Adaptive servo ventilation for sleep apnoea in heart failure: the FACE study 3-month data

Sleep Apnea and Heart Failure-Current State-of-The-Art

Sleep-disordered breathing (SDB), including obstructive and central sleep apnea, significantly exacerbates heart failure (HF) through adverse cardiovascular mechanisms. This review aims to synthesize existing literature to clarify the relationship between SDB and HF, focusing on the pathophysiological mechanisms, diagnostic challenges, and the effectiveness of treatment modalities like continuous positive airway pressure (CPAP) and adaptive servo-ventilation ASV. We analyzed peer-reviewed articles from 2003 to 2024 sourced from PubMed, EMBASE, Scopus, and Web of Science databases. The prevalence of SDB in HF patients is high, often underdiagnosed, and underappreciated. Management strategies, including CPAP and ASV, have been shown to mitigate symptoms and improve cardiac function. However, despite the availability of effective treatments, significant challenges in screening and diagnosis persist, affecting patient management and outcomes. DB significantly impacts HF prognosis. Enhanced screening strategies and broader utilization of therapeutic interventions like CPAP and ASV are essential to improve the management and outcomes of HF patients with concomitant SDB. Future research should focus on refining diagnostic and treatment protocols to optimize care for HF patients with SDB.

Central sleep apnea: emphasizing recognition and differentiation

INTRODUCTION

Central sleep apnea (CSA) is a sleep-related breathing disorder in which the effort to breathe is intermittently diminished or absent. CSA is a common disorder among patients with different cardiovascular disorders, including heart failure. In addition, a growing number of medications have been shown to induce CSA and CSA can emerge after initiation of treatment for obstructive sleep apnea. Accumulating evidence shows that CSA is a heterogeneous disorder with individual differences in clinical and biological characteristics and/or underlying pathophysiological mechanisms.

AREAS COVERED

This narrative review offers an overview of the diagnostic aspects and classification of CSA, with an emphasis on heart failure patients, patients with CSA due to a medication and treatment-emergent CSA. The importance of evaluation of prognostic biomarkers in patients with different types of CSA is discussed. This narrative review synthesizes literature on CSA sourced from the PubMed database up to February 2024.

EXPERT OPINION

CSA presents a remarkably diverse disorder, with treatment modalities exhibiting potentially varied efficacy across its various phenotypes. This highlights the imperative for tailored management strategies that are rooted in phenotype classification.

Effects of Adaptive Servo-Ventilation on Quality of Life: The READ-ASV Registry

Rationale: Adaptive servo-ventilation (ASV) effectively treats sleep-disordered breathing, including central sleep apnea (CSA) and coexisting obstructive sleep apnea (OSA).Objectives: The prospective, multicenter European READ-ASV (Registry on the Treatment of Central and Complex Sleep-Disordered Breathing with Adaptive Servo-Ventilation) registry investigated the effects of first-time ASV therapy on disease-specific quality of life (QoL).Methods: The registry enrolled adults with CSA with or without OSA who had ASV therapy prescribed between September 2017 and March 2021. The primary endpoint was change in disease-specific QoL (Functional Outcomes of Sleep Questionnaire [FOSQ]) score between baseline and 12-month follow-up. Sleepiness determined using the Epworth Sleepiness Scale (ESS) score was a key secondary outcome. For subgroup analysis, participants were classified as symptomatic (FOSQ score < 17.9 and/or ESS score > 10) or asymptomatic (FOSQ score ⩾ 17.9 and/or ESS score ⩽ 10).Results: A total of 801 individuals (age, 67 ± 12 yr; 14% female; body mass index, 31 ± 5 kg/m2; apnea-hypopnea index, 48 ± 22/h) were enrolled; analyses include those with paired baseline and follow-up data. After 12 ± 3 months on ASV, median (interquartile range) FOSQ score had increased significantly from baseline (+0.8 [-0.2 to 2.2]; P < 0.001; n = 499). This was due to a significantly increased FOSQ score in symptomatic participants (+1.69 [0.38 to 3.05]), with little change in asymptomatic individuals (+0.11 [-0.39 to 0.54]). The median ESS score also improved significantly from baseline during ASV (-2.0 [-5.0 to 0.0]; P < 0.001).Conclusions: ASV treatment of CSA with or without coexisting OSA was associated with improvements in disease-specific QoL and daytime sleepiness, especially in individuals with sleep-disordered breathing symptoms before therapy initiation. These improvements in patient-reported outcomes support the use of ASV in this population.

Association of Sex With Cardiovascular Outcomes in Heart Failure Patients With Obstructive or Central Sleep Apnea

BACKGROUND

This study investigated the association of sex with cardiovascular outcomes in a prospective cohort of patients with heart failure (HF) with obstructive sleep apnea or central sleep apnea.

METHODS AND RESULTS

Patients were screened for sleep apnea on admission using multichannel cardiopulmonary monitoring from May 2015 to July 2018. The primary outcome was a composite of cardiovascular death or unplanned hospitalization for worsening HF. Ultimately, 453 patients with HF with obstructive sleep apnea or central sleep apnea were included; 71 (15.7%) and 382 (84.3%) were women and men, respectively. During a median follow-up of 2.33 years, 248 (54.7%) patients experienced the primary outcome. In the overall population, after adjusting for potential confounders, women had an increased risk of the primary outcome (66.2% versus 52.6%; hazard ratio [HR], 1.47 [95% CI, 1.05-2.04]; P=0.024) and HF rehospitalization (62.0% versus 46.6%; HR, 1.55 [95% CI, 1.10-2.19]; P=0.013) compared with men but a comparable risk of cardiovascular death (21.1% versus 23.3%; HR, 0.78 [95% CI, 0.44-1.37]; P=0.383). Likewise, in patients with HF with obstructive sleep apnea, women had a higher risk of the primary outcome (81.8% versus 46.3%, HR, 2.37 [95% CI, 1.28-4.38]; P=0.006) and HF rehospitalization (81.8% versus 44.7%, HR, 2.46 [95% CI, 1.32-4.56], P=0.004). However, in patients with HF with central sleep apnea, there was no statistically significant difference between women and men.

CONCLUSIONS

In hospitalized patients with HF, female sex was associated with an increased risk of the primary outcome and HF rehospitalization, especially in those with obstructive sleep apnea. Screening for sleep apnea should be emphasized to improve the prognosis.

REGISTRATION

URL: https://www.clinicaltrials.gov. Unique identifier: NCT02664818.

FACE study: 2-year follow-up of adaptive servo-ventilation for sleep-disordered breathing in a chronic heart failure cohort

BACKGROUND

Sleep-disordered breathing (SDB) is a common comorbidity in patients with heart failure (HF) and is associated with worse prognosis.

OBJECTIVES

This study evaluated the effects of adaptive servo-ventilation (ASV) on morbidity and mortality in a large heterogeneous population of HF patients with different etiologies/phenotypes.

METHODS

Consecutive HF patients with predominant central sleep apnea (± obstructive sleep apnea) indicated for ASV were included; the control group included patients who refused or stopped ASV before three months follow-up. Six homogenous clusters were determined using the latent class analysis (LCA) method. The primary endpoint was time to composite first event (all-cause death, lifesaving cardiovascular intervention, or unplanned hospitalization for worsening of chronic HF).

RESULTS

Of 503 patients at baseline, 324 underwent 2-year follow-up. Compared to control group, 2-year primary endpoint event-free survival was significantly greater in patients in ASV group only in univariable analysis (1.67, 95% [1.12-2.49]; p = 0.01). Secondary endpoints, event-free of cardiovascular death or heart failure-related hospitalization and all-cause death or all-cause hospitalization were positively impacted by ASV (univariate and multivariable analysis). LCA identified two groups, with preserved and mid-range left ventricular ejection fraction (LVEF) and severe hypoxia, in whom ASV increase prognosis benefit.

CONCLUSIONS

Patients with HF and SDB are a highly heterogeneous group identified using LCA. Systematic deep phenotyping is essential to ensure that ASV is prescribed to those benefit from therapy, as ASV use in patients with severe hypoxic burden and those with HFpEF was associated with a significant reduction in cardiovascular events and mortality.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT01831128.

Ventilatory failure in chronic neuromuscular disease

Patients with neuromuscular diseases (NMD) can present to the neurologist with symptoms and signs of respiratory failure, either acutely or as an insidious process in the outpatient setting. Since the advent of non-invasive ventilation, the outcomes of patients with ventilatory failure due to NMD have dramatically improved. However, the natural history of different NMDs requires a nuanced approach to respiratory investigation and management. Respiratory failure dictates the prognosis of many NMDs and timing the most appropriate investigation and referral to ventilation services is crucial in optimising care.

Insights into the Interaction of Heart Failure with Preserved Ejection Fraction and Sleep-Disordered Breathing

Heart failure with preserved ejection fraction (HFpEF) is emerging as a widespread disease with global socioeconomic impact. Patients with HFpEF show a dramatically increased morbidity and mortality, and, unfortunately, specific treatment options are limited. This is due to the various etiologies that promote HFpEF development. Indeed, cluster analyses with common HFpEF comorbidities revealed the existence of several HFpEF phenotypes. One especially frequent, yet underappreciated, comorbidity is sleep-disordered breathing (SDB), which is closely intertwined with the development and progression of the "obese HFpEF phenotype". The following review article aims to provide an overview of the common HFpEF etiologies and phenotypes, especially in the context of SDB. As general HFpEF therapies are often not successful, patient- and phenotype-individualized therapeutic strategies are warranted. Therefore, for the "obese HFpEF phenotype", a better understanding of the mechanistic parallels between both HFpEF and SDB is required, which may help to identify potential phenotype-individualized therapeutic strategies. Novel technologies like single-cell transcriptomics or CRISPR-Cas9 gene editing further broaden the groundwork for deeper insights into pathomechanisms and precision medicine.

Sleep and Breathing Conference highlights 2023: a summary by ERS Assembly 4

This paper presents some of the highlights of the Sleep and Breathing Conference 2023 https://bit.ly/46MxJml.

Changes in cognitive function and daytime sleepiness in patients with chronic heart failure and Cheyne-Stokes respiration with adaptive servo ventilation treatment

STUDY OBJECTIVES

Cheyne - Stokes respiration (CSR) is prevalent in patients with chronic heart failure (CHF). Adaptive Servo Ventilation (ASV) alleviates CSR and improves objective sleep quality. We investigated the effects of ASV on neurocognitive function in the symptomatic phenotype of patients with CSR and CHF.

METHODS

This case series included patients diagnosed with stable CHF (NYHA ≥ II) and CSR (N = 8). Sleep and neurocognitive function were assessed at baseline and after 1- and 6-months following initiation of ASV treatment.

RESULTS

In CHF patients (n = 8, median age 78.0[64.5-80.8] years and BMI 30.0[27.0-31.5] kg/m2, median ejection fraction 30[24-45]%, Epworth Sleepiness Scale (ESS) score 11.5[9.0-15.0]), ASV markedly improved respiration during sleep (Apnea-Hypopnea Index (AHI) 44.1[39.0-51.5]n/h at baseline, 6.3[2.4-9.7]n/h at 6 months treatment, respectively, p < 0.01). The 6-min-walk test distance increased by treatment from (295.0[178.8-385.0] m to 356.0[203.8-495.0] m (p = 0.05)). Sleep structure was modified, and Stage 3 increased markedly from 6.4[1.7-20.1] % to 20.8[14.2-25.3] %, p < 0.02). Sleep latency in the Maintenance of Wakefulness Test increased from 12.0[6.0-30.0] min to 26.3[12.0-30.0] min, (p = 0.04). In the Attention Network Test, evaluating neurocognition, the number of lapses decreased from 6.0[1.0-44.0] to 2.0[0.3-8.0], (p = 0.05) and the overall number of responses to a preset stimulus increased after treatment (p = 0.04).

CONCLUSIONS

ASV treatment in CHF patients with CSR may improve sleep quality, neurocognition and daytime performance.

Identifying novel subgroups in heart failure patients with unsupervised machine learning: A scoping review

Background

Heart failure is currently divided into three main forms, HFrEF, HFpEF, and HFmrEF, but its etiology is diverse and highly heterogeneous. Many studies reported a variety of novel subgroups in heart failure patients, with unsupervised machine learning methods. The aim of this scoping review is to provide insights into how these techniques can diagnose and manage HF faster and better, thus providing direction for future research and facilitating its routine use in clinical practice.

Methods

The review was performed following PRISMA-SCR guideline. We searched the PubMed database for eligible publications. Studies were included if they defined new subgroups in HF patients using clustering analysis methods, and excluded if they are (1) Reviews, commentary, or editorials, (2) Studies not about defining new sub-types, or (3) Studies not using unsupervised algorithms. All study screening and data extraction were conducted independently by two investigators and narrative integration of data extracted from included studies was performed.

Results

Of the 498 studies identified, 47 were included in the analysis. Most studies (61.7%) were published in 2020 and later. The largest number of studies (46.8%) coming from the United States, and most of the studies were authored and included in the same country. The most commonly used machine learning method was hierarchical cluster analysis (46.8%), the most commonly used cluster variable type was comorbidity (61.7%), and the least used cluster variable type was genomics (12.8%). Most of the studies used data sets of less than 500 patients (48.9%), and the sample size had negative correlation with the number of clustering variables. The majority of studies (85.1%) assessed the association between cluster grouping and at least one outcomes, with death and hospitalization being the most commonly used outcome measures.

Conclusion

This scoping review provides an overview of recent studies proposing novel HF subgroups based on clustering analysis. Differences were found in study design, study population, clustering methods and variables, and outcomes of interests, and we provided insights into how these studies were conducted and identify the knowledge gaps to guide future research.