Apnea-hypopnea index supplied by CPAP devices: time for standardization?

The Future of Telemedicine for Obstructive Sleep Apnea Treatment: A Narrative Review

Obstructive sleep apnea is a common type of sleep-disordered breathing associated with multiple comorbidities. Nearly a billion people are estimated to have obstructive sleep apnea, which carries a substantial economic burden, but under-diagnosis is still a problem. Continuous positive airway pressure (CPAP) is the first-line treatment for OSAS. Telemedicine-based interventions (TM) have been evaluated to improve access to diagnosis, increase CPAP adherence, and contribute to easing the follow-up process, allowing healthcare facilities to provide patient-centered care. This narrative review summarizes the evidence available regarding the potential future of telemedicine in the management pathway of OSA. The potential of home sleep studies to improve OSA diagnosis and the importance of remote monitoring for tracking treatment adherence and failure and to contribute to developing patient engagement tools will be presented. Further studies are needed to explore the impact of shifting from teleconsultations to collaborative care models where patients are placed at the center of their care.

Guidelines for the assessment and management of residual sleepiness in obstructive apnea-hypopnea syndrome: Endorsed by the French Sleep Research and Medicine Society (SFRMS) and the French Speaking Society of Respiratory Diseases (SPLF)

Excessive daytime sleepiness (EDS) is frequent among patients with obstructive sleep apnea hypopnea syndrome (OSAHS) and can persist despite the optimal correction of respiratory events (apnea, hypopnea and respiratory efforts), using continuous positive airway pressure (CPAP) or mandibular advancement device. Symptoms like apathy and fatigue may be mistaken for EDS. In addition, EDS has multi-factorial origin, which makes its evaluation complex. The marketing authorization [Autorisation de Mise sur le Marché (AMM)] for two wake-promoting agents (solriamfetol and pitolisant) raises several practical issues for clinicians. This consensus paper presents recommendations of good clinical practice to identify and evaluate EDS in this context, and to manage and follow-up the patients. It was conducted under the mandate of the French Societies for sleep medicine and for pneumology [Société Française de Recherche et de Médecine du Sommeil (SFRMS) and Société de Pneumologie de Langue Française (SPLF)]. A management algorithm is suggested, as well as a list of conditions during which the patient should be referred to a sleep center or a sleep specialist. The benefit/risk balance of a wake-promoting drug in residual EDS in OSAHS patients must be regularly reevaluated, especially in elderly patients with increased cardiovascular and psychiatric disorders risks. This consensus is based on the scientific knowledge at the time of the publication and may be revised according to their evolution.

Remote Monitoring of Positive Airway Pressure Data: Challenges, Pitfalls, and Strategies to Consider for Optimal Data Science Applications

Over recent years, positive airway pressure (PAP) remote monitoring has transformed the management of OSA and produced a large amount of data. Accumulated PAP data provide valuable and objective information regarding patient treatment adherence and efficiency. However, the majority of studies that have analyzed longitudinal PAP remote monitoring have summarized data trajectories in static and simplistic metrics for PAP adherence and the residual apnea-hypopnea index by the use of mean or median values. The aims of this article are to suggest directions for improving data cleaning and processing and to address major concerns for the following data science applications: (1) conditions for residual apnea-hypopnea index reliability, (2) lack of standardization of indicators provided by different PAP models, (3) missing values, and (4) consideration of treatment interruptions. To allow fair comparison among studies and to avoid biases in computation, PAP data processing and management should be conducted rigorously with these points in mind. PAP remote monitoring data contain a wealth of information that currently is underused in the field of sleep research. Improving the quality and standardizing data handling could facilitate data sharing among specialists worldwide and enable artificial intelligence strategies to be applied in the field of sleep apnea.

The individual and societal price of non-adherence to continuous positive airway pressure, contributors and strategies for improvement

INTRODUCTION

Continuous positive airway pressure (CPAP) is the first line therapy for obstructive sleep apnea (OSA). CPAP is highly effective for improving symptoms and quality of life but the major issue is adherence, with up to 50% of OSA discontinuing CPAP in the first 3 years after CPAP initiation.

AREAS COVERED

We present the individual and societal cost of non-adherence to CPAP, factors associated with non-adherence to CPAP, as well as current strategies for improving adherence including telehealth, couples-based interventions and behavioral interventions. We also report on challenges and pitfalls for the visualization and analysis of CPAP remote monitoring platforms.

EXPERT OPINION

CPAP termination rates and adherence to therapy remain major issues despite technical improvements in CPAP devices. The individual and societal price of non-adherence to CPAP for OSA patients goes beyond excessive sleepiness and includes cardiovascular events, all-cause mortality, and increased health costs. Strategies for improving CPAP adherence should be individually tailored and aim to also improve lifestyle habits including physical activity and nutrition. Access to these strategies should be supported by refining visualization dashboards of CPAP remote monitoring platforms, and by disseminating telehealth and innovative analytics, including artificial intelligence.

Factors Associated With Residual Apnea-Hypopnea Index Variability During CPAP Treatment

BACKGROUND

CPAP is the first-line therapy for OSA. A high or variable residual apnea-hypopnea index (rAHI) reflects treatment failure and potentially is triggered by exacerbation of cardiovascular comorbidities. Previous studies showed that high rAHI and large rAHI variability are associated with underlying comorbidities, OSA characteristics at diagnosis, and CPAP equipment, including mask type and settings.

RESEARCH QUESTION

What factors are associated with predefined groups with low to high rAHI variability?

STUDY DESIGN AND METHODS

This registry-based study included patients with a diagnosis of OSA who were receiving CPAP treatment with at least 90 days of CPAP remote monitoring. We applied the hidden Markov model to analyze the day-to-day trajectories of rAHI variability using telemonitoring data. An ordinal logistic regression analysis identified factors associated with a risk of having a higher and more variable rAHI with CPAP treatment.

RESULTS

The 1,126 included patients were middle-aged (median age, 66 years; interquartile range [IQR], 57-73 years), predominantly male (n = 791 [70.3%]), and obese (median BMI, 30.6 kg/m² (IQR, 26.8-35.2 kg/m²). Three distinct groups of rAHI trajectories were identified using hidden Markov modeling: low rAHI variability (n = 393 [35%]), moderate rAHI variability group (n = 420 [37%]), and high rAHI variability group (n = 313 [28%]). In multivariate analysis, factors associated with high rAHI variability were age, OSA severity at diagnosis, heart failure, opioids and alcohol consumption, mental and behavioral disorders, transient ischemic attack and stroke, an oronasal mask, and level of leaks when using CPAP.

INTERPRETATION

Identifying phenotypic traits and factors associated with high rAHI variability will allow early intervention and the development of personalized follow-up pathways for CPAP treatment.

Ventilator integrated polygraphy for patients using non-invasive ventilation; Case report

The COVID-19 pandemic has meant that home respiratory services have needed to be reviewed. As a result, new solutions have been developed and implemented. The Vivo 45™ (Breas, Mölnlycke, Sweden) is a ventilator that offers clinicians the ability to attach effort belts to the device. This allows the clinician to review ventilator traces with the addition of thoracic and abdominal activity. This allows more flexibility for the monitoring of patients at home and in the hospital, with detection of patient ventilator asynchrony (PVA). Decreasing PVA may improve ventilator adherence and increased ventilator usage improves survival. We report three cases of patients undergoing overnight monitoring with the Vivo 45™, highlighting the benefit of ventilator integrated polygraphy. In our three cases we demonstrate a simple safe tool to optimize NIV treatment over one or two-night recordings using ventilator downloaded software with the addition of effort belts and pulse oximetry without involving more than one machine and without hospitalization in a sleep unit.

Telemonitoring for the Follow-Up of Obstructive Sleep Apnea Patients Treated with CPAP: Accuracy and Impact on Therapy

Continuous positive airway pressure (CPAP) telemonitoring (TMg) has become widely implemented in routine clinical care. Objective measures of CPAP compliance, residual respiratory events, and leaks can be easily monitored, but limitations exist. This review aims to assess the role of TMg in CPAP-treated obstructive sleep apnea (OSA) patients. We report recent data related to the accuracy of parameters measured by CPAP and try to determine the role of TMg in CPAP treatment follow-up, from the perspective of both healthcare professionals and patients. Measurement and accuracy of CPAP-recorded data, clinical management of these data, and impacts of TMg on therapy are reviewed in light of the current literature. Moreover, the crucial questions of who and how to monitor are discussed. TMg is a useful tool to support, fine-tune, adapt, and control both CPAP efficacy and compliance in newly-diagnosed OSA patients. However, clinicians should be aware of the limits of the accuracy of CPAP devices to measure residual respiratory events and leaks and issues such as privacy and cost-effectiveness are still a matter of concern. The best methods to focus our efforts on the patients who need TMg support should be properly defined in future long-term studies.

A longitudinal study of the accuracy of positive pressure therapy machine-detected apnea-hypopnea events

STUDY OBJECTIVES

During positive airway pressure (PAP) therapy for sleep apnea syndromes, the machine detected respiratory event index (REI_FLOW) is an important method for clinicians to evaluate the beneficial effects of PAP. There are concerns about the accuracy of this detection, which also confounds a related question-how common and severe are residual events on PAP.

METHODS

Subjects with OSA who underwent a split night polysomnography were recruited prospectively. Those treated with PAP and tracked by the EncoreAnywhere system were analyzed. The ones who stopped PAP within one month were excluded for this analysis. Compliance, therapy data and waveform data were analyzed. Machine detected versus manually scored events were compared at the 1st, 3rd, 6th and 12th month from PAP initiation. Logistic regression was used to determine factors associated with a high REI_FLOW difference.

RESULTS

One hundred and seventy-nine patients with a mean age 59.06 ± 13.97 years old, median body mass index 33.60 (29.75-38.75) kg/m², and median baseline AHI 46.30 (31.50-65.90) times/hour were included. The difference between the machine detected REI_FLOW and manually scored REI_FLOW was 10.72 ±8.43 in the first month and remained stable for up to 12 months. Male sex and large leak ≥ 1.5% were more frequent in patients who had an REI_FLOW difference of ≥ 5 / hour of use. A titration arousal index ≥ 15/ hour of sleep, and higher ratio of unstable to stable breathing were also associated with an REI_FLOW difference ≥ 5 times/hour of use.

CONCLUSIONS

There is a substantial and sustained difference between manual and automated event estimates during PAP therapy, and some associated factors were identified.