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14.03.2023 | Sleep Breathing Physiology and Disorders • Original Article

Use of historical remote monitoring data to determine predictors of CPAP non-compliance in patients with OSA

verfasst von: Jake Cowen, Stephanie Harrison, Lydia Thom, Matt Thomas, Joanna Sedano, Phil Stephens, Gregory Y. H. Lip, Sonya Craig

Erschienen in: Sleep and Breathing | Ausgabe 5/2023

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Abstract

Purpose

Continuous positive airway pressure (CPAP) is the gold standard treatment for obstructive sleep apnoea. This study aimed to use complete usage data collected remotely from modern CPAP devices to identify compliance trends and clinical predictors of CPAP usage.

Methods

Group usage data were analysed for a large cohort at a single tertiary sleep-centre before a detailed review of a 90-day reporting window for each patient was conducted. Individual data were collected for a smaller cohort of patients including demographics, past medical history and diagnostic sleep study results. A zero-inflated negative binomial regression model was used to determine associations between patient characteristics and usage days.

Results

Of 6450 patients who were prescribed CPAP and included in the initial service analysis, 476 patients were included in the sub-group. Complete usage data revealed that 46% of patients were fully compliant with CPAP therapy. Compliance fell from 55 to 46% by day 90 and remained at this rate going forward. Significant predictors of CPAP non-compliance included being in the lowest quartile of Index of Multiple Deprivation scores (most deprived) compared with the highest quartile (least deprived) (p = .005), and less severe oxygen desaturation index (ODI) on diagnosis (p = .03).

Conclusions

Complete usage data show that compliance at day 90 appears to be a good indicator of future CPAP usage. Predictors of CPAP non-compliance may include lower socioeconomic status, and lower ODI.

Marin-Oto M, Vicente E, Marin J (2019) Long term management of obstructive sleep apnea and its comorbidities. Multidiscip Respir Med 14:21. https://doi.org/10.1186/s40248-019-0186-3

Dunietz G, Chervin R, Burke J et al (2021) Obstructive sleep apnea treatment and dementia risk in older adults. Sleep 44(9):zsab076. https://doi.org/10.1093/sleep/zsab076

Jean-Louis G, Zizi F, Clark L et al (2008) Obstructive sleep apnea and cardiovascular disease: role of the metabolic syndrome and its components. J Clin Sleep Med 4(3):261–272CrossRefPubMedPubMedCentral

McNicholas W, Bonsignore M (2007) Sleep apnoea as an independent risk factor for cardiovascular disease: current evidence, basic mechanisms and research priorities. Eur Respir J 29:156–178. https://doi.org/10.1183/09031936.00027406CrossRefPubMed

Steier J, Martin A, Harris J et al (2014) Predictive relative prevalence estimates for obstructive sleep apnoea and the associated healthcare provisions across the UK. Thorax 69(4):390–392. https://doi.org/10.1136/thoraxjnl-2013-203887CrossRefPubMed

Garvey J, Pengo M, Drakatos P et al (2015) Epidemiological aspects of obstructive sleep apnoea. J Thorac Dis 7(5):920–929. https://doi.org/10.3978/j.issn.2072-1439/2015.04.52CrossRefPubMedPubMedCentral

Epstein L, Kristo D, Strollo P et al (2009) Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnoea in adults. J Clin Sleep Med 5(3):263–276CrossRefPubMed

Nice CKS (2015) Management of sleep apnoea. [Online]. Available from: https://cks.nice.org.uk/topics/obstructive-sleep-apnoeasyndrome/management/management/. Accessed Nov 2022

West SD, Jones DR, Stradling JR (2006) Comparison of three ways to determine and deliver pressure during nasal CPAP therapy for obstructive sleep apnoea. Thorax 61(3):226–231CrossRefPubMed

10.

Turino C, de Batlle J, Woehrle H, et al. (2017) Management of continuous positive airway pressure treatment compliance using telemonitoring in obstructive sleep apnoea. Eur Respir J 49(2):1601128. https://doi.org/10.1183/13993003.01128-2016

11.

Franklin K, Lindberg E (2015) Obstructive sleep apnoea is a common disorder in the population – a review on the epidemiology of sleep apnoea. J Thorac Dis 7(8):1311–1322. https://doi.org/10.3978/j.issn.2072-1439.2015.06.11CrossRefPubMedPubMedCentral

12.

Turino C, de Batlle J, Woehrle H et al (2017) Management of continuous positive airway pressure treatment compliance using telemonitoring in obstructive sleep apnoea. Eur Respir J 49(2):1601128. https://doi.org/10.1183/13993003/01128-2016

13.

Munafo D, Hevener W, Crocker M et al (2016) A telehealth program for CPAP adherence reduces labor and yields similar adherence and efficacy when compared to standard of care. Sleep Breath 20:777–785. https://doi.org/10.1007/s11325-015-1298-4CrossRefPubMedPubMedCentral

14.

Fox N, Hirsch-Allen AJ, Goodfellow E et al (2012) The impact of a telemedicine monitoring system on positive airway pressure adherence in patients with obstructive sleep apnea: a randomised controlled trial. Sleep 35:477–481. https://doi.org/10.5665/sleep.1728CrossRefPubMedPubMedCentral

15.

Hwang D, Chang JW, Benjafield AV et al (2018) Effect of telemedicine education and telemonitoring on continous positive airway pressure adherence. Am J Respir Crit Care Med 197:117–126CrossRefPubMed

16.

Shaughnessy G, Morgenthaler T (2019) The effect of patient-facing applications on positive airway pressure therapy adherence: a systematic-review. J Clin Sleep Med 15(5):769–777CrossRefPubMedPubMedCentral

17.

Cistulli P, Armitstead J, Pepin JL et al (2019) Short-term CPAP adherence in obstructive sleep apnea: a big data analysis using real world data. Sleep Med 59:114–116CrossRefPubMedPubMedCentral

18.

Frasnelli M, Baty F, Niedermann J et al (2016) Effect of telemetric monitoring in the first 30 days of continuous positive airway pressure adaptation for obstructive sleep apnoea syndrome – a controlled pilot study. J Telemed Telecare 22(4):209–214CrossRefPubMed

19.

Sawyer AM, Gooneratne N, Marcus CL et al (2011) A systematic review of CPAP adherence across age groups: clinical and empiric insights for developing CPAP adherence interventions. Sleep Med Rev 15(6):343–356CrossRefPubMedPubMedCentral

20.

Bertrand M, Bastien CH, Boutin I et al (2022) A psychological view on the effectiveness of psychological interventions on positive airway pressure treatment adherence and sleep quality in patients with obstructive sleep apnea. 91:62–74. https://doi.org/10.1016/j.sleep.2021.11.016

21.

Chai-Coetzer CL, Yuan-Ming L, Antic N et al (2013) Predictors of long-term adherence to continuous positive airway pressure therapy in patients with obstructive sleep apnea and cardiovascular disease in the SAVE study. Sleep 26(12):1929–1937. https://doi.org/10.5665/sleep.3232CrossRef

22.

McArdle N, Devereux G, Heidarnejad H et al (1999) Long-term use of CPAP therapy for sleep apnea/hypopnea syndrome. Am J Respir Crit Care Med 159(4pt1):1108–14. https://doi.org/10.1164/ajrccm.159.4.9807111CrossRefPubMed

23.

Krieger J, Kurtz D, Petiau C et al (1996) Long-term compliance with CPAP therapy in obstructive sleep apnea patients and in snorers. Sleep 19(9 Suppl):S136–S143. https://doi.org/10.1093/sleep/19.sippl_9.s136CrossRefPubMed

24.

Edinger JD, Carwile S, Miller P et al (1994) Psychological status, syndromatic measures, and compliance with nasal CPAP therapy for sleep apnoea. Percept Mot Skills 78:1116–1118. https://doi.org/10.2466/pms.1994.78.3c.1116CrossRefPubMed

25.

Sopkova Z, Dorkova Z, Tkacova R (2009) Predictors of compliance with continuous positive airway pressure treatment in patients with obstructive sleep apnea and metabolic syndrome. Wien Klin Wochenschr 121(11–12):398–404. https://doi.org/10.1007/s00508-009-1181-zCrossRefPubMed

26.

Jacobsen A, Eriksen F, Hansen R et al (2017) Determinants for adherence to continuous positive airway pressure therapy in obstructive sleep apnea. PLoS One 12(12):e0189614. https://doi.org/10.1371/journal.pone.0189614CrossRefPubMedPubMedCentral

27.

Kohler M, Smith D, Tippett V et al (2010) Predictors of long-term compliance with continuous positive airway pressure. Thorax 65(9):829–832CrossRefPubMed

28.

Patel S, Kon S, Nolan C et al (2018) The Epworth Sleepiness Scale: minimum clinically important difference in obstructive sleep apnoea. Am J Respir Crit Care Med 197(7):961–963CrossRefPubMedPubMedCentral

29.

Pepin JL, Viot-Blanc V, Escourrou P et al (2009) Prevalence of excessive residual sleepiness in CPAP treated sleep-apnoea patients: the French multi-centre study. Eur Respir J 33(5):1062–1067CrossRefPubMed

30.

Bakker J, O’Keeffe K, Neill A et al (2011) Ethnic disparities in CPAP adherence in New Zealand: effects of socioeconomic status, health literacy and self-efficacy. Sleep 34(11):1595–1603CrossRefPubMedPubMedCentral

31.

Platt A, Field S, Asch D et al (2009) Neighborhood of residence is associated with daily adherence to CPAP therapy. Sleep 32(6):799–806CrossRefPubMedPubMedCentral

32.

NHS England (2021) CORE20PLUS5 – an approach to reducing health inequalities. [Online]. Available from: https://www.england.nhs.uk/about/equality/equalityhub/core20plus5/. Accessed Nov 2022

Titel: Use of historical remote monitoring data to determine predictors of CPAP non-compliance in patients with OSA
verfasst von: Jake Cowen
Stephanie Harrison
Lydia Thom
Matt Thomas
Joanna Sedano
Phil Stephens
Gregory Y. H. Lip
Sonya Craig
Publikationsdatum: 14.03.2023
Verlag: Springer International Publishing
Erschienen in: Sleep and Breathing / Ausgabe 5/2023
Print ISSN: 1520-9512
Elektronische ISSN: 1522-1709
DOI: https://doi.org/10.1007/s11325-023-02806-3

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Use of historical remote monitoring data to determine predictors of CPAP non-compliance in patients with OSA