The Association Between Sleep Breathing Impairment Index and Cardiovascular Risk in Male Patients with Obstructive Sleep Apnea

The Association of High Arousal Threshold with Hypertension and Diabetes in Obstructive Sleep Apnea

Objective

Compared to low arousal threshold (AT), high AT is an easily overlooked characteristic for obstructive sleep apnea (OSA) severity estimation. This study aims to evaluate the relationship between high AT, hypertension and diabetes in OSA, compared to those with apnea-hypopnea index (AHI).

Methods

A total of 3400 adults diagnosed with OSA were retrospectively recruited. Propensity score matching (PSM) was conducted to further categorize these patients into the low and high AT groups based on the strategy established by previous literature. The different degrees of AHI and quantified AT (AT score) were subsequently measured. The correlation of AT and AHI with the occurrence of various comorbidities in OSA was estimated by logistic regression analysis with odds ratio (OR).

Results

After PSM, 938 pairs of patients arose. The median AT score of high and low AT group was 21.7 and 12.2 scores, and the adjusted OR of high AT for hypertension and diabetes was 1.31 (95% CI = 1.07-1.62, P < 0.01) and 1.45 (95% CI = 1.01-2.08, P < 0.05), respectively. Compared to low AT score group, the OR significantly increased in patients with very high AT score (30 ≤ AT score), especially for diabetes (OR = 1.79, 95% CI = 1.02-3.13, P < 0.05). The significant association was not observed in AHI with increasing prevalent diabetes.

Conclusion

Higher AT is significantly associated with increased prevalence of hypertension and diabetes in patients with OSA. Compared with AHI, AT score is a potentially comprehensive indicator for better evaluating the relationship between OSA and related comorbidities.

Incremental values of AOPP, IL-6, and GDF15 for identifying arteriosclerosis in patients with obstructive sleep apnea

BACKGROUND

The objective of this study was to determine the independent and incremental values of advanced oxidative protein product (AOPP), interleukin 6 (IL-6), and growth differentiation factor 15 (GDF15) in identifying arteriosclerosis in patients with obstructive sleep apnea (OSA).

METHODS

A total of 104 individuals diagnosed with OSA by polysomnography were recruited in our study. Arteriosclerosis was defined by measuring the ultrafast pulse wave velocity of the carotid artery. Peripheral venous blood samples were collected to analyze the levels of AOPP, IL-6, and GDF15 utilizing commercially available enzyme-linked immunosorbent assays.

RESULTS

Compared to OSA patients without arteriosclerosis, those with arteriosclerosis exhibited significantly higher levels of AOPP, IL-6, and GDF15. GDF15 remained significantly associated with arteriosclerosis even after accounting for clinical factors such as age, gender, body mass index, systolic blood pressure, fasting blood glucose, smoking, and the apnea-hypoxia index (AHI). GDF15 demonstrated the largest area under the curve (AUC) for identifying arteriosclerosis in OSA patients (AUC, 0.85 [0.77-0.94]). The logistic regression model, combining clinical factors and AHI, was enhanced by the inclusion of AOPP and IL-6 (Chi-square = 25.06), and even further improved when GDF15 was added (Chi-square = 50.74). The integrated discrimination index increased by 0.06 to 0.16 when GDF15 was added to the models including clinical factors, AOPP, and IL-6.

CONCLUSIONS

This study verified the independent and incremental value of GDF15 in identifying arteriosclerosis in OSA patients, surpassing clinical risk factors and other serum biomarkers such as AOPP and IL-6.

Redefining Comorbid Insomnia and Sleep Apnea: The Association of Sleep Breathing Impairment and Insomnia with Incident Diabetes

Rationale: Obstructive sleep apnea (OSA) is a prevalent sleep disorder that is frequently comorbid with insomnia and often accompanied by metabolic diseases such as type 2 diabetes. Although the apnea-hypopnea index (AHI) is currently the diagnostic criterion for gauging the severity of OSA, the AHI has not consistently predicted incident diabetes. Objectives: To test whether a combined insomnia-OSA (COMISA) phenotype based on comorbid insomnia and sleep breathing impairment index (COMISA-SBII) predicts incident diabetes and to compare the association with an AHI definition of COMISA (COMISA-AHI) in the MrOS (Osteoporotic Fractures in Men) study. Methods: The study samples came from participants in the MrOS sleep study without diabetes at their baseline examination. The SBII was derived as the product of the duration of each respiratory event (apnea and hypopnea) and the accompanying desaturation area from baseline unattended polysomnography. A subgroup of individuals classified as having comorbid insomnia (difficulties falling asleep, waking up in the middle of the night and/or early morning awakenings >15 times per month, and daytime impairments) and sleep breathing impairment (greater than 50th percentile of SBII) were identified at baseline. The primary outcome was incident diabetes during the follow-up visits. Cox proportional models were built to assess the adjusted hazard ratios of COMISA-AHI and COMISA-SBII. Prediction model performances of incident diabetes were compared across different models. Results: A total of 2,365 men (mean age, 76 yr) without diabetes at baseline were included. During a median follow-up of 10.0 years, diabetes developed in 181. After adjusting for demographic characteristics, comorbidities, and behavioral risk factors, participants with COMISA-SBII had a higher risk of incident diabetes (hazard ratio, 1.82; 95% confidence interval, 1.15-2.89) than those without sleep disorders (those with an SBII ⩽13.17 and no insomnia). The result remained significant in the risk competing model. Compared with COMISA-AHI, the addition of COMISA-SBII to a crude model with established risk factors significantly improved the predictive value of incident diabetes. Conclusions: COMISA-SBII, but not COMISA-AHI, predicted incident diabetes after accounting for multiple covariates in a cohort of older men. A comorbid insomnia phenotype based on SBII plus insomnia symptoms may be an important clinical subtype.

Obstructive sleep apnoea heterogeneity and cardiovascular disease

Obstructive sleep apnoea (OSA), characterized by recurrent periods of upper airway obstruction and intermittent hypoxaemia, is prevalent in patients with cardiovascular disease (CVD), and is therefore important to consider in the prevention and management of CVD. Observational studies indicate that OSA is a risk factor for incident hypertension, poorly controlled blood pressure, stroke, myocardial infarction, heart failure, cardiac arrhythmias, sudden cardiac death and all-cause death. However, clinical trials have not provided consistent evidence that treatment with continuous positive airway pressure (CPAP) improves cardiovascular outcomes. These overall null findings might be explained by limitations in trial design and low levels of adherence to CPAP. Studies have also been limited by the failure to consider OSA as a heterogeneous disorder that consists of multiple subtypes resulting from variable contributions from anatomical, physiological, inflammatory and obesity-related risk factors, and resulting in different physiological disturbances. Novel markers of sleep apnoea-associated hypoxic burden and cardiac autonomic response have emerged as predictors of OSA-related susceptibility to adverse health outcomes and treatment response. In this Review, we summarize our understanding of the shared risk factors and causal links between OSA and CVD and emerging knowledge on the heterogeneity of OSA. We discuss the varied mechanistic pathways that result in CVD that also vary across subgroups of OSA, as well as the potential role of new biomarkers for CVD risk stratification.

The effectiveness of sleep breathing impairment index in assessing obstructive sleep apnea severity

STUDY OBJECTIVES

Using the apnea-hypopnea index (AHI) and the sleep breathing impairment index (SBII) to assess the severity of obstructive sleep apnea (OSA) to study how effective SBII is in assessing the severity and cardiovascular disease (CVD) prognosis.

METHODS

This study comprised a total of 147 patients with diagnosed OSA. The AHI and SBII were calculated from the polysomnography. Patients were enrolled in the cluster analysis using 20 symptoms and the SBII. The prognostic indicator was determined as the moderate-to-high Framingham 10-year CVD risk.

RESULTS

Cluster analysis revealed 3 separate groups: cluster 1 (n = 45, 30.61%) had the lowest symptoms complaints yet the highest PSQI score; cluster 2 (n = 70, 47.62%) had considerably increased symptom complaints but the lowest Epworth Sleepiness Scale score, intermediate PSG indices, a higher low arousal threshold possibility, and a lower SBII quantile; cluster 3 (n = 32, 21.77%) had the largest percentage of smokers, a predominant symptom of restless sleep, severe PSG characteristics, a lower low arousal threshold likelihood, a greater SBII quantile and a higher Framingham CVD risk. There were no differences in severity indicated by AHI between groups. Higher SBII rather than AHI is associated with an increased 10-year CVD risk.

CONCLUSIONS

SBII provides higher sensitivity when evaluating OSA severity and better predictive capabilities for CVD outcomes. SBII may be a more effective substitute for AHI in the future.

CITATION

Dai L, Cao W, Luo J, Huang R, Xiao Y. The effectiveness of sleep breathing impairment index in assessing obstructive sleep apnea severity. J Clin Sleep Med. 2023;19(2):267-274.

Shorter respiratory event duration is related to prevalence of type 2 diabetes

BACKGROUND

Obstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea-hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM.

METHODS

Patients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses.

RESULTS

A total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92-0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91-0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12-1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM.

CONCLUSION

The average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.

New Metrics from Polysomnography: Precision Medicine for OSA Interventions

Obstructive sleep apnea (OSA) is a highly preventable disease accompanied by multiple comorbid conditions. Despite the well-established cardiovascular and neurocognitive sequelae with OSA, the optimal metric for assessing the OSA severity and response to therapy remains controversial. Although overnight polysomnography (PSG) is the golden standard for OSA diagnosis, the abundant information is not fully exploited. With the development of deep learning and the era of big data, new metrics derived from PSG have been validated in some OSA consequences and personalized treatment. In this review, these metrics are introduced based on the pathophysiological mechanisms of OSA and new technologies. Emphasis is laid on the advantages and the prognostic value against apnea-hypopnea index. New classification criteria should be established based on these metrics and other clinical characters for precision medicine.

Duration of respiratory events in obstructive sleep apnea: In search of paradoxical results

Research related to the duration of respiratory events in obstructive sleep apnea (OSA) has been scarce, perhaps due to the dominant role played by the apnea-hypopnea index (AHI) in the diagnosis and severity estimation of OSA. Lately, however, researchers and clinicians have started to acknowledge the importance of this overlooked parameter. Intuitively, 40-s-long apneas have more harmful physiological and health consequences than 10-s-long apneas. But is this the case? Here, we review the research-based evidence showing physiological, hemodynamic, clinical, sleep quality, and health consequences of long vs. short respiratory events. Most of the reviewed studies support the idea that longer respiratory events have more severe physiological and clinical consequences than shorter events, most probably due to the higher hypoxic burden associated with longer respiratory events. However, a few but highly qualified studies provide clear evidence that short respiratory events have also a deleterious effect on sleep and the physiological and clinical aspects of OSA. The somewhat paradoxical findings that short respiratory events are also associated with a high risk of all-cause mortality is a serious concern. From these results, it is therefore evident that the duration of respiratory events should be quantified when diagnosing and assessing the severity of OSA.

Association of sleep-related disorders with cardiovascular disease among adults in the United States: A cross-sectional study based on national health and nutrition examination survey 2005–2008

Background and objective

The association between sleep-related disorders and cardiovascular diseases (CVDs) remains controversial and lacks epidemiological evidence in the general population. We investigated whether sleep-related disorders are related to CVDs in a large, nationally representative, diverse sample of American adults.

Materials and methods

Data were collected from the National Health and Nutrition Examination Survey (NHANES) 2005–2008. Logistic regression was performed to explore associations of sleep-related disorders with the prevalence of total and specific CVDs. Stratified subgroup analysis was performed to exclude interactions between variables and sleep-related disorders. Non-linearity was explored using restricted cubic splines.

Results

In total, 7,850 participants aged over 20 years were included. After controlling for confounders, multivariate regression analysis showed that sleep problems were associated increases in risk of 75% for CVD (OR: 1.75; 95% CI 1.41, 2.16), 128% for congestive heart failure (CHF) (OR: 2.28; 95% CI 1.69, 3.09), 44% for coronary heart disease (CHD) (OR: 1.44; 95% CI 1.12, 1.85), 96% for angina pectoris (AP) (OR: 1.96; 95% CI 1.40, 2.74), 105% for heart attack (OR: 2.05; 95% CI 1.67, 2.53) and 78% for stroke (OR: 1.78; 95% CI 1.32, 2.40). Daytime sleepiness was associated increases in risk of 54% for CVD (OR: 1.54; 95% CI 1.25, 1.89), 73% for CHF (OR: 1.73; 95% CI 1.22, 2.46), 53% for AP (OR: 1.53; 95% CI 1.12, 2.10), 51% for heart attack (OR: 1.51; 95% CI 1.18, 1.95), and 60% for stroke (OR: 1.60; 95% CI 1.09, 2.36). Participants with insufficient sleep had a 1.42-fold higher likelihood of CVD (OR: 1.42; 95% CI 1.13, 1.78) and a 1.59-fold higher likelihood of heart attack (OR: 1.59; 95% CI 1.19, 2.13) than participants with adequate sleep. Prolonged sleep-onset latency was associated with an increased risk of CVD (OR: 1.59; 95% CI 1.17, 2.15), CHF (OR: 2.08; 95% CI 1.33, 3.23) and heart attack (OR: 1.76; 95% CI 1.29, 2.41). Short sleep-onset latency was associated with a 36% reduction in stroke risk (OR: 0.64; 95% CI 0.45, 0.90). The association of sleep problems with CVD risk was more pronounced in the group younger than 60 years (p for interaction = 0.019), and the relationship between short sleep-onset latency and total CVD differed by sex (p for interaction = 0.049). Additionally, restricted cubic splines confirmed a linear relationship between sleep-onset latency time and CVD (p for non-linearity = 0.839) and a non-linear relationship between sleep duration and CVD (p for non-linearity <0.001).

Conclusion

According to a limited NHANES sample used to examine sleep-related disorders and CVD, total and specific CVDs could be associated with certain sleep-related disorders. Additionally, our study uniquely indicates that CVD risk should be considered in participants younger than 60 years with sleep problems, and shortened sleep-onset latency may be a CVD protective factor in females.

Risk of Cardiovascular Disease in Apnoeic Individuals: Role of Comorbid Insomnia Disorder

Given the limited data available, the aim of this study was to examine the 10-year cardiovascular disease (CVD) risk associated with comorbid insomnia disorder and its specific subtypes in apnoeic individuals. Data from 1104 apnoeic individuals recruited from the database of the Erasme Hospital Sleep Laboratory were analysed. Only apnoeic individuals with a Framingham Risk Score ≥10% were included in the group at moderate-to-high 10-year CVD risk. Logistic regression analyses were conducted to examine the risk of 10-year CVD risk associated with comorbid insomnia disorder and its specific subtypes in apnoeic individuals. Moderate-to-high 10-year CVD risk was present in 59.6% of the apnoeic individuals in our sample. After adjustment for the main confounding factors, multivariate logistic regression analyses revealed that comorbid insomnia disorder and, more particularly, its subtype with short sleep duration were significantly associated with moderate-to-high 10-year CVD risk in apnoeic individuals. In this study, we demonstrate that comorbid insomnia disorder and, more specifically, its subtype with short sleep duration appear to have a negative cumulative effect on 10-year CVD risk in apnoeic individuals, which justifies more systematic research and adequate therapeutic management of this disorder to allow for better cardiovascular disease prevention in this particular subpopulation.

Sleep and Stroke: Opening Our Eyes to Current Knowledge of a Key Relationship

PURPOSE OF REVIEW

To elucidate the interconnection between sleep and stroke.

RECENT FINDINGS

Growing data support a bidirectional relationship between stroke and sleep. In particular, there is strong evidence that sleep-disordered breathing plays a pivotal role as risk factor and concur to worsening functional outcome. Conversely, for others sleep disorders (e.g., insomnia, restless legs syndrome, periodic limb movements of sleep, REM sleep behavior disorder), the evidence is weak. Moreover, sleep disturbances are highly prevalent also in chronic stroke and concur to worsening quality of life of patients. Promising novel technologies will probably allow, in a near future, to guarantee a screening of commonest sleep disturbances in a larger proportion of patients with stroke. Sleep assessment and management should enter in the routinary evaluation of stroke patients, of both acute and chronic phase. Future research should focus on the efficacy of specific sleep intervention as a therapeutic option for stroke patients.