Variability in obstructive sleep apnea: Analysis of pacemaker-detected respiratory disturbances

Moubarak, Ghassan; Bouzeman, Abdeslam; d’Orth, Thibaut de Geyer; Bouleti, Claire; Beuzelin, C.; Cazeau, Serge

doi:10.1016/j.hrthm.2016.11.033

Cited by 20 publications

(14 citation statements)

References 20 publications

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“…Specifically, in 36% of patients in whom multiple measurements were taken over a period of 7 days prior to the sleep study, we recorded RDI values both below and above the identified cutoff for severe SA. Similar observations of a wide intra-individual variability in AHI/RDI values were reported in a series of patients undergoing multiple polysomnographic recordings [23] at different time points (mean interval 3.3 weeks), as well as in a cohort of 58 patients [24] with PMKs equipped with a respiratory sensor from a different brand (mean intraindividual day-to-day RDI variability 19% ± 21%). In our opinion, this preliminary result seems to question the clinical validity of a single assessment by means of PSG, in that the variability of the value overtime could result in inaccurate diagnoses and therapeutic decisions.…”

Section: Discussionsupporting

confidence: 82%

Feasibility of automated detection of sleep apnea using implantable pacemakers and defibrillators: a comparison with simultaneous polysomnography recording

Rocca

Albanese

Placidi

et al. 2019

J Interv Card Electrophysiol

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Purpose Sleep-related breathing disorders (SRBD) have been associated with adverse cardiovascular events and prognosis. Some modern pacemakers (PMK) and implantable cardioverter defibrillators (ICD) are equipped with thoracic impedance monitoring systems which allow detecting fluctuations in tidal volume occurring in SRBD. This study aimed at assessing the accuracy of a novel transthoracic impedance-based PMK/ICD sensor for automatic detection of SRBD.Methods We prospectively enrolled 31 consecutive patients scheduled for implantation of a PMK or an ICD with sleep respiratory disturbances monitoring capability. The results of unattended home nocturnal recordings expressed as apnea/hypopnea index (AHI) were compared with the respiratory disturbance index (RDI) stored in the cardiac device memory at the time polygraphy was performed. Results Among the 31 enrolled patients (20 men, mean age 70 ± 8 years), a comparison between the data from polygraphy and cardiac device was feasible in 29 patients. According to the results of home nocturnal recording, a severe SRBD was observed in 7/29 (24.1%) patients. On the basis of receiver-operating characteristic curve analysis of RDI values, the optimal RDI cutoff value to identify severe SRBD was 47 episodes/h (sensitivity 100%, specificity 100%). Bland-Altman agreement analysis of AHI-RDI revealed a bias between measurements of − 11 episodes/h, with limits of agreement − 38 to 15 episodes/h. Conclusions In the present study, the novel transthoracic impedance-based monitoring system ApneaScan TM appeared effective in screening PMK and ICD patients for SRBD.

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Section: Discussionsupporting

confidence: 82%

Feasibility of automated detection of sleep apnea using implantable pacemakers and defibrillators: a comparison with simultaneous polysomnography recording

Rocca

Albanese

Placidi

et al. 2019

J Interv Card Electrophysiol

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“…The large sample size may explain why the RESPIRE study showed a statistically significant association between increased severity of SA and AF, which was not found in the smaller 6-month pilot study by Moubarak et al 9 The findings of RESPIRE, however, confirm those of a recent study by Mazza et al, 15 which showed that pacemaker patients with device-diagnosed severe SA at baseline have twice the risk of AF compared with pacemaker patients with nonsevere SA (hazard ratio 2.38; 95% CI 1.21-4.66; P 5 .025). Severe SA at baseline and history of AF (paroxysmal) were also found to be independent predictors of AF.…”

Section: Discussionmentioning

confidence: 83%

“…7 Pacemakers capable of detecting respiratory disturbance may be used as a screening tool for detecting SAS and provide long-term information on changes in the severity of SA over time. [8][9][10] The feature has the added advantage vs polysomnography of monitoring sleep continuously every night.…”

Section: Introductionmentioning

confidence: 99%

Incidence of sleep apnea and association with atrial fibrillation in an unselected pacemaker population: Results of the observational RESPIRE study

et al. 2020

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BACKGROUND Patients with atrial fibrillation (AF) often have sleep apnea (SA), but diagnosis of SA with polysomnography is costly. SA monitoring is a pacemaker feature that measures respiratory disturbance index, the sum of abnormal respiratory events divided by sleep duration. OBJECTIVE The purpose of this study was to evaluate the incidence and severity of SA and its association with AF in an unselected population fitted with pacemakers. METHODS RESPIRE (REgistry of Sleep APnea monItoring and Atrial Fibrillation in pacemakeR patients) was a multicenter, international, observational, open-label study following adult subjects for 18 months after implantation with an SA monitoring-enabled dual-chamber pacemaker. Severe SA was defined as average respiratory disturbance index 20 from implantation to follow-up visit. The first co-primary end point was the difference in significant AF (cumulative AF episodes lasting 24 hours over 2 consecutive days) between subjects with severe and those nonsevere SA at 12 months in the full analysis set (N 5 553). The second co-primary end point was the rate of major serious adverse events at 18 months in the modified intention-to-treat set (N 5 1024). RESULTS Severe SA was detected in 31.1% (172 of 553). A higher incidence of significant AF was reported in patients with severe SA than in patients with nonsevere SA (25.0% vs 13.9%; difference 11.1%; 95% confidence interval 3.7%-18.4%; P 5 .002). Significant AF increased with time in both groups, but at a faster rate in the severe SA group. No intergroup difference in the overall rate of major serious adverse events was observed (P 5 .065). CONCLUSION SA screening over 12 months identified severe SA in almost one-third of unselected patients fitted with pacemakers. Severe SA was associated with a higher incidence of significant AF.

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“…Some recent publications have added significant information about the detection of SA in patients with cardiac implants 2,9–13 . D’Onofrio et al .…”

Section: Discussionmentioning

confidence: 99%

Validation of an apnea and hypopnea detection algorithm implemented in implantable cardioverter defibrillators. The AIRLESS study

Defaye

Mendelson

Tamisier

et al. 2019

Sci Rep

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Diagnosis of sleep apnea (SA) using simple tools has the potential to improve the efficacy of cardiac implants in the prevention of cardiac arrhythmias. The aim of the present study was to validate a transthoracic impedance sensor for SA diagnosis in patients with cardiac implants. We compared the apnea-hypopnea index (AHI) obtained from polysomnography (AHI PSG ) with the AHI obtained from autoscoring algorithms of the ApneaScan implantable impedance respiration sensor (AHI AS ) three months after implantation of cardioverter-defibrillator (ICD) or cardiac resynchronization therapy-defibrillator (CRT-D) devices. Twenty-five patients with indications for implantation of ICD or CRT-D (INCEPTA; Boston Scientific) (24 men, 59.9 ± 14.4 years; LVEF 30.3 ± 6.4%; body mass index 25.9 ± 4.2 kg/m²) were included. Mean AHI- PSG was 21.9 ± 19.1 events/hr. A significant correlation was found between AHI PSG and AHI AS especially for the most severe SA (Spearman correlation: 0.71, p < 0.001). Intraclass Correlation Coefficient (was in the expected range: 0.67, 95% CI: 0.39–0.84. The mean bias was 5.4 events per hour (mean AHI: 23.3 ± 14.6 versus 29.7 ± 13.7 for AHI- PSG and AHI- AS, respectively). An optimal cutoff value for the AHI AS at 30 events/h was obtained from the Receiver Operator Characteristic (ROC) curve analysis, which yielded a sensitivity of 100%, a specificity of 80%, PPV = 67%, NPV = 100%. Using an advanced algorithm for autoscoring of transthoracic impedance included in ICDs is reliable to identify SA and has the potential to improve the management of patients with cardiac implants.

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Variability in obstructive sleep apnea: Analysis of pacemaker-detected respiratory disturbances

Cited by 20 publications

References 20 publications

Feasibility of automated detection of sleep apnea using implantable pacemakers and defibrillators: a comparison with simultaneous polysomnography recording

Feasibility of automated detection of sleep apnea using implantable pacemakers and defibrillators: a comparison with simultaneous polysomnography recording

Incidence of sleep apnea and association with atrial fibrillation in an unselected pacemaker population: Results of the observational RESPIRE study

Validation of an apnea and hypopnea detection algorithm implemented in implantable cardioverter defibrillators. The AIRLESS study

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