2021 Volume 85 Issue 3 Pages 252-260
Background: Whether all atrial fibrillation (AF) patients should be evaluated for sleep apnea before catheter ablation (CA) remains controversial. Watch-type peripheral arterial tonometry (W-PAT) is a home sleep testing device and an easier tool for diagnosing sleep apnea than polysomnography. We investigated the prevalence and predictors of sleep apnea using W-PAT in unscreened sleep apnea patients with AF before CA.
Methods and Results: The study was conducted under a retrospective, single-center, observational design. We included 776 consecutive patients who underwent both W-PAT and AF ablation. Sleep apnea assessments were successfully performed in 774 patients (99.7%; age 65±11 years, 73.3% male; body mass index [BMI] 24.1±3.5, 56.8% paroxysmal AF). The mean apnea-hypopnea index (AHI) was 20.1±15.6. Although 81.7% of the patients had normal Epworth sleepiness scores (mean 6.5), only 88 (11.4%) had a normal AHI (AHI <5) and 412 (53.2%) had moderate-severe sleep apnea (AHI ≥15). Obesity, male sex, nonparoxysmal AF, hypertension, and a left atrial diameter (LAd) ≥40 mm were predictors of moderate-severe sleep apnea. However, the prevalence of moderate-severe sleep apnea in patients without those predictors (i.e., non-obesity (44.2%), female sex (43.0%), paroxysmal AF (43.9%), no hypertension (45.5%)), and LAd <40 mm (41.0%) was considerably high.
Conclusions: Almost all patients successfully underwent W-PAT to diagnose sleep apnea. Patients undergoing AF ablation had a high prevalence of sleep apnea, and screening for sleep apnea was important in those patients even if they did not have sleepiness or risk factors.
Obstructive sleep apnea (OSA) is the most common sleep-disordered breathing worldwide, with an estimated prevalence of 15–30% in the general population, and an association with sleep fragmentation, episodic hypoxemia, hypercapnia, and intrathoracic pressure changes.1 Atrial fibrillation (AF) is the most common cardiac tachyarrhythmia, and is associated with an impaired quality of life, heart failure, thromboembolic strokes, sudden death, and cardiovascular morbidity.2,3
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Consistent data derived from experimental, epidemiological, and clinical studies shows that sleep apnea is a potential risk factor for the incidence and recurrence of AF.4,5 The estimated prevalence of sleep apnea in patients with AF has been found to be much higher (49–62%) than in control participants without AF.6,7 Individuals with sleep apnea often feel fatigue, concentration impairment, and sleepiness during the daytime. Some symptoms of sleep apnea overlap with symptoms of AF. Further, at least 50% of patients with severe sleep apnea do not report symptoms of unrestful sleep. This proportion is even higher in patients with sleep apnea and cardiovascular disease, who often primarily report symptoms of underlying cardiovascular disease rather than typical signs of sleep apnea.8,9
Untreated OSA is an important predictor of AF treatment failure after chemical or electrical cardioversion, as well as after successful AF ablation.10 Moreover, treatment of OSA is associated with significant reduction of recurrence after AF ablation. However, it is underdiagnosed and consequently undertreated in clinical practice.
Polysomnography (PSG) is currently considered the gold standard diagnostic test for sleep apnea. However, due to limited access and cost issues, PSG is difficult for all AF patients to obtain. Home sleep apnea tests (HSATs), which have limitations, are an alternative method of diagnosing sleep apnea, and may be less costly and more convenient in some populations with AF.11 Whether all AF patients undergoing catheter ablation (CA) should undergo sleep apnea screening remains controversial.12,13
This study had a retrospective, single-center, observational design. A total of 828 consecutive patients who underwent initial CA of AF from March 2018 to August 2019 were enrolled, including 3 patients receiving α-blockers, 12 who underwent pacemaker implantation, and 7 with chronic obstructive lung disease. We enrolled nonvalvular AF patients without decompensated heart failure. We excluded 22 patients who had been previously diagnosed with sleep apnea. We performed HSAT using the Watch-PAT200U (W-PAT) (Watch-PAT; Itamar Medical Ltd., Caesarea, Israel) in 776 of 802 patients (Figure 1). We sent the device home with the patients after we decided in the outpatient clinic to perform CA of AF. Patients self-administered the HSAT and returned both the device and a screening questionnaire (Epworth Sleepiness Scale (ESS); see below) before their admission for CA. All patients gave informed consent for both the ablation procedure and the use of their clinical data in a retrospective study. The study protocol was approved by the institutional ethics committee.
Study flowchart.
Apnea-Hypopnea Index (AHI) Measurement by W-PAT The W-PAT measurements consisted of the peripheral arterial tonometry (PAT) signal, oxygen saturation, heart rate, wrist activity (actigraphy), snoring, and body position. W-PAT indirectly detected apnea-hypopnea events by selectively measuring the peripheral arterial volume changes using a finger-mounted plethysmograph. This information was collated with pulse oximetry in conjunction with the heart rate, and was further analyzed using a predeveloped automated computer program. The W-PAT device had an algorithm able to differentiate between sleep and awake states every 30s, and can calculate both the total sleep time and the total recording time. The analysis algorithm used 4 functions to detect different parameters, including the AHI, respiratory disturbance index, oxygen desaturation index, minimum, mean, and maximum oxygen saturations, and sleep stages. Respiratory indexes calculated using PAT-based portable devices have been proven to be positively correlated with those calculated from PSG scoring.14,15
Definitions and EndpointsThe diagnosis of sleep apnea was according to the Adult Obstructive Sleep Apnea Task Force of the American Academy of Sleep Medicine. A normal sleep study was defined as an AHI <5, mild sleep apnea as AHI range ≥5 and <15, moderate sleep apnea as an AHI range ≥15 and <30, and severe sleep apnea as an AHI ≥30. The ESS is a commonly used 8-item questionnaire to assess subjective daytime sleepiness.16 It is unidimensional and closely related to the frequency of apneas in sleep apnea.17 The ESS scores were determined from the questionnaire sent home with the patients together with the W-PAT before CA.
Paroxysmal AF was defined as an AF episode that terminated spontaneously or following the administration of antiarrhythmic drugs within 7 days of onset. Persistent AF was defined as an AF episode lasting ≥7 days and up to 1 year. Long-lasting AF was defined as persisting for ≥1 year.
The aim of this study was to elucidate the prevalence of sleep apnea patients who did not undergo sleep apnea screening before CA using the W-PAT and their risk of moderate or severe sleep apnea. Consequently, the primary endpoints of the study were (1) the AHI distribution among patients whose AHI data were available, and (2) the predictors of moderate and severe sleep apnea.
Statistical AnalysisDescriptive statistics are reported as the mean±SD for continuous variables and as absolute frequencies and percentages for categorical variables. Parametric data were compared using Student’s t-test or paired Student’s t-test, and nonparametric data were compared using the Mann-Whitney U-test, Wilcoxon signed rank test, chi-squared test, or Fisher’s exact test, as appropriate. A multivariable logistic regression analysis was performed to determine the risk factors for moderate or severe sleep apnea using the following variables: male sex, age ≥65 years old, body mass index (BMI) ≥25 kg/m2, nonparoxysmal AF (persistent AF and long-lasting AF), history of heart failure, hypertension, diabetes, vascular disease, ESS ≥11, left ventricular diastolic diameter (LVDd) ≥55 mm, left atrial diameter (LAd) ≥40 mm, and ejection fraction <50% on echocardiography. All statistical analyses were performed using JMP13.2.1 software (SAS Institute, Inc., Cary, NC, USA).
The study flow chart is shown in Figure 1: 774 of the 776 patients (99.7%) successfully recorded data using W-PAT. The mean AHI was 20.1±15.6 in 774 patients. Patients with an AHI <5 (no sleep apnea), 5≤AHI<15 (mild sleep apnea), 15≤AHI<30 (moderate sleep apnea), and ≥30 (severe sleep apnea) comprised 88 (11.4%), 274 (35.4%), 252 (32.6%), and 160 (20.7%), respectively (Figure 2).
Apnea-hypopnea index (AHI) distribution in the overall patient chohort.
The baseline characteristics are listed in Table 1. The mean age was 64.6±11.0 years, and mean BMI was 24.1±3.5 kg/m2, and 73.3% of the patients were men. The mean respiratory disturbance index (RDI) was 24.5 and median oxygen desaturation index (ODI) was 6.9.
| Characteristic | Overall (n=774) |
|---|---|
| Age, years | 64.6±11.0 |
| Male sex, n (%) | 567 (73.3) |
| Height, cm | 166.7±9.3 |
| Body weight, kg | 67.2±12.7 |
| BMI, kg/m2 | 24.1±3.5 |
| AF type | |
| Paroxysmal, n (%) | 440 (56.8) |
| Persistent, n (%) | 252 (32.6) |
| Long-lasting, n (%) | 82 (10.6) |
| History of heart failure, n (%) | 110 (14.2) |
| Hypertension, n (%) | 400 (51.7) |
| Diabetes, n (%) | 132 (17.1) |
| Ischemic stroke, n (%) | 41 (5.3) |
| Vascular disease, n (%) | 42 (5.4) |
| CHADS2 score | |
| 0, n (%) | 231 (29.8) |
| 1, n (%) | 299 (38.6) |
| 2, n (%) | 164 (21.2) |
| ≥3, n (%) | 80 (10.3) |
| Mean | 1.14 |
| CHA2DS2-VASc score | |
| 0 or 1 n (%) | 333 (43.0) |
| 2 or 3 n (%) | 334 (43.2) |
| ≥4, n (%) | 107 (13.8) |
| Mean | 1.89 |
| Echocardiographic parameters | |
| LVDd, mm | 47.6±5.2 |
| LVEF, % | 63.6±10.7 |
| LAd, mm | 39.8±6.4 |
| ESS | 6.5±4.3 |
| AHI | 20.1±15.6 |
| RDI | 24.5±15.5 |
| 4% ODI | 6.9 (3.2–14.8) |
All data are mean±standard deviation unless otherwise indicated. AF, atrial fibrillation; AHI, apnea-hypopnea index; BMI, body mass index; ESS, Epworth sleepiness scale; LAd, left atrial dimension; LVDd, left ventricular dilated diameter; LVEF, left ventricular ejection fraction; 4%ODI, 4% oxygen desaturation index; RDI, respiratory disturbance index.
Patients in the moderate or severe sleep apnea groups were older (no sleep apnea vs. mild sleep apnea vs. moderate or severe sleep apnea, 61.7±12.2, 64.7±11.7, 65.1±10.2 years, P<0.0001). Moderate or severe sleep apnea was more common in males (63.6% vs. 68.6% vs. 78.4%, P=0.0018). Patients in the moderate or severe sleep apnea groups had a higher BMI (25.0±3.5 kg/m2) than those in the no sleep apnea (22.2±3.2 kg/m2) and mild sleep apnea groups (23.4±3.2 kg/m2) (P<0.0001). Patients in the moderate or severe sleep apnea groups had a higher prevalence of hypertension (no sleep apnea vs. mild sleep apnea vs. moderate or severe sleep apnea, 38.6% vs. 45.3% vs. 58.7%, P<0.0001). Patients in the moderate and severe sleep apnea groups had a higher CHADS2 score (mean 0.86 vs. 1.09 vs. 1.24, P=0.0006) and CHA2DS2-VASc score (mean 1.52 vs. 1.87 vs. 1.99, P=0.014). Patients in the moderate and severe sleep apnea groups had a larger LAd (no sleep apnea, 35.6±5.7 mm; mild sleep apnea, 38.7±6.3 mm; moderate or severe sleep apnea, 41.3±6.2 mm; P<0.0001). The ESS was relatively low (6.5±4.3) in the overall patient group and was similar among the groups (no sleep apnea, 5.8±3.7; mild sleep apnea, 6.4±4.3; moderate or severe sleep apnea, 6.6±4.3, P=0.26) (Table 2).
| Characteristic | No sleep apnea (n=88) |
Mild sleep apnea (n=274) |
Moderate or severe sleep apnea (n=412) |
P value* |
|---|---|---|---|---|
| Age, years | 61.7±12.2 | 64.7±11.7 | 65.1±10.2 | <0.0001 |
| Male sex, n (%) | 56 (63.6) | 188 (68.6) | 323 (78.4) | 0.0018 |
| Height, cm | 166.5±10.0 | 166.2±9.7 | 167.0±8.8 | 0.57 |
| Body weight, kg | 61.8±10.8 | 64.9±12.3 | 70.0±12.6 | <0.0001 |
| BMI, kg/m2 | 22.2±3.2 | 23.4±3.2 | 25.0±3.5 | <0.0001 |
| History of heart failure, n (%) | 10 (11.4) | 32 (11.7) | 68 (16.5) | 0.15 |
| Hypertension, n (%) | 34 (38.6) | 124 (45.3) | 242 (58.7) | <0.0001 |
| Diabetes, n (%) | 11 (12.5) | 46 (16.8) | 75 (18.2) | 0.41 |
| Ischemic stroke, n (%) | 3 (3.4) | 17 (6.2) | 21 (5.1) | 0.56 |
| Vascular disease, n (%) | 3 (3.4) | 10 (3.7) | 29 (7.1) | 0.096 |
| CHADS2 score | ||||
| 0, n (%) | 41 (46.6) | 97 (35.4) | 93 (22.6) | – |
| 1, n (%) | 24 (27.2) | 95 (34.7) | 180 (43.7) | – |
| 2, n (%) | 17 (19.3) | 52 (19.0) | 95 (23.1) | – |
| ≥3, n (%) | 6 (6.8) | 30 (10.9) | 44 (10.7) | – |
| Mean | 0.86 | 1.09 | 1.24 | 0.0006 |
| CHA2DS2-VASc score | ||||
| 0 or 1 n (%) | 48 (54.5) | 126 (46.0) | 159 (38.6) | – |
| 2 or 3 n (%) | 32 (36.3) | 105 (38.3) | 197 (47.8) | – |
| ≥4, n (%) | 8 (9.1) | 43 (15.7) | 56 (13.6) | – |
| Mean | 1.52 | 1.87 | 1.99 | 0.014 |
| Echocardiographic parameters | ||||
| LVDd, mm | 46.6±4.9 | 47.3±4.8 | 48.0±5.4 | 0.026 |
| LVEF, % | 66.1±7.8 | 64.7±10.5 | 62.4±11.2 | 0.0019 |
| LAd, mm | 35.6±5.7 | 38.7±6.3 | 41.3±6.2 | <0.0001 |
| ESS | 5.8±3.7 | 6.4±4.3 | 6.6±4.3 | 0.26 |
| RDI | 8.3±5.9 | 14.8±5.3 | 34.4±14.5 | <0.0001 |
| 4% ODI | 1.0 (0.5–1.3) | 3.8 (2.5–5.3) | 14.0 (9.1–22.7) | <0.0001 |
All data are mean±standard deviation or median (1 st–3rd quartile) unless otherwise indicated. *Difference among no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea groups and is based on the Fisher exact test for categorical variables and Wilcoxon rank-sum test for continuous variables. Abbreviations as in Table 1.
The severity of sleep apnea according to the type of AF is shown in Figure 3. The prevalence of no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea was 16.1%, 40.0%, and 43.9%, respectively, in the paroxysmal AF patients, whereas the prevalence of no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea was 1.2%, 26.8%, and 72.0%, respectively, in the long-lasting AF patients.
Apnea-hypopnea index (AHI) according to atrial fibrillation (AF) type.
Univariate and multivariate logistic regression analyses were performed to determine the risk factors of moderate and severe sleep apnea before CA of AF (Table 3). The significant risk factors in the unscreened sleep apnea patients before CA of AF were male sex, obesity (BMI ≥25 kg/m2), nonparoxysmal AF, hypertension, vascular disease, LVDd ≥55 mm, LA dilatation (LAd ≥40 mm), ejection fraction <50%, and estimated glomerular filtration rate <60 mL/min/1.73 m2 in the univariate analysis. Male sex (odds ratio (OR), 1.58; 95% confidence interval (CI): 1.10–2.29, P=0.014), obesity (OR, 2.32; 95% CI: 1.63–3.30, P<0.0001), nonparoxysmal AF (OR, 1.86; 95% CI: 1.32–2.62, P=0.0004), hypertension (OR, 1.60; 95% CI: 1.15–2.23, P=0.005), and LA dilatation (OR, 1.48; 95% CI: 1.04–2.10, P=0.030) were significant predictors of moderate or severe sleep apnea before CA of AF in the multivariate analysis.
| A. Univariate analysis | Univariate P values |
OR | 95% CI |
|---|---|---|---|
| Male | 0.0006 | 1.76 | 1.27–2.42 |
| Age ≥65 years | 0.76 | 1.05 | 0.79–1.39 |
| BMI ≥25 | <0.0001 | 2.83 | 2.07–3.86 |
| Nonparoxysmal AF | <0.0001 | 2.44 | 1.82–3.27 |
| History of heart failure | 0.052 | 1.51 | 0.99–2.28 |
| Hypertension | <0.0001 | 1.84 | 1.38–2.45 |
| Diabetes | 0.36 | 1.19 | 0.82–1.74 |
| Vascular disease | 0.037 | 2.04 | 1.05–3.99 |
| LVDd ≥55 mm | 0.014 | 1.95 | 1.15–3.31 |
| LAd ≥40 mm | <0.0001 | 2.70 | 2.02–3.62 |
| LVEF <50% | 0.0015 | 2.28 | 1.37–3.79 |
| ESS ≥11 | 0.19 | 1.28 | 0.89–1.86 |
| eGFR <60 mL/min/1.73 m2 | 0.0063 | 1.54 | 1.13–2.09 |
| B. Multivariate analysis | Multivariate P values |
OR | 95% CI |
| Male | 0.014 | 1.58 | 1.10–2.29 |
| Age ≥65 years | 0.93 | 0.98 | 0.69–1.41 |
| BMI ≥25 | <0.0001 | 2.32 | 1.63–3.30 |
| Nonparoxysmal AF | 0.0004 | 1.86 | 1.32–2.62 |
| History of heart failure | 0.73 | 0.92 | 0.56–1.50 |
| Hypertension | 0.005 | 1.60 | 1.15–2.23 |
| Diabetes | 0.35 | 0.82 | 0.53–1.25 |
| Vascular disease | 0.40 | 1.38 | 0.65–2.89 |
| LVDd ≥55 mm | 0.48 | 1.26 | 0.67–2.37 |
| LAd ≥40 mm | 0.030 | 1.48 | 1.04–2.10 |
| LVEF <50% | 0.30 | 1.39 | 0.75–2.57 |
| ESS ≥11 | 0.97 | 1.01 | 0.67–1.52 |
| eGFR <60 mL/min/1.73 m2 | 0.088 | 1.36 | 0.96–1.94 |
eGFR, estimated glomerular filtration rate. Other abbreviations as in Table 1.
The severity of sleep apnea in patients without each sleep apnea predictor compared with those with each sleep apnea predictor is shown in Figure 4. The respective prevalence of no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea was 15.5%, 41.6%, and 43.0% in female patients, and 9.9%, 33.2%, and 57.0%, in male patients (Figure 4A). In obese patients the respective prevalence of no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea was 4.3%, 26.5%, and 69.2% compared with 15.4%, 40.4%, and 44.2% in non-obese patients (Figure 4B). In Figure 4C shows the respective prevalence of no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea as 14.4%, 40.1%, and 45.4% in patients without hypertension vs. 8.5%, 31.0%, and 60.5% in patients with hypertension. According to the presence of LA dilatation the respective prevalence of no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea was 17.9%, 41.0%, and 41.0% with LAd <40 mm, and 4.9%, 29.8%, and 65.3% in the patients with an LAd ≥40 mm (Figure 4D). Finally, the severity of sleep apnea according to the ESS score is shown in Figure 4E. The prevalence of no sleep apnea, mild sleep apnea, and moderate or severe sleep apnea was 12.3%, 35.8%, and 51.9% in patients with an ESS <11, and 7.3%, 34.8%, and 58.0%, respectively, in patients with an ESS ≥11. Only 12.3% of patients with a normal ESS (ESS <11) had a normal AHI (AHI <5).
Apnea-hypopnea index (AHI) according to sex (A), obesity (B), hypertension (C), left atrial dilatation (D), and Epworth Sleepiness Scale (E).
The present study of routine HSAT using a novel PAT for unscreened sleep apnea patients with AF before CA revealed the following findings. (1) Almost all patients with AF (99.7%) could self-administer this device without assistance and succeeded in obtaining their AHI data. (2) Only 11.4% of patients had no sleep apnea (AHI <5). More than half of the patients had moderate (32.6%) or severe (20.7%) sleep apnea. (3) Persistent AF patients had a higher prevalence of sleep apnea than paroxysmal AF patients. Long-lasting AF patients had the highest prevalence of sleep apnea and their AHI was the most severe among the 3 types of AF. (4) The ESS score was not a predictor of moderate or severe sleep apnea. Moderate or severe sleep apnea patients with AF often did not recognize much sleepiness. (5) Risk factors for moderate or severe sleep apnea were male sex, obesity, nonparoxysmal AF, hypertension, and LA dilatation. However, the majority of the patients without these predictors of moderate or severe sleep apnea did have sleep apnea.
Advantage of Novel HSAT Over PSG in AF Patients Before CAHSAT has potential benefits compared with PSG for patients with suspected sleep apnea, including convenience, comfort, better access to testing, and cost effectiveness.11 The disadvantage of conventional HSAT is the need for additional diagnostic testing of patients who cannot technically perform the HSAT. A previous study reported that 82% of initial HSAT attempts were technically acceptable using conventional type 3 devices (nasal pressure, thoracic and abdominal excursion, oxygen saturation, ECG, body position, and oral thermistors in some cases).18 PAT is a type of HSAT that allows an automatic calculation of the scoring, and has demonstrated a high degree of correlation to the AHI as compared with PSG.14 Almost all patients in our study cohort could mount the watch-type device on their own and succeeded in getting their AHI. The simple device and the patients’ high health literacy could be reasons why the technical failure rate was low in our study. If almost all AF patients could get their AHI determined by a one-time HSAT before CA, testing could be less expensive and less burdensome for both patients and medical staff, and HSAT could be more suitable as a sleep apnea screening method before CA of AF compared with PSG.
Prevalence of OSA in AF Patients Before CAPrevious studies showed that 16–21% of AF patients had moderate to severe OSA by PSG before CA.19,20 Those studies investigated OSA and all patients underwent PSG before CA. However, the major CA registries of AF patients have not reported the prevalence of sleep apnea,21,22 which means AF patients do not routinely undergo sleep apnea screening tests before CA in the real-world clinical settings. Khan et al showed that 66% of AF patients were never screened for OSA and 75% of the unscreened AF patients were at a high risk for OSA by screening questionnaire.23 However, the American Academy of Sleep Medicine recommends that questionnaires should not be used to diagnose sleep apnea in adults in the absence of PSG or HSAT.1 In our study only 11.4% of the patients with AF before CA were free from sleep apnea, and 53.3% of all participants had moderate or severe sleep apnea by the HSAT despite the inclusion of patients who had not been previously screened for sleep apnea. We should take these unscreened patients into consideration when we perform CA in AF patients.
Different Severities of Sleep Apnea According to AF TypeStevenson et al showed that the proportion of patients with sleep apnea and the severity of the AHI were greater in those with high-frequency paroxysmal AF or persistent AF vs. low-frequency paroxysmal AF.4 In accordance with that study, our results showed that nonparoxysmal AF was a risk factor for moderate or severe sleep apnea. Patients with persistent AF had a higher prevalence of sleep apnea, and their AHI was more severe than that in patients with paroxysmal AF. Furthermore, long-lasting AF patients had the highest prevalence of sleep apnea and their AHI was the most severe among the 3 types of AF. Atrial stretch and neurohumoral activation lead to progressive structural atrial substrate remodeling in OSA patients, and it is this progressive atrial remodeling that contributes to the reentry substrate for AF, which is more extensive in patients with nonparoxysmal AF.10 Severe sleep apnea may cause patients with paroxysmal AF to develop persistent AF earlier than AF patients without sleep apnea.
Predictors of Sleep Apnea in Unscreened Patients Before CA of AFWe revealed that male sex (OR=1.58), obesity (OR=2.32), nonparoxysmal AF (OR=1.86), hypertension (OR=1.60), and LA dilatation (OR=1.48) were significant predictors of moderate or severe sleep apnea before CA of AF in the multivariate analysis. Negative swings of intrathoracic pressure during inspiration against an occluded upper airway in OSA cause myocardial stretch and changes in the transmural pressure gradients, particularly affecting the thin-walled atria.24 This mechanism may explain why LA dilatation was an independent risk factor of sleep apnea.
Our result suggested that obese patients, those with hypertension and females did not have a certain higher possibility of sleep apnea among those with AF before CA. Published evidence suggests that obesity is strongly associated with OSA, and weight loss has a beneficial effect on OSA and AHI reduction.25 However, although the majority of our study cohort were non-obese (64%), 84.6% of them had sleep apnea and more than half of the sleep apnea patients had moderate or severe sleep apnea. Similarly, 85.6% of the non-hypertensive patients had sleep apnea and more than half of the non-hypertensive sleep apnea patients had moderate or severe sleep apnea. Moreover, 84.5% of the female patients had sleep apnea and half of them had it moderately or severely. We should consider sleep apnea screening for CA candidates with AF even if they do not have any risk factors.
On the other hand, the ESS score was not associated with sleep apnea. The mean score was 6.5, and 81.7% of the patients’ ESS scores were <11. However, 87.7% of the patients with an ESS score <11 had sleep apnea, and 51.9% of them had moderate or severe sleep apnea. Generally, the ESS can help to quantify subjective daytime sleepiness and an ESS score <11 can be interpreted as normal daytime sleepiness. However, some previous studies have shown that the absence of subjective sleepiness is not a reliable means of ruling out sleep apnea in patients with AF.26,27 Even if patients with AF do not experience sleepiness, we cannot deny the presence of sleep apnea without performing a HSAT or PSG prior to CA.
Sleep Apnea Screening in Unscreened Patients Before CA of AFThe prevalence of sleep apnea in patients with AF has been found to be between 49% and 62%.6,7 Only 11.4% of our study cohort had a normal AHI and the mean AHI was high (20.1), and 53.2% of them had moderate or severe sleep apnea (AHI ≥15). However, many of them did not report sleepiness, so we would have overlooked their sleep apnea prior to CA for AF unless we had performed sleep apnea screening. There are several clinical benefits to diagnosing asymptomatic sleep apnea in patients undergoing AF ablation. First, though no randomized study has reported the effect of continuous positive airway pressure (CPAP) on AF recurrence after CA, several meta-analyses in some nonrandomized studies have established that CPAP treatment is associated with higher AF-free survival rates in patients with OSA and AF undergoing CA.28–30 Some studies have shown that conversion from AF to sinus rhythm reduces the AHI following CA or cardioversion. Naruse et al described a decrease in the median AHI from 22 to 15 following successful ablation, but almost all patients with moderate or severe sleep-disordered breathing before CA still had sleep-disordered breathing after CA.31
Therefore, we should routinely perform sleep apnea screening using HSAT in patients with AF before CA, and consider carrying out PSG in patients with moderate or severe sleep apnea after CA to decide the indication for CPAP. As a result of these examinations, we should treat the patient’s sleep apnea in order to decrease AF recurrence after CA. Second, when patients undergo pulmonary vein isolation under deep sedation, sedative-induced obstructive respiratory episodes frequently occur in OSA patients. These obstructive respiratory events lead to apnea and deep breathing, making it difficult for operators to stabilize the position of the ablation catheter during deep breathing. If the patient’s sleep apnea is detected by using HSAT before CA, the operators can avoid deep sedation during pulmonary vein isolation and may more easily achieve better catheter stability. Finally, sleep apnea and AF are highly prevalent in patients with a wide variety of cardiovascular diseases, including hypertension, heart failure, and coronary artery disease. Sleep apnea is an independent risk factor for the development of these cardiovascular diseases.32–34 Screening for sleep apnea in patients with AF and treating their OSA by CPAP treatment and lifestyle modifications, such as for obesity and alcohol consumption, may prevent worsening of their underlying cardiovascular disease. Further studies are needed to elucidate the effect of CPAP on patients with AF after CA who do not have symptoms or the risk of sleep apnea, including obesity.
Study LimitationsThe main limitations of this study are associated with the retrospective, observational design. We believe, however, the findings obtained in our clinical practice compare favorably with those of a well-organized prospective study because we collected sequential data on unscreened sleep apnea patients with AF before CA during a relatively short period (18 months), and the sample size was large (n=776). Second, PAT demonstrated a high degree of correlation of the AHI with PSG, but the evidence of accuracy in patients with AF or who have central sleep apnea is not adequate.
Third, this study was based on a single-center experience. To ensure that PAT is more efficacious for unscreened sleep apnea patients with AF before CA than PSG, our results should be confirmed by a multicenter study.
The HSAT using W-PAT had high patient acceptance. It detected a high prevalence of sleep apnea in patients unscreened for sleep apnea prior to their scheduled CA of AF, despite that the majority of patients not reporting much sleepiness. Obesity, male sex, nonparoxysmal AF, hypertension, and LA dilatation were risk factors for sleep apnea. However, even patients without these risk factors had a high prevalence of sleep apnea. Electrophysiologists should perform routine sleep apnea screening before CA of AF in order to reduce AF recurrence and cardiovascular events, and ensure ease of operation during CA.
We thank the nursing staff, clinical engineers, and office administrators of Sakurabashi-Watanabe Hospital for their invaluable help in conducting this study. We also thank Mr. John Martin and Mr. Jokl Dan H. for their linguistic assistance with the manuscript.
K. Inoue has received honoraria from Johnson and Johnson KK, Medtronic, Bayer, Boehringer Ingelheim, and Bristol Myers Squibb. The other authors declare no conflicts of interest.
Y.S. is a member of Circulation Journal’s Editorial Team.
The present study was approved by Sakurabashi-Watanabe Hospital (reference no. 20-36).
