Mask side-effects in long-term CPAP-patients impact adherence and sleepiness: the InterfaceVent real-life study.

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 (IQ25-75: 60-74), initial Apnea-Hypopnea-Index (AHI) of 39 (31-56)/h, residual AHIflow 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).

Is the 2013 American Thoracic Society CPAP-tracking system algorithm useful for managing non-adherence in long-term CPAP-treated patients?

BACKGROUND: Whereas telemedicine usage is growing, the only clinical algorithm for Continuous Positive Airway Pressure (CPAP) adherence management is that stipulated by the 2013 American Thoracic Society (ATS). The capacity of the latter to predict non-adherence in long-term CPAP-treated patients has not been validated. METHODS: Patients from the prospective real-life InterfaceVent study (NCT03013283, study conducted in an adult cohort undergoing at least 3 months of CPAP) and eligible for ATS algorithm usage were analysed. The residual device Apnea-Hypopnea-Index (AHIflow) and High Large Leak (HLL) thresholds proposed in the ATS algorithm were evaluated for predicting adherence (i.e. AHIflow > 10/h, HLLs 95th > 24 L/min for ResMed® devices and ResMed® nasal mask, HLLs 95th > 36 l/min for ResMed® devices and ResMed® oronasal masks, HLLs > 1 h for Philips® devices and HHLs > 60 l/min for Fisher & Paykel® devices). Adherence was defined according to the 2013 ATS algorithm (i.e. CPAP use > 4 h/j for at least 70% of days). RESULTS: 650/1484 patients eligible for ATS algorithm usage were analysed (15.38% non-adherent, 74% male with a median (IQ25-75) age of 68 (61-77) years, a body mass index of 30.8 (27.7-34.5) kg/m2, an initial AHI of 39 (31-55) events/h, and CPAP-treatment-duration of 5.1 (2.2-7.8) years). Logistic regression analysis demonstrated no significant relationship between the ATS proposed AHIflow or HLL thresholds and non-adherence. Complementary ROC curve analysis failed to determine satisfactory AHIflow and HLL thresholds. CONCLUSION: When managing non-adherence in long-term CPAP-treated patients, our data do not validate absolute AHIflow or HLL thresholds in general. TRIAL REGISTRATION: The INTERFACE-VENT study is registered on ClinicalTrials.gov (Identifier: study ( NCT03013283 ).

Apnoea-hypopnoea indices determined via continuous positive airway pressure (AHI-CPAPflow) versus those determined by polysomnography (AHI-PSGgold): a protocol for a systematic review and meta-analysis.

INTRODUCTION: To date, continuous positive airway pressure (CPAP) remains the cornerstone of obstructive sleep apnoea treatment. CPAP data describing residual sleep-disordered breathing events (ie, the CPAP-measured apnoea-hypopnoea indices (AHI-CPAPflow)) is difficult to interpret because it is an entirely different metric than the polysomnography (PSG) measured AHI gold standard (AHI-PSGgold). Moreover, manufacturer definitions for apnoea and hypopnoea are not only different from those recommended for PSG scoring, but also different between manufacturers. In the context of CPAP initiation and widespread telemedicine at home to facilitate sleep apnoea care, there is a need for concrete evidence that AHI-CPAPflow can be used as a surrogate for AHI-PSGgold. METHODS AND ANALYSIS: No published systematic review and meta-analysis (SRMA) has compared the accuracy of AHI-CPAPflow against AHI-PSGgold and the primary objective of this study is therefore to do so using published data. The secondary objectives are to similarly evaluate other sleep disordered breathing indices and to perform subgroup analyses focusing on the inclusion/exclusion of central apnoea patients, body mass index levels, CPAP device brands, pressure titration modes, use of a predetermined and fixed pressure level or not, and the impact of a 4% PSG desaturation criteria versus 3% PSG on accuracy. The Preferred Reporting Items for SRMA protocols statement guided study design. Randomised controlled trials and observational studies of adult patients (≥18 years old) treated by a CPAP device will be included. The CPAP intervention and PSG comparator must be performed synchronously. PSGs must be scored manually and follow the American Academy of Sleep Medicine guidelines (2007 AASM criteria or more recent). To assess the risk of bias in each study, the Quality Assessment of Diagnostic Accuracy Studies 2 tool will be used. ETHICS AND DISSEMINATION: This protocol received ethics committee approval on 16 July 2020 (IRB_MTP_2020_07_2020000404) and results will be disseminated via peer-reviewed publications. PROSPERO/TRIAL REGISTRATION NUMBERS: CRD42020159914/NCT04526366; Pre-results.

Feasibility of Type 3 Polygraphy for Evaluating Leak Determinants in CPAP-Treated OSA Patients: A Step Toward Personalized Leak Management.

BACKGROUND: Unintentional leaks (ULs) are frequent adverse effects in CPAP-treated patients. We previously published a novel methodology for analyzing the determinants of UL using polysomnography. We now propose a simplified recording system using a type 3 polygraphic device (Somnolter; Nomics S.A.). RESEARCH QUESTION: (1) To describe individual UL determinants provided by the Somnolter software in automatic-CPAP-treated OSA patients; (2) To subsequently describe the clinical consensus of four physicians on how to manage each individual UL situation. STUDY DESIGN AND METHODS: Somnoler recordings performed under nasal automatic-CPAP were automatically analyzed with APIOS software. For each polygraphic recording, APIOS provided the OR and the CIs for potential determinants of UL: mouth opening, CPAP pressure, body position, and mandibular oscillation. Based on these results, each of four physicians was asked to choose one of four strategies: (1) increase or decrease therapeutic pressure; (2) change nasal mask for oro-nasal mask/chinstrap; (3) favor a nonsupine or supine position; (4) no action for individual leak management. Subsequently, a meeting was held to determine a consensus choice for each individual case. RESULTS: Seventy-eight consecutive patients underwent home-polygraphy with Somnolter. Fifty recordings were analyzed (16 females; 65 [57-75] years of age; BMI = 31.1 [27.4-35.3]). Individual diagnosis of UL was routinely feasible. The determinants of UL were heterogeneous in the population, and diagnosis of UL was not feasible in 10 patients. Based on the results from this analysis, we established consensus leak management strategies at the individual level. The average Cohen κ coefficient for the four raters was 0.58. Pressure modification was proposed in 36% of patients, no action in 24%, installation of a facial mask/chinstrap in 22%, and positional treatment in 18%. INTERPRETATION: The use of type 3 polygraphy for characterizing leak determinants in patients treated with nasal automatic-CPAP is feasible in routine practice. Leak determinants are patient specific. Interrater concordance for determining individual leak management strategies demonstrated a "fair" level of agreement. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT03381508; URL: www.clinicaltrials.gov).

Comparison of Auto- and Fixed-Continuous Positive Airway Pressure on Air Leak in Patients with Obstructive Sleep Apnea: Data from a Randomized Controlled Trial.

Auto-CPAP may cause sleep fragmentation due to variations in pressure and unintentional leaks. The aim of this study was to compare air leak between fixed-CPAP and auto-CPAP after 4 months of CPAP treatment. This study is an ancillary analysis of a randomized, double-blind, parallel, controlled trial over 4 months, comparing fixed- and auto-CPAP in newly diagnosed patients with OSA. The following data were extracted from the CPAP devices: mean and 90th percentile pressure, residual apnea-hypopnea index, mean CPAP use, and amount of leak. Within each arm, patients were also randomly allocated to use of one of the three different brands of devices. Since the leak was reported differently for each device, median leak value was determined for each brand and leaks were classified as "above the median" or "below the median". Data from 269 patients were analyzed. The univariate analysis showed that tobacco consumption, CPAP level, and oronasal masks were associated with leaks above the median value but not the type of CPAP. The multivariate analysis showed that only CPAP level and oronasal masks were associated with leaks below the median. There were no differences in the types of mask used between fixed- and auto-CPAP. There was no impact of the type of CPAP on leaks or the type of interface used. We used a method based on the median leak value to standardize comparisons across devices which report leaks with different definitions.