Management and Treatment of Patients With Obstructive Sleep Apnea Using an Intelligent Monitoring System Based on Machine Learning Aiming to Improve Continuous Positive Airway Pressure Treatment Compliance: Randomized Controlled Trial

Cecilia Turino, Ivan D Benítez, Xavier Rafael-Palou, Ana Mayoral, Alejandro Lopera, Lydia Pascual, Rafaela Vaca, Anunciación Cortijo, Anna Moncusí-Moix, Mireia Dalmases, Eloisa Vargiu, Jordi Blanco, Ferran Barbé, Jordi de Batlle, Cecilia Turino, Ivan D Benítez, Xavier Rafael-Palou, Ana Mayoral, Alejandro Lopera, Lydia Pascual, Rafaela Vaca, Anunciación Cortijo, Anna Moncusí-Moix, Mireia Dalmases, Eloisa Vargiu, Jordi Blanco, Ferran Barbé, Jordi de Batlle

Abstract

Background: Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnea (OSA), but treatment compliance is often unsatisfactory.

Objective: The aim of this study was to assess the effectiveness and cost-effectiveness of an intelligent monitoring system for improving CPAP compliance.

Methods: This is a prospective, open label, parallel, randomized controlled trial including 60 newly diagnosed patients with OSA requiring CPAP (Apnea-Hypopnea Index [AHI] >15) from Lleida, Spain. Participants were randomized (1:1) to standard management or the MiSAOS intelligent monitoring system, involving (1) early compliance detection, thus providing measures of patient's CPAP compliance from the very first days of usage; (2) machine learning-based prediction of midterm future CPAP compliance; and (3) rule-based recommendations for the patient (app) and care team. Clinical and anthropometric variables, daytime sleepiness, and quality of life were recorded at baseline and after 6 months, together with patient's compliance, satisfaction, and health care costs.

Results: Randomized patients had a mean age of 57 (SD 11) years, mean AHI of 50 (SD 27), and 13% (8/60) were women. Patients in the intervention arm had a mean (95% CI) of 1.14 (0.04-2.23) hours/day higher adjusted CPAP compliance than controls (P=.047). Patients' satisfaction was excellent in both arms, and up to 88% (15/17) of intervention patients reported willingness to keep using the MiSAOS app in the future. No significant differences were found in costs (control: mean €90.2 (SD 53.14) (US $105.76 [SD 62.31]); intervention: mean €96.2 (SD 62.13) (US $112.70 [SD 72.85]); P=.70; €1=US $1.17 was considered throughout). Overall costs combined with results on compliance demonstrated cost-effectiveness in a bootstrap-based simulation analysis.

Conclusions: A machine learning-based intelligent monitoring system increased daily compliance, reported excellent patient satisfaction similar to that reported in usual care, and did not incur in a substantial increase in costs, thus proving cost-effectiveness. This study supports the implementation of intelligent eHealth frameworks for the management of patients with CPAP-treated OSA and confirms the value of patients' empowerment in the management of chronic diseases.

Trial registration: ClinicalTrials.gov NCT03116958; https://ichgcp.net/clinical-trials-registry/NCT03116958.

Keywords: continuous positive airway pressure; machine learning; obstructive sleep apnea; patient compliance; remote monitoring.

Conflict of interest statement

Conflicts of Interest: None declared.

©Cecilia Turino, Ivan D Benítez, Xavier Rafael-Palou, Ana Mayoral, Alejandro Lopera, Lydia Pascual, Rafaela Vaca, Anunciación Cortijo, Anna Moncusí-Moix, Mireia Dalmases, Eloisa Vargiu, Jordi Blanco, Ferran Barbé, Jordi de Batlle. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.10.2021.

Figures

Figure 1
Figure 1
Study flowchart. CPAP: continuous positive airway pressure, ITT: intention-to-treat
Figure 2
Figure 2
Cost-effectiveness analysis based on treatment compliance (CPAP hours/day) and total costs for each arm, performed using a bootstrap probabilistic sensitivity analysis. CPAP: continuous positive airway pressure.

References

    1. Senaratna CV, Perret JL, Lodge CJ, Lowe AJ, Campbell BE, Matheson MC, Hamilton GS, Dharmage SC. Prevalence of obstructive sleep apnea in the general population: A systematic review. Sleep Medicine Reviews. 2017 Aug;34:70–81. doi: 10.1016/j.smrv.2016.07.002.S1087-0792(16)30064-8
    1. Sánchez-de-la-Torre M, Campos-Rodriguez F, Barbé F. Obstructive sleep apnoea and cardiovascular disease. The Lancet Respiratory Medicine. 2013 Mar;1(1):61–72. doi: 10.1016/s2213-2600(12)70051-6.
    1. Iftikhar IH, Bittencourt L, Youngstedt SD, Ayas N, Cistulli P, Schwab R, Durkin MW, Magalang UJ. Comparative efficacy of CPAP, MADs, exercise-training, and dietary weight loss for sleep apnea: a network meta-analysis. Sleep Med. 2017 Feb;30:7–14. doi: 10.1016/j.sleep.2016.06.001.S1389-9457(16)30045-4
    1. Martínez-García Miguel-Angel, Capote F, Campos-Rodríguez Francisco, Lloberes P, Díaz de Atauri María Josefa, Somoza M, Masa JF, González Mónica, Sacristán Lirios, Barbé Ferrán, Durán-Cantolla Joaquín, Aizpuru F, Mañas Eva, Barreiro B, Mosteiro M, Cebrián Juan J, de la Peña Mónica, García-Río Francisco, Maimó Andrés, Zapater J, Hernández Concepción, Grau SanMarti N, Montserrat JM, Spanish Sleep Network Effect of CPAP on blood pressure in patients with obstructive sleep apnea and resistant hypertension: the HIPARCO randomized clinical trial. JAMA. 2013 Dec 11;310(22):2407–15. doi: 10.1001/jama.2013.281250.1788459
    1. Barbé Ferran, Durán-Cantolla Joaquín, Sánchez-de-la-Torre Manuel, Martínez-Alonso Montserrat, Carmona C, Barceló Antonia, Chiner E, Masa JF, Gonzalez M, Marín Jose M, Garcia-Rio F, Diaz de Atauri J, Terán Joaquín, Mayos M, de la Peña Mónica, Monasterio C, del Campo F, Montserrat JM, Spanish Sleep And Breathing Network Effect of continuous positive airway pressure on the incidence of hypertension and cardiovascular events in nonsleepy patients with obstructive sleep apnea: a randomized controlled trial. JAMA. 2012 May 23;307(20):2161–8. doi: 10.1001/jama.2012.4366.1167316
    1. Sawyer AM, Gooneratne NS, Marcus CL, Ofer D, Richards KC, Weaver TE. A systematic review of CPAP adherence across age groups: clinical and empiric insights for developing CPAP adherence interventions. Sleep Med Rev. 2011 Dec;15(6):343–56. doi: 10.1016/j.smrv.2011.01.003. S1087-0792(11)00005-0
    1. Hussain SF, Irfan M, Waheed Z, Alam N, Mansoor S, Islam M. Compliance with continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea among privately paying patients- a cross sectional study. BMC Pulm Med. 2014 Nov 29;14(1):188. doi: 10.1186/1471-2466-14-188. 1471-2466-14-188
    1. Campos-Rodriguez F, Martinez-Alonso M, Sanchez-de-la-Torre M, Barbe F. Long-term adherence to continuous positive airway pressure therapy in non-sleepy sleep apnea patients. Sleep Medicine. 2016 Jan;17:1–6. doi: 10.1016/j.sleep.2015.07.038.
    1. Rolfe I, Olson LG, Saunders NA. Long-term acceptance of continuous positive airway pressure in obstructive sleep apnea. Am Rev Respir Dis. 1991 Nov;144(5):1130–3. doi: 10.1164/ajrccm/144.5.1130.
    1. McArdle N, Devereux G, Heidarnejad H, Engleman H M, Mackay T W, Douglas N J. Long-term use of CPAP therapy for sleep apnea/hypopnea syndrome. Am J Respir Crit Care Med. 1999 Apr;159(4 Pt 1):1108–14. doi: 10.1164/ajrccm.159.4.9807111.
    1. Wozniak D, Lasserson T, Smith I. Educational, supportive and behavioural interventions to improve usage of continuous positive airway pressure machines in adults with obstructive sleep apnoea. Cochrane Database Syst Rev. 2014 Jan 08;(1):CD007736. doi: 10.1002/14651858.CD007736.pub2.
    1. Bruyneel M. Telemedicine in the diagnosis and treatment of sleep apnoea. Eur Respir Rev. 2019 Mar 31;28(151):180093. doi: 10.1183/16000617.0093-2018. 28/151/180093
    1. Pépin Jean L, Tamisier R, Hwang D, Mereddy S, Parthasarathy S. Does remote monitoring change OSA management and CPAP adherence? Respirology. 2017 Nov 12;22(8):1508–1517. doi: 10.1111/resp.13183.
    1. Aardoom JJ, Loheide-Niesmann L, Ossebaard HC, Riper H. Effectiveness of eHealth Interventions in Improving Treatment Adherence for Adults With Obstructive Sleep Apnea: Meta-Analytic Review. J Med Internet Res. 2020 Feb 18;22(2):e16972. doi: 10.2196/16972. v22i2e16972
    1. Rafael-Palou X, Vargiu E, Turino C, Steblin A, Sánchez-de-la-Torre M, Barbe F. Towards an Intelligent Monitoring System for Patients with Obstrusive Sleep Apnea. ICST Transactions on Ambient Systems. 2017 Dec 19;4(16):153481. doi: 10.4108/eai.19-12-2017.153481.
    1. Lloberes P, Durán-Cantolla J, Martínez-García. Marín JM, Ferrer A, Corral J, Masa JF, Parra O, Alonso-Álvarez ML, Terán-Santos J. Diagnosis and treatment of sleep apnea-hypopnea syndrome. Archivos de Bronconeumología ((English Edition)) 2011 Jan;47(3):143–156. doi: 10.1016/s1579-2129(11)70034-9.
    1. MiSAOS. [2021-09-19]. .
    1. Rafael-Palou X, Turino C, Steblin A, Sánchez-de-la-Torre Manuel, Barbé Ferran, Vargiu E. Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy. BMC Med Inform Decis Mak. 2018 Sep 18;18(1):81. doi: 10.1186/s12911-018-0657-z. 10.1186/s12911-018-0657-z
    1. CVE-DOGC-A-13051031-2013: Resolution SLT/353/2013, of February 13, on the review of public prices for the services provided by the Catalan Health Institute. [2021-09-19]. .
    1. Pépin Jean-Louis, Jullian-Desayes I, Sapène Marc, Treptow E, Joyeux-Faure M, Benmerad M, Bailly S, Grillet Y, Stach B, Richard P, Lévy Patrick, Muir J, Tamisier R. Multimodal Remote Monitoring of High Cardiovascular Risk Patients With OSA Initiating CPAP: A Randomized Trial. Chest. 2019 Apr;155(4):730–739. doi: 10.1016/j.chest.2018.11.007.S0012-3692(18)32768-5
    1. Stepnowsky C, Edwards C, Zamora T, Barker R, Agha Z. Patient perspective on use of an interactive website for sleep apnea. Int J Telemed Appl. 2013;2013:239382–10. doi: 10.1155/2013/239382. doi: 10.1155/2013/239382.
    1. Kuna ST, Shuttleworth D, Chi L, Schutte-Rodin S, Friedman E, Guo H, Dhand S, Yang L, Zhu J, Bellamy SL, Volpp KG, Asch DA. Web-Based Access to Positive Airway Pressure Usage with or without an Initial Financial Incentive Improves Treatment Use in Patients with Obstructive Sleep Apnea. Sleep. 2015 Aug 01;38(8):1229–36. doi: 10.5665/sleep.4898. sp-00550-14
    1. Hwang D, Chang JW, Benjafield AV, Crocker ME, Kelly C, Becker KA, Kim JB, Woodrum RR, Liang J, Derose SF. Effect of Telemedicine Education and Telemonitoring on Continuous Positive Airway Pressure Adherence. The Tele-OSA Randomized Trial. Am J Respir Crit Care Med. 2018 Jan;197(1):117–126. doi: 10.1164/rccm.201703-0582oc.
    1. Frasnelli M, Baty F, Niedermann J, Brutsche MH, Schoch OD. 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. 2015 Aug 06;22(4):209–214. doi: 10.1177/1357633x15598053.
    1. Turino C, de Batlle J, Woehrle H, Mayoral A, Castro-Grattoni A, Gómez Sílvia, Dalmases M, Sánchez-de-la-Torre Manuel, Barbé Ferran. Management of continuous positive airway pressure treatment compliance using telemonitoring in obstructive sleep apnoea. Eur Respir J. 2017 Feb 08;49(2):1601128. doi: 10.1183/13993003.01128-2016. 49/2/1601128
    1. Isetta V, Negrín Miguel A, Monasterio C, Masa JF, Feu N, Álvarez Ainhoa, Campos-Rodriguez F, Ruiz C, Abad J, Vázquez-Polo Francisco J, Farré Ramon, Galdeano M, Lloberes P, Embid C, de la Peña Mónica, Puertas J, Dalmases M, Salord N, Corral J, Jurado B, León Carmen, Egea C, Muñoz Aida, Parra O, Cambrodi R, Martel-Escobar M, Arqué Meritxell, Montserrat JM, Spanish Sleep Network A Bayesian cost-effectiveness analysis of a telemedicine-based strategy for the management of sleep apnoea: a multicentre randomised controlled trial. Thorax. 2015 Nov 26;70(11):1054–61. doi: 10.1136/thoraxjnl-2015-207032.thoraxjnl-2015-207032
    1. Anttalainen U, Melkko S, Hakko S, Laitinen T, Saaresranta T. Telemonitoring of CPAP therapy may save nursing time. Sleep Breath. 2016 Dec 4;20(4):1209–1215. doi: 10.1007/s11325-016-1337-9.10.1007/s11325-016-1337-9

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