CPAP telemonitoring can track Cheyne-Stokes respiration and detect serious cardiac events: The AlertApnée Study

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.

The PAP-RES algorithm: Defining who, why and how to use positive airway pressure therapy for OSA

Obstructive sleep apnea (OSA) is a common condition that is increasing in prevalence worldwide. Untreated OSA has a negative impact on health-related quality of life and is an independent risk factor for cardiovascular diseases. Despite available data suggesting that cardiovascular risk might differ according to clinical phenotypes and comorbidities, current approaches to OSA treatment usually take a "one size fits all" approach. Identification of cardiovascular vulnerability biomarkers and clinical phenotypes associated with response to positive airway pressure (PAP) therapy could help to redefine the standard treatment paradigm. The new PAP-RES (PAP-RESponsive) algorithm is based on the identification of OSA phenotypes that are likely to impact therapeutic goals and modalities. The paradigm shift is to propose a simplified approach that defines therapeutic goals based on OSA phenotype: from a predominantly "symptomatic phenotype" (individuals with high symptom burden that negatively impacts on daily life and/or accident risk or clinically significant insomnia) to a "vulnerable cardiovascular phenotype" (individuals with comorbidities [serious cardiovascular or respiratory disease or obesity] that have a negative impact on cardiovascular prognosis or a biomarker of hypoxic burden and/or autonomic nervous system dysfunction). Each phenotype requires a different PAP therapy care pathway based on differing health issues and treatment objectives.

ERS International Congress 2023: highlights from the Sleep Disordered Breathing Assembly

The topic of sleep-related breathing disorders is always evolving, and during the European Respiratory Society (ERS) International Congress 2023 in Milan, Italy, the latest research and clinical topics in respiratory medicine were presented. The most interesting issues included new diagnostic tools, such as cardiovascular parameters and artificial intelligence, pathophysiological traits of sleep disordered breathing from routine polysomnography or polygraphy signals, and new biomarkers and the diagnostic approach in patients with excessive daytime sleepiness. This article summarises the most relevant studies and topics presented at the ERS International Congress 2023. Each section has been written by early career members of ERS Assembly 4.

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.

High nocturnal periodic breathing reported by PAP adherence data predicts decompensation of heart failure

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) often coexists with heart failure (HF) and is commonly treated with positive airway pressure (PAP) therapy. Periodic breathing (PB) may be present in HF and is an indicator of poor prognosis, but there is no easy way to detect PB in an outpatient setting. However, it can be detected by analyzing PAP usage data. The study aimed to assess if high PB% detected by PAP machine could predict impending HF exacerbation and if better PAP adherence is associated with reduced hospitalization and mortality.

METHODS

We retrospectively reviewed medical records of 115 patients with OSA from the sleep clinic of our VA Medical Center. The cross-sectional data on demographics, labs, PAP adherence, PB% in the previous 30 days, echocardiogram in the previous 6 months, and hospitalizations and mortality in the subsequent 180 days were extracted. Based on left ventricular ejection fraction (LVEF), patients were classified into (1) HF with normal-midrange LVEF (LVEF ≥40%, n = 74) and (2) HF with reduced LVEF (LVEF < 40%, n = 41). Pairwise correlation and linear regressions were done to assess predictors of PB%. Binomial and logistic regressions assessed the relationship of PB% and PAP adherence with hospitalization from HF and all-cause mortality.

RESULTS

In the HF with reduced LVEF group, the mean PB% was 2.6 times higher (P < .001) and PAP adherence was 29% lower (P < .001). PB% positively correlated with brain natriuretic peptide level (r = .447, P < .01) and number of hospitalizations (r = .331, P < .01). Higher PB% negatively correlated with LVEF (r = -.423, P < .01) and estimated glomerular filtration rate (r = -.246, P < .01). Every 10% increase in PAP adherence decreased odds of hospitalization by 0.78 times (P < .001) and odds of death by 0.86 (P = .043).

CONCLUSIONS

High PB% detected by PAP machine data is a predictor of impending HF exacerbation and hospitalization. Improved PAP adherence and optimization of medical therapy may reduce hospitalization and all-cause mortality.

CITATION

Ullah MI, Tamanna S, Bhagat R. High nocturnal periodic breathing reported by PAP adherence data predicts decompensation of heart failure. J Clin Sleep Med. 2023;19(3):431-441.

Early identification of heart failure deterioration through respiratory monitoring with adaptive servo-ventilation

Cardiac decompensation is associated with worse prognosis in patients with heart failure. Reliable methods to predict cardiac decompensation events are not yet available. Sleep-disordered breathing (SDB) is a frequent comorbidity in heart failure, and it has been shown to correlate with heart failure severity. This prospective observational trial investigated SDB characteristics in patients with heart failure with the aim to identify patterns that may predict early cardiac decompensation. Patients with heart failure with diagnosed SDB and hospitalised for cardiac decompensation were prospectively enrolled and treated with adaptive servo-ventilation (ASV). SDB characteristics, daily body weight and clinical cardiac decompensation events were collected over a 1-year follow-up. Clinical events were categorised by an independent clinical event committee. A total of 43 patients were enrolled (81% male, mean [SD] age 71 [11] years, body mass index 30 kg/m² , 95% New York Heart Association function class III or IV, mean [SD] left ventricular ejection fraction 37% [11%], median apnea-hypopnoea index [AHI] of 37 events/h). A total of 48 cardiac decompensation events were recorded during the 1-year study period. Respiratory rate was found to be significantly lower in patients with cardiac decompensation. The AHI and applied inspiratory pressure ASV-device support were significantly increased 10 days before a clinical cardiac decompensation event. Device usage was also found to be significantly decreased 2 nights before cardiac decompensation. Device-derived respiratory data in ASV therapy devices for SDB may therefore serve as a monitoring tool to predict early clinical cardiac decompensation events. Prediction and avoidance of cardiac decompensation, in turn, may attenuate serious health consequences in patients with heart failure.

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.

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.