Prevalence, risk factors, and type of sleep apnea in patients with paroxysmal atrial fibrillation

Managing elderly patients with atrial fibrillation and multimorbidity: call for a systematic approach

INTRODUCTION

Atrial fibrillation (AF) is often accompanied by comorbidities. Not only cardiovascular but also non-cardiovascular comorbidities have been associated with AF. Multimorbidity is therefore a common finding in patients with AF, especially in elderly patients. Multimorbidity is associated with adverse outcomes, adds complexity to AF management, and poses a significant burden on healthcare costs. It is expected that the prevalence of elderly patients with multimorbidity will increase significantly. It is therefore crucial to outline implications for clinical practice and guide comprehensive multimorbidity management.

AREAS COVERED

This perspective article outlines multimorbidity in AF and the importance of comprehensive comorbidity management. It addresses current clinical practice guided by international guidelines and the need for integrated care including a patient-centered focus, comprehensive AF management, coordinated multidisciplinary care, and supporting technology. Moreover, it proposes a novel model of care delivery following a systematic approach to multimorbidity management.

EXPERT OPINION

Providing comprehensive care by means of a multidisciplinary team and patient engagement is crucial to provide optimal personalized care for elderly patients with AF and multimorbidity. A systematic integrated care approach seems promising, but further studies are needed to investigate the feasibility of a systematic approach and prioritization of comorbidity management in patients with multimorbidity.

Exploring the bidirectional relationship between sleep disorders and atrial fibrillation: implications for risk stratification and management

BACKGROUND

Atrial fibrillation (AF) is characterized by the absence of p-waves on ECG and irregular rhythm. It often presents with palpitations either palpitations may occur acutely over a short period or intermittently over several years. Other cardinal symptoms of atrial fibrillation include fatigue, dyspnea, and lightheadedness; it is important however to note that most affected individuals are asymptomatic. Concurrently, sleep disorders such as obstructive sleep apnea (OSA), insomnia, narcolepsy, and circadian rhythm disorders which are a group of conditions associated with the body's internal clock that affect the timing of sleep and alertness, are raising concerns due to their potential associations to arrhythmias. This review explores the bidirectional relationship between AF and sleep disorders, highlighting their implications for risk stratification and management strategies.

MAIN BODY

The narrative approach of this review synthesizes evidence from numerous studies obtained through meticulous literature searches. Specific sleep disorders with a bidirectional relationship with AF are the focus, with scrutiny on the prevalence of this connection. The examination delves into the pathophysiology of sleep-related autonomic dysregulation and inflammation, emphasizing potential management modalities. Various meta-analysis cohorts have highlighted a strong connection between sleep disorders and atrial fibrillation (AF). Patients with sleep disorders, especially OSA, have a higher likelihood of developing AF, and conversely, those with AF are more prone to sleep disorders. This impact is not limited to development, as sleep disorders also contribute to the progression of AF, with AF, in turn, negatively impacting sleep duration and quality. Sleep disorders may play an important role in atrial remodeling as well as electrophysiological abnormalities, rendering the atrial tissue more susceptible to arrhythmogenesis. The narrative review suggests that treating sleep disorders could not only improve sleep quality but also reduce risk factors associated with atrial fibrillation. The effective management of sleep disorders emerges as a potential challenge in preventing and treating atrial fibrillation.

CONCLUSION

In conclusion, this narrative study highlights the bidirectional relationship between sleep disorders and atrial fibrillation. There is a positive correlation, affecting the development, progression, and management of atrial fibrillation. The detrimental impact of sleep disorders on atrial remodeling and electrophysiological abnormalities underscores the significance of their diagnosis and treatment. Education about the importance of sleep and the benefits of sleep disorder treatment becomes imperative for patients with AF and sleep disorders.

Sleep Apnea and Atrial Fibrillation: Clinical Features and Screening Diagnostic Options

INTRODUCTION

Obstructive sleep apnea (OSA) is associated with an increased risk of hypertension, coronary artery disease, heart failure (HF), and atrial fibrillation (AF).

MATERIALS AND METHODS

A total of 179 patients aged 34-81 years were included in the study. The median age was 63 years (interquartile range: 56-69 years). Of these patients, 105 (58.7%) were men, and 74 (41.3%) were women; there were cases of paroxysmal (n = 99), persistent (n = 64), and permanent AF (n = 16). All patients underwent investigations including respiratory sleep monitoring, echocardiography, and 24 h Holter electrocardiography monitoring. Statistical analyses were performed using IBM SPSS Statistics 26.0.

RESULTS

OSA was detected in 131 (73.2%) patients. In patients with OSA, paroxysmal AF was commonest (n = 65), followed by persistent AF (n = 51) and permanent AF (n = 15). The patients with sleep apnea had increased body mass index (33.6 kg/m2; p = 0.02), waist circumference (114 cm; p < 0.001), and neck circumference (42 cm; p < 0.001) values. HF (OR 2.9; 95% CI: 1.4-5.9; p = 0.004) and type 2 diabetes (OR 3.6; 95% CI: 1.5-8.3; p = 0.001) were more common in patients with AF and OSA. The STOP-BANG scale (AUC = 0.706 ± 0.044; 95% CI: 0.619-0.792; p < 0.001) and the Berlin questionnaire (AUC = 0.699 ± 0.044; 95% CI: 0.614-0.785) had a higher predictive ability for identifying sleep apnea.

CONCLUSIONS

Patients with AF demonstrate a high prevalence of OSA and an increased association with cardiovascular comorbidities. The STOP-BANG scale and the Berlin questionnaire can be used to screen for OSA in patients with AF.

Sex-based differences in obstructive sleep apnea and atrial fibrillation: Implication of atrial fibrillation burden

Background

Obstructive sleep apnea (OSA) is a risk factor for atrial fibrillation (AF); however, it is unclear whether AF increases the risk of OSA. Furthermore, sex differences among patients with both AF and OSA remain unclear. We aimed to determine the association between an increased AF burden and OSA and investigate the differences in clinical characteristics between women and men with AF and OSA.

Methods

This was a descriptive, cross-sectional analysis from a prospective cohort study. Patients with non-valvular AF were recruited from the cardiac electrophysiology clinic of a tertiary center; they underwent a home sleep apnea test and 14-day ambulatory electrocardiography. Moderate-to-severe OSA was defined as an apnea-hypopnea index of ≥15.

Results

Of 320 patients with AF, 53.4% had moderate-to-severe OSA, and the mean body mass index (BMI) was 25.6 kg/m2. Less women (38.2%) had moderate-to-severe OSA than men (59.3%) (p < 0.001). In the multivariate analysis, age, being a man, and BMI were significantly associated with moderate-to-severe OSA. AF burden was associated with moderate-to-severe OSA only in men (odds ratio: 1.008; 95% confidence interval: 1.001-1.014). Women and men with OSA had similar BMI (p = 0.526) and OSA severity (p = 0.754), but women were older than men (70.1 ± 1.3 vs. 63.1 ± 0.9 years, p < 0.001). Women with moderate-to-severe OSA had a lower AF burden than men did (27.6 ± 7.1 vs. 49.5 ± 3.9%, p = 0.009).

Conclusions

AF burden is a sex-specific risk factor for OSA and is limited to men. In contrast, women with both AF and OSA have a lower AF burden than men, despite being older and having similar OSA severity and body habitus. Thus, AF may develop later in women with OSA than in men.

International Consensus Statement on Obstructive Sleep Apnea

BACKGROUND

Evaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA).

METHODS

Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus.

RESULTS

The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA-associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated.

CONCLUSION

This review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence-based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.

Atrial fibrillation-specific refinement of the STOP-Bang sleep apnoea screening questionnaire: insights from the Virtual-SAFARI study

BACKGROUND

Sleep-disordered breathing (SDB) is prevalent in up to 50% of patients referred for atrial fibrillation (AF) catheter ablation (CA). Currently, it remains unclear how to improve pre-selection for SDB screening in patients with AF.

AIM

We aimed to (1) assess the accuracy of the STOP-Bang screening questionnaire for detection of SDB within an AF population referred for CA; (2) derive a refined, AF-specific SDB score to improve pre-selection.

METHODS

Consecutive AF patients referred for CA without a history of SDB and/or SDB screening were included. Patients were digitally referred to the previously implemented Virtual-SAFARI SDB screening and management pathway including a home sleep test. An apnoea-hypopnoea index (AHI) of  ≥ 15 was interpreted as moderate-to-severe SDB. Logistic regression analysis was used to assess characteristics associated with moderate-to-severe SDB to refine pre-selection for SDB screening.

RESULTS

Of 206 included patients, 51% were diagnosed with moderate-to-severe SDB. The STOP-Bang questionnaire performed poorly in detecting SDB, with an area under the receiver operating characteristic curve (AUROC) of 0.647 (95% Confidence-Interval (CI) 0.573-0.721). AF-specific refinement resulted in the BOSS-GAP score. Therein, BMI with cut-off point ≥ 27 kg/m2 and previous stroke or transient ischaemic attack (TIA) were added, while tiredness and neck circumference were removed. The BOSS-GAP score performed better with an AUROC of 0.738 (95% CI 0.672-0.805) in the overall population.

CONCLUSION

AF-specific refinement of the STOP-Bang questionnaire moderately improved detection of SDB in AF patients referred for CA. Whether questionnaires bring benefits for pre-selection of SDB compared to structural screening in patients with AF requires further studies.

TRIAL REGISTRATION NUMBER

ISOLATION was registered NCT04342312, 13-04-2020.

Cardiovascular Complications of Obstructive Sleep Apnea in the Intensive Care Unit and Beyond

Obstructive sleep apnea (OSA) is a common disease with a high degree of association with and possible etiological factor for several cardiovascular diseases. Patients who are admitted to the Intensive Care Unit (ICU) are incredibly sick, have multiple co-morbidities, and are at substantial risk for mortality. A study of cardiovascular manifestations and disease processes in patients with OSA admitted to the ICU is very intriguing, and its impact is likely significant. Although much is known about these cardiovascular complications associated with OSA, there is still a paucity of high-quality evidence trying to establish causality between the two. Studies exploring the potential impact of therapeutic interventions, such as positive airway pressure therapy (PAP), on cardiovascular complications in ICU patients are also needed and should be encouraged. This study reviewed the literature currently available on this topic and potential future research directions of this clinically significant relationship between OSA and cardiovascular disease processes in the ICU and beyond.

Cardiovascular remodeling in obstructive sleep apnea: focus on arterial stiffness, left ventricular geometry and atrial fibrillation

INTRODUCTION

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that is associated with increased risk of cardiovascular disease. The main interest of this clinical review is to discuss the cardiovascular consequences of OSA with a special focus on left ventricular (LV) function and structure, arterial stiffness and atrial fibrillation.

AREA COVERED

We present an overview of the definition, prevalence, and risk factors of OSA and outline the association between OSA and cardiovascular complications. We then briefly discuss echocardiographic assessment in OSA with focus on the left atrium and LV. Finally, we highlight the importance of adherence to continuous positive airway pressure (CPAP) therapy with regard to reducing the risk of cardiovascular disease.

EXPERT COMMENTARY

Although OSA has a strong association with cardiovascular complications, it is often underdiagnosed and undertreated. Patients with resistant hypertension and atrial fibrillation with poor therapeutic success after cardioversion or catheter ablation should be more often screened for OSA. Patients with nocturnal adverse cardiovascular events (stroke, arrhythmias, angina, coronary events) should be closely assessed with regard to OSA, and if confirmed, timely treated by lifestyle modification, CPAP, and aggressive antihypertensive treatment. Adherence to CPAP in OSA patients is essential in terms of reducing the risk of cardiovascular events.

Epicardial adipose tissue, obesity and the occurrence of atrial fibrillation: an overview of pathophysiology and treatment methods

INTRODUCTION

Obesity is a chronic disease, which has significant health consequences and is a staggering burden to health care systems. Obesity can have harmful effects on the cardiovascular system, including heart failure, hypertension, coronary heart disease, and atrial fibrillation (AF). One of the possible substrates might be epicardial adipose tissue (EAT), which can be the link between AF and obesity. EAT is a fat deposit located between the myocardium and the visceral pericardium. Numerous studies have demonstrated that EAT plays a pivotal role in this relationship regarding atrial fibrillation.

AREAS COVERED

This review will focus on the role of obesity and the occurrence of atrial fibrillation (AF) and examine the connection between these and epicardial adipose tissue (EAT). The first part of this review will explain the pathophysiology of EAT and its association with the occurrence of AF. Secondly, we will review bariatric and metabolic surgery and its effects on EAT and AF.

EXPERT COMMENTARY

In this review, the epidemiology, pathophysiology, and treatments methods of AF are explained. Secondly the effects on EAT were elucidated. Due to the complex pathophysiological link between EAT, AF, and obesity, it is still uncertain which treatment strategy is superior.

Cardiorespiratory Polygraphy for Detection of Obstructive Sleep Apnea in Patients With Atrial Fibrillation

Background: Obstructive sleep apnea (OSA) is a modifiable risk factor of atrial fibrillation (AF) but is underdiagnosed in these patients due to absence of good OSA screening pathways. Polysomnography (PSG) is the gold standard for diagnosing OSA but too resource-intensive as a screening tool. We explored whether cardiorespiratory polygraphy (PG) devices using an automated algorithm for Apnea-Hypopnea Index (AHI) determination can meet the requirements of a good screening tool in AF patients.

Methods: This prospective study validated the performance of three PGs [ApneaLink Air (ALA), SOMNOtouch RESP (STR) and SpiderSAS (SpS)] in consecutive AF patients who were referred for PSG evaluation. Patients wore one of the three PGs simultaneously with PSG, and a different PG during each of three consecutive nights at home. Severity of OSA was classified according to the AHI during PSG (<5 = no OSA, 5–14 = mild, 15–30 = moderate, >30 = severe).

Results: Of the 100 included AF patients, PSG diagnosed at least moderate in 69% and severe OSA in 33%. Successful PG execution at home was obtained in 79.1, 80.2 and 86.8% of patients with the ALA, STR and SpS, respectively. For the detection of clinically relevant OSA (AHI ≥ 15), an area under the curve of 0.802, 0.772 and 0.803 was calculated for the ALA, STR and SpS, respectively.

Conclusions: This study indicates that home-worn PGs with an automated AHI algorithm can be used as OSA screening tools in AF patients. Based on an appropriate AHI cut-off value for each PG, the device can guide referral for definite PSG diagnosis.

Atrial fibrillation in older patients and artificial intelligence: a quantitative demonstration of a link with some of the geriatric multidimensional assessment tools-a preliminary report

Atrial fibrillation (AF) associates with disability and frailty. Aim of this study was to evaluate in older AF patients, using artificial intelligence (AI), the relations between geriatric tools and daily standing and resting periods. We enrolled thirty-one > 65 years patients undergoing electrical cardioversion of AF (age: 79 ± 6 years; women: 41.9%; CHA₂DS₂-VASc: 3.7 ± 1.2; MMSE: 27.7 ± 2.7; GDS: 3.0 ± 2.8). The data of the first day following the procedure were analyzed using machine-learning techniques in a specifically designed cloud platform. Standing, activity, time (582 ± 139 min) was directly associated with MMSE and inversely with GDS. Sleep length was 472 ± 230 min. Light sleep, the longer resting phase, was inversely related to GDS. The Chest Effort Index, a measure of obstructive sleep apnea, grew with GDS. In conclusion, AI devices can be routinely used in improving older subjects' evaluation. A correlation exists between standing time, MMSE, and depressive symptoms. GDS associates to length and quality of sleep.

Screening for Obstructive Sleep Apnea in an Atrial Fibrillation Population: What's the Best Test?

Background

Among individuals with nonvalvular atrial fibrillation (AF), the prevalence of obstructive sleep apnea (OSA) can be as high as 85%. Continuous positive airway pressure treatment for moderate or severe OSA might improve AF outcomes and quality of life, so early identification of OSA might be of value. However, screening questionnaires for OSA are suboptimal because they are weighted toward tiredness and loud snoring, which might be absent in AF patients. NoSAS (Neck, Obesity, Snoring, Age, Sex) is a new OSA questionnaire that excludes these parameters. Acoustic pharyngometry (AP) is a potential novel screening technique that measures pharyngeal cross-sectional area, which is reduced in patients with OSA.

Methods

We prospectively compared the accuracy of the NoSAS, the STOP-BANG questionnaire (Snoring, Tiredness, Observed apnea, blood Pressure, Body mass index, Age, Neck circumference and Gender), and AP with home sleep apnea testing (HSAT) in consecutive patients with nonvalvular AF.

Results

Of 188 participants, 86% had OSA and 49% had moderate or severe OSA. Mean Epworth Sleepiness Scale scores were low; 5.9 (SD, 3.9), indicating that most participants were not sleepy. Receiver operating characteristic curves for comparisons of screening tests with HSAT showed suboptimal accuracy. For moderate plus severe and severe only groups respectively, the area under the curve was 0.50 (95% confidence interval [CI], 0.42-0.58) and 0.42 (95% CI, 0.34-0.52) for AP, 0.65 (95% CI, 0.58-0.73) and 0.63 (95% CI, 0.52-0.74) for the STOP-BANG questionnaire, and 0.68 (95% CI, 0.60-0.75) and 0.69 (95% CI, 0.59-0.80) for the NoSAS.

Conclusions

AP and NoSAS are not sufficiently accurate for screening AF patients for OSA. Because of the high rates of OSA in this cohort, the potential benefits of OSA treatment, and the suboptimal accuracy of current screening questionnaires, cardiologists should consider HSAT for AF patients.

Sleep apnea screening instrument evaluation and novel model development and validation in the paroxysmal atrial fibrillation population

Standard sleep apnea (SA) screening instruments perform suboptimally in the atrial fibrillation (AF) population. We evaluated and optimized common OSA screening tools in the AF population. Participants of the Sleep Apnea and Atrial Fibrillation Biomarkers and Electrophysiologic Atrial Triggers (SAFEBEAT, NCT02576587) age (±5 years)-, sex-, body mass index (BMI ± 5 kg/m²)-matched case control study (n = 150 each group) completed concurrent questionnaires and overnight polysomnography. Models based on STOP, STOP-BANG, Berlin, NoSAS and Epworth Sleepiness Scale and also models with STOP-BANG predictors with resting heart rate or left atrial volume were constructed. “Best subset” analysis was used to select a predictor subset for evaluation. We assessed test performance for two outcome thresholds: apnea-hypopnea index (AHI) ≥ 5 and AHI ≥ 15. Paroxysmal AF participants were: 61.3 ± 12.1 years, BMI = 31.2 ± 6.6 kg/m² with median AHI = 11.8(IQR: 3.8, 24.5); 65 (43.3%) with AHI ≥ 15. Only STOP and STOP-BANG did not perform worse in AF relative to controls. For AHI ≥ 15, STOP-BANG (AUC 0.71, 95%CI:0.55–0.85) did not perform as well as NABS – a composite of neck circumference, age, and BMI as continuous variables and snoring (AUC 0.88, 95%CI:0.76–0.96). Optimal model for AHI ≥ 15 was NABS (sensitivity = 45%, specificity = 97%). For AHI ≥ 5, NABS was also the best performing (AUC 0.82, 95%CI:0.68–0.92, sensitivity = 78%, specificity = 67%). We identify a novel, short-item SA screening instrument for use in paroxysmal AF, i.e. NABS, with improved discriminative ability compared to commonly-used instruments. Further validation studies are needed to assess utility in other AF subtypes.

Trial registration: clinicaltrials.gov NCT02576587.

Atrial fibrillation is associated with central sleep apnea in clinic patients undergoing diagnostic polysomnography

Introduction

Sleep apnea is highly prevalent in patients with atrial fibrillation (AF). Obstructive sleep apnea (OSA) is the most common type, and best studied in the context of AF. However, recent investigations have indicated that central sleep apnea (CSA) may be a risk factor for incident AF. We evaluated the burden of CSA events in patients referred for diagnostic polysomnography (PSG) and whether AF is associated with CSA.

Methods

We identified patients with and without a history of AF who underwent clinically indicated PSG in a matched manner. OSA was defined as obstructive apnea‐hypopnea index (AHI) ≥15/h, and CSA was defined as central apnea index (CAI) ≥5/h. The association between AF and CSA was evaluated using multivariable logistic regression.

Results

Among 465 patients included, mean AHI was 25.5/h, and mean CAI was 1.7/h. OSA prevalence was 53.3%, while CSA prevalence was 8.4%. The prevalence of OSA in the AF and non‐AF groups (54.7% vs 52.0%, P = .56) was similar. CSA was more common in the AF group (12.3% vs 4.4%, P = .002). In multivariable analysis, AF (OR: 2.19 [1.02, 5.03], P = .05), male gender (OR: 2.5 [1.17, 5.84], P = .02), and older age (OR: 2.44, [1.16, 5.46], P = .02) were associated with CSA.

Conclusion

Though CSA is much less common than OSA in patients with AF, the presence of AF is independently associated with CSA.

Comparing manual and automatic scoring of sleep monitoring data from portable polygraphy

We used sleep monitoring data from a study that investigated the prevalence, characteristics, risk factors and type of sleep apnea (SA) in 579 patients with paroxysmal atrial fibrillation. Most patients were screened for two nights, resulting in 1,043 sleep recordings that each contained data from one night. SA was diagnosed using the Nox T3 portable sleep monitor. An experienced sleep specialist scored the recordings manually using Noxturnal software. A total of 157 women (27%) and 422 men (73%) were examined; 477 (82.7%) had an apnea-hypopnea index (AHI) ≥ 5/hr, whereas moderate to severe SA (AHI ≥ 15/hr) was diagnosed in 243 patients (42.1%). The AHI derived from automatic and manual scoring showed a good agreement (Pearson's r coefficient of 0.96). The median difference in AHI was very small (i.e., 0.72 [mean difference, 1.06]), but was statistically significant (p < .0001). Automatic scoring classified sleep recordings with more than 90% accuracy into SA categories of mild (AHI ≥ 5/hr), moderate (AHI ≥ 15/hr) and severe (AHI ≥ 30/hr). We found a minor (11%-21%) mis-estimation of the number of recordings right above and below the boundary separating mild and moderate SA. The accuracy of automatic scoring differed from recording to recording, especially regarding the sensitivity of detecting disrupted breathing events. We found low to moderate agreement for the duration of disrupted breathing events (r = .53), for which the automatic scoring led to a statistically significant overestimation by 5.22 s (p < .0001).