Insomnia symptoms in primary care: A prospective study focusing on prevalence of undiagnosed co-morbid sleep disordered breathing

Clinical Characteristics and Treatment Efficacy for Co-Morbid Insomnia and Sleep Apnea (COMISA): Evidence from Qualitative and Quantitative Analysis

OBJECTIVES

A multitude of physical and mental challenges are being faced in the population with Co-morbid Insomnia and Sleep Apnea (COMISA). Unfortunately, research about clinical characteristics and management of COMISA based on quantitative evidence is lacking.

METHOD

Standard procedures for literature retrieval, selection and quality assessment, data extraction, analysis, and interpretation were conducted step by step. For studying the sleep characteristics, common complications and widely recognized treatment options for COMISA, Weighted Mean Difference (WMD) and Odds Ratio (OR) were applied to assess the mean and risk differences between compared groups. Outcomes included sleep health parameters and secondary impairments in physical and mental well-being.

RESULTS

COMISA showed worse sleep quality than OSA only by PSQI (WMD = 3.38 point) and heavier sleep fragmentation (WMD = 11.46 min) than insomnia only. Besides, COMISA patients showed a higher risk for depression (OR [95%CI] = 5.03[2.31, 10.93]) and PTSD (OR [95%CI] = 3.96[1.85, 8.46]) in comparison with OSA alone. Compared to insomnia alone, COMISA patients suffered from more than two times higher risk of cardiovascular diseases, hypertension, and diabetes. In treating COMISA patients, combining CBTI with PAP treatment can enhance the improvement of insomnia severity (ISI, WMD [95%CI] =-3.26[-4.51, -2.00] point) and sleep efficiency (WMD [95%CI] = 6.39[1.97, 10.81] %) compared to PAP alone.

CONCLUSIONS

Impaired sleep domains in COMISA cover sleep quality and sleep structure. Also, COMISA has a higher risk for cardiometabolic diseases and mental disorders. Combining CBTI with PAP can be a recommended treatment to relieve sleep impairments for COMISA.

Sleep and obstructive sleep apnea in women with infertility

PURPOSE

Obstructive sleep apnea (OSA) is associated with polycystic ovarian syndrome (PCOS), a common cause of infertility. Understanding predictors and outcomes of OSA in women with infertility may guide treatment.

METHODS

A descriptive cross-sectional survey was performed to assess OSA in women presenting to an infertility clinic using validated sleep questionnaires to assess sleep and fertility outcomes. An Infertile-C group (controls with male or tubal factors) and an Infertile-S group (unknown/other infertile causes) were analyzed to assess OSA risk and other sleep disorders (e.g., restless legs syndrome (RLS) and insomnia) with fertility outcomes (time to pregnancy, PCOS, irregular menstruation, and miscarriage).

RESULTS

In 258 women, occurrences of OSA diagnosis (6%) and RLS (10%) were reported similar to women of child-bearing age in the general population. PCOS was unassociated with OSA risk. Predictors of OSA risk were BMI, insomnia symptoms, and sleep aid use. Obese women with high OSA risk were more likely to have other comorbidities (e.g., depression). In adjusted models, prior clinical OSA diagnosis was associated with miscarriage (odds ratio: 6.17 (1.24, 30.62), p = 0.026). RLS was associated with irregular menstruation (odds ratio: 3.73 (1.21, 11.53), p = 0.022).

CONCLUSIONS

Similar to other populations, women with infertility and OSA risk have more health comorbidities and higher BMI and may present with insomnia symptoms. While the data are limited, this study supports the potential associations of OSA and miscarriage. Further work is needed to evaluate OSA in female infertility.

Links between Sleep Apnoea and Insomnia in a British Cohort

Poor sleep is a major public health problem with implications for a wide range of critical health outcomes. Insomnia and sleep apnoea are the two most common causes of poor sleep, and recent studies have shown that these disorders frequently co-occur. Comorbid insomnia and sleep apnoea can substantially impair quality of life and increase the overall risk of mortality. However, the causal and physiological links between sleep apnoea and insomnia are unclear. It is also unknown whether having a higher risk for one condition can increase the risk of developing the other. Here, we investigated links between sleep apnoea and insomnia in a British population using a combination of self-reported questionnaires and causal inference. We found that 54.3% of the cohort had moderate insomnia, 9.4% had moderate sleep apnoea, and that 6.2% scored high for both conditions. Importantly, having a higher risk of sleep apnoea was associated with a higher risk of insomnia and vice versa. To determine the causal directionality between sleep apnoea and insomnia, we used Mendelian randomisation and found evidence that sleep apnoea could cause insomnia, but not the reverse. To elucidate how both sleep apnoea and insomnia were linked to each other, we looked at the behavioural markers of poor sleep. We found that feeling fatigued after sleeping and having noticeable sleep problems were linked to a higher burden of both sleep apnoea and insomnia. In conclusion, our results show that sleep apnoea increases the risk of developing insomnia, and both conditions can result in fatigue. We highlight the importance of considering and treating the symptoms of both conditions.

Insomnia

OBJECTIVE

This article provides an overview of the current definitions, diagnostic tools, and overall management of insomnia.

LATEST DEVELOPMENTS

The treatment of insomnia has shifted over time, with a growing emphasis on nonpharmacologic therapies as a first-line intervention and the leveraging of technology to aid in the dissemination of these therapies. With this evolution, the definition of insomnia has changed to reflect a common treatment pathway. As pharmacologic treatment options have increased, so has concern about the dangerous short-term and long-term adverse effects of these treatment options.

ESSENTIAL POINTS

Insomnia is a common disorder, frequently overlapping with other neurologic and psychiatric disorders, which can cause significant distress and disruption to patients' lives. Nonpharmacologic therapies are highly effective and are now considered first-line treatments. Although efficacy is variable, numerous pharmacologic interventions are available, and many options come with considerable concern about adverse effects, particularly in populations over 65 years old.

Sleep medicine: Practice, challenges and new frontiers

Sleep medicine is an ambitious cross-disciplinary challenge, requiring the mutual integration between complementary specialists in order to build a solid framework. Although knowledge in the sleep field is growing impressively thanks to technical and brain imaging support and through detailed clinic-epidemiologic observations, several topics are still dominated by outdated paradigms. In this review we explore the main novelties and gaps in the field of sleep medicine, assess the commonest sleep disturbances, provide advices for routine clinical practice and offer alternative insights and perspectives on the future of sleep research.

Cardiopulmonary Sleep Spectrograms Open a Novel Window Into Sleep Biology-Implications for Health and Disease

The interactions of heart rate variability and respiratory rate and tidal volume fluctuations provide key information about normal and abnormal sleep. A set of metrics can be computed by analysis of coupling and coherence of these signals, cardiopulmonary coupling (CPC). There are several forms of CPC, which may provide information about normal sleep physiology, and pathological sleep states ranging from insomnia to sleep apnea and hypertension. As CPC may be computed from reduced or limited signals such as the electrocardiogram or photoplethysmogram (PPG) vs. full polysomnography, wide application including in wearable and non-contact devices is possible. When computed from PPG, which may be acquired from oximetry alone, an automated apnea hypopnea index derived from CPC-oximetry can be calculated. Sleep profiling using CPC demonstrates the impact of stable and unstable sleep on insomnia (exaggerated variability), hypertension (unstable sleep as risk factor), improved glucose handling (associated with stable sleep), drug effects (benzodiazepines increase sleep stability), sleep apnea phenotypes (obstructive vs. central sleep apnea), sleep fragmentations due to psychiatric disorders (increased unstable sleep in depression).

Sleep deprivation impairs cognitive performance, alters task-associated cerebral blood flow and decreases cortical neurovascular coupling-related hemodynamic responses

Sleep deprivation (SD) is a common condition and an important health concern. In addition to metabolic and cardiovascular risks, SD associates with decreases in cognitive performance. Neurovascular coupling (NVC, "functional hyperemia") is a critical homeostatic mechanism, which maintains adequate blood supply to the brain during periods of intensive neuronal activity. To determine whether SD alters NVC responses and cognitive performance, cognitive and hemodynamic NVC assessments were conducted prior to and 24 h post-SD in healthy young male individuals (n = 10, 27 ± 3 years old). Cognition was evaluated with a battery of tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB). Hemodynamic components of NVC were measured by transcranial Doppler sonography (TCD) during cognitive stimulation, dynamic retinal vessel analysis (DVA) during flicker light stimulation, and functional near infrared spectroscopy (fNIRS) during finger tapping motor task. Cognitive assessments revealed impairments in reaction time and sustained attention after 24 h of SD. Functional NIRS analysis revealed that SD significantly altered hemodynamic responses in the prefrontal cortex and somatosensory cortex during a motor task. NVC-related vascular responses measured by DVA and TCD did not change significantly. Interestingly, TCD detected decreased task-associated cerebral blood flow (CBF) in the right middle cerebral artery in sleep deprived participants. Our results demonstrate that 24 h of SD lead to impairments in cognitive performance together with altered CBF and hemodynamic components of cortical NVC responses.

Sleep disordered breathing symptoms are associated with depressive symptoms: A longitudinal study of Chinese adolescents

BACKGROUND

Little is known about the prospective association between sleep disordered breathing (SDB) and depressive symptoms in Chinese adolescents. This study examined the independent predictive role of SDB symptoms in depressive symptoms in a large sample of adolescents.

METHODS

A total of 11831 adolescents who participated in the baseline survey of Shandong Adolescent Behavior and Health Cohort and 7072 adolescents who were resurveyed 1 year later were included for the analyses. Adolescents completed a self-administered questionnaire about demographics, mental health, sleep problems, and family environment. SDB symptoms were assessed by 3 items about loud snoring, breathing pauses, and snorting/gasping. The Chinese Youth Self-Report anxious/depressed subscale was used to assess depressive symptoms.

RESULTS

In the cross-sectional analyses, 11.8% adolescents had depressive symptoms, and elevated frequency of SDB symptoms were significantly associated with depressive symptoms. In the longitudinal study, 4.5% of adolescents had persistent depressive symptoms, the incidence rate of depressive symptoms at 1-year follow-up was 6.5%, and elevated frequency of any SDB symptoms (often: OR=2.23, 95%CI:1.50-3.32) at baseline was significantly associated with incident depressive symptoms after adjusting for potential confounders. The associations between SDB symptoms and depressive symptoms were similar for boys and girls.

LIMITATION

SDB symptoms and depressive symptoms were measured by self-report.

CONCLUSION

SDB symptoms are an independent and significant predictor of depressive symptoms in adolescents. Further research is needed to understand the biological mechanisms between SDB and mood dysregulation in adolescents.

Cardiopulmonary coupling-derived sleep quality is associated with improvements in blood pressure in patients with obstructive sleep apnea at high-cardiovascular risk

OBJECTIVE

Investigate if changes in objective sleep quality index (SQI) assessed through cardiopulmonary-coupling analysis impacts blood pressure (BP) in patients with obstructive sleep apnea at high-cardiovascular risk.

METHODS

Secondary analysis of ECG and pulse-oximetry-[oxygen saturation (SpO2)] data from the Heart Biomarker Evaluation in Apnea Treatment study, multicenter, controlled trial in patients with cardiovascular disease and moderate-severe obstructive sleep apnea, randomly assigned to intervention of healthy lifestyle and sleep hygiene education (HLSE; control group), continuous positive airway pressure (CPAP) or nocturnal supplemental oxygen (NSO). Participants with good-quality ECG-signal and SpO2-signal (n = 241) were included.

RESULTS

CPAP-therapy significantly improved BP, with net average improvement in mean arterial blood pressure during sleep (MAP) when compared with nocturnal supplemental oxygen-therapy or healthy lifestyle and sleep education-therapy, -3.92 (P = 0.012) and -3.83 (P = 0.016), respectively. When stratified on the basis of baseline-SQI, CPAP-therapy improves 24-h MAP -3.02 (P = 0.030) and MAP -5.00 (P = 0.001), in patients with compromised baseline-SQI (SQI < 55). Stratifying the cohort based on changes in SQI during the study period (SQI-SQI), controlling for sex, age over 60, apnea-hypopnea index, SpO2 less than 80%, baseline BP and cardiovascular disease, significant differences are observed comparing the groups that Improved-SQI (SQI < 55, SQI ≥ 55) and Declined-SQI (SQI ≥ 55, SQI < 55) in MAP -4.87 (P = 0.046) and mean diastolic blood pressure (MDP) -4.42 (P = 0.026) as well as MAP -6.36 (P = 0.015), mean systolic blood pressure wake (MSP) -7.80 (P = 0.048) and MDP -5.64 (P = 0.009), respectively. Improved SQI reflects the magnitude of positive effect on BP which is reached mostly through initiation of CPAP-therapy.

CONCLUSION

Cardiopulmonary coupling-derived sleep quality impacted 24-h MAP and MDP, as well as BP during wake, in patients participating in the Heart Biomarker Evaluation in Apnea Treatment-study.

Can improvements in sleep quality positively affect serum adiponectin-levels in patients with obstructive sleep apnea?

BACKGROUND

Assess if changes in sleep quality (Sleep Quality Index, SQI) based on cardiopulmonary coupling-analysis (CPC) impacts serum adiponectin-levels in patients with cardiovascular disease (CVD).

METHODS

Secondary analysis of electrocardiogram (ECG) data from the Heart Biomarker Evaluation in Apnea Treatment study (HeartBEAT), a multicenter, controlled trial in patients with CVD and moderate-severe sleep apnea, randomly assigned to intervention of Continuous Positive Airway Pressure (CPAP), Nocturnal Supplemental Oxygen (NSO) or Healthy Lifestyle and Sleep Hygiene Education (HLSE; control group). Participants with good-quality ECG-signal (n = 241) were included.

RESULTS

Improving CPC-sleep quality was associated with net average improvements in serum adiponectin-levels 2.69 μg/ml (p = 0.005) irrespective of therapy initiated. After controlling for confounders, a unit increase in SQI was associated with increase in serum adiponectin-levels 0.071 μg/ml (p = 0.012) and decrease in insulin-levels 0.197 μIU/ml (p = 0.0018). Similarly, a percentage point increase in sleep apnea indicator (SAI) was associated with decrease in serum adiponectin-levels of 0.071 μg/ml (p = 0.017) and increase in insulin-levels of 0.218 μIU/ml (p = 0.020). A percentage point increase in CPC-sleep fragmentation (eLFC_BB) had a predicted increase in glucose-levels 0.371 mg/dl (p = 0.009) and insulin-levels 0.284 μIU/ml (p = 0.010). In patients receiving CPAP-therapy, a difference in serum adiponictin levels of 3.82 μg/ml (p = 0.025) is observed comparing patients in which SQI-improved to patients that SQI-declined during the study period. The difference is mostly due to a decrease in serum adiponectin levels in patients that decline in SQI (-3.20 μg/ml).

CONCLUSION

Improvements in sleep quality were associated with higher serum adiponectin-levels, and improved measures of glycemic metabolism which may have beneficial effects on metabolic syndrome and cardiovascular health.

CLINICAL TRIAL REGISTRATION NAME AND NUMBER

The Heart Biomarker Evaluation in Apnea Treatment (HeartBEAT) study is registered at https://clinicaltrials.gov/ct2/show/NCT01086800.

Multimorbidity in COPD, does sleep matter?

A good night's sleep is a prerequisite for sustainable mental and physical health. Sleep disorders, including sleep disordered breathing, insomnia and sleep related motor dysfunction (e.g., restless legs syndrome), are common in patients with chronic obstructive pulmonary disease (COPD), especially in more severe disease. COPD is commonly associated with multimorbidity, and sleep disorders as a component of this multimorbidity spectrum have a further negative impact on COPD-related comorbidities. Indeed, concomitant diseases in COPD and in obstructive sleep apnea (OSA) are similar, suggesting that the combination of COPD and OSA, the so called OSA-COPD overlap syndrome (OVS), affects patient outcomes. Potential clinically important interactions of OVS exist in cardiovascular and metabolic disease, arthritis, anxiety, depression, neurocognitive disorder and the fatigue syndrome. Correct diagnosis for recognition and treatment of sleep-related disorders in COPD is recommended. However, surprisingly limited information is available and further research and improved diagnostic tools are needed. In the absence of clear evidence, we agree with the recommendation of the Global Initiative on Chronic Obstructive Lung Disease that sleep disorders should be actively searched for and treated in patients with COPD. We believe that both aspects are important components of the holistic approach required in patients with chronic multimorbid conditions.

Electrocardiogram-based sleep analysis for sleep apnea screening and diagnosis

PURPOSE

Despite the increasing number of research studies of cardiopulmonary coupling (CPC) analysis, an electrocardiogram-based technique, the use of CPC in underserved population remains underexplored. This study aimed to first evaluate the reliability of CPC analysis for the detection of obstructive sleep apnea (OSA) by comparing with polysomnography (PSG)-derived sleep outcomes.

METHODS

Two hundred five PSG data (149 males, age 46.8 ± 12.8 years) were used for the evaluation of CPC regarding the detection of OSA. Automated CPC analyses were based on ECG signals only. Respiratory event index (REI) derived from CPC and apnea-hypopnea index (AHI) derived from PSG were compared for agreement tests.

RESULTS

CPC-REI positively correlated with PSG-AHI (r = 0.851, p < 0.001). After adjusting for age and gender, CPC-REI and PSG-AHI were still significantly correlated (r = 0.840, p < 0.001). The overall results of sensitivity and specificity of CPC-REI were good.

CONCLUSION

Compared with the gold standard PSG, CPC approach yielded acceptable results among OSA patients. ECG recording can be used for the screening or diagnosis of OSA in the general population.

Occurrence of atrial fibrillation in pacemaker patients and its association with sleep apnea and heart rate variability

AIMS

Sleep apnea (SA) is a risk factor for atrial fibrillation (AF) occurrence. Sympathovagal imbalance is a mechanism that predisposes to the development of AF and that occurs in SA. Some pacemakers can detect SA events and continuously measure a time domain measure of heart rate variability (HRV), i.e. the standard deviation of 5-min median atrial-atrial sensed intervals (SDANN). We evaluated the association between the occurrence of AF and device-detected SA and SDANN in patients who received pacemakers.

METHODS

We enrolled 150 consecutive patients undergoing implantation of a dual-chamber pacemaker, capable of SA and SDANN estimation. The SA was defined as severe if the Respiratory Disturbance Index was ≥30 episodes/h for at least one night during the first week after implantation.

RESULTS

Sixteen patients in permanent AF were excluded from our analysis. During follow-up, AF (cumulative device-detected AF duration > 6 h/day) occurred in 24(18%) patients out of the remaining 134 patients. Severe SA was detected in 84 patients. SDANN values were available in 74 patients and the median value was 76 ms [25°-75°percentile:58-77]. The risk of AF was higher in patients with severe SA (log-rank test; p = .033). The presence of either or both conditions (severe SA and SDANN < 76 ms) was associated with shorter time to AF event (p = .042) and was an independent predictor of AF (hazard ratio: 2.37; 95%CI:1.08 to 5.21; p = .033).

CONCLUSION

In pacemaker patients, device-diagnosed severe SA and reduced SDANN are associated with a higher risk of AF.