Sleep apnea and diabetes: insights into the emerging epidemic

Changes in physiological signal entropy in patients with obstructive sleep apnoea: a systematic review

Background and Objective.Obstructive sleep apnoea (OSA) affects an estimated 936 million people worldwide, yet only 15% receive a definitive diagnosis. Diagnosis of OSA poses challenges due to the dynamic nature of physiological signals such as oxygen saturation (SpO2) and heart rate variability (HRV). Linear analysis methods may not fully capture the irregularities present in these signals. The application of entropy of routine physiological signals offers a promising method to better measure variabilities in dynamic biological data. This review aims to explore entropy changes in physiological signals among individuals with OSA.Approach.Keyword and title searches were performed on Medline, Embase, Scopus, and CINAHL databases. Studies had to analyse physiological signals in OSA using entropy. Quality assessment used the Newcastle-Ottawa Scale. Evidence was qualitatively synthesised, considering entropy signals, entropy type, and time-series length.Main results.Twenty-two studies were included. Multiple physiological signals related to OSA, including SpO2, HRV, and the oxygen desaturation index (ODI), have been investigated using entropy. Results revealed a significant decrease in HRV entropy in those with OSA compared to control groups. Conversely, SpO2and ODI entropy values were increased in OSA. Despite variations in entropy types, time scales, and data extraction devices, studies using receiver operating characteristic curves demonstrated a high discriminative accuracy (>80% AUC) in distinguishing OSA patients from control groups.Significance. This review highlights the potential of SpO2entropy analysis in developing new diagnostic indices for patients with OSA. Further investigation is needed before applying this technique clinically.

Sleep stages classification by fusing the time-related synchronization analysis and brain activations

Sleep staging plays an important role in the diagnosis and treatment of clinical sleep disorders. The sleep staging standard defines every 30 seconds as a sleep period, which may mean that there exist similar brain activity patterns during the same sleep period. Thus, in this work, we propose a novel time-related synchronization analysis framework named time-related multimodal sleep scoring model (TRMSC) to explore the potential time-related patterns of sleeping. In the proposed TRMSC, the time-related synchronization analysis is first conducted on the single channel electrophysiological signal, i.e., Electroencephalogram (EEG) and Electrooculogram (EOG), to explore the time-related patterns, and the spectral activation features are also extracted by spectrum analysis to obtain the multimodal features. With the extracted multimodal features, the feature fusion and selection strategy is utilized to obtain the optimal feature set and achieve robust sleep staging. To verify the effectiveness of the proposed TRMSC, sleep staging experiments were conducted on the Sleep-EDF dataset, and the experimental results indicate that the proposed TRMSC has achieved better performance than other existing strategies, which proves that the time-related synchronization features can make up for the shortcomings of traditional spectrum-based strategies and achieve a higher classification accuracy. The proposed TRMSC model may be helpful for portable sleep analyzers and provide a new analytical method for clinical sleeping research.

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.

Tailored Approach to Sleep Health Education (TASHE): a randomized controlled trial of a web-based application

STUDY OBJECTIVES

In a randomized controlled trial, we compared the effect of the Tailored Approach to Sleep Health Education (TASHE) on obstructive sleep apnea (OSA) self-efficacy among community-dwelling blacks in New York City.

METHODS

Study participants were 194 blacks at high risk for OSA based on the Apnea Risk Evaluation System. TASHE intervention was delivered via a Wi-Fi-enabled tablet, programmed to provide online access to culturally and linguistically tailored information designed to address unique barriers to OSA care among blacks. Blacks in the attention-controlled arm received standard sleep information via the National Sleep Foundation website. Blacks in both arms accessed online sleep information for 2 months. Outcomes (OSA health literacy, self-efficacy, knowledge and beliefs, and sleep hygiene) were assessed at baseline, at 2 months, and at 6 months.

RESULTS

We compared outcomes in both arms based on intention-to-treat analysis using adjusted Generalized Linear Mixed Modeling. TASHE exposure significantly increased OSA self-efficacy (OSA outcome expectation [β = .5; 95% CI: .1-.9] and OSA treatment efficacy [β = 0.4; 95% CI: .0-.8]) at 2 months but not at 6 months. Additionally, TASHE exposure improved sleep hygiene at 6 months (β = 6.7; 95% CI: 2.2-11.3) but not at 2 months.

CONCLUSIONS

Community-dwelling blacks exposed to TASHE materials reported increased OSA self-efficacy compared with standard sleep health education. Stakeholder-engaged, theory-based approaches, as demonstrated in the TASHE intervention, can be used successfully to deliver effective sleep health messages.

CLINICAL TRIAL REGISTRATION

Registry: ClinicalTrials.gov; URL: https://clinicaltrials.gov/ct2/show/NCT02507089; Identifier: NCT02507089.

Strategies for the Prevention of Coronary Artery Disease Complications: Can We Do Better?

Billions of dollars have been spent over the past 25 years on developing new therapies for the prevention/treatment of adverse cardiac events related to atherosclerotic cardiovascular disease. Although some therapies have been lifesaving, several mega-randomized studies have shown only a <2% absolute reduction in adverse events with a large residual event rate. Is all this money well spent? Atherosclerosis develops decades before an adverse event, and the trials previously alluded to have nearly always been applied to secondary prevention, decades after disease initiation. Will earlier intervention result in a lower incidence of events? Individuals with an absence of the usual cardiac risk factors have a lifelong low incidence of events. Early initiation of strategies against the common cardiovascular risk factors in primary or primordial prevention will lower the incidence of adverse events, although many groups have not been well studied, including individuals younger than 40 years of age. New strategies are required to realize a radical reduction in events, and this article proposes new methods of prevention/treatment for coronary artery disease complications.

Impact of non-apnea sleep disorders on diabetic control and metabolic outcome - A population-based cohort study

OBJECTIVE

There has been a growing recognition that obstructive sleep apnea (OSA) could increase the propensity for type 2 diabetes the metabolic syndrome. However, studies concerning about the impact of non-apnea sleep disorders (NSD) on diabetes control and metabolic outcomes are relatively scarce. Our aim is to investigate the impact of non-apnea sleep disorders (NSD) on diabetic control and associated metabolic outcomes in patients with type 2 diabetes.

METHODS

The data were obtained from two nationwide population-based databases for a period 2007 to 2012. A total 66,992 patients with type 2 diabetes were enrolled and divided into two cohorts based on comorbidity with or without a NSD diagnosis, and were followed up four years. The primary outcomes were to compare rate of change in HbA1c and associated metabolic outcomes during follow-up visits between patients with or without NSD. The secondary outcome is to examine whether NSD were associated with poor glycemic control of the last clinical records while controlling for the baseline HbA1c value.

RESULTS

Of the 66,992 patients with type 2 diabetes, 14.82% had comorbidity with a NSD. HbA1C decreases were significantly lower by 0.04% in the NSD group (P < 0.05), and triglyceride (TG) decreases remained significantly lower by 2.53% in the NSD group (P < 0.05). Furthermore, patients in the NSD group had an 8% higher risk of poor glycemic control (HbA1C >9) (OR = 1.08; 95%CI, 1.01-1.16).

CONCLUSION

Our findings indicated patients with type 2 diabetes comorbid with NSD had a slower improvement in HbA1c compared with the comparison cohort. It may because there may exist potential floor effect given those with NSD having significantly lower HbA1c values at baseline. On the other hand, the poor diabetic control among those with NSD may be also affected by other confounders such as medical treatment or interventions. Nevertheless, given the rapidly increasing prevalence of metabolic diseases and subsequent complications, the results may highlight the importance of sleep in the clinical management of type 2 diabetes.

Obstructive sleep apnea and stroke: links to health disparities

Obstructive sleep apnea (OSA) is a novel cardiovascular and cerebrovascular risk factor that presents unique opportunities to understand and reduce seemingly intractable stroke disparity among non-Hispanic blacks and Hispanic/Latinos. Individuals from these 2 groups have up to a 2-fold risk of stroke and greater burden of OSA. Obstructive sleep apnea directly and indirectly increases risk of stroke through a variety of autonomic, chemical, and inflammatory mechanisms and vascular risk factors such as hypertension, obesity, and diabetes mellitus. Untreated OSA exacerbates poststroke prognosis, as it may also influence rehabilitation efforts and functional outcomes such as cognitive function after a stroke. Conversely, treatment of OSA may reduce the risk of stroke and may yield better poststroke prognosis. Unfortunately, in racial/ethnic minority groups, there are limited awareness, knowledge, and screening opportunities for OSA. Increasing awareness and improving screening strategies for OSA in minorities may alleviate stroke risk burden and improve stroke outcomes in these populations. This review article is intended to highlight the epidemiology, clinical characteristics, pathophysiology, diagnosis, and treatment of OSA in relation to stroke risk, with an emphasis on race-ethnic disparities.

Risk of Type 2 Diabetes in Patients With Nonapnea Sleep Disorders in Using Different Types of Hypnotics: A Population-Based Retrospective Cohort Study

There has been insufficient evidence on whether exposure to hypnotics affects the risk of type 2 diabetes (T2DM). The aim of this study was to examine patients with nonapnea sleep disorders using zolpidem, benzodiazepines (BZDs), or a combination of both, and their risk of T2DM. This was a population-based retrospective cohort study using data from 1997 to 2011. Data from the Taiwan National Health Insurance Research Database were employed for this study. A total of 45,602 patients with nonapnea sleep disorders and use of hypnotics were identified as the study cohort. The control cohort comprised 40,799 age- and sex-matched patients. We conducted a Cox proportional hazard regression analysis to estimate the effects of hypnotics on risk of T2DM. The overall incidence of T2DM was 20.1 per 1000 person-years for patients using zolpidem, which was significantly higher than that of the control group (11.9 per 1000 person-years). Overall, patients with nonapnea sleep disorders using zolpidem had a higher risk of T2DM compared with patients not using zolpidem and the control cohort (adjusted hazard ratio [HR] = 1.41, 95% confidence interval [CI] = 1.35-1.48). We also observed a significantly higher risk of T2DM in patients with both zolpidem and BZD use (adjusted HR = 1.77, 95% CI = 1.64-1.91) than that of those without zolpidem use and BZD use. Compared with patients not using hypnotics, patients using zolpidem had a higher risk of developing T2DM; the risk was particularly pronounced in those using both zolpidem and BZDs.

Associations between sleep disturbances and diabetes mellitus among blacks with metabolic syndrome: Results from the Metabolic Syndrome Outcome Study (MetSO)

INTRODUCTION

The association between sleep disturbances and cardiometabolic diseases has been understudied in blacks with metabolic syndrome.

METHODS

This study is a cross-sectional analysis of the Metabolic Syndrome Outcome Study (MetSO) trial. We assessed insomnia symptoms, sleep duration, and risk for sleep apnea. Multivariate logistic regression models evaluated the association between sleep disturbances with diabetes mellitus (DM) and the combined outcomes of DM and hypertension as well as DM and dyslipidemia.

RESULTS

The sample consisted of 1,013 participants, mean age of 62 ± 14 years and 61% female. DM was diagnosed in 60% of the sample. Sleep apnea risk was observed in 48% of the sample, while 10% had insomnia symptoms and 65% reported short sleep duration (< 6 hours). Sleep apnea risk, but not insomnia or sleep duration, was associated with DM (OR 1.66; 95% CI 1.21-2.28), adjusting for age, sex, income, obesity (BMI ≥ 30 kg/m(2)), tobacco use, alcohol use, hypertension, dyslipidemia, and depression. In fully adjusted models, sleep apnea risk was associated with the combined outcome of DM-hypertension (OR 1.95; 95% CI 1.42-2.69), but not with diabetes-dyslipidemia.

CONCLUSION

We observed a strong association between sleep apnea risk and diabetes mellitus among blacks with metabolic syndrome.

The concomitant relationship shared by sleep disturbances and type 2 diabetes: developing telemedicine as a viable treatment option

Individually, sleep disturbances and type 2 diabetes pose pervasive challenges to health. In addition, the negative symptomology associated with each condition is exacerbated further when presenting concomitantly. This relationship formulates a destructive loop wherein those with diabetes experience decreased sleep quality, which, in turn, worsens a wide range of health threats experienced by those with diabetes, including obesity and glucose intolerance. Because major lifestyle changes and daily care are needed to effectively manage both diabetes and sleep disturbances, an efficient and timely modality of treatment is essential. Advanced technology incorporating telemedicine and telehealth has the potential to enhance treatment by delivering accepted standard of care, medical monitoring, and education quickly and seamlessly--even in rural locations. This type of intervention has the added potential benefit of fostering patient empowerment.

Sleep in America: role of racial/ethnic differences

Sleep duration in America has gradually declined over the last four decades and appears to have reached a plateau for the last six years, with recent studies reporting that the population's current average sleep duration is approximately 6 h. In this paper, we examine epidemiologic and community-based data on sleep complaints reported by American adults, specifically addressing the role of race/ethnicity in the subjective report of sleep problems. Subjective and objective findings indicate that black (throughout the text, we use the term black in lieu of African American for there are instances where we refer to individuals with self-ascribed race/ethnicity as black, African American, African, or Caribbean American; the term white is used to denote individuals of European descent). Americans have higher rates of long (≥9 h) and short (≤5 h) sleep than their white counterparts, and this may mediate a higher risk of cardiovascular disease, obesity and diabetes among blacks. In addition, studies show mixed results on sleep complaints among blacks compared to those among other ethnicities. This paper explores factors that may contribute to racial/ethnic differences in sleep including intra-ethnic variation, cultural biases, genetics and psychosocial factors.

Linking sleep to hypertension: greater risk for blacks

Background. Evidence suggests that insufficient sleep duration is associated with an increased likelihood for hypertension. Both short (<6 hours) and long (>8 hour) sleep durations as well as hypertension are more prevalent among blacks than among whites. This study examined associations between sleep duration and hypertension, considering differential effects of race and ethnicity among black and white Americans. Methods. Data came from a cross-sectional household interview with 25,352 Americans (age range: 18-85 years). Results. Both white and black short sleepers had a greater likelihood of reporting hypertension than those who reported sleeping 6 to 8 hours. Unadjusted logistic regression analysis exploring the race/ethnicity interactions between insufficient sleep and hypertension indicated that black short (<6 hours) and long (>8 hours) sleepers were more likely to report hypertension than their white counterparts (OR = 1.34 and 1.37, resp.; P < 0.01). Significant interactions of insufficient sleep with race/ethnicity were observed even after adjusting to effects of age, sex, income, education, body mass index, alcohol use, smoking, emotional distress, diabetes, coronary heart disease, and stroke. Conclusion. Results suggest that the race/ethnicity interaction is a significant mediator in the relationship between insufficient sleep and likelihood of having a diagnosis of hypertension.

Race/ethnicity, sleep duration, and diabetes mellitus: analysis of the National Health Interview Survey

BACKGROUND

The effect of race/ethnicity on the risk of diabetes associated with sleep duration has not been systematically investigated. This study assessed whether blacks reporting short (<6 hours) or long (>8 hours) sleep durations were at greater risk for diabetes than their white counterparts. In addition, this study also examined whether the influence of race/ethnicity on associations between abnormal sleep durations and the presence of diabetes were independent of individuals' sociodemographic and medical characteristics.

METHODS

A total of 29,818 Americans (age range: 18-85 years) enrolled in the 2005 National Health Interview Survey, a cross-sectional household interview survey, provided complete data for this analysis.

RESULTS

Of the sample, 85% self-ascribed their ethnicity as white and 15% as black. The average age was 47.4 years, and 56% were female. Results of univariate regression analysis adjusting for medical comorbidities showed that black and white participants who reported short sleep duration (<6 hours) were more likely to have diabetes than individuals who reported sleeping 6 to 8 hours (odds ratios 1.66 and 1.87, respectively). Likewise, black and white participants reporting long sleep duration (>8 hours) had a greater likelihood of reporting diabetes compared with those sleeping 6 to 8 hours (odds ratios 1.68 and 2.33, respectively). Significant interactions of short and long sleep with black and white race were observed. Compared with white participants, greater diabetes risk was associated with being short or long sleepers of black race.

CONCLUSION

The present findings suggest that American short and long sleepers of black race may be at greater risk for diabetes independently of their sociodemographic profile or the presence of comorbid medical conditions, which have been shown to influence habitual sleep durations. Among black individuals at risk for diabetes, healthcare providers should stress the need for adequate sleep.

Sleep scoring using artificial neural networks

Rapid development of computer technologies leads to the intensive automation of many different processes traditionally performed by human experts. One of the spheres characterized by the introduction of new high intelligence technologies substituting analysis performed by humans is sleep scoring. This refers to the classification task and can be solved - next to other classification methods - by use of artificial neural networks (ANN). ANNs are parallel adaptive systems suitable for solving of non-linear problems. Using ANN for automatic sleep scoring is especially promising because of new ANN learning algorithms allowing faster classification without decreasing the performance. Both appropriate preparation of training data as well as selection of the ANN model make it possible to perform effective and correct recognizing of relevant sleep stages. Such an approach is highly topical, taking into consideration the fact that there is no automatic scorer utilizing ANN technology available at present.