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DOI: 10.1055/s-0043-1776769
Performance of the NOSE Questionnaire in Mask Selection for Home CPAP Titration
Abstract
Introduction Many patients abandon CPAP treatment because they find the mask uncomfortable. Therefore, specialists may benefit from the predictive value of airway assessment tools.
Objective To identify nasal ventilation failure through the Nasal Obstruction Symptom Evaluation (NOSE) scale in patients with obstructive sleep apnea (OSA) who undergo home-based auto-adjusting CPAP titration and to determine whether there is a correlation between NOSE score and the type of mask selected.
Materials and Methods In this prospective correlational study, the NOSE scale was used in terms of mask selection and titration indicators. Patients were classified based on their NOSE score: > or < 50.
Results We included 303 patients; 226 men (74.5%), BMI: 33.2 ± 6.1 kg/m2, neck circumference (cm): 42.8 ± 3.6 and Epworth (ESS) score: 9.2 ± 5.6, mild OSA: 12 (3.9%), moderate OSA: 127 (41.9%), and severe OSA: 164 (54.1%). The mean NOSE score was 24.3 ± 22.8 and 42 patients (13.8%) had NOSE scores > 50. Indicators for both groups were: compliance (5.9 ± 1.3 vs. 5.8 ± 1.4 hours) p: 0.41, therapeutic pressure (9.1 ± 2.0 vs. 8.8 ± 1.6 cm of H2O) p: 0.23, residual AHI (2.3 ± 1.8 vs. 2.8 ± 2.6 events/hour) p: 0.25, and leaks (20.5 ± 10.6 vs. 21.3 ± 10.7 liters/minute) p: 0.64. According to adjusted multiple regression, a NOSE of > 50 was not a predictor of mask selection.
Conclusions A > 50 NOSE score was not a predictor of mask selection, and it was not correlated to titration performance.
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Introduction
Continuous positive airway pressure (CPAP) is considered the treatment of choice for moderate-severe obstructive sleep apnea (OSA). Even though CPAP is effective, long-term compliance ranges between 40% and 80% as 10-20% of patients abandon treatment after the first night.[1] [2] Discomfort -one of the determining factors of intolerance- is frequently the reason for abandonment.[3] [4] [5] [6] Though the first choice is an anatomical mask with a minimal contact design (i.e., a nasal mask or nasal pillow), patients report difficulty breathing normally through the nose during sleep. Others suffer from nasal obstruction during the day—defined as resistance or discomfort due to insufficient airflow through the nose secondary to anatomical anomalies (deviated septum, congenital bone deformity, trauma), inflammatory processes (chronic rhinitis or hypertrophic mucosa, nasal polyps), and tumors.[5] [7] [8]
Before examination of the airways, it is necessary to use practical predictive tools to identify the adequate type of interface or determine the need for specific treatment (medical, endoscopic, or surgical).[9] Specialists can assess nasal ventilatory failure through physical examination, validated questionnaires, objective studies like rhinodebitomanometry and acoustic rhinometry. These tests have proven useful to measure the extent of nasal obstruction; however, they are not routinely performed at sleep care units.[10] [11]
With the objective to identify nasal ventilatory failure symptoms, we test the NOSE scale (Nasal Obstruction Symptom Evaluation), in OSA patients undergoing home-based auto-adjusting CPAP titration and its correlation with the type of mask selected.
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Materials and Methods
Study Design
This single-center, prospective and correlational study analyzed systematically collected data from auto-adjusting CPAP titration tests performed in OSA patients who had a consultation with a sleep specialist in a community hospital between May 2019 and January 2021.
The protocol was approved by the Institutional Review Board of Buenos Aires Hospital Británico in according with Helsinki declaration (protocol n°. #932, approved on April 24, 2019).
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Population
We included patients diagnosed with obstructive sleep apnea referred for home-based CPAP titration. We excluded patients with a history of nasal surgery, obesity-hypoventilation syndrome, periodic breathing, or baseline central apnea and patients who needed other treatment modalities (i.e., two levels of continuous pressure, servo-controlled ventilation, concomitant oxygen).
The baseline apnea-hypopnea index (AHI) was obtained from polysomnography (PSG) and respiratory polygraphy (RP) recordings. Body mass index (BMI) and neck circumference were obtained before CPAP devices were delivered.
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Auto-adjusting CPAP therapy - Compliance and efficacy
Devices were calibrated between 4 and 15 cm of H2O without humidifier. Data were obtained by downloading the memory card (SD cards) of CPAP devices using Encore pro® II Philips-Respironics® and ResScan®- ResMed® software or ResMed® Air View® online platform for remote monitoring (a routine procedure to monitor treatment).
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Mask Selection
Mask type, size, and model were selected using our Sleep and Ventilation Unit̀s standard procedure, after a demonstration of interface use[12] [13]; a minimum of 3 different interfaces were tested. Then, the “mask fit” function was used to evaluate unintentional leaks. Final selection was based on patient's preference/tolerance and leak testing results. Full face masks were only used by patients who could not tolerate nasal masks. All patients received basic training on CPAP use and mask fitting.
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The NOSE Scale
Patients completed a Spanish[14] validated version of NOSE scale (see attached NOSE questionnaire), which includes 5 items on nasal symptoms perceived by the patient during the last month. Each question was answered using a 5-point Likert scale. The responses to all 5 questions were added and then multiplied by 5 to obtain a total score ranging between 0-100, where the highest value corresponds to the most severe symptoms of nasal obstruction. Patients were divided into 2 groups based on their NOSE score: > or < 50 points. The clinical specialists in charge of mask selection were blinded to the patients̀ NOSE score.
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Correlation Indicators
Data from auto-adjusting CPAP readings were compared to the type of interface selected (compliance in hours/nights, working pressure, mean airway pressure, mean leak and residual AHI) and NOSE scores. Effective pressure data were obtained after a visual analysis of each night's pressure/time curve and leak periods >30 liters/minute[7] were excluded (equipment compensation limit). The effective therapeutic pressure was selected based on nights with more intensive use, fewer leaks, and residual AHI < 5 events/hour.[7]
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Statistical Analysis
Results are expressed as percentages for categorical variables and as mean or standard deviation (±) for numerical variables. Differences were compared using Fisher's exact test, Mann Whitney, or χ2. Finally, a logistic multiple regression analysis was performed considering NOSE score > 50 = 1 as an independent variable (this threshold was selected based on pilot study data),[8] baseline AHI (events/hour), obesity = 1 (BMI > 30 kg/m2), age (years) for the 3 categories of masks used (nasal, full face, and nasal pillow).
Statistical analysis was conducted using Graph Pad Prism-5™ software.
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Results
We included 303 patients who visited the Sleep Unit at our hospital over the course of 20 months, 226 men (74.5%), BMI: 33.2 ± 6.1 kg/m2, neck circumference (cm): 42.8 ± 3.6, Epworth's (ESS) score: 9.2 ± 5.6. 9.2 ± 5.6).
OSA diagnosis was based on respiratory polygraphy in 230 cases (75.9%). Results were: 12 (3.9%) mild, 127 (41.9%) moderate and 164 (54.1%) severe OSA. The mean NOSE score was 24.3 ± 22.8. Forty-two patients (13.8%) had > 50 NOSE scores. [Table 1] shows population characteristics and the results of CPAP titration.
BMI: body mass index. OSA: Obstructive sleep apnea. CPAP: Continuous Positive Airway Pressure.
* Percentage and number of patients. Values expressed as mean and standard deviation (± ).
There were differences between those with NOSE scores > or < 50 in terms of age (54.3 ± 10.0 vs. 59.4 ± 11.9 years, p: 0.008) and ESS (11.4 ± 6.7 vs. 8.8 ± 5.4 points, p: 0.014). [Table 2].
Mask type selection was not correlated to > or < 50 NOSE (p > 0.5) as shown in [Figure 1].
![](https://www.thieme-connect.de/media/10.1055-s-00056804/202304/thumbnails/10-1055-s-0043-1776769-i861-1.jpg)
![Zoom Image](/products/assets/desktop/css/img/icon-figure-zoom.png)
No differences were observed between groups in terms of compliance and efficacy indicators during titration with home-based auto-adjusting CPAP: compliance (5.9 ± 1.3 vs. 5.8 ± 1.4 hours) p: 0.41 ([Figure 2A]), therapeutic pressure (9.1 ± 2.0 vs. 8.8 ± 1.6 cm of H2O) p: 0.23 ([Figure 2B]), residual AHI (2.3 ± 1.8 vs. 2.8 ± 2.6 events/hour) p: 0.25 ([figure 2C]), no leaks (20.5 ± 10.6 vs. 21.3 ± 10.7 liters/minute) p: 0.64. [Figure 2D] and [Table 3].
![](https://www.thieme-connect.de/media/10.1055-s-00056804/202304/thumbnails/10-1055-s-0043-1776769-i861-2.jpg)
![Zoom Image](/products/assets/desktop/css/img/icon-figure-zoom.png)
In an adjusted multiple regression model, a > 50 NOSE score was not a predictor of mask selection. [Table 4].
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Discussion
NOSE scores suggestive of symptomatic nasal obstruction (> 50) were not associated with the type of mask selected for home-based CPAP titration. In our experience, the selection of full-face masks and a high NOSE score were infrequent.
Sleep care centers may incorporate systematized questionnaires like NOSE to identify nasal ventilatory failure, select the type of mask and estimate the extent to which symptoms may affect tolerance to CPAP.[8] [10] [11] In a similarly designed study conducted on 198 patients, Lebret et al. used NOSE at the beginning of CPAP treatment. After 4 months, they reported that a > 50 NOSE score was independently associated to full face masks[8] (sensitivity; 34.8%; specificity; 87.5%). In our study, however, the use of full-face masks was low (6% vs. 11%.) with a higher proportion (12.8%) in the > 50 NOSE group, which corresponded to titration tests of a few nights. These differences may influence the performance of the questionnaire. Other variables like the prevalence of obesity, OSA severity, and CPAP implementation may impact symptom perception and influence mask selection.
Notably, in our study, patients with a high NOSE completed a successful, multiple-night CPAP test, with no differences in leak rates or residual AHI. Moreover, we found no differences in therapeutic pressures, which means that nasal ventilatory failure is neither directly correlated to airway resistance nor determines patient's comfort during CPAP.[9]
A common mistake made during demonstrations of mask use is to choose full face masks for patients who report mouth breathing. Evidence suggests that full face masks are associated with higher-pressure demands, leaks, intolerance, less comfort, and poorer compliance.[9] The fact that our protocol prioritizes nasal masks[12] [13] may have affected the results of our study. To the best of our knowledge, there is no NOSE score capable of predicting interface selection during CPAP titration. We chose > or < 50 because this value is interpreted as significant nasal obstruction, as suggested by other authors.[8] In addition to nasal symptoms, a history of otorhinolaryngological surgery and smoking may be factors to consider in the decision-making process.
An important limitation to this study is that comorbidities, anatomical abnormalities and associated treatments (including previews surgery or procedures in upper airway) were not completely documented; another is that the small number of observations limited the predictive analysis to a few variables. On the other hand, our study has 2 strengths: first, a significant number of patients who started on CPAP had symptoms suggestive of nasal respiratory failure and tolerated masks with adequate compliance and efficacy. Secondly, NOSE is not a predictor of interface selection during titration.
Larger studies with more patients and multiple clinical prediction variables are needed to identify—through the use of questionnaires—those who need a multidimensional approach to facilitate CPAP therapy through a healthy nose.
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Conclusion
A > 50 NOSE score was not a predictor of mask selection in CPAP titration, and it was not correlated to titration test performance.
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Conflict of Interest
None declared.
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References
- 1 Sullivan CE, Issa FG, Berthon-Jones M, Eves L. Reversal of obstructive sleep apnoea by continuous positive airway pressure applied through the nares. Lancet 1981; 1 (8225): 862-865
- 2 Gay P, Weaver T, Loube D, Iber C. Positive Airway Pressure Task Force, Standards of Practice Committee, American Academy of Sleep Medicine. Evaluation of positive airway pressure treatment for sleep related breathing disorders in adults. Sleep 2006; 29 (03) 381-401
- 3 Weaver TE, Grunstein RR. Adherence to continuous positive airway pressure therapy: the challenge to effective treatment. Proc Am Thorac Soc 2008; 5 (02) 173-178
- 4 Weaver TE, Sawyer AM. Adherence to continuous positive airway pressure treatment for obstructive sleep apnoea: implications for future interventions. Indian J Med Res 2010; 131: 245-258
- 5 Shapiro GK, Shapiro CM. Factors that influence CPAP adherence: an overview. Sleep Breath 2010; 14 (04) 323-335
- 6 Kohler M, Smith D, Tippett V, Stradling JR. Predictors of long-term compliance with continuous positive airway pressure. Thorax 2010; 65 (09) 829-832
- 7 Blanco M, Ernst G, Salvado A, Borsini E. Impact of Mask Type on the Effectiveness of and Adherence to Unattended Home-Based CPAP Titration. Sleep Disord 2019; 2019: 4592462
- 8 Lebret M, Arnol N, Martinot JB. et al. Nasal Obstruction Symptom Evaluation Score to Guide Mask Selection in CPAP-Treated Obstructive Sleep Apnea. Otolaryngol Head Neck Surg 2018; 159 (03) 590-592
- 9 Borel JC, Tamisier R, Dias-Domingos S. et al; Scientific Council of The Sleep Registry of the French Federation of Pneumology (OSFP). Type of mask may impact on continuous positive airway pressure adherence in apneic patients. PLoS One 2013; 8 (05) e64382
- 10 Inoue A, Chiba S, Matsuura K, Osafune H, Capasso R, Wada K. Nasal function and CPAP compliance. Auris Nasus Larynx 2019; 46 (04) 548-558
- 11 Yepes-Nuñez JJ, Bartra J, Muñoz-Cano R. et al. Assessment of nasal obstruction: correlation between subjective and objective techniques. Allergol Immunopathol (Madr) 2013; 41 (06) 397-401
- 12 Blanco M, Schonfeld S. Eduardo Borsini Proceso de selección de máscaras para el tratamiento con CPAP. Revista Fronteras en Medicina 2019; (01) 0029-0035
- 13 Blanco M, Schonfeld S, Borsini E. Selección de máscaras para el tratamiento con CPAP en el síndrome de apneas obstructivas del sueño. Rem Am Med Resp 2020; 1: 1-8
- 14 Larrosa F, Roura J, Dura MJ, Guirao M, Alberti A, Alobid I. Adaptation and validation of the Spanish version of the Nasal Obstruction Symptom Evaluation (NOSE) Scale. Rhinology 2015; 53 (02) 176-180
Address for correspondence
Publikationsverlauf
Eingereicht: 03. Januar 2022
Angenommen: 31. Januar 2023
Artikel online veröffentlicht:
22. November 2023
© 2023. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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References
- 1 Sullivan CE, Issa FG, Berthon-Jones M, Eves L. Reversal of obstructive sleep apnoea by continuous positive airway pressure applied through the nares. Lancet 1981; 1 (8225): 862-865
- 2 Gay P, Weaver T, Loube D, Iber C. Positive Airway Pressure Task Force, Standards of Practice Committee, American Academy of Sleep Medicine. Evaluation of positive airway pressure treatment for sleep related breathing disorders in adults. Sleep 2006; 29 (03) 381-401
- 3 Weaver TE, Grunstein RR. Adherence to continuous positive airway pressure therapy: the challenge to effective treatment. Proc Am Thorac Soc 2008; 5 (02) 173-178
- 4 Weaver TE, Sawyer AM. Adherence to continuous positive airway pressure treatment for obstructive sleep apnoea: implications for future interventions. Indian J Med Res 2010; 131: 245-258
- 5 Shapiro GK, Shapiro CM. Factors that influence CPAP adherence: an overview. Sleep Breath 2010; 14 (04) 323-335
- 6 Kohler M, Smith D, Tippett V, Stradling JR. Predictors of long-term compliance with continuous positive airway pressure. Thorax 2010; 65 (09) 829-832
- 7 Blanco M, Ernst G, Salvado A, Borsini E. Impact of Mask Type on the Effectiveness of and Adherence to Unattended Home-Based CPAP Titration. Sleep Disord 2019; 2019: 4592462
- 8 Lebret M, Arnol N, Martinot JB. et al. Nasal Obstruction Symptom Evaluation Score to Guide Mask Selection in CPAP-Treated Obstructive Sleep Apnea. Otolaryngol Head Neck Surg 2018; 159 (03) 590-592
- 9 Borel JC, Tamisier R, Dias-Domingos S. et al; Scientific Council of The Sleep Registry of the French Federation of Pneumology (OSFP). Type of mask may impact on continuous positive airway pressure adherence in apneic patients. PLoS One 2013; 8 (05) e64382
- 10 Inoue A, Chiba S, Matsuura K, Osafune H, Capasso R, Wada K. Nasal function and CPAP compliance. Auris Nasus Larynx 2019; 46 (04) 548-558
- 11 Yepes-Nuñez JJ, Bartra J, Muñoz-Cano R. et al. Assessment of nasal obstruction: correlation between subjective and objective techniques. Allergol Immunopathol (Madr) 2013; 41 (06) 397-401
- 12 Blanco M, Schonfeld S. Eduardo Borsini Proceso de selección de máscaras para el tratamiento con CPAP. Revista Fronteras en Medicina 2019; (01) 0029-0035
- 13 Blanco M, Schonfeld S, Borsini E. Selección de máscaras para el tratamiento con CPAP en el síndrome de apneas obstructivas del sueño. Rem Am Med Resp 2020; 1: 1-8
- 14 Larrosa F, Roura J, Dura MJ, Guirao M, Alberti A, Alobid I. Adaptation and validation of the Spanish version of the Nasal Obstruction Symptom Evaluation (NOSE) Scale. Rhinology 2015; 53 (02) 176-180
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