key: cord-0030371-4rdek5s3 authors: Rabec, Claudio; Fresnel, Emeline; Rétory, Yann; Zhu, Kaixian; Joly, Karima; Kerfourn, Adrien; Dudoignon, Benjamin; Mendoza, Alexis; Cuvelier, Antoine; Muir, Jean-François; Melloni, Boris; Chabot, Jean-François; Gonzalez-Bermejo, Jésus; Patout, Maxime title: Addition of bacterial filter alters positive airway pressure and non-invasive ventilation performances date: 2022-04-14 journal: Eur Respir J DOI: 10.1183/13993003.02636-2021 sha: 97151443871d28ab03d53ee7e9afe3e4f8d2ddf6 doc_id: 30371 cord_uid: 4rdek5s3 The recommendation to add a bacterial filter on home positive pressure devices has significant negative impact on their performances and precludes auto-titrating positive airway pressure to function. These data suggest to not follow such recommendation. https://bit.ly/31YrWyo The aim of our study was to assess the impact of the adjunction of an inline filter in a ventilator circuit used during NIV and fixed and auto-titrating PAP. To assess ventilator performance, we used an experimental setup made of a three-dimensional printed head mimicking human upper airways and trachea connected to an artificial lung (ASL5000, IngMar Medical, USA) as previously described [3] . We compared ventilator performances without any filter (i.e. normal use of the ventilator) and with five commercial low-resistance breathing filters: Anesth-Guard (Teleflex Medical, USA), Clear-Guard 3 (Intersurgical, UK), Clear-Guard Midi (Intersurgical, UK), Eco SlimLine (L3 Medical, France) and Flo-Guard (Intersurgical, UK). For NIV, we used Dreamstation BiPAP AVAPS, BiPAP A40 and Trilogy 100 ventilators (Philips Respironics, USA). We used a pressure support mode; inspiratory positive airway pressure (IPAP) at 15 and 25 cmH 2 O; expiratory positive airway pressure (EPAP) at 5 cmH 2 O. We computed triggering delay (ms), inspiratory pressure-time product (PTPt) (cmH 2 O·s), pressure differential (cmH 2 O), defined as the difference between the delivered inspiratory pressure and the set pressure, and tidal volume (mL). Simulated patient-ventilator asynchrony (sPVA) events were classified according the SomnoNIV group framework [7] . For PAP, we used a DreamStation PAP device (Philips Respironics, USA). We computed regulation delay (ms), PTPt (cmH 2 O·s) and the maximal delivered pressure (cmH 2 O). For auto-titrating PAP assessment, we simulated obstructive events by applying 10 cmH 2 O to a Starling resistance as previously described [8] . After 6 min without any event, 20 s length obstructive events were simulated every 60 s. A total of 24 obstructive events were simulated. We assessed the EPAP reached during the last 4 min of the simulation. Shareable abstract (@ERSpublications) The recommendation to add a bacterial filter on home positive pressure devices has significant negative impact on their performances and precludes auto-titrating positive airway pressure to function. These data suggest to not follow such recommendation. https://bit.ly/31YrWyo Results are expressed as median and interquartile range, except for sPVA, which is expressed as mean and 95% confidence intervals. Chi-squared, Mann-Whitney, Wilcoxon and Friedman tests were used. Dunn's correction was applied for multiple comparisons using the setup without filter as reference. All tests were two-sided. The significance level was set at 0.05. Statistical analysis was performed with Prism 9.0.0 (GraphPad Software, USA). The addition of filter resulted in a significant impact on NIV performances with an increased triggering delay: 11 ms (9-16 ms) ( p=0.010); a lower inspiratory pressure: −1.63 cmH 2 O (−2.10-−1.1 cmH 2 O) ( p<0.001); a lower tidal volume: −61 mL (−55-−31 mL) ( p=0.025); and an increase in PTPt: 1.38 cmH 2 O·s (0.70-1.73 cmH 2 O·s) ( p<0.001). The addition of filters did not significantly impact the rate of sPVA: 33% (95% CI 25-41%) versus 27% (95% CI 24-31%) ( p=0.261) (table 1) Following recommendations suggesting the use of inline bacterial filter to reduce the risk of particle inhalation, our experimental model shows that 1) during NIV, adding a bacterial filter significantly increased the work of breathing and decreased the delivered volume; 2) during PAP, adding a bacterial filter increased the work of breathing and decreased the delivered pressure; and 3) during auto-titrating PAP, the use of bacterial filter resulted in lower pressure and inaccurate characterisation of respiratory events. Home NIV is delivered to patients with advanced chronic respiratory failure [9] who have a poor prognosis [10] . As the addition of filters leads to an increase of work of breathing and a lower tidal volume, they may aggravate hypoventilation and thus dramatically impact on NIV efficacy and worsen prognosis. If physicians were to follow the recommendation to add an inline filter, our data suggest to closely monitor patients and to adjust NIV settings to alleviate the impact on the work of breathing and on the delivered volume. With PAP, the delivered pressure was lower both with CPAP (−0.81 cmH 2 O) and auto-adjusting PAP (−3.18 cmH 2 O). Such a drop in the delivered pressure is likely to have clinical consequences with poorer control of upper airway. In our study, we have demonstrated that adding an inline filter greatly altered the automated detection of obstructive events. Clinicians should therefore not base their clinical decision using the residual event data provided by a PAP device when using an inline filter. Our results show that the addition of an inline filter could strongly impact on the effectiveness of the auto-adjusting PAP device tested. Indeed, we have shown that the addition of filters resulted in a lower delivered pressure and a higher number of residual obstructive events. We hypothesise that filters impact the efficacy of this device by interfering with the detection of obstructive respiratory events leading to an increase in the residual apnoea-hypopnoea index reported by the device. Our results show that auto-adjusting PAP should not be used with an inline filter. In line with previous bench studies [3, 11] , our results highlight that PAP and NIV devices should be used as per their user manual without any alteration on their regular setup. Indeed, any change may impair their efficacy. There are some limitations in our study. First, we only performed a bench model study. However, a clinical trial assessing six different types of experimental condition, and three different type of lung mechanics would have not been feasible especially given the night-to-night variability [12] . Second, we identified significant differences between filters, but we did to evaluate their clinical relevance or their long-term consequences. Third, we did not assess the impact of filter insertion on the volatile organic compound. Finally, these results may not be extensible to other machines and manufacturers. Auto-adjusting PAP Mask pressure (cmH 2 O) Medical Device Recall AASM Guidance in Response to Philips Recall of PAP Devices Recommended approaches to minimize aerosol dispersion of SARS-CoV-2 during noninvasive ventilatory support can cause ventilator performance deterioration: a benchmark comparative study Autoadjusted versus fixed CPAP for obstructive sleep apnoea: a multicentre, randomised equivalence trial Computerized adjustable versus fixed NCPAP treatment of obstructive sleep apnea Bench model to simulate upper airway obstruction for analyzing automatic continuous positive airway pressure devices Framework for patient-ventilator asynchrony during long-term non-invasive ventilation Combined effects of leaks, respiratory system properties and upper airway patency on the performance of home ventilators: a bench study Long-term noninvasive ventilation in the Geneva Lake area: indications, prevalence, and modalities Long-term survival following initiation of home non-invasive ventilation: a European study Protective recommendations for non-invasive ventilation during COVID-19 pandemic: a bench evaluation of the effects of instrumental dead space on alveolar ventilation The accuracy of repeated sleep studies in OSA: a longitudinal observational study with 14 nights of oxygen saturation monitoring Acknowledgements: Maxime Patout is the guarantor of the content of the manuscript, including the data and analysis. The authors would like to thank ANTADIR for funding the experiments and the centre EXPLOR for performing the experiments with auto-titrating PAP; and ASV santé, Jean-Christian Borel and M. Philippe Roussel from AGIRADOM (Grenoble).