Sleep apnea detection by a cardiac resynchronization device integrated thoracic impedance sensor: A validation study against the gold standard polysomnography

Obstructive sleep apnea diagnosis and beyond using portable monitors

Obstructive sleep apnea (OSA) is a chronic sleep and breathing disorder with significant health complications, including cardiovascular disease and neurocognitive impairments. To ensure timely treatment, there is a need for a portable, accurate and rapid method of diagnosing OSA. This review examines the use of various physiological signals used in the detection of respiratory events and evaluates their effectiveness in portable monitors (PM) relative to gold standard polysomnography. The primary objective is to explore the relationship between these physiological parameters and OSA, their application in calculating the apnea hypopnea index (AHI), the standard metric for OSA diagnosis, and the derivation of non-AHI metrics that offer additional diagnostic value. It is found that increasing the number of parameters in PMs does not necessarily improve OSA detection. Several factors can cause performance variations among different PMs, even if they extract similar signals. The review also highlights the potential of PMs to be used beyond OSA diagnosis. These devices possess parameters that can be utilized to obtain endotypic and other non-AHI metrics, enabling improved characterization of the disorder and personalized treatment strategies. Advancements in PM technology, coupled with thorough evaluation and validation of these devices, have the potential to revolutionize OSA diagnosis, personalized treatment, and ultimately improve health outcomes for patients with OSA. By identifying the key factors influencing performance and exploring the application of PMs beyond OSA diagnosis, this review aims to contribute to the ongoing development and utilization of portable, efficient, and effective diagnostic tools for OSA.

Implants with Sensing Capabilities

Because of the aging human population and increased numbers of surgical procedures being performed, there is a growing number of biomedical devices being implanted each year. Although the benefits of implants are significant, there are risks to having foreign materials in the body that may lead to complications that may remain undetectable until a time at which the damage done becomes irreversible. To address this challenge, advances in implantable sensors may enable early detection of even minor changes in the implants or the surrounding tissues and provide early cues for intervention. Therefore, integrating sensors with implants will enable real-time monitoring and lead to improvements in implant function. Sensor integration has been mostly applied to cardiovascular, neural, and orthopedic implants, and advances in combined implant-sensor devices have been significant, yet there are needs still to be addressed. Sensor-integrating implants are still in their infancy; however, some have already made it to the clinic. With an interdisciplinary approach, these sensor-integrating devices will become more efficient, providing clear paths to clinical translation in the future.

Implantable cardiac devices in sleep apnoea diagnosis: A systematic review and meta-analysis

BACKGROUND

A particularly high burden of sleep apnoea is reported in patients treated with cardiac implants such as pacemakers and defibrillators. Sleep apnoea diagnosis remains a complex procedure mainly based on sleep and respiratory indices captured by polysomnography (PSG) or respiratory polygraphy (PG).

AIM

We aimed to evaluate the performance of implantable cardiac devices for sleep apnoea diagnosis compared to reference methods.

METHOD

Systematic structured literature searches were performed in PubMed, Embase and. Cochrane Library was performed to identify relevant studies. Quantitative characteristics of the studies were summarized and a qualitative synthesis was performed by a randomized bivariate meta-analysis and completed by pre-specified sensitivity analyses for different implant types and brands.

RESULTS

16 studies involving 999 patients met inclusion criteria and were included in the meta-analysis. The majority of patients were men, of mean age of 64 ± 4.6 years. Sensitivity of cardiac implants for sleep apnoea diagnosis ranged from 60 to 100%, specificity from 50 to 100% with a prevalence of sleep apnoea varying from 22 to 91%. For an apnoea-hypopnoea index threshold ≥30 events/h during polysomnography (corresponding to severe sleep apnoea), the overall performance of the implants was relevant with a sensitivity of 78% and a specificity of 79%. Subgroup analyses on implant type and brand provided no additional information owing to the small number of studies.

CONCLUSION

The respiratory disturbance index provided by cardiac implants is clinically relevant and might improve access to sleep apnoea diagnosis in at-risk cardiovascular populations. PROSPERO Registration number: CRD42020181656.

A Minimum Set of Physiological Parameters to Diagnose Obstructive Sleep Apnea Syndrome Using Non-Invasive Portable Monitors. A Systematic Review

Introduction. Despite its high accuracy, polysomnography (PSG) has several drawbacks for diagnosing obstructive sleep apnea (OSA). Consequently, multiple portable monitors (PMs) have been proposed. Objective. This systematic review aims to investigate the current literature to analyze the sets of physiological parameters captured by a PM to select the minimum number of such physiological signals while maintaining accurate results in OSA detection. Methods. Inclusion and exclusion criteria for the selection of publications were established prior to the search. The evaluation of the publications was made based on one central question and several specific questions. Results. The abilities to detect hypopneas, sleep time, or awakenings were some of the features studied to investigate the full functionality of the PMs to select the most relevant set of physiological signals. Based on the physiological parameters collected (one to six), the PMs were classified into sets according to the level of evidence. The advantages and the disadvantages of each possible set of signals were explained by answering the research questions proposed in the methods. Conclusions. The minimum number of physiological signals detected by PMs for the detection of OSA depends mainly on the purpose and context of the sleep study. The set of three physiological signals showed the best results in the detection of OSA.

Pacemaker guided screening for severe sleep apnea, a possible option for patients with atrial fibrillation: A systematic review and meta-analysis

INTRODUCTION

Obstructive sleep apnea is often underdiagnosed in atrial fibrillation (AF) patients although it is an important risk factor. A systematic review and meta-analysis was performed to assess which techniques cardiac implantable electronic devices (CIED) and Holter monitors use to screen for sleep apnea (SA), and to evaluate if these are suitable for AF patients from a diagnostic accuracy perspective.

METHODS

The search was conducted in accordance with the PRISMA-guidelines. PICO was defined as (P) patients with AF, (I) Holter monitors or CIED suitable for screening for SA, (C) overnight polysomnography (PSG), (O) positive screening with subsequent positive polysomnographic diagnosis of SA. Optimal index test cut-off points corresponding to reference test cut-off for severe SA (PSG-AHI ≥ 30) were compared. Meta-analysis was conducted for the diagnostic odds ratio (DOR), with forest plot and ROC-curve for summary DOR.

RESULTS

A total of five prospective cohort studies (n = 192) were included in the systematic review of which four studies (n = 132) were included in the meta-analysis. All included studies use transthoracic impedance measurement as a screening parameter. No studies evaluating Holter monitors were included. The population consisted of patients indicated for pacemaker implantation. The summary DOR was 27.14 (8.83; 83.37), AUC was 0.8689 (0.6872; 0.9456) and Q* was 0.8390 (0.7482; 0.9013).

CONCLUSION

At optimal pacemaker-cut-off, pacemaker-guided screening for severe SA in patients with AF can be an effective triage tool for clinical practice. Further studies with larger sample sizes are needed to strengthen the evidence for this conclusion.

Central Sleep Apnea and Pacing-Induced Cardiomyopathy

The role of central sleep apnea (CSA) in pacing-induced cardiomyopathy (PICM) remains speculative. In a prospective trial entitled UPGRADE, the presence of CSA was assessed by single-night polysomnography (PSG) in 54 PICM patients within 1 month after left ventricular lead implantation (with biventricular stimulation still not activated). CSA was diagnosed in half of patients (n = 27). Patients with moderate or severe CSA were randomized to cardiac resynchronization therapy (CRT) versus right ventricular pacing (RVP) in a double-blinded cross-over design and re-scheduled for a follow-up PSG within 3 to 5 months. After crossing-over of stimulation mode another PSG was conducted 3 to 5 months later. CRT led to a significant increase in left ventricular ejection fraction and significant reduction in left ventricular end systolic volumes and N-terminal pro brain natriuretic peptide plasma levels, whereas no significant effects were observed with ongoing RVP. CSA was significantly improved after 3.9 (3.2 to 4.4) months of CRT: apnea-hypopnea index decreased from 39.1 (32.1 to 54.0) events per hour at baseline to 22.2/h (10.9 to 36.7) by CRT (p <0.001). Central apnea index decreased from 27.1/h (17.7 to 36.1) at baseline to 6.8/h (1.1 to 14.4) after CRT activation (p <0.001). Ongoing RVP yielded only a minor improvement in apnea-hypopnea index and central apnea index. Pre-existent CSA did not affect structural response rate and had no impact on mid-term follow-up (median 2.8 years). In conclusion, CSA is highly prevalent in patients with PICM. CRT upgrading significantly improves CSA leading to a similar outcome in PICM patients without pre-existent CSA.

Supplemental dataset on the influence of cardiac resynchronisation therapy in pacing-induced cardiomyopathy and concomitant central sleep Apnea

This article contains supplemental data to the publication “Central Sleep Apnea and Pacing-Induced Cardiomyopathy” [1], which was the most recent publication of the “UPGRADE” study. It provides in-depth analysis of the effects of cardiac resynchronisation therapy (CRT) in patients suffering from pacing-induced cardiomyopathy (PICM) on cardiac remodeling as well as functional cardiac parameters in comparison to continuous right ventricular pacing (RVP). Furthermore, it also covers additional data on several sleep parameters, which were not presented in the main article including the index for obstructive sleep apnea (OSA), the index for mixed sleep apnea and the oxygen saturation measurements during polysomnography. Further, Kaplan-Meier curves are presented for major adverse cardiac events (MACE) and overall mortality by severity of sleep apnea. Generally, the “UGRADE” study was a single-center prospective double-blinded randomized controlled trial lasting from 2014 to 2020. The methodology included a cross-over design giving the possibility to detect differences while CRT was activated and while continuous RVP was applied. The presented data should aid clinicians in daily practice as upgrading to CRT is not limited to improvement in cardiac parameters, but also modifies sleep apnea in patients with PICM, a generally sparsely studied entity of heart failure.

[Sleep disordered breathing in patients with chronic heart failure: prognosis and management]

Sleep disordered breathing is a frequent comorbidity (50-75%) in patients with chronic heart failure, but it is usually underestimated. This review analyzes sleep disordered breathing in patients with chronic heart failure, demonstrates pathogenetic relationships and the prognostic role of sleep apnea. The authors present modern treatment options for sleep apnea in this cohort (from non-invasive ventilation to implantable devices), highlight the role of drug therapy and outline perspectives of different treatment approaches. This clinical problem is designated as multidisciplinary, which requires a dialogue between researchers and doctors of various specialties to organize comprehensive effective care for this cohort of patients.

Sensors for rate-adaptive pacing: How they work, strengths, and limitations

Chronotropic incompetence is the inability of the sinus node to increase heart rate commensurate with increased metabolic demand. Cardiac pacing alone may be insufficient to address exercise intolerance, fatigue, dyspnea on exertion, and other symptoms of chronotropic incompetence. Rate-responsive (adaptive) pacing employs sensors to detect physical or physiological indices and mimic the response of the normal sinus node. This review describes the development, strengths, and limitations of a variety of sensors that have been employed to address chronotropic incompetence. A mini-tutorial on programming rate-adaptive parameters is included along with emphasis that patients' lifestyles and underlying medical conditions require careful consideration. In addition, special sensor applications used to respond prophylactically to physiologic signals are detailed and an in-depth discussion of sensors as a potential aid in heart failure management is provided.

Novel Technology to Capture Objective Data from Patients' Recovery from Laparoscopic Endometriosis Surgery

STUDY OBJECTIVE

To assess the feasibility of a noncontact radio sensor as an objective measurement tool to study postoperative recovery from endometriosis surgery.

DESIGN

Prospective cohort pilot study.

SETTING

Center for minimally invasive gynecologic surgery at an academically affiliated community hospital in conjunction with in-home monitoring.

PATIENTS

Patients aged above 18 years who sleep independently and were scheduled to have laparoscopy for the diagnosis and treatment of suspected endometriosis.

INTERVENTIONS

A wireless, noncontact sensor, Emerald, was installed in the subjects' home and used to capture physiologic signals without body contact. The device captured objective data about the patients' movement and sleep in their home for 5 weeks before surgery and approximately 5 weeks postoperatively. The subjects were concurrently asked to complete a daily pain assessment using a numeric rating scale and a free text survey about their daily symptoms.

MEASUREMENTS AND MAIN RESULTS

Three women aged 23 years to 39 years and with mild to moderate endometriosis participated in the study. Emerald-derived sleep and wake times were contextualized and corroborated by select participant comments from retrospective surveys. In addition, self-reported pain levels and 1 sleep variable, sleep onset to deep sleep time, showed a significant (p <.01), positive correlation with next-day-pain scores in all 3 subjects: r = 0.45, 0.50, and 0.55. In other words, the longer it took the subject to go from sleep onset to deep sleep, the higher their pain score the following day.

CONCLUSION

A patient's experience with pain is challenging to meaningfully quantify. This study highlights Emerald's unique ability to capture objective data in both preoperative functioning and postoperative recovery in an endometriosis population. The utility of this uniquely objective data for the clinician-patient relationship is just beginning to be explored.

Increased respiratory disturbance index measured using an advanced device algorithm is associated with heart failure development

Previous studies suggested that sleep-disordered breathing was associated with cardiovascular diseases such as heart failure (HF). Recently, algorithms of cardiac implantable electronic devices (CIEDs) have been developed to detect advanced sleep apnea (SA); the Apnea Scan (AP Scan) being an example. The purpose of this study was to investigate the association between respiratory disturbance index (RDI) measured using the AP Scan algorithm and HF development. We retrospectively studied consecutive patients with CIEDs equipped with the AP Scan algorithm which were implanted between December 1, 2011 and March 31, 2019. These patients were divided into 2 groups according to the trends of RDI: patients with a continually high RDI > 30 (severe SA group) and those without a continually high RDI (non-severe SA group). There were 16 and 46 patients in the severe and non-severe SA groups, respectively. Increased left ventricular end-diastolic and end-systolic dimensions were observed in the severe SA group. Regarding cardiovascular events, HF was observed in 8 patients (50.0%) in the severe SA group and 1 patient (2.2%) in the non-severe SA group; thus, there was a significantly higher proportion of patients with HF in the severe SA group. In conclusion, continually high RDI was associated with HF development in patients with CIEDs equipped with the AP Scan algorithm. Therefore, an elevated RDI may be a risk factor for the development of HF in patients with CIEDs.