Compared with invasive ventilation, non-invasive ventilation (NIV) has two unique characteristics: the non-hermetic nature of the system and the fact that the ventilator-lung assembly cannot be considered as a single-compartment model because of the presence of variable resistance represented by the upper airway. When NIV is initiated, the ventilator settings are determined empirically based on a clinical evaluation and diurnal blood gas variations. However, NIV is predominantly applied during sleep. Consequently, to assess overnight patient–machine ‘agreement’ and efficacy of ventilation, more specific and sophisticated monitoring is needed. The effectiveness of NIV might therefore be more correctly assessed by sleep studies than by daytime assessment. The most available and simple monitoring can be done from flow and pressure curves from the mask or the ventilator circuit. Examination of these tracings can give useful information to evaluate if the settings chosen by the operator were the right ones for that patient. However, as NIV allows a large range of ventilatory parameters and settings, it is mandatory to have information about this to better understand patient–ventilator interaction. Ventilatory modality, mode of triggering, pressurisation slope, use or not of positive end expiratory pressure and type of exhalation as well as ventilator performances may all have physiological consequences. Leaks and upper airway resistance variations may, in turn, modify these patterns. This article discusses the equipment available for NIV, analyses the effect of different ventilator modes and settings and of exhalation and connecting circuits on ventilatory traces and gives the background necessary to understand their impact on nocturnal monitoring of NIV.

Empirically determined noninvasive ventilation (NIV) settings may not achieve optimal ventilatory support. Some ventilators include monitoring modules to assess ventilatory quality. We conducted a bench-to-bedside study to assess the ventilatory quality of the VPAP^TMIII-ResLink^TM(ResMed, North Ryde, Australia).We tested the accuracy of minute ventilation (MV) and leak calculations given by VPAP^TMIII-ResLink^TMcompared to those measured by a bench model at varied leak levels and ventilator settings. We systematically assessed NIV efficacy using this system from 2003 to 2006. Ventilation was considered inadequate if leak (>24 L·min⁻¹), continuous desaturation (>30% of the trace) or desaturation dips (>3%) were present.On the bench test, both methods were highly correlated (r = 0.947, p>0.0001 and r = 0.959, p<0.0001 for leak and MV, respectively). We performed 222 assessments in 169 patients (aged 66.42±16 yrs, 100 males). Abnormalities were detected on 147 (66%) out of 222 occasions. Leak was the most common abnormality (34.2%) followed by desaturation dips (23.8%). The most effective therapeutic solutions were a chin strap if leak was detected (61.2%) and expiratory positive airway pressure increase for desaturation dips (59.5%). In 15.7% of cases, when abnormalities persisted, a polygraphy was performed.The systematic use of this device enables NIV to be optimised, limiting the indication of sleep studies to complex cases.

Background: For some patients, Continuous Positive Airway Pressure (CPAP) remains an uncomfortable therapy despite the constant development of technological innovations. To date, no real life study has investigated the relationship between mask related side-effects (MRSEs) and CPAP-non-adherence (defined as < 4 h/day) or residual-excessive-sleepiness (RES, Epworth-Sleepiness-Scale (ESS) score ≥ 11) in the long-term. Methods: The InterfaceVent-CPAP study is a prospective real-life cross-sectional study conducted in an apneic adult cohort undergoing at least 3 months of CPAP with unrestricted mask-access (34 different masks). MRSEs were evaluated using visual-analogue-scales, CPAP-data using CPAP-software, sleepiness using ESS. Results: 1484 patients were included in the analysis (72.2% male, median age 67 years (IQ_25–75: 60–74), initial Apnea–Hypopnea-Index (AHI) of 39 (31–56)/h, residual AHI_flow was 1.9 (0.9–4) events/h), CPAP-treatment lasted 4.4 (2.0–9.7) years, CPAP-usage was 6.8 (5.5–7.8) h/day, the prevalence of CPAP-non-adherence was 8.6%, and the prevalence of RES was 16.17%. Leak-related side-effects were the most prevalent side-effects (patient-reported leaks concerned 75.4% of responders and had no correlation with CPAP-reported-leaks). Multivariable logistic regression analyses evaluating explanatory-variable (demographic data, device/mask data and MRSEs) effects on variables-of-interest (CPAP-non-adherence and RES), indicated for patient-MRSEs significant associations between: (i) CPAP-non-adherence and dry-mouth (p = 0.004); (ii) RES and patient-reported leaks (p = 0.007), noisy mask (p < 0.001), dry nose (p < 0.001) and harness pain (p = 0.043). Conclusion: In long-term CPAP-treated patients, leak-related side-effects remain the most prevalent side-effects, but patient-reported leaks cannot be predicted by CPAP-reported-leaks. Patient-MRSEs can be independently associated with CPAP-non-adherence and RES, thus implying a complementary role for MRSE questionnaires alongside CPAP-device-reported-data for patient monitoring. Trial registration InterfaceVent is registered with ClinicalTrials.gov (NCT03013283).

Background: Noninvasive ventilation (NIV) represents an effective treatment for chronic respiratory failure. However, empirically determined NIV settings may not achieve optimal ventilatory support. Therefore, the efficacy of NIV should be systematically monitored. The minimal recommended monitoring strategy includes clinical assessment, arterial blood gases (ABG) and nocturnal transcutaneous pulsed oxygen saturation (SpO₂). Polysomnography is a theoretical gold standard but is not routinely available in many centers. Simple tools such as transcutaneous capnography (TcPCO₂) or ventilator built-in software provide reliable informations but their role in NIV monitoring has yet to be defined. The aim of our work was to compare the accuracy of different combinations of tests to assess NIV efficacy.Methods: This retrospective comparative study evaluated the efficacy of NIV in consecutive patients through four strategies (A, B, C and D) using four different tools in various combinations. These tools included morning ABG, nocturnal SpO₂, TcPCO₂and data provided by built-in software via a dedicated module. Strategy A (ABG + nocturnal SpO₂), B (nocturnal SpO₂ + TcPCO₂) and C (TcPCO₂ + builtin software) were compared to strategy D, which combined all four tools (NIV was appropriate if all four tools were normal).Results: NIV was appropriate in only 29 of the 100 included patients. Strategy A considered 53 patients as appropriately ventilated. Strategy B considered 48 patients as appropriately ventilated. Strategy C misclassified only 6 patients with daytime hypercapnia.Conclusion: Monitoring ABG and nocturnal SpO₂is not enough to assess NIV efficacy. Combining data from ventilator built-in software and TcPCO₂seems to represent the best strategy to detect poor NIV efficacy.TrialregistrationInstitutional Review Board of the Société de Pneumologie de Langue Française (CEPRO 2016 Georges)