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

Marie-Caroline Rotty, Carey M Suehs, Jean-Pierre Mallet, Christian Martinez, Jean-Christian Borel, Claudio Rabec, Fanny Bertelli, Arnaud Bourdin, Nicolas Molinari, Dany Jaffuel, Marie-Caroline Rotty, Carey M Suehs, Jean-Pierre Mallet, Christian Martinez, Jean-Christian Borel, Claudio Rabec, Fanny Bertelli, Arnaud Bourdin, Nicolas Molinari, Dany Jaffuel

Abstract

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).

Keywords: Leaks; Side-effects; Sleep apnea; Telemedicine.

Conflict of interest statement

Dr Carey Suehs reports one grant from AstraZeneca, outside the submitted work.

Dr. Jean Christian Borel reports grants from Philips, during the conduct of the study; grants and personal fees from Philips, salaries from AGIR à dom, personal fees and other from RESMED, other from NOMICS, outside the submitted work.

Dr Claudio Rabec has performed lecturing at sponsored meetings and/or participated in boards for the following companies in the last 5 years: Resmed, Philips, Lowenstein, Air Liquide Medical Systems.

Pr. Arnaud Bourdin reports grants, personal fees, non-financial support and other from AstraZeneca, grants, personal fees, non-financial support and other from Boeringher Ingelheim, grants, personal fees, non-financial support and other from GlaxoSmithKline, personal fees, non-financial support and other from Novartis, personal fees and non-financial support from Teva, personal fees, non-financial support and other from Regeneron, personal fees, non-financial support and other from Chiesi Farmaceuticals, grants, personal fees, non-financial support and other from Actelion, personal fees from Gilead, non-financial support and other from Roche, other from Nuvaira, from null, outside the submitted work.

Dr Dany Jaffuel has performed lecturing at sponsored meetings for the following companies in the last 5 years: Apard, Bastide, Loewenstein Medical, Philips, SEFAM. He has sat on advisory boards for the following companies in the last 5 years: Lowenstein Medical, SEFAM. He has received sponsorship support to attend academic meetings in the last 5 years from Lowenstein Medical, Resmed, Philips and SEFAM.

MCR, JPM, CM, FB, NM, report no conflicts of interest in relation to the present work.

Figures

Fig. 1
Fig. 1
Study flow chart. CPAP: Continuous Positive Airway Pressure. *Multiple masks or mask-types not included (multiple mask-types for 66 patients, Liberty® mask for two patients, Oracle® oral mask for 3 patients)
Fig. 2
Fig. 2
Relationship between patient-reported leaks and device-reported leaks: individual data and linear regression
Fig. 3
Fig. 3
Principal Component Analysis (PCA) of the mask related side-effects for a nasal, b oronasal, c nasal pillows masks. Note that PCA is a procedure that transforms possibly correlated variables into a smaller number of uncorrelated variables called principal components. In this process, linear relationships among variables are found (components), with each component being uncorrelated with the others (orthogonal) in directions defined by an eigenvector. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible (with the restriction of being orthogonal to/independent of the preceding component). Within this framework, the reader should understand that two arrows pointing in the same direction and close to each other are positively correlated, two arrows pointing in opposite directions are negatively correlated, and arrows at right angles are independent. Here, the three plots present a similar explained total variance for PC1 of 31.90% to 32.36%, PC2 of only 11.7% to 12.4% and only minor differences in positioning of the vectors for each MRSE on the 3 plots. In consequence, PCA analyses suggest few differences for MRSE associations between mask types. Independently of the mask-type, two groups of eigenvectors can be described. The first group is composed of red eyes, itchy eyes, dry nose, runny nose, stuffed nose and dry mouth eigenvectors (PCA group-1). The second group is composed of mask pain, harness pain, mask injury, harness injury, heavy mask, patient reported leaks, partner disturbing leaks and noisy mask eigenvectors (PCA group-2). These two groups are independent between them whereas their constitutive MRSE variables are associated. For nasal pillow masks, the group-2 composition is similar but with an increased association between constitutive MRSE variables
Fig. 4
Fig. 4
Visual Analogue Scales for mask related side-effect scores (0–10 score) according to mask type

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Source: PubMed

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