Sleep Apnea and Sudden Cardiac Death

Sleep-disordered breathing destabilizes ventricular repolarization: Cross-sectional, longitudinal, and experimental evidence

BACKGROUND

Sleep-disordered breathing (SDB) increases the risk of cardiac arrhythmias and sudden cardiac death.

OBJECTIVE

This study sought to characterize the associations between SDB, intermittent hypoxemia, and the beat-to-beat QT variability index (QTVI), a measure of ventricular repolarization lability associated with cardiac arrhythmias and sudden cardiac death.

METHODS

Three distinct cohorts were used: a matched sample of 122 participants with and without severe SDB for cross-sectional analysis; a matched sample of 52 participants with and without incident SDB for longitudinal analysis; and a sample of 19 healthy adults exposed to acute intermittent hypoxia and ambient air on 2 separate days. The cross-sectional and longitudinal cohorts were the Sleep Heart Health Study participants with no known comorbidities who were not taking any drugs known to affect cardiac repolarization and satisfied the inclusion criteria. Electrocardiographic measures were calculated from 1-lead electrocardiograms.

RESULTS

Participants with severe SDB had greater QTVI than those without SDB (P = .027). Total sleep time with <90% oxygen saturation, but not the arousal frequency, was a predictor of QTVI. QTVI during sleep was predictive of all-cause mortality. With incident SDB, mean QTVI increased from -1.23 to -0.86 during 5 years (P = .017). Finally, experimental exposure of healthy adults to acute intermittent hypoxia for 4 hours progressively increased QTVI (P = .016).

CONCLUSION

The results show that both prevalent SDB and incident SDB are associated with ventricular repolarization instability and suggest intermittent hypoxemia as the underlying mechanism that may contribute to increased mortality in SDB.

The value of circadian heart rate variability for the estimation of obstructive sleep apnea severity in adult males

OBJECTIVES

Heart rate variability (HRV) is becoming more prevalent as a measurable parameter in wearable sleep-monitoring devices, which are simple and effective instruments for illness evaluation. Currently, most studies on investigating OSA severity and HRV have measured heart rates during wakefulness or sleep. Therefore, the objective of this study was to investigate the circadian rhythm of HRV in male patients with OSA and its value for the estimation of OSA severity using group-based trajectory modeling.

METHODS

Patients with complaints of snoring were enrolled from the Sleep Center of Shandong Qianfoshan Hospital. Patients were divided into 3 groups according to apnea hypopnea index (AHI in events/h), as follows: (<15, 15≤AHI<30, and ≥30). HRV parameters were calculated using 24 h Holter monitoring, which included time-domain and frequency-domain indices. Circadian differences in the standard deviation of normal to normal (SDNN) were evaluated for OSA severity using analysis of variance, trajectory analysis, and multinomial logistic regression.

RESULTS

A total of 228 patients were enrolled, 47 with mild OSA, 48 moderate, and 133 severe. Patients with severe OSA exhibited reduced triangular index and higher very low frequency than those in the other groups. Circadian HRV showed that nocturnal SDNN was considerably higher than daytime SDNN in patients with severe OSA. The difference among the OSA groups was significant at 23, 24, 2, and 3 o'clock sharp between the severe and moderate OSA groups (all P<0.05). The heterogeneity of circadian HRV trajectories in OSA was strongly associated with OSA severity, including sleep structure and hypoxia-related parameters. Among the low-to-low, low-to-high, high-to-low, and high-to-high groups, OSA severity in the low-to-high group was the most severe, especially compared with the low-to-low and high-to-low SDNN groups, respectively.

CONCLUSIONS

Circadian HRV in patients with OSA emerged as low daytime and high nocturnal in SDNN, particularly in men with severe OSA. The heterogeneity of circadian HRV revealed that trajectories with low daytime and significantly high nighttime were more strongly associated with severe OSA. Thus, circadian HRV trajectories may be useful to identify the severity of OSA.

The Effects of Obstructive Sleep Apnea on the Cardiovascular System: A Comprehensive Review

Obstructive sleep apnea (OSA) is an increasingly relevant cause of cardiovascular morbidity worldwide. Although the association between OSA and the cardiovascular system is well-known, the extent of its effects is still a topic of interest, including pathophysiologic mechanisms, cardiovascular sequelae, and OSA therapies and their effects. Commonly described mechanisms of cardiovascular etiologies revolve around sympathetic activation, inflammation, and intermittent hypoxia resulting from OSA. Ultimately, these effects lead to manifestations in the cardiovascular system, such as arrhythmias, hypertension, and heart failure, among others. The resulting sequelae of OSA may also have differential effects based on gender and age; several studies suggest female gender to have more susceptibility to cardiovascular mortality, as well as an increase in age. Furthermore, several therapies for OSA, both established and emerging, show a reduction in cardiovascular morbidity and may even reduce cardiovascular burden. Namely, the establishment of CPAP has led to improvement in hypertension and cardiac function in patients with heart failure and even reduced the progression of early stages of atherosclerosis. Effective management of OSA decreases abnormal neural sympathetic activity, which results in better rhythm control and blood pressure control, both in waking and sleep cycles. With newer therapies for OSA, its effects on the cardiovascular system may be significantly reduced or even reversed after long-term management. The vast extent of OSA on the cardiovascular system, as well as current and future therapeutic strategies, will be described in detail in this review.

Sleep apnea, the risk of out-of-hospital cardiac arrest, and potential benefits of continuous positive airway pressure therapy: A nationwide study

OBJECTIVE

Patients with sleep apnea (SA) are at increased cardiovascular risk. However, little is known about the risk of out-of-hospital cardiac arrest (OHCA) in patients with SA. Therefore, we studied the relation between SA patients who did and did not receive continuous positive airway pressure (CPAP) therapy with OHCA in the general population.

METHODS

Using nationwide databases, we conducted a nested case-control study with OHCA-cases of presumed cardiac causes and age/sex/OHCA-date matched non-OHCA-controls from the general population. Conditional logistic regression models with adjustments for well-known OHCA risk factors were performed to generate odds ratio (OR) of OHCA comparing patients with SA receiving and not receiving CPAP therapy with individuals without SA.

RESULTS

We identified 46,578 OHCA-cases and 232,890 matched non-OHCA-controls [mean: 71 years, 68.8% men]. Compared to subjects without SA, having SA without CPAP therapy was associated with increased odds of OHCA after controlling for relevant confounders (OR:1.20, 95%-Cl:1.06-1.36), while having SA with CPAP therapy was not associated with OHCA (OR:1.04, 95%-Cl:0.93-1.36). Regardless of CPAP therapy, age and sex did not significantly influence our findings. Our findings were confirmed in: (I) patients with neither ischemic heart disease nor heart failure (untreated SA, OR:1.24, 95%-CI:1.04-1.47; SA with CPAP, OR:1.08, 95%-CI:0.93-1.25); and (II) in patients without cardiovascular disease (untreated SA, OR:1.33, 95%-CI:1.07-1.65; SA with CPAP, OR:1.14, 95%-CI:0.94-1.39).

CONCLUSION

SA not treated with CPAP was associated with OHCA, while no increased risk of OHCA was found for SA patients treated with CPAP.

Sleep-Disordered Breathing Destabilizes Ventricular Repolarization

Rationale

Sleep-disordered breathing (SDB) increases the risk of cardiac arrhythmias and sudden cardiac death.

Objectives

To characterize the associations between SDB, intermittent hypoxemia, and the beat-to-beat QT variability index (QTVI), a measure of ventricular repolarization lability associated with a higher risk for cardiac arrhythmias, sudden cardiac death, and mortality.

Methods

Three distinct cohorts were used for the current study. The first cohort, used for cross-sectional analysis, was a matched sample of 122 participants with and without severe SDB. The second cohort, used for longitudinal analysis, consisted of a matched sample of 52 participants with and without incident SDB. The cross-sectional and longitudinal cohorts were selected from the Sleep Heart Health Study participants. The third cohort comprised 19 healthy adults exposed to acute intermittent hypoxia and ambient air on two separate days. Electrocardiographic measures were calculated from one-lead electrocardiograms.

Results

Compared to those without SDB, participants with severe SDB had greater QTVI (-1.19 in participants with severe SDB vs. -1.43 in participants without SDB, P = 0.027), heart rate (68.34 vs. 64.92 beats/minute; P = 0.028), and hypoxemia burden during sleep as assessed by the total sleep time with oxygen saturation less than 90% (TST90; 11.39% vs. 1.32%, P < 0.001). TST90, but not the frequency of arousals, was a predictor of QTVI. QTVI during sleep was predictive of all-cause mortality. With incident SDB, mean QTVI increased from -1.23 to -0.86 over 5 years (P = 0.017). Finally, exposing healthy adults to acute intermittent hypoxia for four hours progressively increased QTVI (from -1.85 at baseline to -1.64 after four hours of intermittent hypoxia; P = 0.016).

Conclusions

Prevalent and incident SDB are associated with ventricular repolarization instability, which predisposes to ventricular arrhythmias and sudden cardiac death. Intermittent hypoxemia destabilizes ventricular repolarization and may contribute to increased mortality in SDB.

A Comprehensive Review of Solriamfetol to Treat Excessive Daytime Sleepiness

Purpose of Review

This is a comprehensive review of the literature regarding the use of Solriamfetol for excessive daytime sleepiness. It covers the background and current therapeutic approaches to treating excessive daytime sleepiness, the management of common comorbidities, and the existing evidence investigating the use of Solriamfetol for this purpose.

Recent Findings

Excessive daytime sleepiness leads to worse quality of life, a medical sequela and significant economic cost. There are multiple phenotypes of excessive daytime sleepiness depending on the comorbidity making treatment challenging. Due to the complexity of etiology there is not a cure for this ailment. Solriamfetol is a norepinephrine/dopamine dual reuptake antagonist that can be used to manage daytime sleepiness. Solriamfetol was first approved by the FDA in 2018 for use in excessive daytime sleepiness associated with obstructive sleep apnea and narcolepsy. Ongoing literature has proved this drug to be a safe and effective alternative pharmacotherapy.

Summary

Recent epidemiological data estimate up to one-third of the general adult population suffers from excessive daytime sleepiness. There is no cure to daytime somnolence and current pharmacotherapeutic regimens have worrisome side effect profiles. Solriamfetol is a new class of drug that offers a safe and effective alternative option for clinical providers treating excessive daytime sleepiness.

Risk of Sleep Apnea Is Associated with Abdominal Obesity Among Asian Americans: Comparing Waist-to-Hip Ratio and Body Mass Index

OBJECTIVE

This study examines associations between the risk of sleep apnea and abdominal obesity (assessed by waist-to-hip ratio (WHR)) and general obesity (assessed by body mass index (BMI)) in a sample of Chinese and Korean American immigrants.

METHODS

The dataset included Chinese and Korean participants aged 50-75 who were recruited from primary care physicians' clinics from April 2018 to June 2020 in the Baltimore-Washington D.C. Metropolitan area (n = 394). Abdominal obesity was determined if WHR ≥ 0.9 in men and WHR ≥ 0.85 in women. General obesity was determined if BMI ≥ 30. The risk of sleep apnea was determined by using the Berlin questionnaire. Poisson regression models examined associations between sleep apnea risk and obesity. Models controlled for socio-demographic risk factors.

RESULTS

Twelve percent of the study participants were classified as a high risk for sleep apnea, and 75% had abdominal obesity whereas 6.4% had general obesity. High risk of sleep apnea was positively associated with abdominal obesity (PR = 1.31, 95% CI: 1.17-1.47) and general obesity (PR = 2.19, 95% CI: 0.90-5.32), marginally significant at p < 0.1).

CONCLUSIONS

Chinese and Korean immigrants living in the USA who are at high risk of sleep apnea have higher abdominal obesity, even after accounting for sociodemographic characteristics. Abdominal obesity may be a better indicator than general obesity when examining the risk of sleep apnea among Asian Americans.

INFORMATION ON CLINICAL TRIAL

Name: Screening To Prevent ColoRectal Cancer (STOP CRC) among At-Risk Asian American Primary Care Patients NCT Number: NCT03481296; Date of registration: March 29, 2018 URL: https://clinicaltrials.gov/ct2/show/NCT03481296?term=Sunmin+Lee&draw=2&rank=1.

Prevalence of Obstructive Sleep Apnea Using Home Sleep Test in Taiwan During the Coronavirus Disease Pandemic

Background

Obstructive sleep apnea syndrome (OSAS) is a common disorder associated with serious sequelae. The current gold standard diagnostic method, polysomnography, is costly and time consuming and requires patients to stay overnight at a facility.

Aim

This study aimed to reveal the prevalence of OSAS in general adult population using a home sleep test (HST) during the coronavirus disease 2019 (COVID-19) pandemic.

Methods

This prospective cohort study was conducted by the Department of Otolaryngology, Taipei City Hospital, Taipei, Taiwan, between January 2020 and December 2021. A total of 1372 patients aged 30-70 years completed an HST using a Type 3 portable sleep monitor (PM). The apnea-hypopnea index (AHI) was analyzed to assess the association of OSAS with age, body mass index (BMI), sex, Epworth Sleepiness Scale (ESS) and the Sleep Apnea Risk Assessment questionnaire (STOP-Bang questionnaire) rating.

Results

The mean age of the patients (782 men, 57%; 590 women, 43%) was 49.24 ± 11.04 years. OSAS was detected in 954 (69.5%) patients with 399 (29.1%) mild OSAS; 246 (17.9%) moderate OSAS; and 309 (22.5%) severe OSAS. Among these, the prevalence of moderate-to-severe OSAS was 143 (10.4%) in women and 412 (30.0%) in men. The mean age was the highest (51.29 ± 11.29) in the mild OSAS group and lowest (47.08 ± 10.87) in the healthy group. OSAS severity was greater with increasing BMI, 23.39 ± 3.44 in the healthy group and 29.29 ± 5.01 in the severe OSAS group. A positive correlation was also noted between the ESS/STOP-Bang questionnaire rating and OSAS severity.

Conclusion

The prevalence of OSAS in Taiwan was 69.5% in our study. It showed strong evidence that OSAS has important public health consequences and PMs are simple, fast, feasible, and cost-effective tools for OSAS screening in the home environment, especially during the COVID-19 pandemic.

A model study for the classification of high-risk groups for cardiac arrest in general ward patients using simulation techniques

Currently, many hospitals use vital signs-based criteria such as modified early warning score (MEWS) and national early warning score (NEWS) to classify high-risk patients for cardiac arrest, but there are limitations in selecting high-risk patients with a possibility of cardiac arrest. The purpose of this study is to develop a cardiac arrest classification model to identify patients at high risk of cardiac arrest based on the patient family and past history, and blood test results after hospitalization, rather than vital signs. This study used electronic medical record (EMR) data from A university hospital, and patients in the high-risk group for cardiac arrest were defined as those who underwent cardio-pulmonary resuscitation (CPR) after cardiac arrest. Considering the use of the rapid response team of A university hospital, patients hospitalized in intensive care units (ICU), emergency medicine departments, psychiatric departments, pediatric departments, cardiology departments, and palliative care wards were excluded. This study included 325,534 patients, of which 3291 low-risk and 382 high-risk patients were selected for study. Data were split into training and validation data sets and univariate analysis was performed for 13 candidate risk factors. Then, multivariate analysis was performed using a bivariate logistic regression model, and an optimal model was selected using simulation analysis. In the training data set, it was calculated as sensitivity 75.25%, precision 21.59%, specificity 66.89%, accuracy 67.79%, F1 score 33.56, area under curve (AUC) 71.1 (95% confidence interval [CI] = 68.9-73.1 P value=<.001). In the validation data set, sensitivity 73.37%, precision 25.81%, specificity 75.03%, accuracy 74.86%, F1 score 38.19, AUC 74.2 (95% CI = 72.1-76.2, P value=<.001) were calculated. A model for classifying the high-risk group of cardiac arrest should be developed from various perspectives. In the future, in order to classify patients with high risk of cardiac arrest, a prospective study on the combined use of the model developed by this study and NEWS or MEWS should be conducted.

Obstructive Sleep Apnea and Cardiovascular Risk: The Role of Dyslipidemia, Inflammation, and Obesity

Introduction: The present study aimed to establish the role of lipid abnormalities and inflammatory markers for developing cardiovascular risk, as well as to address the importance of obesity as a common comorbidity in patients with obstructive sleep apnea (OSA).

Methods: The study was conducted as a prospective cohort study including 120 patients with newly diagnosed OSA between 2019 and 2020, at University Clinical Hospital Center “Bezanijska kosa”, Belgrade, Serbia. The diagnosis was established by polysomnography. In all patients, sociodemographic data, respiratory, lipid, and inflammatory parameters were collected and complete echocardiographic study and 24-h blood pressure monitoring were performed.

Results: The mean patient age was 55.7 ± 13.8 years. Study population was mostly male (70.0%) and obese (56.7%). At least 30 apneas or hypopneas per hour were present in 39.0% of patients. A strong positive correlation was found between OSA severity and BMI (r = 0.562, p < 0.001), both associated with lipid, inflammatory and respiratory parameters, and cardiovascular profile of patients with OSA (p < 0.05 for all). Echocardiographic study and 24-h blood pressure monitoring parameters were in turn correlated with lipid and inflammatory markers (p < 0.05 for all).

Conclusion: The results of this study support the important role of dyslipidemia and inflammation, as well as coexistence of obesity in the pathogenesis of numerous conditions linked with an increased risk of cardiovascular morbidity and mortality in patients with OSA.

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.