Discussion
Our study showed significant differences in patient-ventilator synchrony and technical performances between the different ventilators, according to underlying lung profiles. For all ventilators, regardless of the underlying lung profile, the AI appeared to be correlated with the level of leakage and PSV. Dedicated NIV ventilators generated a lower AI compared with ICU and transport ventilators. These differences in AI between ventilators were more pronounced with a restrictive ventilatory pattern (online supplemental e-Tables 6, 8 and 9), and to a lesser extent with a normal pattern (online supplemental e-Tables 7, 10 and 11); whereas, the difference between ventilators was not significant for the obstructive pattern (online supplemental e-Tables 5, 12 and 13). The most frequently observed forms of PVA were auto-triggering and cycling asynchrony. Except for peak flow and minute ventilation, other parameters of ventilatory mechanics were different between ventilators, with some heterogeneity between ventilator categories. We also demonstrated that dedicated NIV ventilators generated less WOBt than ICU or transport ventilators.
Despite the development of new generations of ventilators (ICU, dedicated NIV, transport), there is still significant heterogeneity in synchrony and technical performances between the different categories of ventilators, even within the same category, for NIV.15 16 Despite the improvement of NIV algorithms in the most recent ICU ventilators, they still appear to be less efficient than dedicated NIV ventilators and generate more PVA regardless of the underlying ventilatory profile. This was already observed with the first ‘NIV modes’ integrated in ICU ventilators.15 This lower performance was confirmed in the bench and clinical study by Carteaux et al,16 in which ICU ventilators, despite their activated NIV algorithm, had a significantly higher AI than dedicated NIV ventilators. In the bench part of this study, transport ventilators also generated more auto-triggering PVA than dedicated NIV ventilators. We did not find such a significant difference between the transport ventilator tested in our study and other ventilators. This could be explained by the difference in the generation of transport ventilators tested, the technology of the bench test used but also the lack of power of our study evaluating only one latest generation of transport ventilator as compared with the latter study.16 Furthermore, transport ventilators have been improved technologically, approaching dedicated NIV ventilator performances.26 29 30
This heterogeneity in ventilator performances in terms of AI and PVA was found between ventilators within the same category.15 Among ICU ventilators in our study, the Servo-U appeared to have the best performance, which was interesting because it is a compressed-gas ventilator and performed better than the Monnal-T75 (turbine-driven), and among dedicated NIV ventilators, the Trilogy-Evo performed better than the Astral-150. The AI and PVA rates should also be interpreted in relation to the level of leakage. The AI was significantly different between the different ventilators only for large, simulated leaks of ≥30 L/min. The lack of difference in AI between ventilators for a leak of 15 L/min may suggest, therefore, that other determinants could be involved in the genesis of PVA, such as ventilator settings.
As previously demonstrated in bench11 15 16 31 and clinical studies,6 10 16 the integration and activation of ‘NIV modes’ in ICU ventilators were not sufficient to render ICU ventilators as efficient as dedicated NIV ventilators, even with turbine-driven technology. Our bench study, using a realistic 3D manikin, confirms this feature for the latest generations of ventilators (ICU, dedicated NIV, transport). We chose not to deactivate ‘NIV mode’ in our study as we systematically use ICU ventilators with their NIV algorithm activated.6 16 Unlike previous bench studies, we also evaluated ventilator performances according to different underlying ventilatory profiles.11 15 16 31 With normal or obstructive ventilatory patterns, ventilators generated little or no PVA in our study. In contrast, with the restrictive pattern, ventilators generated more PVA with a large heterogeneity of AI between them. In addition, the AI was found to be not significantly different between ventilators for the obstructive pattern. This feature could partly be explained by the ventilator settings applied. Although we used the same settings for the different lung profiles, these settings could have been more suitable for an obstructive ventilatory pattern. Indeed, these results could be related to the underlying ventilatory profile, and we hypothesised that low compliance (restrictive profile) may be more deleterious than high resistance (obstructive profile) in terms of PVA risk. According to our results, the three ICU ventilators, Evita-XL, V500 and V800, were less suitable for restrictive profiles.
Auto-triggering and cycling abnormalities were the most frequently observed PVA in our study. Auto-triggering was also reported as the most frequent PVA in the bench study of Carteaux et al.16 In clinical studies, cycling asynchrony,10 32 ineffective efforts or even double-triggering6 were the most frequently reported PVA. These differences should take into account the evaluation conditions, that is, test bench vs clinical conditions, ventilator settings, and technological evolution over time. Auto-triggering and cycling abnormalities are closely related to inspiratory trigger sensitivity and expiratory trigger cycling setting, respectively.8 32 In our study, the inspiratory trigger was set to be very sensitive. This could have led to an increase in auto-triggering, but we did not observe any excessive auto-triggering under the various measurement conditions. We used a fixed expiratory cycling trigger without considering the underlying ventilatory pattern. Cycling abnormalities which can increase the patient’s WOBt can also be increased by inspiratory or expiratory non-intentional air leakage between mask and patient’s face.8 32 33
Differences of ventilatory performances between ventilators could be an explanation for the difference of AI. Inspiratory triggering delay, pressure rise time and expiratory cycling seem to be the main determinants of patient-ventilator synchrony during acute13 31 and chronic NIV.28 In addition to the choice of ventilator used for NIV, this highlights the importance of clinician-set settings. The measured pressure at the mask, reflecting the applied pressure, was lower with ICU ventilators than with dedicated NIV ventilators in our study; whereas, minute ventilation was comparable, suggesting similar ventilatory efficiency between ventilators for CO2 removal. Interestingly, Garnier et al34 also reported difficulties of ICU ventilators to reach the targeted pressurisation level. The PTPt, indirectly reflecting the WOBt,35 was lower with dedicated NIV ventilators than with ICU ventilators. This physiological benefit was previously demonstrated with dedicated NIV ventilators.13 16 31 Concerning the transport ventilator in our study, its technical performance in limiting PVA and improving mechanical ventilatory conditions was intermediate between dedicated NIV and ICU ventilators. Such results were reported previously with older transport ventilators.20 32
Apart from PSV level and to limit confounding factors, we applied standardised settings that could be used across the different ventilators tested, but these settings were not adapted to ventilatory conditions (air leakage, underlying lung profile particularly). Finally, our results highlight the need to individualise NIV settings, including inspiratory trigger,36 37 pressure rise time,38 expiratory cycling8 32 and PEEP,23 to each clinical situation to ensure the best compromise between the effectiveness of NIV according to underlying respiratory disease and its tolerance by patients.10 39
Our study exhibits some limitations. First, it is an experimental physiological study carried out in a bench test environment, and its results are probably not applicable to different clinical situations. Indeed, although we used a rather realistic 3D manikin head, only one manikin morphology and one type of facemask were studied, without being subjected, as in clinical practice, to the risk of interface mobilisation likely to generate or aggravate PVA. We used only a dual-limb circuit and did not test dedicated NIV ventilators with a single-limb circuit and a vented mask or an expiratory valve, even though they could be used to administrate NIV with fewer PVAs.16 As NIV practices could vary widely in terms of type of interfaces, circuits and ventilators used,3 it is obviously not possible to conduct a bench study encompassing all clinical situations, and therefore, to extrapolate our results to all clinical situations. In addition to our study, high-performance modern turbine-driven ventilators have also been tested in bench studies using different circuit configurations as well as different interfaces, including the helmet.17
Moreover, although we simulated different lung profiles, these simulations cannot represent all the ventilatory characteristics of patients treated with NIV in ICU or respiratory departments. On the other hand, we did not evaluate different levels of simulated inspiratory or expiratory leakage, which are frequently observed in clinical situations. Despite all these limitations, our results should still help clinicians selecting ventilator models and settings for NIV use, depending on the profile of the underlying respiratory pathology.