Does obstructive sleep apnoea modulate cardiac autonomic function in paroxysmal atrial fibrillation?

Sequential AF patients were recruited via two centres as part of a prospective diagnostic accuracy study for sleep apnoea in patients with AF [3]. Approval for this trial was obtained from the Northern Sydney Local Health District Human Research Ethics Committee (HREC/16/HAWKE/25) and the North Shore Private Hospital Ethics Committee (approval number 2016–012). The study was performed in accordance with the 1964 Helsinki Declaration and its later amendments. All the patients gave their informed written consent to participate in the study. The trial was registered with the Australian New Zealand Clinical Trials Registry (ANZCTR): 12,616,001,016,426.

The patients were sequentially recruited via two pathways: emergency department admissions with AF and pulmonary vein isolation waitlists at two tertiary centres between July 2016 and September 2019. All the patients had a history of AF (≥ 2 episodes in the past 12 months) and underwent in-laboratory polysomnography (PSG) to investigate OSA. The patients with a previous known diagnosis of sleep apnoea were excluded.

Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 27.0, Armonk, NY: IBM Corp. HRV parameters which were not normally distributed were natural-log transformed to normalise their skewed distributions. Data are presented as the mean + / − standard deviation (SD), or as mean (interquartile range (IQR)) for non-normally distributed data. HRV parameters were compared using t-tests (continuous variables) or chi-square tests (categorical variables) as appropriate. Analysis of covariance (ANCOVA) was performed to adjust for age, sex and BMI. Correlations between HRV parameters and standard measures of OSA severity (AHI, ODI and T < 90%) were performed. This was an exploratory analysis of the comparison of multiple HRV parameters reflecting different aspects of ANS modulation; therefore, we did not adjust the significance level for multiple comparisons. We considered a p value of < 0.05 statistically significant.

A total of 101 AF patients underwent overnight polysomnography. The patients with OSA demonstrated a higher BMI and were predominantly male compared to the no-OSA group. They also had increased hypertension but reduced thyroid disease and peripheral vascular disease. There were no significant differences in other cardiovascular comorbidities including diabetes, ischaemic heart disease (IHD), congestive cardiac failure (CCF) and cerebrovascular disease (CVD), although the OSA group did have a lower ejection fraction (55.5 ± 9.7 vs 59.6 ± 1.1%, p = 0.027). The OSA group also had an increased left atrial area (25.5 ± 5.3 vs 22.3 ± 4.5 cm², p = 0.032) and increased proportion of “high burden AF”, defined as > 12 self-reported episodes in the last 12 months. CHA₂DS₂-Vasc scores were not significantly different between the groups (1.4 ± 1.2 vs 1.7 ± 1.4, p = 0.270). Neither were there significant differences in anti-arrhythmic medications between groups. Although nine patients were excluded from the final HRV analysis, excluded patients were not significantly different from the group in terms of key baseline characteristics including age, sex and BMI. Baseline characteristics are presented in Table 2.

There were no significant differences in the presence of arrhythmia (AF beats, ventricular ectopic beats (VEBs) and supraventricular ectopic beats (SVBs)) between AF patients with and without OSA using a cut-off AHI of 5/h (see Table 2). On subgroup analysis, however, PAF patients with severe OSA (AHI ≥ 30/h) had more AF beats and ventricular ectopic beats (VEBs) than those without severe OSA (22.7 ± 42.8% vs 3.7 ± 17.9%, p = 0.006, 1.7 ± 3.8 vs 0.3 ± 0.9%, p = 0.004, respectively). Similarly, ANOVA for OSA severity groups showed that PAF patients with severe OSA had a higher % AF beats than patients with no OSA or moderate OSA (mean difference 19.8 ± 7.3%, p = 0.040; 22.7 ± 8.3%, p = 0.036 respectively, see Fig. 2) and that PAF patients with severe OSA had a higher %VEBs than patients with mild or moderate OSA (mean difference 1.6 ± 0.5%, p = 0.019; 1.6 ± 0.6%, p = 0.035, respectively). There were no significant differences in SVEs across OSA severity groups.

In non-REM sleep, time-domain measures of HRV did not differ between OSA and no-OSA groups (Table 3). However, we saw selective differences in frequency-domain measures (Table 4). Specifically, PAF patients with OSA showed increased parasympathetic modulation (HF-nu: 48.0 ± 14.6 vs 39.1 ± 15.7, p = 0.01) and reduced sympathetic modulation (LF-nu 43.7 ± 18.0 vs 54.1 ± 19.7, p = 0.01). Consistent with these results, the LF/HF ratio showed a relative decrease in parasympathetic modulation (1.2 ± 1.0 vs 2.1 ± 2.0, p = 0.007) (Table 4). Furthermore, these results remained significant after adjusting for age, sex and BMI.

In REM sleep, time-domain measures of HRV did not differ between OSA and no-OSA groups (AHI ≥ or < 5/h) (Table 3) in PAF patients. PAF patients with OSA showed increased parasympathetic modulation (HF-nu 32.6 ± 16.0 vs 40.5 ± 17.4, p = 0.036); however, significance was not maintained after adjusting for age, sex and BMI (Table 4). We extended the analysis to include OSA at different severity levels (AHI < or > 15/h, AHI < or > 30/h), although the above changes were not significant in these groups (see Tables S3, S4, S5 and S6 in the supplemental material).

We examined correlations between HRV parameters and AHI, as well as other markers of OSA severity, including those that reflect hypoxic burden (ODI and %T < 90). In REM sleep, there was a weak negative correlation between LF-nu and all markers of OSA severity (AHI, ODI and %T < 90). Correlation analysis of other HRV (time and frequency) measures with OSA severity metrics were not significant (Supplementary material, Table S1 and S2).

In non-REM sleep, we saw a weak negative correlation between average NN interval and ODI as well as %T < 90. Correlations of other time and frequency HRV measures with markers of OSA severity (AHI, ODI and T < 90%) were not significant. (Supplementary material, Tables S1 and S2).

The study methodology provided an opportunity to compare the presence of nocturnal arrhythmia between AF patients with and without OSA, although this was not a primary aim of the study. On patient recall at interview, the patients in the OSA group reported a higher incidence of “high burden” AF, defined as ≥ 10 episodes in the past 12 months (8/36 patients (22%) vs 23/62 patients (37.1%), p = 0.039. On the sleep study night, there was no significant difference in % AF beats between the OSA and no-OSA groups, although the trend towards increased %AF beats in the OSA group was noted (2.9 ± 16.6 vs 8.1 ± 26.4%, p = 0.283. On subgroup analysis, however, the patients with severe OSA (AHI > 30/h) had more AF beats and more ventricular ectopic beats, but not supraventricular ectopic beats on nocturnal polysomnography. Similarly, PAF patients with severe OSA had a higher % AF beats than patients with no OSA or moderate OSA (mean difference 19.8 ± 7.3%, p = 0.040; 22.7 ± 8.3%, p = 0.036, respectively, Fig. 2). These findings of higher AF burden according to OSA severity are consistent with the findings of Mehra et al. [44], showing that nocturnal arrhythmia including AF and VEBs were more common in patients with severe sleep-disordered breathing, also using a cut-off of AHI > 30/h. To our knowledge, our study is the first to replicate this finding in a cohort of patients with PAF with and without OSA.

Although this study provides some novel insights into the HRV profile of those with OSA and PAF, there are limitations to the study. Twenty-four hour Holter recording is ideal for HRV analysis, accounting for both diurnal and nocturnal variability [7]. For this study, HRV parameters were derived from nocturnal polysomnograpy and thus are subject to all the usual autonomic perturbations of sleep, which may explain the selective differences seen across time and frequency-domain measures. Furthermore, we were unable to control for differences in undiagnosed conduction disturbances between the two groups, including, for example, the presence of sinus nodal disease which has a high prevalence in AF patients [45]. However, we analysed only periods of sinus rhythm in order to minimise the contribution of AV nodal dysfunction. Our study contained some patients who had undergone previous PVI: patients had, on average, undergone 0.4 ± 0.6 previous PVI procedures. Since PVI may cause neuronal damage to the intrinsic cardiac nervous system [46], caution must be used when extrapolating the results to other groups. Although we excluded periods of arrhythmia, it is possible that autonomic disturbances related to the arrhythmia may have preceded or persisted beyond these events. It is also possible that HRV parameters may have been impacted by autonomic disruptions from acute obstructive respiratory events in the OSA group. We attempted to allow for this by excluding ECG trace during and immediately following sleep apnoea events from the analysis; however, we excluded a post-event period of 15 s, and it is possible autonomic disturbance may persist beyond this interval. In addition, some sub-criterion respiratory events are likely to have remained in the analysis.

There is mounting evidence that the perturbations during OSA have a profound influence on the myocardium [6]. Atrial remodelling leading to changes to the electrical conduction and ANS activation is thought to trigger and maintain AF [6]. Our work shows altered autonomic function in PAF patients with co-morbid OSA which we believe supports previous observations that progression of AF is promoted by the presence of modifiable risk factors such as OSA [5, 6]. Treatment of OSA may modulate autonomic function and protect the atrial myocardium from pro-arryhthmic autonomic influences from OSA. Therefore, future studies should look to replicate our findings in a larger cohort and determine the effect of OSA therapy on modulation of the ANS and whether indeed such interventions may mitigate arrhythmogenesis in PAF.