Sleep Apnea and Heart

Positional obstructive sleep apnea in patients with atrial fibrillation

PURPOSE

Obstructive sleep apnea (OSA) is a common, potentially modifiable condition implicated in the pathogenesis of atrial fibrillation (AF). The presence and severity of OSA is largely sleep position-dependent, yet there is high variability in positional dependence among patients with OSA. We investigated the prevalence of positional OSA (POSA) and examined associated factors in patients with AF.

METHODS

We recruited an equal number of patients with and without AF who underwent diagnostic polysomnography. Patients included had ≥ 120 min of total sleep time with 30 min of sleep in both supine and lateral positions. POSA was defined as an overall apnea hypopnea index (AHI) ≥ 5/h, supine AHI (sAHI) ≥ 5/h, and sAHI greater than twice the non-supine AHI. POSA prevalence was compared in patients with and without AF adjusting for age, sex, OSA severity, and heart failure.

RESULTS

A total of patients (male: 56%, mean age 62 years) were included. POSA prevalence was similar between the two groups (46% vs. 39%; p = 0.33). Obesity and severe OSA (AHI ≥ 30/h) were associated with low likelihood of POSA (OR [CI] of 0.17 [0.09-0.32] and 0.28 [0.12-0.62]). In patients with AF, male sex was associated with a higher likelihood of POSA (OR [CI] of 3.16 [1.06-10.4]).

CONCLUSION

POSA is common, affecting more than half of patients with AF, but the prevalence was similar in those without AF. Obesity and more severe OSA are associated with lower odds of POSA. Positional therapy should be considered in patients with mild OSA and POSA.

Elucidation of obstructive sleep apnoea related blood pressure surge using a novel continuous beat-to-beat blood pressure monitoring system

BACKGROUND

Obstructive sleep apnoea (OSA) episode related blood pressure (BP) surge may mediate the association of OSA with cardiovascular disease. However, BP is not measured during a clinical sleep study.

METHOD

We tested the feasibility of incorporating the Caretaker physiological monitor, which utilizes a novel continuous beat-to-beat (b-b) BP monitoring technology, into polysomnography (PSG) and aimed to characterize BP surges related to obstructive respiratory events. B-b BP was concurrently collected and merged with PSG data on a posthoc basis. We compared BP surge between mean respiratory (apnoea, hypopnea and desaturation-alone events) and nonrespiratory events (spontaneous or leg movement-related arousals). We examined the association of the degree of oxygen desaturation with BP surge in a given respiratory event combining all events. A total of 17 consecutive patients (12 men, mean 52 years old, nine diagnostic and eight split-night PSGs) undergoing clinically indicated PSG were included after excluding one patient with poor signal quality due to excessive movement.

RESULTS

Caretaker was well tolerated. Mean respiratory BP surge ranged from 5 to 19 mmHg [Median (IQR) = 13.9 (9.5--16.2)]. Mean BP surge between the respiratory and nonrespiratory events was similar [13.8 (4.5) vs. 14.9 (5.3) mmHg, P = 0.13]. Accounting for the count distribution of desaturation/BP surge data pair events, there was a linear correlation between the degree of oxygen desaturation and BP surge (R = 0.57, P < 0.001). In eight patients undergoing split-night sleep studies, the number of BP surge events (≥10 mmHg/h) decreased during continuous positive airway pressure in all but one patient.

CONCLUSION

We demonstrated highly variable OSA-related BP surge patterns using the Caretaker's b-b BP monitoring technology that has the potential to be integrated into sleep studies.

Sleep time and efficiency in patients undergoing laboratory-based polysomnography

STUDY OBJECTIVES

Sleep quality in patients studied with laboratory-based polysomnography may differ from sleep quality in patients studied at home but remains clinically relevant and important to describe. We assessed objective sleep quality and explored factors associated with poor sleep in patients undergoing laboratory-based polysomnography.

METHODS

We reviewed diagnostic polysomnography studies from a 10-year period at a single sleep center. Total sleep time (TST) and sleep efficiency (SE) were assessed as markers of sleep quality. Poor sleep was defined as TST ≤ 4 hours or SE ≤ 50%. Multivariable analysis was performed to determine associations between objective sleep quality as an outcome and multiple candidate predictors including age, sex, race, body mass index, comorbidities, severity of obstructive sleep apnea, and central nervous system medications.

RESULTS

Among 4957 patients (age 53 ± 15 years), average TST and median SE were 5.8 hours and 79%, respectively. There were 556 (11%) and 406 (8%) patients who had poor sleep based on TST and SE, respectively. In multivariable analysis, those who were older (per 10 years: 1.48 [1.34, 1.63]), male (1.38 [1.14,1.68]), and had severe obstructive sleep apnea (1.76 [1.28, 2.43]) were more likely to have short sleep. Antidepressant use was associated with lower odds of short sleep (0.77 [0.59,1.00]). Older age (per 10 years: 1.48 [1.34, 1.62]), male sex (1.34 [1.07,1.68]), and severe obstructive sleep apnea (2.16 [1.47, 3.21]) were associated with higher odds of poor SE.

CONCLUSIONS

We describe TST and SE from a single sleep center cohort. Multiple demographic characteristics were associated with poor objective sleep in patients during laboratory-based polysomnography.

CITATION

Harrison EI, Roth RH, Lobo JM, et al. Sleep time and efficiency in patients undergoing laboratory-based polysomnography. J Clin Sleep Med. 2021;17(8):1591-1598.

The Influence of Obesity on the Association of Obstructive Sleep Apnea and Atrial Fibrillation

BACKGROUND AND OBJECTIVE

The association between obstructive sleep apnea (OSA) and atrial fibrillation (AF) has been closely studied. However, obesity is a powerful confounder in the causal relationship between OSA and cardiovascular disease. The contribution of obesity in the relationship between OSA and AF remains unclear.

METHODS

We recruited 457 consecutive patients equally with and without AF who underwent clinically indicated diagnostic polysomnography at a single academic sleep center. Multivariable logistic regression adjusting for age, sex, hypertension, and heart failure was performed to study the independent association between OSA and AF stratified by obesity.

RESULTS

A total of 457 patients (male: 56.2%, mean age 63.1 ± 13.3 years) was included. OSA prevalence was similar between those with and without AF (52.6% vs. 47.4%, respectively; p = 0.24). In multivariable analysis, no association was found between AF and OSA regardless of obesity status. When severe OSA (vs. non-severe OSA) was modeled as a dependent variable, AF was associated with a higher likelihood of severe OSA in non-obese patients [odds ratio (OR): 2.29, 95% confidence interval (CI): 1.23-4.35, p = 0.01], but not in obese patients (OR: 0.95, 95% CI: 0.48-1.90, p = 0.89).

CONCLUSION

The association of OSA with AF was present only in the non-obese and was limited to severe OSA patients. In contrast, no association was found in obese patients. The association between OSA and AF is partly dependent on the body habitus.

Pulse arrival time, a novel sleep cardiovascular marker: the multi-ethnic study of atherosclerosis

BACKGROUND

Pulse arrival time (PAT) is commonly used to estimate blood pressure response. We hypothesised that PAT response to obstructive respiratory events would be associated with increased cardiovascular risk in people with obstructive sleep apnoea.

METHODS

PAT, defined as the time interval between electrocardiography R wave and pulse arrival by photoplethysmography, was measured in the Multi-Ethnic Study of Atherosclerosis Sleep study participants. The PAT response to apnoeas/hypopnoeas was defined as the area under the PAT waveform following respiratory events. Cardiovascular outcomes included markers of subclinical cardiovascular disease (CVD): left ventricular mass, carotid plaque burden score and coronary artery calcification (CAC) (cross-sectional) and incident composite CVD events (prospective). Multivariable logistic and Cox proportional hazard regressions were performed.

RESULTS

A total of 1407 participants (mean age 68.4 years, female 47.5%) were included. Higher PAT response (per 1 SD increase) was associated with higher left ventricular mass (5.7 g/m² higher in fourth vs first quartile, p<0.007), higher carotid plaque burden score (0.37 higher in fourth vs first quartile, p=0.02) and trended to greater odds of CAC (1.44, 95% CI 0.98 to 2.15, p=0.06). A total of 65 incident CVD events were observed over the mean of 4.1 (2.6) years follow-up period. Higher PAT response was associated with increased future CVD events (HR: 1.20, 95% CI 1.02 to 1.42, p=0.03).

CONCLUSION

PAT is independently associated with markers of subclinical CVD and incident CVD events. Respiratory-related PAT response is a novel and promising polysomnography metric with cardiovascular implications.

Visit-to-visit blood pressure variability and sleep architecture

Visit-to-visit blood pressure (BP) variability (BPV) is an independent risk factor of cardiovascular disease (CVD). Sleep architecture characterizes the distribution of different stages of sleep and may be important in CVD development. We examined the association between visit-to-visit BPV and sleep architecture using in-lab polysomnographic data from 3,565 patients referred to an academic sleep center. BPV was calculated using the intra-individual coefficient of variation of BP measures collected 12 months before the sleep study. We conducted multiple linear regression analyses to assess the association of systolic and diastolic BPV with sleep architecture-rapid eye movement (REM) and non-rapid eye movement (NREM) sleep duration. Our results show that systolic BPV was inversely associated with REM sleep duration (p = .058). When patients were divided into tertile groups based on their BPV, those in the third tertile (highest variability) spent 2.7 fewer minutes in REM sleep than those in the first tertile (lowest variability, p = .032), after adjusting for covariates. We did not find an association of systolic BPV with other measures of sleep architecture. Diastolic BPV was not associated with sleep architecture either. In summary, our study showed that greater systolic BPV was associated with lower REM sleep duration. Future investigation is warranted to clarify the directionality, mechanism, and therapeutic implications.