Impact of Sleep Apnea on Nocturnal Parasympathetic Activity in Atrial Fibrillation Patients After Catheter Ablation　― Implications for Heart Rate Variability Analysis ―

Hibiki Iwakoshi; Yusuke C Asada; Mitsuko Nakata; Masahiro Makino; Jun Munakata; Nobunari Tomura; Satoshi Shimoo; Tetsuro Nishimura; Hirokazu Shiraishi; Satoaki Matoba; Keitaro Senoo

doi:10.1253/circj.CJ-23-0682

Abstract

Background: The impact of sleep apnea (SA) on heart rate variability (HRV) in atrial fibrillation (AF) patients has not been investigated.

Methods and Results: Of 94 patients who underwent AF ablation between January 2021 and September 2022, 76 patients who had a nocturnal Holter electrocardiography and polysomnography conducted simultaneously were included in the analysis. A 15-min duration of HRV, as determined by an electrocardiogram during apnea and non-apnea time, were compared between patients with and without AF recurrence at 12 months’ postoperatively. Patients had a mean age of 63.4±11.6 years, 14 were female, and 20 had AF recurrence at 12 months’ follow-up. The root mean square of the difference between consecutive normal-to-normal intervals (RMSSD, ms) an indicator of a parasympathetic nervous system, was more highly increased in patients with AF recurrence than those without, during both apnea and non-apnea time (apnea time: 16.7±4.5 vs. 13.5±3.3, P=0.03; non-apnea time: 20.9±9.5 vs. 15.5±5.9, P<0.01). However, RMSSD during an apneic state was decreased more than that in a non-apneic state in both groups of patients with and without AF recurrence (AF recurrence group: 16.7±4.5 vs. 20.9±9.5, P<0.01; non-AF recurrence group; 13.5±3.3 vs. 15.5±5.9, P=0.03). Consequently, the effect of AF recurrence on parasympathetic activity was offset by SA. Similar trends were observed for other parasympathetic activity indices; high frequency (HF), logarithm of HF (lnHF) and the percentage of normal-to-normal intervals >50 ms (pNN50).

Conclusions: Without considering the influence of SA, the results of nocturnal HRV analysis might be misinterpreted. Caution should be taken when using nocturnal HRV as a predictor of AF recurrence.

It is known that parasympathetic activity is more involved in the development and persistence of atrial fibrillation (AF) than sympathetic activity.¹^–³ Physiological reports show that the neurotransmitter, acetylcholine, shortens action potential duration and refractory period in atrial muscle heterogeneously by activating inward direct current potassium channels.⁴^,⁵ It is also reported that the vagal-releasing polypeptide increases delayed rectifying potassium currents and decreases sodium currents, which causes conduction delays in atrial muscle in a non-cholinergic pathway.⁶^,⁷ This cardiac autonomic activity is reflected in heart rate variability (HRV), a fluctuation in the time intervals between adjacent heartbeats.⁸^,⁹

HRV fluctuates with body position, diet and the physical and emotional stresses of daily life, but it fluctuates more during the night than during the day, so parasympathetic properties are more pronounced at night.¹⁰ HRV during nocturnal sleep is therefore a reliable indicator of cardiac autonomic assessment, and nocturnal HRV measurements have been reported to be a possible predictor of new onset AF.¹¹^,¹² In fact, a recent meta-analysis shows that HRV, especially higher RMSSD (within short-term and long-term periods), was closely related to recurrent AF.¹³

Sleep apnea (SA) has been reported to be a complication in 21–74% in patients with AF, which is higher than that in healthy individuals and patients with other cardiac conditions.¹⁴^–¹⁶ Therefore, the impact of SA on HRV should be considered when assessing HRV during sleep in patients with AF. For example, during SA, parasympathetic activity is suppressed, whereas sympathetic activity is tensed due to hypoxia and changes in intrathoracic pressure caused by upper airway obstruction.¹⁷ The association between HRV and SA is inversely related to the association between HRV and AF recurrence, and SA might alter the impact on the relationship between AF recurrence and HRV.

Therefore, we investigated the relationship between HRV changes and AF recurrence and the effect of SA on HRV changes in a prospective observational study using simultaneous nocturnal Holter electrocardiogram (ECG) and polysomnography in patients with AF after catheter ablation.

Methods

Of those patients who were admitted to Kyoto Prefectural University Hospital for AF ablation between January 2021 and September 2022, we consecutively enrolled 94 patients who simultaneously underwent screening for SA with a polysomnography test and nocturnal Holter ECG during hospitalization. Information on the AF ablation procedure carried out in our hospital can be found in the Supplementary File. Of these, 76 patients were included in the full analysis set; 10 patients for whom polysomnography or a Holter ECG record could not be performed due to poor sensing were excluded and 8 patients for whom HRV analysis was difficult due to high frequency of arrhythmia (3 patients with sinus pause and 5 patients with AF or frequent premature atrial contraction [PAC]) were also excluded (Figure 1). All patients were followed up for 12 months after discharge, and AF recurrence, excluding the blanking period, was assessed every 3 months by using a 12-lead ECG, Holter ECG, or portable electrocardiograph. AF recurrence was defined as AF or atrial tachycardia lasting >30 s. All patients provided informed and written consent.

Figure 1.

Study flowchart. The full analysis set was defined as completion of 12-month follow up after AF ablation. AF, atrial fibrillation; ECG, electrocardiogram; HRV, heart rate viability; PSG, polysomnography.

The polysomnography test was performed with a LS-330 (Fukuda Lifetech), a modified portable SA test recommended by the American Academy of Sleep Studies (AASM) guidelines, which can record nasal airflow and nasal pressure, thoracic and abdominal respiratory movements, transcutaneous blood oxygen saturation, pulse wave, body position, and body movements. A polysomnography test was performed for 10 h at night (21:00–07:00) on the next day after ablation was performed. Subjects were instructed to remain in a supine position for as long as possible, except for waking up to defecate. They self-recorded the time of sleep onset, time of awakening, and time of mid-onset awakening. The average sleep duration and sleep efficiency (time spent asleep/time spent in bed) were calculated from subject self-recordings and information from the body movement sensor. Upon polysomnography analysis, apnea was defined as “≥90% decrease from baseline in respiratory airflow lasting ≥10 s” and hypopnea as “≥30% decrease from baseline in respiratory airflow lasting ≥10 s” and accompanied by “≥3% decrease in SpO2” according to the AASM criteria.¹⁸

Analysis software (SCM-8000, version 56.04; FUKUDA Denshi co, Ltd) was used for the HRV analysis in this study. In this software, the following algorithm is set up for R wave peak detection. First, the highest and sharpest apex of the QRS wave in each of the 2 channels is defined as the trigger position, and then the middle of the trigger position of each channel is defined as the peak position of the R wave. The R wave to R wave interval is measured with reference to this position. The above process is performed automatically. This software has passed the Japanese national standard test “JIS T 60601-2-47:2018; Medical electrical equipment – Part 2-47: Individual requirements for basic safety and basic performance of Holter ECG systems (equivalent to international standard IEC 60601-2-47)”. This standard test also includes content on HRV and has been used in many studies.¹⁹^–²²

In order to assess autonomic activity during specific respiratory states and to reduce as much as possible the influence of body position and artifacts on HRV, short-term HRV was measured during apnea and non-apnea time.⁹ The period for the analysis was determined to be 15 min, in accordance with the guidelines of the Task Forces of the European Society of Cardiology and the North American Society of Electrophysiology, as well as with previous studies.⁸^,²³ The extraction method was as follows. First, non-sleep time was excluded from the entire ECG record based on the subject’s self-record and body movement sensor information. Second, among the events identified as apnea/hypopnea times by polysomnography, the longest sustained event was selected. Apnea that occurred intermittently within 10 s interspersed with compensatory breathing was considered a series of apnea events. Finally, we extracted the consecutive 15 min before the end of the event for analysis, not including arrhythmia time (AF, extrasystole, and bradyarrhythmia; Figure 2). Non-apnea time was also extracted using the same method from the time that was not determined to be apnea/hypopnea time.

Figure 2.

Sampling method for apnea and non-apnea time. Polysomnography analysis results are shown. Respiratory airflow is illustrated by the black line waveform. The red bold bars show the sleep apnea period. The period for heart rate viability (HRV) analysis was extracted according to the following procedure: among the events identified as apnea (red squares)/non-apnea (blue squares) times by polysomnography, the longest sustained event was selected, and consecutive 15 min was extracted before the end of the event for HRV analysis, not including arrhythmia time (AF, extrasystole, and bradyarrhythmia).

In the analysis of short-term HRV, some time-domain indices that are sensitive to recording time cannot be used appropriately, so we measured the most commonly used indices in accordance with the same guidelines of the Task Forces of the European Society of Cardiology and the North American Society of Electrophysiology and previous main studies.⁸^,⁹^,²³ Of the time-domain indices, the mean (AVNN; ms) and standard deviation (SDNN; ms) of normal-to-normal intervals in normal sinus rhythm, the root mean square of the difference between consecutive NN intervals (RMSSD; ms), and the percentage of NN intervals >50 ms that are different from the preceding interval (pNN50; %) were measured. Of the frequency domain indices converted by using the modified entropy method and evaluated in the range of 0–0.40 Hz, the low-frequency component (LF; ms²), ranging from 0.04 to 0.15 Hz, the high-frequency component (HF; ms²), ranging from 0.15 to 0.4 Hz, and their natural logarithms (lnLF, lnHF) were calculated.

In addition, in order to examine the effect of sampling time on HRV indices in the exploratory way, we randomly selected 5 subjects each with and without AF recurrence among the subjects in this study and confirmed that there was no significant difference in each of the HRV indices at specific times during sleep (23:00–23:15, 01:00–01:15, and 03:00–03:15) (Supplementary Table 1).

Statistical Analysis

Continuous variable data are presented as mean±standard deviation for normally distributed data and median [interquartile range] for non-normally distributed data. Tests between continuous variables were performed as follows. When comparing HRV indices between the sampling time by AF status, a paired t-test was used for normally distributed data and Wilcoxon’s signed rank test for non-normally distributed data. And when comparing HRV indices between the ablation procedures by apnea status, a t-test was used for normally distributed data and Wilcoxon’s rank sum test for non-normally distributed data. To estimate the effect of AF recurrence and SA on HRV indices, a linear mixed-effects model was used with AF recurrence, SA, and their interaction as fixed effects, and study participants as a random effect. The hypothesis tests were conducted between Group 1 (AF recurrence +, apnea +), Group 2 (AF recurrence +, apnea −), Group 3 (AF recurrence −, apnea +), and Group 4 (AF recurrence −, apnea −) by testing whether the marginal estimate of each group was significantly different. The significance level for the test was set at P<0.05. According to the explanatory nature of this study, we did not make any adjustment for multiple comparison. Statistical analyses were performed using JMP Pro for Windows (Version 16.1.0; SAS Institute Inc.).

All patients gave informed and written consent to participate in the study.

Results

For the 76 subjects, the mean age was 63.4±11.6 years, and 14 (18.4%) were female. The mean BMI was 24.7±3.7 kg/m², and 6 (7.9%) were highly obese with a BMI ≥30 kg/m². For the type of AF, 49 (64.5%) were paroxysmal and 27 (35.5%) were persistent, and 57 (75.0%) subjects were treated with ablation therapy for the first time. The treatment procedures included cryo-balloon in 35 (46.1%) and radiofrequency in 41 (53.9%) patients. The average sleep duration for the subjects was 7.4±1.6 h, and sleep efficiency was calculated to be approximately 74%. The mean apnea hypopnea index (AHI) was 18.3±12.6/h. Except for 3 patients (4.0%) with an AHI <5/h, 34 patients (44.7%) had an AHI <15, 28 patients (36.8%) had an AHI <30, and 11 patients (14.5%) had an AHI ≥30 (Table). During a mean follow-up of 307±117 days after a 3-month blanking period, 20 patients (26.3%) had AF recurrence.

Table.

Patient Characteristics

	Total (n=76)
Characteristics
Age, years	63.4±11.6
Sex, Female (%)	14 (18.4)
BMI	24.7±3.7
Type of AF
Paroxysmal AF, n (%)	49 (64.5)
Persistent AF, n (%)	27 (35.5)
Times of ablation, n (%)
1st session	57 (75.0)
2nd session and more	19 (25.0)
Procedures used for ablation, n (%)
Cryoballoon ablation	35 (46.1)
Radiofrequency ablation	41 (53.9)
CHADS₂ score	1.2±1.0
CHA₂DS₂-VASc score	2.0±1.6
Medications, n (%)
β-blocker	43 (56.6)
Antiarrhythmic agents	20 (26.3)
Laboratory data
BNP, pg/mL	83.3±102.8
Cre, mg/dL	0.96±0.62
TG, mg/dL	152.6±93.7
LDL-C, mg/dL	110.0±25.8
HDL-C, mg/dL	59.0±17.2
UA, mg/dL	5.7±1.4
HbA1c, %	6.2±1.2
Echocardiography data
LV ejection fraction, %	61.7±10.7
LV diameter (diastolic), mm	47.8±6.3
LV diameter (systolic), mm	31.1±7.6
LA diameter, mm	39.7±6.7
LA volume index, mL/m²	40.2±10.8
Polysomnography data
Sleep duration, h	7.4±1.6
Sleep efficiency, %	74
AHI, n/h	18.3±12.6
AHI <5, n (%)	3 (4.0)
5≤AHI<15, n (%)	34 (44.7)
15≤AHI<30, n (%)	28 (36.8)
30≤AHI, n (%)	11 (14.5)
Oxygen desaturation index (3%), n/h	19.7±10.0
HRV indices (total sleep time)
AVNN, ms	895.9±113.9
SDNN, ms	48.1±19.5
RMSSD, ms	19.4±8.6
pNN50, %	0.65 [0.2. 2.2]
LF, ms	80.7 [26.1, 187.5]
HF, ms	61.2 [37.3, 114.8]
lnLF	4.25±1.32
lnHF	4.19±0.87

Continuous variable data are presented as mean±standard deviation for normally distributed data and median [interquartile range] for non-normally distributed data. AF, atrial fibrillation; AHI, apnea and hypopnea index; AVNN, average of normal-to-normal intervals; BMI, body mass index; BNP, brain natriuretic peptide; Cre, creatinine; HbA1c, hemoglobin A1c; HDL-C, high density lipoprotein cholesterol; HF, high frequency power; HRV, heart rate variability; LA, left atrium; LDL-C, low density lipoprotein cholesterol; LF, low frequency power; lnHF, natural logarithm of HF; lnLF, natural logarithm of LF; LV, left ventricle; pNN50, the percentage of normal-to-normal intervals >50 ms that are different from preceding interval; RMSSD, root of the mean of squares of successive differences; SDNN, standard variation of normal-to-normal intervals; TG, triglyceride; UA, uric acid.

As shown in Figure 3A, RMSSD, reflecting parasympathetic activity, was significantly higher in the AF recurrence group than in the non-AF recurrence group during apnea time (mean±SD; 16.7±4.5 vs. 13.5±3.3, P=0.03) and non-apnea time (mean±SD; 20.9±9.5 vs. 15.5±5.9, P<0.01). In contrast, in a comparison of apnea and non-apnea time within the same AF status, RMSSD was significantly lower during apnea time in the AF recurrence group (mean±SD; 16.7±4.5 vs. 20.9±9.5, P<0.01) and in the non-AF recurrence group (mean±SD; 13.5±3.3 vs. 15.5±5.9, P=0.03). There was a significant difference between non-apnea time of the AF recurrence group and apnea time of the non-AF recurrence group (mean±SD; 20.9±9.5 vs. 13.5±3.3, P<0.01). There was no significant difference between apnea time in the AF recurrence group and non-apnea time in the non-AF recurrence group (mean±SD; 16.7±4.5 vs. 15.5±5.9, P=0.39).

Figure 3.

Heart rate viability analysis of the parasympathetic nervous system. (A) RMSSD, root of the mean of squares of successive differences. (B) HF, high frequency power. (C) lnHF, natural logarithm of HF. (D) pNN50, the percentage of normal-to-normal intervals >50 ms that are different from the preceding interval. AF, atrial fibrillation.

Other indices of parasympathetic activity showed similar trends. For example, HF (Figure 3B) was significantly higher in the AF recurrence group than in the non-AF recurrence group during apnea time (median [IQR]; 56.3 [41.1, 71.5] vs. 38.2 [27.2, 49.3], P=0.04) and non-apnea time (median [IQR]; 84.5 [50.7, 116.3] vs. 45.5 [26.7, 96.7], P=0.02). In a comparison of apnea and non-apnea time within each group, high frequency power (HF) during apnea time was also lower in both the AF recurrence group (median [IQR]; 56.3 [41.1, 71.5] vs. 84.5 [50.7, 116.3], P=0.04) and the non-AF recurrent group (median [IQR]; 38.2 [27.2, 49.3] vs. 45.5 [26.7, 96.7], P<0.01). There was a significant difference between non-apnea time in the AF recurrence group and apnea time in the non-AF recurrence group (median [IQR]; 84.5 [50.7, 116.3] vs. 38.2 [27.2, 49.3], P<0.01). No significant difference was found between apnea time in the AF recurrence group and non-apnea time in the non-AF recurrence group (median [IQR]; 56.3 [41.1, 71.5] vs. 45.5 [26.7, 96.7], P=0.71).

Similar results were also shown for the natural logarithm of HF (lnHF) (Figure 3C). lnHF was significantly higher in the AF recurrence group than in the non-AF recurrence group during apnea time (mean±SD; 3.94±0.67 vs. 3.61±0.58, P=0.04) and non-apnea time (mean±SD; 4.29±0.59 vs. 3.79±0.85, P<0.01). In a comparison of apnea and non-apnea time within each group, lnHF during apnea time was also lower in both the AF recurrence group (mean±SD; 3.94±0.67 vs. 4.29±0.59, P=0.03) and non-AF recurrent group (mean±SD; 3.61±0.58 vs. 3.79±0.85, P=0.048). There was a significant difference between non-apnea time in the AF recurrence group and apnea time in the non-AF recurrence group (mean±SD; 4.29±0.59 vs. 3.61±0.58, P<0.01). No significant difference was found between apnea time in the AF recurrence group and non-apnea time in the non-AF recurrence group (mean±SD; 3.94±0.67 vs. 3.79±0.85, P=0.42).

pNN50 (Figure 3D) showed a higher trend in the AF recurrence group than in the non-AF recurrence during non-apnea time (median [IQR]; 0.9 [0.1, 2.1] vs. 0.3 [0.0, 0.9], P=0.07), but there was no specific trend during apnea time (median [IQR]; 0.3 [0.0, 1.2] vs. 0.4 [0.1, 0.9], P=0.76). pNN50 during apnea time was significantly lower in the AF recurrence group (median [IQR]; 0.3 [0,0, 1.2] vs. 0.9 [0.1, 2.1], P=0.04), but was not significant in the non-AF recurrence group (median [IQR]; 0.4 [0.1, 0.9] vs. 0.3 [0.0, 0.9], P=0.28). There was a significant difference between non-apnea time in the AF recurrence group and apnea time in the non-AF recurrence group (median [IQR]; 0.9 [0.1, 2.1] vs. 0.4 [0.1, 0.9], P<0.01), but no significant difference between apnea time in the AF recurrence group and non-apnea time in the non-AF recurrence group (median [IQR]; 0.3 [0.0, 1.2] vs. 0.3 [0.0, 0.9], P=0.70).

Discussion

AF recurrence was associated with higher parasympathetic indices of HRV (RMSSD, HF, pNN50), whereas SA was associated with lower parasympathetic indices of HRV. Consequently, the nocturnal parasympathetic hyperactivity seen in patients with AF recurrence was offset during SA. These results support the hypothesis that features of HRV biomarkers associated with AF might be counteracted by a SA state.

A number of studies have examined the association between AF recurrence and parasympathetic indices of HRV, but the results differ depending on whether the recording period is only at night.¹³^,²⁴^–²⁶ To evaluate the association of parasympathetic activity with HRV, there are advantages to use ECG recorded during sleep, such as what has been done in this study. First, parasympathetic activity generally increases at night, and HRV shows greater fluctuations during sleep than during daytime wakefulness.¹⁰^,²⁷ Second, HRV is affected by diet itself, alcohol and caffeine intake, and fatigue and stress caused by daily activities. Furthermore, because body position also influences HRV, it is desirable for HRV evaluation to use ECG recorded when the subject is in a constant body position. However, in these previous studies, the effect of SA on HRV was not examined.

Because of the high rate of SA complications (21–74%) in patients with AF, the influence of SA on HRV is not negligible.¹⁴^–¹⁶ In a meta-analysis of the effects of SA on HRV parasympathetic indices, it was shown that nighttime RMSSD and HF were significantly lower in patients with obstructive SA compared to healthy controls.²⁸ In a study by Mohammadieh et al, parasympathetic activity during non-apnea time in paroxysmal AF patients with SA was higher than that in patients without SA.²⁹ This is explained by a study whereby in rats exposed to chronic intermittent hypoxia, the cholinergic response of the atrial myocardium was enhanced, and the β-adrenergic response was attenuated, increasing vulnerability to AF, and patients with AF with SA might similarly have an enhanced parasympathetic response.³⁰ We confirmed that parasympathetic hyperactivity during non-apnea time was associated with AF in our study. In addition, we further examined HRV during apnea time, which was intentionally excluded in the study by Mohammadieh et al,²⁹ and found that the increases in parasympathetic indices seen during non-apnea time were counteracted in the apneic state (Figure 4).

Figure 4.

Illustration of the impact of AF and sleep apnea on HRV. (A) Nocturnal parasympathetic activity is hyperactive in patients with AF recurrence; however, (B) parasympathetic activity is suppressed during the sleep apnea period, which masks the characteristics of the HRV index seen in patients with AF recurrence. AF, atrial fibrillation; HRV, heart rate viability.

These results suggest that nocturnal parasympathetic activity in patients with AF is not always active, but is a combination of hyperactivity during non-apnea and suppression during apnea. As mentioned above, parasympathetic indices of nocturnal HRV might be useful in predicting recurrence after AF ablation, but given the difficulty of extracting only non-apnea time from ECG recordings, and the high rate of SA complications in AF patients, the nocturnal HRV measured from Holter ECGs is likely to reflect results modified by SA. Therefore, if nocturnal HRV is to be used as an indicator of AF recurrence, it is recommended that SA should be assessed at the same time; if the influence of SA cannot be assessed, nocturnal HRV might not be used as an indicator of AF recurrence. Several previous studies have also observed an association between nocturnal HRV and new onset of AF. For example, Raman et al reported that nocturnal normalized HF was significantly higher in new-onset AF patients than in non-onset patients (mean±SD; 1.02±0.64 vs. 0. 92±0.73, P=0.02).¹¹ However, the time-domain parasympathetic indices, such as RMSSD and pNN50, were not described. Blanchard et al reported that RMSSD was significantly higher in new-onset AF patients than in non-onset patients (median [IQR]; 85 [55, 121] vs. 60 [45, 85], P<0. 0001), but there was no significant difference in pNN50 between the 2 groups (median [IQR]; 18 [11, 32] vs. 18 [9, 33], P<0.0001).¹² Also, there was no description of HF; thus, there are no consistent results on the relationship between nocturnal parasympathetic activity and new onset of AF. SA might have influenced these results, and caution should be taken when using the nocturnal HRV index as a marker for new-onset AF.

Study Limitations

This study has the following limitations. First, the AF ablation procedure (cryoballoon or radiofrequency) is not unified; however, some reports have shown that HRV after AF ablation was not affected by the ablation procedure used,³¹ and we also did not find any differences when different ablation procedures were used in our study (Supplementary Table 2). Second, in this study, HRV assessment was only performed the day after AF ablation and no consideration was given to HRV assessment and its change during the post-ablation follow-up. Therefore, further research is needed to determine the association between SA and daily variation in HRV and AF recurrence. Third, because most of the patients in our study had mild-to-moderate SA and there were only 11 cases of severe SA, we did not investigate the relationship between the severity of SA and HRV. In addition, it has been reported that during non-rapid eye movement (REM) sleep, the neurotransmitter pathway from the suprachiasmatic nucleus to the central autonomic nucleus is activated and parasympathetic activity is increased compared to during awake hours or REM sleep,³²^,³³ but the effects of such sleep stages on HRV were not considered in our study, because no information on electroencephalogram or eye movements during sleep was obtained. Finally, β-blockers or other drugs are reported to have affected HRV in previous studies,³⁴^,³⁵ In the comparison of HRV between apnea time and non-apnea time in the AF recurrence group (Group 1 vs. Group 2) and between apnea time and non-apnea time in non-AF recurrence group (Group 3 vs. Group 4), β-blockers or other drugs do not influence the results due to the intra-patient comparisons. In the comparison of HRV during apnea time between the AF recurrence group and the non-AF recurrence group (Group 1 vs. Group 3) and HRV during non-apnea time between the AF recurrence group and the non-AF recurrence group (Group 2 vs. Group 4), these drugs might have affected the outcome. However, in this study, there was no significant difference in the proportion of β-blockers or other drugs used between the AF recurrence group and the non-AF recurrence group, suggesting that the influence of these drugs is minimal.

Conclusions

If the influence of SA is not considered, the results of nocturnal HRV analyses might be misinterpreted. Caution should be exercised when using nocturnal HRV as a predictor of recurrent AF.

Sources of Funding

The study was not supported by any grants.

Disclosures

K.S. and S.M. belong to an endowed department funded by Japan Lifeline and Biotronik.

Author Contributions

H.I. and K.S. contributed to the conception and design of the work. M.M., J.M., N.T., S.S., T.N., H.S., and S.M. all helped with data collection and interpretation for this study. Y.C.A. and M.N. helped with data analysis. Moreover, the manuscript was drafted by H.I. The manuscript was also revised critically by the other authors. All agreed to be accountable for all aspects of the work, ensuring integrity and accuracy, and gave final approval.

IRB Information

The study was approved by the Medical Ethics Review Committee of the Kyoto Prefectural University of Medicine (approval number: ERB-C-1907).

Patient Consent Statement

All patients gave informed and written consent.

Permission to Reproduce Material From Other Sources

We do not reproduce any material from other sources in the study.

Data Availability

The individual deidentified participant data supporting the findings of this study will not be shared. Due to privacy and ethical concerns, the data are not publicly available.

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-23-0682

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