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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. [ABSTRACT FROM AUTHOR]

Background: Current bilevel positive-pressure ventilators for home noninvasive ventilation (NIV) provide physicians with software that records items important for patient monitoring, such as compliance, tidal volume (Vt), and leaks. However, to our knowledge, the validity of this information has not yet been independently assessed.Methods: Testing was done for seven home ventilators on a bench model adapted to simulate NIV and generate unintentional leaks (ie, other than of the mask exhalation valve). Five levels of leaks were simulated using a computer-driven solenoid valve (0-60 L/min) at different levels of inspiratory pressure (15 and 25 cm H(2)O) and at a fixed expiratory pressure (5 cm H(2)O), for a total of 10 conditions. Bench data were compared with results retrieved from ventilator software for leaks and Vt.Results: For assessing leaks, three of the devices tested were highly reliable, with a small bias (0.3-0.9 L/min), narrow limits of agreement (LA), and high correlations (R(2), 0.993-0.997) when comparing ventilator software and bench results; conversely, for four ventilators, bias ranged from -6.0 L/min to -25.9 L/min, exceeding -10 L/min for two devices, with wide LA and lower correlations (R(2), 0.70-0.98). Bias for leaks increased markedly with the importance of leaks in three devices. Vt was underestimated by all devices, and bias (range, 66-236 mL) increased with higher insufflation pressures. Only two devices had a bias < 100 mL, with all testing conditions considered.Conclusions: Physicians monitoring patients who use home ventilation must be aware of differences in the estimation of leaks and Vt by ventilator software. Also, leaks are reported in different ways according to the device used. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the efficacy of delivering a mixture of helium and oxygen gas (He–O2) in spontaneous ventilation. Three high oxygen flow reservoir masks were tested: the Heliox21, specifically designed for helium; the Hi-Ox80 mask, with an inspiratory and an expiratory valve; and a standard high-concentration face mask.Methods: This prospective randomized crossover study was performed in six healthy volunteers in a laboratory setting. Volunteers breathed a mixture of 78% He/22% O2 through each of the masks under two different breathing conditions (rest and hyperventilation: minute ventilation of 14.9 ± 6.1 and 26.7 ± 8.7 L min(−1), respectively) and four different He–O2 flow rates (7, 10, 12, and 15 L min(−1)).Results: A nasopharyngeal catheter was used to estimate He pharyngeal concentration (Fp [He]) in the airways in order to determine the percentage of contamination with room air (% air cont) at end-expiration. Under all testing conditions, the Hi-Ox80 mask presented a significantly lower % air cont. During resting breathing pattern, a Fp [He] higher than 50% was achieved in 54% of the tests performed with the Hi-Ox80 mask compared to 29% for the Heliox21 mask and only 17% for the standard mask. At hyperventilation, a Fp [He] higher than 50% was achieved in 17% of the tests performed with the Hi-Ox mask compared to 4% for the other two masks.Conclusion: He–O2 administration via the usual high-concentration reservoir masks results in significant dilution by room air. The Hi-Ox80 mask minimized room air contamination and much more frequently achieved a pharyngeal He concentration higher than 50%. [ABSTRACT FROM AUTHOR]

Objective: To determine the prevalence of patient-ventilator asynchrony in patients receiving non-invasive ventilation (NIV) for acute respiratory failure.Design: Prospective multicenter observation study.Setting: Intensive care units in three university hospitals.Methods: Patients consecutively admitted to ICU were included. NIV, performed with an ICU ventilator, was set by the clinician. Airway pressure, flow, and surface diaphragmatic electromyography were recorded continuously for 30 min. Asynchrony events and the asynchrony index (AI) were determined from visual inspection of the recordings and clinical observation.Results: A total of 60 patients were included, 55% of whom were hypercapnic. Auto-triggering was present in 8 (13%) patients, double triggering in 9 (15%), ineffective breaths in 8 (13%), premature cycling 7 (12%) and late cycling in 14 (23%). An AI > 10%, indicating severe asynchrony, was present in 26 patients (43%), whose median (25-75 IQR) AI was 26 (15-54%). A significant correlation was found between the magnitude of leaks and the number of ineffective breaths and severity of delayed cycling. Multivariate analysis indicated that the level of pressure support and the magnitude of leaks were weakly, albeit significantly, associated with an AI > 10%. Patient comfort scale was higher in pts with an AI < 10%.Conclusion: Patient-ventilator asynchrony is common in patients receiving NIV for acute respiratory failure. Our results suggest that leaks play a major role in generating patient-ventilator asynchrony and discomfort, and point the way to further research to determine if ventilator functions designed to cope with leaks can reduce asynchrony in the clinical setting. [ABSTRACT FROM AUTHOR]

A high-quality, low-cost ventilator, dubbed HEV, has been developed by the particle physics community working together with biomedical engineers and physicians around the world. The HEV design is suitable for use both in and out of hospital intensive care units, provides a variety of modes and is capable of supporting spontaneous breathing and supplying oxygen-enriched air. An external air supply can be combined with the unit for use in situations where compressed air is not readily available. HEV supports remote training and post market surveillance via a Web interface and data logging to complement standard touch screen operation, making it suitable for a wide range of geographical deployment. The HEV design places emphasis on the ventilation performance, especially the quality and accuracy of the pressure curves, reactivity of the trigger, measurement of delivered volume and control of oxygen mixing, delivering a global performance which will be applicable to ventilator needs beyond the COVID-19 pandemic. This article describes the conceptual design and presents the prototype units together with a performance evaluation., Competing Interests: We declare we have no competing interests., (© 2022 The Authors.)

Background: Closed-loop modes automatically adjust ventilation settings, delivering individualized ventilation over short periods of time. The objective of this randomized controlled trial was to compare safety, efficacy and workload for the health care team between IntelliVent®-ASV and conventional modes over a 48-hour period., Methods: ICU patients admitted with an expected duration of mechanical ventilation of more than 48 hours were randomized to IntelliVent®-ASV or conventional ventilation modes. All ventilation parameters were recorded breath-by-breath. The number of manual adjustments assesses workload for the healthcare team. Safety and efficacy were assessed by calculating the time spent within previously defined ranges of non-optimal and optimal ventilation, respectively., Results: Eighty patients were analyzed. The median values of ventilation parameters over 48 hours were similar in both groups except for PEEP (7[4] cmH2O versus 6[3] cmH2O with IntelliVent®-ASV and conventional ventilation, respectively, P=0.028) and PETCO2 (36±7 mmHg with IntelliVent®-ASV versus 40±8 mmHg with conventional ventilation, P=0.041). Safety was similar between IntelliVent®-ASV and conventional ventilation for all parameters except for PMAX, which was more often non-optimal with IntelliVent®-ASV (P=0.001). Efficacy was comparable between the 2 ventilation strategies, except for SpO2 and VT, which were more often optimal with IntelliVent®-ASV (P=0.005, P=0.016, respectively). IntelliVent®-ASV required less manual adjustments than conventional ventilation (P<0.001) for a higher total number of adjustments (P<0.001). The coefficient of variation over 48 hours was larger with IntelliVent®-ASV in regard of maximum pressure, inspiratory pressure (PINSP), and PEEP as compared to conventional ventilation., Conclusions: IntelliVent®-ASV required less manual intervention and delivered more variable PEEP and PINSP, while delivering ventilation safe and effective ventilation in terms of VT, RR, SpO2 and PETCO2.

Objectives: To document the prevalence of asynchrony events during noninvasive ventilation in pressure support in infants and in children and to compare the results with neurally adjusted ventilatory assist., Design: Prospective randomized cross-over study in children undergoing noninvasive ventilation., Setting: The study was performed in a PICU., Patients: From 4 weeks to 5 years., Interventions: Two consecutive ventilation periods (pressure support and neurally adjusted ventilatory assist) were applied in random order. During pressure support (PS), three levels of expiratory trigger (ETS) setting were compared: initial ETS (PSinit), and ETS value decreased and increased by 15%. Of the three sessions, the period allowing for the lowest number of asynchrony events was defined as PSbest. Neurally adjusted ventilator assist level was adjusted to match the maximum airway pressure during PSinit. Positive end-expiratory pressure was the same during pressure support and neurally adjusted ventilator assist. Asynchrony events, trigger delay, and cycling-off delay were quantified for each period., Results: Six infants and children were studied. Trigger delay was lower with neurally adjusted ventilator assist versus PSinit and PSbest (61 ms [56-79] vs 149 ms [134-180] and 146 ms [101-162]; p = 0.001 and 0.02, respectively). Inspiratory time in excess showed a trend to be shorter during pressure support versus neurally adjusted ventilator assist. Main asynchrony events during PSinit were autotriggering (4.8/min [1.7-12]), ineffective efforts (9.9/min [1.7-18]), and premature cycling (6.3/min [3.2-18.7]). Premature cycling (3.4/min [1.1-7.7]) was less frequent during PSbest versus PSinit (p = 0.059). The asynchrony index was significantly lower during PSbest versus PSinit (40% [28-65] vs 65.5% [42-76], p < 0.001). With neurally adjusted ventilator assist, all types of asynchronies except double triggering were reduced. The asynchrony index was lower with neurally adjusted ventilator assist (2.3% [0.7-5] vs PSinit and PSbest, p < 0.05 for both comparisons)., Conclusion: Asynchrony events are frequent during noninvasive ventilation with pressure support in infants and in children despite adjusting the cycling-off criterion. Compared with pressure support, neurally adjusted ventilator assist allows improving patient-ventilator synchrony by reducing trigger delay and the number of asynchrony events. Further studies should determine the clinical impact of these findings.

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.

Purpose: To determine if, compared with pressure support (PS), neurally adjusted ventilatory assist (NAVA) reduces trigger delay, inspiratory time in excess, and the number of patient-ventilator asynchronies in intubated patients., Methods: Prospective interventional study in spontaneously breathing patients intubated for acute respiratory failure. Three consecutive periods of ventilation were applied: (1) PS1, (2) NAVA, (3) PS2. Airway pressure, flow, and transesophageal diaphragmatic electromyography were continuously recorded., Results: All results are reported as median (interquartile range, IQR). Twenty-two patients were included, 36.4% (8/22) having obstructive pulmonary disease. NAVA reduced trigger delay (ms): NAVA, 69 (57-85); PS1, 178 (139-245); PS2, 199 (135-256). NAVA improved expiratory synchrony: inspiratory time in excess (ms): NAVA, 126 (111-136); PS1, 204 (117-345); PS2, 220 (127-366). Total asynchrony events were reduced with NAVA (events/min): NAVA, 1.21 (0.54-3.36); PS1, 3.15 (1.18-6.40); PS2, 3.04 (1.22-5.31). The number of patients with asynchrony index (AI) >10% was reduced by 50% with NAVA. In contrast to PS, no ineffective effort or late cycling was observed with NAVA. There was less premature cycling with NAVA (events/min): NAVA, 0.00 (0.00-0.00); PS1, 0.14 (0.00-0.41); PS2, 0.00 (0.00-0.48). More double triggering was seen with NAVA, 0.78 (0.46-2.42); PS1, 0.00 (0.00-0.04); PS2, 0.00 (0.00-0.00)., Conclusions: Compared with standard PS, NAVA can improve patient-ventilator synchrony in intubated spontaneously breathing intensive care patients. Further studies should aim to determine the clinical impact of this improved synchrony.

Objective: To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure., Design: Prospective multicenter randomized cross-over study., Setting: Intensive care units in three university hospitals., Methods: Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis., Results: Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs., Conclusion: In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

An online algorithm for determining respiratory mechanics in patients using non-invasive ventilation (NIV) in pressure support mode was developed and embedded in a ventilator system. Based on multiple linear regression (MLR) of respiratory data, the algorithm was tested on a patient bench model under conditions with and without leak and simulating a variety of mechanics. Bland-Altman analysis indicates reliable measures of compliance across the clinical range of interest (± 11-18% limits of agreement). Resistance measures showed large quantitative errors (30-50%), however, it was still possible to qualitatively distinguish between normal and obstructive resistances. This outcome provides clinically significant information for ventilator titration and patient management.

Objective: To explore the user-friendliness and ergonomics of seven new generation intensive care ventilators., Design: Prospective task-performing study., Setting: Intensive care research laboratory, university hospital., Methods: Ten physicians experienced in mechanical ventilation, but without prior knowledge of the ventilators, were asked to perform eight specific tasks [turning the ventilator on; recognizing mode and parameters; recognizing and setting alarms; mode change; finding and activating the pre-oxygenation function; pressure support setting; stand-by; finding and activating non-invasive ventilation (NIV) mode]. The time needed for each task was compared to a reference time (by trained physiotherapist familiar with the devices). A time >180 s was considered a task failure., Results: For each of the tests on the ventilators, all physicians' times were significantly higher than the reference time (P < 0.001). A mean of 13 +/- 8 task failures (16%) was observed by the ventilator. The most frequently failed tasks were mode and parameter recognition, starting pressure support and finding the NIV mode. Least often failed tasks were turning on the pre-oxygenation function and alarm recognition and management. Overall, there was substantial heterogeneity between machines, some exhibiting better user-friendliness than others for certain tasks, but no ventilator was clearly better that the others on all points tested., Conclusions: The present study adds to the available literature outlining the ergonomic shortcomings of mechanical ventilators. These results suggest that closer ties between end-users and manufacturers should be promoted, at an early development phase of these machines, based on the scientific evaluation of the cognitive processes involved by users in the clinical setting.

An automated classification algorithm for the detection of expiratory ineffective efforts in patient-ventilator interaction is developed and validated. Using this algorithm, 5624 breaths from 23 patients in a pulmonary ward were examined. The participants (N = 23) underwent both conventional and non-invasive ventilation. Tracings of patient flow, pressure at the airway, and transdiaphragmatic pressure were manually labeled by an expert. Overall accuracy of 94.5% was achieved with sensitivity 58.7% and specificity 98.7%. The results demonstrate the viability of using pattern classification techniques to automatically detect the presence of asynchrony between a patient and their ventilator.

Objective: Noninvasive ventilation (NIV) is often applied with ICU ventilators. However, leaks at the patient-ventilator interface interfere with several key ventilator functions. Many ICU ventilators feature an NIV-specific mode dedicated to preventing these problems. The present bench model study aimed to evaluate the performance of these modes., Design and Setting: Bench model study in an intensive care research laboratory of a university hospital., Methods: Eight ICU ventilators, widely available in Europe and featuring an NIV mode, were connected by an NIV mask to a lung model featuring a plastic head to mimic NIV conditions, driven by an ICU ventilator imitating patient effort. Tests were conducted in the absence and presence of leaks, the latter condition with and without activation of the NIV mode. Trigger delay, trigger-associated inspiratory workload, and pressurization were tested in conditions of normal respiratory mechanics, and cycling was also assessed in obstructive and restrictive conditions., Results: On most ventilators leaks led to an increase in trigger delay and workload, a decrease in pressurization, and delayed cycling. On most ventilators the NIV mode partly or totally corrected these problems, but with large variations between machines. Furthermore, on some ventilators the NIV mode worsened the leak-induced dysfunction., Conclusions: The results of this bench-model NIV study confirm that leaks interfere with several key functions of ICU ventilators. Overall, NIV modes can correct part or all of this interference, but with wide variations between machines in terms of efficiency. Clinicians should be aware of these differences when applying NIV with an ICU ventilator.