Author + information
- Dominik Linz, MD, PhD,
- Anthony G. Brooks, PhD,
- Adrian D. Elliott, PhD,
- Jonathan M. Kalman, MBBS, PhD,
- R. Doug McEvoy, MD,
- Dennis H. Lau, MBBS, PhD and
- Prashanthan Sanders, MBBS, PhD∗ (, )@PrashSanders
- ↵∗Centre for Heart Rhythm Disorders, Department of Cardiology, Royal Adelaide Hospital, Adelaide, 5000, Australia
Sleep-disordered breathing (SDB) severity is largely determined by the number of apneas and hypopneas/h during a single overnight sleep study, following which patients are categorized as no, mild, moderate, or severe SDB (1). However, SDB severity in an individual patient may not be stable over time, but may instead exhibit a considerable night-to-night variability, which might result in a dynamic exposure to SDB-related conditions affecting the timing and extent of cardiovascular responses such as atrial fibrillation (AF) (2). Although chronic atrial structural alterations have already been described in AF patients with SDB (3), clinical evidence for a dynamic AF substrate related to nightly SDB severity is lacking.
In this observational cohort study, we examined the relationship between simultaneous long-term day-by-day SDB and AF monitoring extracted from a deidentified home monitoring database of 191 patients with LivaNova Reply 200 (LivaNova, London, United Kingdom) or Kora 100 DR (Sorin CRM, Clamart, France) dual-chamber pacemakers implanted according to guideline-directed indications. Irrespective of the diagnosis of SDB or AF, daily SDB severity was assessed by the implemented sleep apnea monitoring (SAM) algorithm measuring a daily respiratory disturbance index (RDI) that has been previously validated against polysomnography (4). Daily AF burden was assessed based on total cumulative “mode switch events,” which were manually adjudicated. A total of 119 patients were excluded for different reasons: <1 month follow-up, SAM turned off, unreliable mode switches, >10% nights with invalid RDI, and >25% AF burden. A binary logistic generalized estimating equation (SPSS, version 24, IBM, Armonk, New York) was used to develop a prediction model for the dichotomous AF outcome (>5 min of cumulative mode switch per day) using the within-patient standardized (via quartiles) SDB severity data.
The final sample consisted of 72 deidentified SAM-monitored dual-chamber pacemaker patients. The mean follow-up per patient was 21 ± 8 weeks, resulting in a total daily monitoring time for the sample of 10,383 days. The average RDI across the sample was 17.9 ± 11.5/h. The individual mean night-to-night RDI coefficient of variation was 41 ± 16%, which reflected an absolute SD of 6.3/h (range: 2/h to 14/h). A total of 57% had at least a single mode-switch episode recorded, and the total mode-switch burden ranged from 0% to 24%, with a median daily episode duration of 12 min (range: 1 min to 84 min). Cumulative daily AF >5 min was observed in 44% of patients. Figure 1 shows an example of simultaneous RDI and AF long-term monitoring. Within each patient, the nights with the highest RDI (in their highest quartile) conferred a 1.6-fold (range: 1.2-fold to 2.1-fold) (p = 0.001) increased risk of having at least 5 min AF during that same day compared with the quartile with the lowest RDI (“SDB begets AF”). To test for a potential bidirectional relationship with “AF begets SDB,” we reanalyzed the dataset with a 1-day offset between the AF episode and the RDI, but found that none of the relationships remained.
These findings have important implications for the assessment of SDB severity and the guidance of SDB treatment. A considerable night-by-night variability in SDB severity exists, which cannot be identified by a single overnight sleep study and would lead to frequent misclassification of SDB status. Rather than a categorical diagnosis of SDB from a single overnight sleep study, SDB burden, determined as the proportion of nights with higher RDI, may be a better metric to assess the extent of dynamic SDB-related cardiovascular responses and cardiovascular outcomes. Further studies in well-characterized patient cohorts are needed to investigate the effect of concomitant risk factors on SDB day-to-day variability and whether the findings are applicable to the general AF population. The identification of best technology to assess daily SDB severity and guide SDB treatment and its effect on clinical outcomes warrants further prospective intervention studies.
Please note: LivaNova R&D department exported the deidentified pacemaker records. Dr. Linz is supported by a Beacon Research Fellowship by the University of Adelaide; has served on the advisory board of LivaNova and Medtronic; has received lecture and/or consulting fees from LivaNova, Medtronic, and ResMed; and has received research funding from Sanofi, ResMed, and Medtronic. Dr. Brooks is an employee of Microport. Dr. Elliott is supported by an Early Career Fellowship from the National Heart Foundation of Australia. Drs. Kalman, McEvoy, and Sanders are supported by Practitioner Fellowships from the National Health and Medical Research Council of Australia. Dr. McEvoy has received research funding from Philips Respironics, ResMed, and Fisher & Paykel. Dr. Lau is supported by the Robert J. Craig Lectureship from the University of Adelaide; has received consulting fees from St. Jude Medical; and has received speaker's fees from St. Jude Medical, Bayer, Boehringer Ingelheim, and Bristol-Myers Squibb/Pfizer. Dr. Sanders is supported by the National Heart Foundation of Australia; has served on the advisory board of Biosense Webster, Medtronic, St. Jude Medical, Boston Scientific, and CathRx; has received lecture and/or consulting fees from Biosense Webster, Medtronic, St. Jude Medical, and Boston Scientific; has received research funding from Medtronic, St. Jude Medical, Boston Scientific, Biotronik, and Sorin; and the University of Adelaide has received, on his behalf, lecture and/or consulting fees from Biosense Webster, Medtronic, St. Jude Medical, and Boston Scientific, and research funding from Medtronic, St. Jude Medical, Boston Scientific, Biotronik, and LivaNova.
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