCLUSIONS

Ultrasound is a simple, bedside adjustable, clinical tool to detect the majority of patient-ventilator asynchronies associated with noninvasive ventilation leaks, provided that it is possible to visualize the airway pressure curve on the ultrasound machine screen. Ultrasound detection of autotriggering and delayed cycling is more accurate than isolated observation of pressure and flow tracings, and more feasible than electromyogram.

Comparison of Inspiratory Effort, Workload and Cycling Synchronization Between Non-Invasive Proportional-Assist Ventilation and Pressure-Support Ventilation Using Different Models of Respiratory Mechanics

Background

This study assessed lung models for the influence of respiratory mechanics and inspiratory effort on breathing pattern and simulator-ventilator cycling synchronization in non-invasive ventilation.

Material/Methods

A Respironics V60 ventilator was connected to an active lung simulator modeling mildly restrictive, severely restrictive, obstructive and mixed obstructive/restrictive profiles. Pressure-support ventilation (PSV) and proportional-assist ventilation (PAV) were set to obtain similar tidal volume (V_T). PAV was applied at flow assist (FA) 40–90% of resistance (Rrs) and volume assist (VA) 40–90% of elastance (Ers). Measurements were performed with system air leak of 25–28 L/minute. Ventilator performance and simulator-ventilator asynchrony were evaluated.

Results

At comparable V_T, PAV had slightly lower peak inspiratory flow and higher driving pressure compared with PSV. Premature cycling occurred in the obstructive, severely restrictive and mildly restrictive models. During PAV, time for airway pressure to achieve 90% of maximum during inspiration (T90) in the severely restrictive model was shorter than those of the obstructive and mixed obstructive/restrictive models and close to that measured in the PSV mode. Increasing FA level reduced inspiratory trigger workload (PTP₃₀₀) in obstructive and mixed obstructive/restrictive models. Increasing FA level decreased inspiratory time (T_I) and tended to aggravate premature cycling, whereas increasing VA level attenuated this effect.

Conclusions

PAV with an appropriate combination of FA and VA decreases work of breathing during the inspiratory phase and improves simulator-ventilator cycling synchrony. FA has greater impact than VA in the adaptation to inspiratory effort demand. High VA level might help improve cycling synchrony.

Breathing variability predicts the suggested need for corrective intervention due to the perceived severity of patient-ventilator asynchrony during NIV

Patient-ventilator asynchrony is associated with intolerance to noninvasive ventilation (NIV) and worsened outcomes. Our goal was to develop a tool to determine a patient needs for  intervention by a practitioner due to the presence of patient-ventilator asynchrony. We postulated that a clinician can determine when a patient needs corrective intervention due to the perceived severity of patient-ventilator asynchrony. We hypothesized a new measure, patient breathing variability, would indicate when corrective intervention is suggested by a bedside practitioner due to the perceived severity of patient-ventilator asynchrony. With IRB approval data was collected on 78 NIV patients. A panel of experts reviewed retrospective data from a development set of 10 NIV patients to categorize them into one of the three categories. The three categories were; "No to mild asynchrony-no intervention needed", "moderate asynchrony-non-emergent corrective intervention required", and "severe asynchrony-immediate intervention required". A stepwise regression with a F-test forward selection criterion was used to develop a positive linear logic model predicting the expert panel's categorizations of the need for corrective intervention. The model was incorporated into a software tool for clinical implementation. The tool was implemented prospectively on 68 NIV patients simultaneous to a bedside practitioner scoring the need for corrective intervention due to the perceived severity of patient-ventilator asynchrony. The categories from the tool and the practitioner were compared with the rate of agreement, sensitivity, specificity, and receiver operator characteristic analyses. The rate of agreement in categorizing the suggested need for clinical intervention due to the perceived presence of patient-ventilator asynchrony between the tool and experienced bedside practitioners was 95% with a Kappa score of 0.85 (p < 0.001). Further analysis found a specificity of 84% and sensitivity of 99%. The tool appears to accurately match the suggested need for corrective intervention by a bedside practitioner. Application of the tool allows for continuous, real time, and non-invasive monitoring of patients receiving NIV, and may enable early corrective interventions to ameliorate potential patient-ventilator asynchrony.

Patient-ventilator asynchrony in adult critically ill patients

INTRODUCTION

Patient-ventilator asynchrony is considered a major clinical problem for mechanically ventilated patients. It occurs during partial ventilatory support, when the respiratory muscles and the ventilator interact to contribute generating the volume output. In this review article, we consider all studies published on patient-ventilator asynchrony in the last 25 years.

EVIDENCE ACQUISITION

We selected 62 studies. The different forms of asynchrony are first defined and classified. We also describe the methods used for detecting and quantifying asynchronies. We then outline the outcome variables considered for evaluating the clinical consequences of asynchronies. The methodology for detection and quantification of patient-ventilator asynchrony are quite heterogeneous. In particular, the Asynchrony Index is calculated differently among studies.

EVIDENCE SYNTHESIS

Sixteen studies established some relationship between asynchronies and one or more clinical outcomes, such as duration of mechanical ventilation (seven studies), mortality (five studies), length of intensive care and hospital stay (four studies), patient comfort (four studies), quality of sleep (three studies), and rate of tracheotomy (three studies). In patients with severe patient-ventilator asynchrony, four of seven studies (57%) report prolonged duration of mechanical ventilation, one of five (20%) increased mortality, one of four (25%) longer intensive care and hospital lengths of stay, four of four (100%) worsened comfort, three of four (75%) deteriorated quality of sleep, and one of three (33%) increased rate of tracheotomy.

CONCLUSIONS

Given the varying outcomes considered and the erratic results, it remains unclear whether asynchronies really affects patient outcome, and the relationship between asynchronies and outcome is causative or associative.

Respiratory muscle activity and patient-ventilator asynchrony during different settings of noninvasive ventilation in stable hypercapnic COPD: does high inspiratory pressure lead to respiratory muscle unloading?

Introduction

High-intensity noninvasive ventilation (NIV) has been shown to improve outcomes in stable chronic obstructive pulmonary disease patients. However, there is insufficient knowledge about whether with this more controlled ventilatory mode optimal respiratory muscle unloading is provided without an increase in patient–ventilator asynchrony (PVA).

Patients and methods

Ten chronic obstructive pulmonary disease patients on home mechanical ventilation were included. Four different ventilatory settings were investigated in each patient in random order, each for 15 min, varying the inspiratory positive airway pressure and backup breathing frequency. With surface electromyography (EMG), activities of the intercostal muscles, diaphragm, and scalene muscles were determined. Furthermore, pressure tracings were derived simultaneously in order to assess PVA.

Results

Compared to spontaneous breathing, the most pronounced decrease in EMG activity was achieved with the high-pressure settings. Adding a high breathing frequency did reduce EMG activity per breath, while the decrease in EMG activity over 1 min was comparable with the high-pressure, low-frequency setting. With high backup breathing frequencies less breaths were pressure supported (25% vs 97%). PVAs occurred more frequently with the low-frequency settings (P=0.017).

Conclusion

High-intensity NIV might provide optimal unloading of respiratory muscles, without undue increases in PVA.

Noninvasive Ventilation

Noninvasive ventilation (NIV) has assumed a prominent role in the treatment of patients with both hypoxemic and hypercapnic acute respiratory failure (ARF). The main theoretic advantages of NIV include avoiding side effects and complications associated with endotracheal intubation, improving patient comfort, and preserving airway defense mechanisms. Factors that affect the success of NIV in patients with ARF are clinicians' expertise, selection of patient, choice of interface, selection of ventilator setting, proper monitoring, and patient motivation. Advances in the understanding of the physiologic aspects of using NIV through different interfaces and ventilator modalities have improved patient-machine interaction, thus enhancing favorable NIV outcome.

Effectiveness of Inspiratory Termination Synchrony with Automatic Cycling During Noninvasive Pressure Support Ventilation

Background

Pressure support ventilation (PSV) is a standard method for non-invasive home ventilation. A bench study was designed to compare the effectiveness of patient-ventilator inspiratory termination synchronization with automated and conventional triggering in various respiratory mechanics models.

Material/Methods

Two ventilators, the Respironics V60 and Curative Flexo ST 30, connected to a Hans Rudolph Series 1101 lung simulator, were evaluated using settings that simulate lung mechanics in patients with chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), or normal lungs. Ventilators were operated with automated (Auto-Trak) or conventional high-, moderate-, and low-sensitivity flow-cycling software algorithms, 5 cmH₂O or 15 cmH₂O pressure support, 5 cmH₂O positive end-expiratory pressure (PEEP), and an air leak of 25–28 L/min.

Results

Both ventilators adapted to the system leak without requiring adjustment of triggering settings. In all simulated lung conditions, automated cycling resulted in shorter triggering delay times (<100 ms) and lower triggering pressure-time product (PTPt) values. Tidal volumes (V_T) increased with lower conventional cycling sensitivity level. In the COPD model, automated cycling had higher leak volumes and shorter cycling delay times than in conventional cycling. Asynchronous events were rare. Inspiratory time (Tinsp), peak expiratory flow (PEF), and cycling off delay time (Cdelay) increased as a result of reduction in conventional cycling sensitivity level. In the ARDS and normal adult lung models, premature cycling was frequent at the high-sensitive cycling level.

Conclusions

Overall, the Auto-Trak protocol showed better patient-machine cycling synchronization than conventional triggering. This was evident by shorter triggering time delays and lower PTPt.

Multifaceted bench comparative evaluation of latest intensive care unit ventilators

BACKGROUND

Independent bench studies using specific ventilation scenarios allow testing of the performance of ventilators in conditions similar to clinical settings. The aims of this study were to determine the accuracy of the latest generation ventilators to deliver chosen parameters in various typical conditions and to provide clinicians with a comprehensive report on their performance.

METHODS

Thirteen modern intensive care unit ventilators were evaluated on the ASL5000 test lung with and without leakage for: (i) accuracy to deliver exact tidal volume (VT) and PEEP in assist-control ventilation (ACV); (ii) performance of trigger and pressurization in pressure support ventilation (PSV); and (iii) quality of non-invasive ventilation algorithms.

RESULTS

In ACV, only six ventilators delivered an accurate VT and nine an accurate PEEP. Eleven devices failed to compensate VT and four the PEEP in leakage conditions. Inspiratory delays differed significantly among ventilators in invasive PSV (range 75-149 ms, P=0.03) and non-invasive PSV (range 78-165 ms, P<0.001). The percentage of the ideal curve (concomitantly evaluating the pressurization speed and the levels of pressure reached) also differed significantly (range 57-86% for invasive PSV, P=0.04; and 60-90% for non-invasive PSV, P<0.001). Non-invasive ventilation algorithms efficiently prevented the decrease in pressurization capacities and PEEP levels induced by leaks in, respectively, 10 and 12 out of the 13 ventilators.

CONCLUSIONS

We observed real heterogeneity of performance amongst the latest generation of intensive care unit ventilators. Although non-invasive ventilation algorithms appear to maintain adequate pressurization efficiently in the case of leakage, basic functions, such as delivered VT in ACV and pressurization in PSV, are often less reliable than the values displayed by the device suggest.

Performance of ICU ventilators during noninvasive ventilation with large leaks in a total face mask: a bench study

Objective:

Discomfort and noncompliance with noninvasive ventilation (NIV) interfaces are obstacles to NIV success. Total face masks (TFMs) are considered to be a very comfortable NIV interface. However, due to their large internal volume and consequent increased CO₂ rebreathing, their orifices allow proximal leaks to enhance CO₂ elimination. The ventilators used in the ICU might not adequately compensate for such leakage. In this study, we attempted to determine whether ICU ventilators in NIV mode are suitable for use with a leaky TFM.

Methods:

This was a bench study carried out in a university research laboratory. Eight ICU ventilators equipped with NIV mode and one NIV ventilator were connected to a TFM with major leaks. All were tested at two positive end-expiratory pressure (PEEP) levels and three pressure support levels. The variables analyzed were ventilation trigger, cycling off, total leak, and pressurization.

Results:

Of the eight ICU ventilators tested, four did not work (autotriggering or inappropriate turning off due to misdetection of disconnection); three worked with some problems (low PEEP or high cycling delay); and one worked properly.

Conclusions:

The majority of the ICU ventilators tested were not suitable for NIV with a leaky TFM.

Sedation in non-invasive ventilation: do we know what to do (and why)?

This review examines some of the issues encountered in the use of sedation in patients receiving respiratory support from non-invasive ventilation (NIV). This is an area of critical and intensive care medicine where there are limited (if any) robust data to guide the development of best practice and where local custom appears to exert a strong influence on patterns of care.

We examine aspects of sedation for NIV where the current lack of structure may be contributing to missed opportunities to improve standards of care and examine the existing sedative armamentarium. No single sedative agent is currently available that fulfils the criteria for an ideal agent but we offer some observations on the relative merits of different agents as they relate to considerations such as effects on respiratory drive and timing, and airways patency. The significance of agitation and delirium and the affective aspect(s) of dyspnoea are also considered.

We outline an agenda for placing the use of sedation in NIV on a more systematic footing, including clearly expressed criteria and conditions for terminating NIV and structural and organizational conditions for prospective multicentre trials.

Bench-test comparison of 26 emergency and transport ventilators

Introduction

Numerous emergency and transport ventilators are commercialized and new generations arise constantly. The aim of this study was to evaluate a large panel of ventilators to allow clinicians to choose a device, taking into account their specificities of use.

Methods

This experimental bench-test took into account general characteristics and technical performances. Performances were assessed under different levels of FIO₂ (100%, 50% or Air-Mix), respiratory mechanics (compliance 30,70,120 mL/cmH₂O; resistance 5,10,20 cmH₂O/mL/s), and levels of leaks (3.5 to 12.5 L/min), using a test lung.

Results

In total 26 emergency and transport ventilators were analyzed and classified into four categories (ICU-like, n = 5; Sophisticated, n = 10; Simple, n = 9; Mass-casualty and military, n = 2). Oxygen consumption (7.1 to 15.8 L/min at F_IO₂ 100%) and the Air-Mix mode (F_IO₂ 45 to 86%) differed from one device to the other. Triggering performance was heterogeneous, but several sophisticated ventilators depicted triggering capabilities as efficient as ICU-like ventilators. Pressurization was not adequate for all devices. At baseline, all the ventilators were able to synchronize, but with variations among respiratory conditions. Leak compensation in most ICU-like and 4/10 sophisticated devices was able to correct at least partially for system leaks, but with variations among ventilators.

Conclusion

Major differences were observed between devices and categories, either in terms of general characteristics or technical reliability, across the spectrum of operation. Huge variability of tidal volume delivery with some devices in response to modifications in respiratory mechanics and F_IO₂ should make clinicians question their use in the clinical setting.

Electronic supplementary material

The online version of this article (doi:10.1186/s13054-014-0506-0) contains supplementary material, which is available to authorized users.

Automated patient-ventilator interaction analysis during neurally adjusted non-invasive ventilation and pressure support ventilation in chronic obstructive pulmonary disease

INTRODUCTION

Delivering synchronous assist during non-invasive ventilation (NIV) is challenging with flow- or pressure-controlled ventilators, especially in patients with chronic obstructive pulmonary disease (COPD). Neurally adjusted ventilatory assist (NAVA) uses diaphragm electrical activity (EAdi) to control the ventilator. We evaluated patient-ventilator interaction in patients with COPD during NIV with pressure support ventilation (PSV) and NAVA using a recently introduced automated analysis.

METHODS

Twelve COPD patients underwent three 30-minute trials: 1) PSV with dedicated NIV ventilator (NIV-PSVVision), 2) PSV with intensive care unit (ICU) ventilator (NIV-PSVServo-I), and 3) with NIV-NAVA. EAdi, flow, and airway pressure were recorded. Patient-ventilator interaction was evaluated by comparing airway pressure and EAdi waveforms with automated computer algorithms. The NeuroSync index was calculated as the percentage of timing errors between airway pressure and EAdi.

RESULTS

The NeuroSync index was higher (larger error) for NIV-PSVVision (24 (IQR 15 to 30) %) and NIV-PSVServo-I (21 (IQR 15 to 26) %) compared to NIV-NAVA (5 (IQR 4 to 7) %; P <0.001). Wasted efforts, trigger delays and cycling-off errors were less with NAVA (P <0.05 for all). The NeuroSync index and the number of wasted efforts were strongly correlated (r2 = 0.84), with a drastic increase in wasted efforts after timing errors reach 20%.

CONCLUSIONS

In COPD patients, non-invasive NAVA improves patient-ventilator interaction compared to PSV, delivered either by a dedicated or ICU ventilator. The automated analysis of patient-ventilator interaction allowed for an objective detection of patient-ventilator interaction during NIV. In addition, we found that progressive mismatch between neural effort and pneumatic timing is associated with wasted efforts.

Noninvasive ventilation with complex critical care ventilator in the treatment of acute exacerbation of chronic obstructive pulmonary disease

OBJECTIVE

To compare the clinical effect of noninvasive positive-pressure ventilation (NIPPV), delivered via critical care ventilator or miniventilator, in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD).

METHODS

Prospective comparison study. Patients with AECOPD underwent NIPPV via: miniventilator with BiLevel positive airway pressure (BiPAP; Group A); critical care ventilator with pressure support ventilation and positive end expiratory pressure (PSV + PEEP; Group B); critical care ventilator with pressure-synchronized intermittent mandatory ventilation (P-SIMV)+PSV + PEEP (Group C). Physiological parameters were recorded before, during and after ventilation.

RESULTS

Patients in Group C (n = 21) showed significantly better improvements in physiological parameters (compared with pretreatment values) than those in Group B (n = 20) or Group A (n = 22).

CONCLUSION

NIPPV delivered via critical care ventilator has a better treatment effect than miniventilator NIPPV in patients with AECOPD. The use of P-SIMV + PSV + PEEP mode provides a significantly better treatment effect than PSV + PEEP alone.

A study of noninvasive positive-pressure mechanical ventilation in the treatment of acute lung injury with a complex critical care ventilator

OBJECTIVE

To test the hypothesis that there would be better clinical outcomes following the treatment of patients with acute lung injury (ALI) using noninvasive positive-pressure mechanical ventilation (NIPPV) delivered via a complex critical care ventilator compared with a conventional mini-ventilator.

METHODS

Patients with ALI who required NIPPV were prospectively enrolled and randomly divided between three intervention groups: group A was ventilated using a mini-ventilator; groups B and C were ventilated using a complex critical care ventilator using different settings. Clinical parameters were recorded before and after 8 h of mechanical ventilation.

RESULTS

A total of 51 patients with ALI were enrolled in the study. Clinical parameters in groups B and C underwent greater improvements than those in group A. Group C demonstrated the lowest treatment failure rate (23.5%). Failure rates were highest in group A (58.8%).

CONCLUSION

The findings of this present study suggest that there were more satisfactory clinical outcomes following the treatment of patients with ALI when NIPPV was delivered using a complex critical care ventilator compared with a conventional mini-ventilator.

Optimizing patient-ventilator synchrony during invasive ventilator assist in children and infants remains a difficult task*

OBJECTIVES

To document and compare the prevalence of asynchrony events during invasive-assisted mechanical ventilation in pressure support mode and in neurally adjusted ventilatory assist in children.

DESIGN

Prospective, randomized, and crossover study.

SETTING

Pediatric and Neonatal Intensive Care Unit, University Hospital of Geneva, Switzerland.

PATIENTS

Intubated and mechanically ventilated children, between 4 weeks and 5 years old.

INTERVENTIONS

Two consecutive ventilation periods (pressure support and neurally adjusted ventilatory assist) were applied in random order. During pressure support, three levels of expiratory trigger setting were compared: expiratory trigger setting as set by the clinician in charge (PSinit), followed by a 10% (in absolute values) increase and decrease of the clinician's expiratory trigger setting. The pressure support session with the least number of asynchrony events was defined as PSbest. Therefore, three periods were compared: PSinit, PSbest, and neurally adjusted ventilatory assist. Asynchrony events, trigger delay, and inspiratory time in excess were quantified for each of them.

MEASUREMENTS AND MAIN RESULTS

Data from 19 children were analyzed. Main asynchrony events during PSinit were autotriggering (3.6 events/min [0.7-8.2]), ineffective efforts (1.2/min [0.6-5]), and premature cycling (3.5/min [1.3-4.9]). Their number was significantly reduced with PSbest: autotriggering 1.6/min (0.2-4.9), ineffective efforts 0.7/min (0-2.6), and premature cycling 2/min (0.1-3.1), p < 0.005 for each comparison. The median asynchrony index (total number of asynchronies/triggered and not triggered breaths ×100) was significantly different between PSinit and PSbest: 37.3% [19-47%] and 29% [24-43%], respectively, p < 0.005). With neurally adjusted ventilatory assist, all types of asynchrony events except double-triggering and inspiratory time in excess were significantly reduced resulting in an asynchrony index of 3.8% (2.4-15%) (p < 0.005 compared to PSbest).

CONCLUSIONS

Asynchrony events are frequent during pressure support in children despite adjusting the cycling off criteria. Neurally adjusted ventilatory assist allowed for an almost ten-fold reduction in asynchrony events. Further studies should determine the clinical impact of these findings.

Noninvasive respiratory support in the perioperative period

PURPOSE OF REVIEW

Pulmonary complications ranging from atelectasis to acute respiratory failure are common causes of poor perioperative outcomes. As the surgical population becomes increasingly at risk for pulmonary dysfunction due to increasing age and weight, development of an approach toward respiratory compromise in these patients is becoming ever more important. Given the utility of noninvasive respiratory support (NRS) in acute respiratory failure, it is likewise likely to also be important in the perioperative period.

RECENT FINDINGS

NRS is evaluated from preoperative risk assessment to its use in prevention and treatment of acute respiratory failure. Data supporting intraoperative use of NRS including preinduction continuous positive airway pressure and postextubation NRS for high-risk individuals and surgeries are examined. Timing and duration of NRS is also addressed. Finally, NRS is proposed for treatment for postoperative acute respiratory failure as an alternative to invasive rescue maneuvers.

SUMMARY

Noninvasive respiratory support should be considered an important adjunct in perioperative pulmonary care. Usage should be individually tailored in regard to timing and application modality specific to patient and surgical circumstances. More studies are needed, however, to determine the relationship demonstrated between short-term improvements in lung function and long-term outcomes.

Noninvasive ventilation: practical advice

PURPOSE OF REVIEW

This critical review discusses the key points that would be of practical help for the clinician who applies noninvasive ventilation (NIV) for treatment of patients with acute respiratory failure (ARF).

RECENT FINDINGS

In recent years, the growing role of NIV in the acute care setting has led to the development of technical innovations to overcome the problems related to gas leakage and dead space. A considerable amount of research has been conducted to improve the quality of the devices as well as optimize ventilation modes used to administer NIV. As a result, also mechanical ventilators have been implemented with modalities aimed at delivering NIV.

SUMMARY

The success of NIV in patients with ARF depends on several factors, including the skills of the clinician, selection of patient, choice of interface, selection of ventilation mode and ventilator setting, monitoring, and the motivation of the patient. Recent advances in the understanding of the physiological aspects of using NIV through different interfaces and ventilator settings have led to improve patient-machine interaction, enhancing favorable NIV outcome.

Neurally adjusted ventilatory assist vs pressure support ventilation for noninvasive ventilation during acute respiratory failure: a crossover physiologic study

BACKGROUND

Patient-ventilator asynchrony is common during noninvasive ventilation (NIV) with pressure support ventilation (PSV). We examined the effect of neurally adjusted ventilatory assist (NAVA) delivered through a facemask on synchronization in patients with acute respiratory failure (ARF).

METHODS

This was a prospective, physiologic, crossover study of 13 patients with ARF (median Pa(O(2))/F(IO(2)), 196 [interquartile range (IQR), 142-225]) given two 30-min trials of NIV with PSV and NAVA in random order. Diaphragm electrical activity (EAdi), neural inspiratory time (T(In)), trigger delay (Td), asynchrony index (AI), arterial blood gas levels, and patient discomfort were recorded.

RESULTS

There were significantly fewer asynchrony events during NAVA than during PSV (10 [IQR, 5-14] events vs 17 [IQR, 8-24] events, P = .017), and the occurrence of severe asynchrony (AI > 10%) was also less under NAVA (P = .027). Ineffective efforts and delayed cycling were significantly less with NAVA (P < .05 for both). NAVA was also associated with reduced Td (0 [IQR, 0-30] milliseconds vs 90 [IQR, 30-130] milliseconds, P < .001) and inspiratory time in excess (10 [IQR, 0-28] milliseconds vs 125 [IQR, 20-312] milliseconds, P < .001), but T(In) was similar under PSV and NAVA. The EAdi signal to its maximal value was higher during NAVA than during PSV ( P = .017). There were no significant differences in arterial blood gases or patient discomfort under PSV and NAVA.

CONCLUSION

In view of specific experimental conditions, our comparison of PSV and NAVA indicated that NAVA significantly reduced severe patient-ventilator asynchrony and resulted in similar improvements in gas exchange during NIV for ARF.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT01426178; URL: www.clinicaltrials.gov.

Sleep in hypercapnic critical care patients under noninvasive ventilation: conventional versus dedicated ventilators

OBJECTIVE

To compare sleep quality between two types of ventilators commonly used for noninvasive ventilation: conventional ICU ventilators and dedicated noninvasive ventilators; and to evaluate sleep during and between noninvasive ventilation sessions in critically ill patients.

DESIGN

Physiological sleep study with a randomized assessment of the ventilator type.

SETTING

Medical ICU in a university hospital.

PATIENTS

Twenty-four patients admitted for acute hypercapnic respiratory failure requiring noninvasive ventilation.

INTERVENTIONS

Patients were randomly assigned to receive noninvasive ventilation with either an ICU ventilators (n = 12) or a dedicated noninvasive ventilators (n = 12), and their sleep and respiratory parameters were recorded by polysomnography from 4 PM to 9 AM on the second, third, or fourth day after noninvasive ventilation initiation.

MEASUREMENTS AND MAIN RESULTS

Sleep architecture was similar between ventilator groups, including sleep fragmentation (number of arousals and awakenings/hr), but the dedicated noninvasive ventilators group showed a higher patient-ventilator asynchrony-related fragmentation (28% [17-44] vs. 14% [7.0-22]; p = 0.02), whereas the ICU ventilators group exhibited a higher noise-related fragmentation. Ineffective efforts were more frequent in the dedicated noninvasive ventilators group than in the ICU ventilators group (34 ineffective efforts/hr of sleep [15-125] vs. two [0-13]; p < 0.01), possibly as a result of a higher tidal volume (7.2 mL/kg [6.7-8.8] vs. 5.8 [5.1-6.8]; p = 0.04). More sleep time occurred and sleep quality was better during noninvasive ventilation sessions than during spontaneous breathing periods (p < 0.05) as a result of greater slow wave and rapid eye movement sleep and lower fragmentation.

CONCLUSIONS

There were no observed differences in sleep quality corresponding to the type of ventilator used despite slight differences in patient-ventilator asynchrony. Noninvasive ventilation sessions did not prevent patients from sleeping; on the contrary, they seem to aid sleep when compared with unassisted breathing.

Patient-ventilator asynchrony during noninvasive ventilation: a bench and clinical study

BACKGROUND

Different kinds of ventilators are available to perform noninvasive ventilation (NIV) in ICUs. Which type allows the best patient-ventilator synchrony is unknown. The objective was to compare patient-ventilator synchrony during NIV between ICU, transport—both with and without the NIV algorithm engaged—and dedicated NIV ventilators.

METHODS

First, a bench model simulating spontaneous breathing efforts was used to assess the respective impact of inspiratory and expiratory leaks on cycling and triggering functions in 19 ventilators. Second, a clinical study evaluated the incidence of patient-ventilator asynchronies in 15 patients during three randomized, consecutive, 20-min periods of NIV using an ICU ventilator with and without its NIV algorithm engaged and a dedicated NIV ventilator. Patient-ventilator asynchrony was assessed using flow, airway pressure, and respiratory muscles surface electromyogram recordings.

RESULTS

On the bench, frequent auto-triggering and delayed cycling occurred in the presence of leaks using ICU and transport ventilators. NIV algorithms unevenly minimized these asynchronies, whereas no asynchrony was observed with the dedicated NIV ventilators in all except one. These results were reproduced during the clinical study: The asynchrony index was significantly lower with a dedicated NIV ventilator than with ICU ventilators without or with their NIV algorithm engaged (0.5% [0.4%-1.2%] vs 3.7% [1.4%-10.3%] and 2.0% [1.5%-6.6%], P < .01), especially because of less auto-triggering.

CONCLUSIONS

Dedicated NIV ventilators allow better patient-ventilator synchrony than ICU and transport ventilators, even with their NIV algorithm. However, the NIV algorithm improves, at least slightly and with a wide variation among ventilators, triggering and/or cycling off synchronization.

Neurally adjusted ventilatory assist (NAVA) improves patient-ventilator interaction during non-invasive ventilation delivered by face mask

PURPOSE

To determine if, compared to pressure support (PS), neurally adjusted ventilatory assist (NAVA) reduces patient-ventilator asynchrony in intensive care patients undergoing noninvasive ventilation with an oronasal face mask.

METHODS

In this prospective interventional study we compared patient-ventilator synchrony between PS (with ventilator settings determined by the clinician) and NAVA (with the level set so as to obtain the same maximal airway pressure as in PS). Two 20-min recordings of airway pressure, flow and electrical activity of the diaphragm during PS and NAVA were acquired in a randomized order. Trigger delay (T(d)), the patient's neural inspiratory time (T(in)), ventilator pressurization duration (T(iv)), inspiratory time in excess (T(iex)), number of asynchrony events per minute and asynchrony index (AI) were determined.

RESULTS

The study included 13 patients, six with COPD, and two with mixed pulmonary disease. T(d) was reduced with NAVA: median 35 ms (IQR 31-53 ms) versus 181 ms (122-208 ms); p = 0.0002. NAVA reduced both premature and delayed cyclings in the majority of patients, but not the median T(iex) value. The total number of asynchrony events tended to be reduced with NAVA: 1.0 events/min (0.5-3.1 events/min) versus 4.4 events/min (0.9-12.1 events/min); p = 0.08. AI was lower with NAVA: 4.9 % (2.5-10.5 %) versus 15.8 % (5.5-49.6 %); p = 0.03. During NAVA, there were no ineffective efforts, or late or premature cyclings. PaO(2) and PaCO(2) were not different between ventilatory modes.

CONCLUSION

Compared to PS, NAVA improved patient ventilator synchrony during noninvasive ventilation by reducing T(d) and AI. Moreover, with NAVA, ineffective efforts, and late and premature cyclings were absent.

Neurally adjusted ventilatory assist improves patient-ventilator interaction during postextubation prophylactic noninvasive ventilation

OBJECTIVES

To compare the respective impact of pressure support ventilation and naturally adjusted ventilatory assist, with and without a noninvasive mechanical ventilation algorithm, on patient-ventilator interaction.

DESIGN

Prospective 2-month study.

SETTING

Adult critical care unit in a tertiary university hospital.

PATIENTS

Seventeen patients receiving a prophylactic postextubation noninvasive mechanical ventilation.

INTERVENTIONS

Patients were randomly mechanically ventilated for 10 mins with: pressure support ventilation without a noninvasive mechanical ventilation algorithm (PSV-NIV-), pressure support ventilation with a noninvasive mechanical ventilation algorithm (PSV-NIV+), neurally adjusted ventilatory assist without a noninvasive mechanical ventilation algorithm (NAVA-NIV-), and neurally adjusted ventilatory assist with a noninvasive mechanical ventilation algorithm (NAVA-NIV+).

MEASUREMENTS AND MAIN RESULTS

Breathing pattern descriptors, diaphragm electrical activity, leak volume, inspiratory trigger delay, inspiratory time in excess, and the five main asynchronies were quantified. Asynchrony index and asynchrony index influenced by leaks were computed. Peak inspiratory pressure and diaphragm electrical activity were similar for each of the four experimental conditions. For both pressure support ventilation and neurally adjusted ventilatory assist, the noninvasive mechanical ventilation algorithm significantly reduced the level of leakage (p < .01). Inspiratory trigger delay was not affected by the noninvasive mechanical ventilation algorithm but was shorter in neurally adjusted ventilatory assist than in pressure support ventilation (p < .01). Inspiratory time in excess was shorter in neurally adjusted ventilatory assist and PSV-NIV+ than in PSV-NIV- (p < .05). Asynchrony index was not affected by the noninvasive mechanical ventilation algorithm but was significantly lower in neurally adjusted ventilatory assist than in pressure support ventilation (p < .05). Asynchrony index influenced by leaks was insignificant with neurally adjusted ventilatory assist and significantly lower than in pressure support ventilation (p < .05). There was more double triggering with neurally adjusted ventilatory assist.

CONCLUSIONS

Both neurally adjusted ventilatory assist and a noninvasive mechanical ventilation algorithm improve patient-ventilator synchrony in different manners. NAVA-NIV+ offers the best compromise between a good patient-ventilator synchrony and a low level of leaks. Clinical studies are required to assess the potential clinical benefit of neurally adjusted ventilatory assist in patients receiving noninvasive mechanical ventilation.

TRIAL REGISTRATION

Clinicaltrials.gov Identifier NCT01280760.

Clinical review: Update on neurally adjusted ventilatory assist--report of a round-table conference

Conventional mechanical ventilators rely on pneumatic pressure and flow sensors and controllers to detect breaths. New modes of mechanical ventilation have been developed to better match the assistance delivered by the ventilator to the patient's needs. Among these modes, neurally adjusted ventilatory assist (NAVA) delivers a pressure that is directly proportional to the integral of the electrical activity of the diaphragm recorded continuously through an esophageal probe. In clinical settings, NAVA has been chiefly compared with pressure-support ventilation, one of the most popular modes used during the weaning phase, which delivers a constant pressure from breath to breath. Comparisons with proportional-assist ventilation, which has numerous similarities, are lacking. Because of the constant level of assistance, pressure-support ventilation reduces the natural variability of the breathing pattern and can be associated with asynchrony and/or overinflation. The ability of NAVA to circumvent these limitations has been addressed in clinical studies and is discussed in this report. Although the underlying concept is fascinating, several important questions regarding the clinical applications of NAVA remain unanswered. Among these questions, determining the optimal NAVA settings according to the patient's ventilatory needs and/or acceptable level of work of breathing is a key issue. In this report, based on an investigator-initiated round table, we review the most recent literature on this topic and discuss the theoretical advantages and disadvantages of NAVA compared with other modes, as well as the risks and limitations of NAVA.

An in vitro assessment of aerosol delivery through patient breathing circuits used with medical air or a helium-oxygen mixture

BACKGROUND

The bench experiments presented herein were conducted in order to investigate the influence of carrier gas, either medical air or a helium-oxygen mixture (78% He, 22% O2), on the droplet size distribution and aerosol mass delivered from a vibrating mesh nebulizer through a patient breathing circuit.

METHODS

Droplet size distributions at the exit of the nebulizer T-piece and at the patient end of the breathing circuit were determined by laser diffraction. Additional experiments were performed to determine the effects on measured size distributions of gas humidity and of the droplet residence time during transport from the nebulizer to the laser diffraction measurement volume. Aerosol deposition in the nebulizer, breathing circuit, and on expiratory and patient filters was determined by photometry following nebulization of sodium fluoride solutions into the breathing circuit during simulated patient breathing.

RESULTS

With no humidification of the carrier gas, droplet volume median diameter (VMD) at the exit of the nebulizer T-piece was 5.5±0.1 μm for medical air, and 4.3±0.1 μm for helium-oxygen. Varying the aerosol residence time between the nebulizer and the measurement volume did not affect the measured size distributions; however, humidification of the carrier gases reduced differences in VMD at the nebulizer exit between medical air and helium-oxygen. At the patient end of the breathing circuit, droplet VMDs were 1.8±0.1 μm for medical air and 2.2±0.1 μm for helium-oxygen. The percentages of sodium fluoride recovered from the nebulizer, breathing circuit, patient filter, and expiratory filter were, respectively, 29.9±8.3, 40.4±5.6, 8.3±1.5, and 21.5±2.1% for air, and 32.6±2.2, 36.3±0.7, 12.0±1.4, and 19.1±1.1% for helium-oxygen.

CONCLUSIONS

Ventilation with helium-oxygen in place of air-oxygen mixtures can influence both the droplet size distribution and mass of nebulized aerosol delivered through patient breathing circuits. Assessment of these effects on aerosol delivery is important when incorporating helium-oxygen into patient ventilation strategies.