Accuracy and utility of a pacemaker respiratory monitoring algorithm for the detection of obstructive sleep apnea in patients with atrial fibrillation

Diagnosis of Obstructive Sleep Apnea in Patients with Associated Comorbidity

Obstructive sleep apnea (OSA) is a heterogeneous disease with many physiological implications. OSA is associated with a great diversity of diseases, with which it shares common and very often bidirectional pathophysiological mechanisms, leading to significantly negative implications on morbidity and mortality. In these patients, underdiagnosis of OSA is high. Concerning cardiorespiratory comorbidities, several studies have assessed the usefulness of simplified screening tests for OSA in patients with hypertension, COPD, heart failure, atrial fibrillation, stroke, morbid obesity, and in hospitalized elders.The key question is whether there is any benefit in the screening for the existence of OSA in patients with comorbidities. In this regard, there are few studies evaluating the performance of the various diagnostic procedures in patients at high risk for OSA. The purpose of this chapter is to review the existing literature about diagnosis in those diseases with a high risk for OSA, with special reference to artificial intelligence-related methods.

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.

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.