Cyclic Alternating Pattern in Obstructive Sleep Apnea Patients with versus without Excessive Sleepiness

Obstructive sleep apnea and epilepsy: understanding the pathophysiology of the comorbidity

Obstructive sleep apnea (OSA) is a sleep disorder of significant health concern with a high prevalence in the general population. It has been found to exhibit a high incidence of comorbidity with epilepsy, the exact underlying pathophysiology of which still remains poorly understood. OSA is characterized by apnea/hypopnea spells and arousals, leading to intermittent hypoxemia and sleep deprivation. Both sleep deprivation and hypoxemia adversely affect the cortical excitability and favor epileptogenesis and worsening of pre-existing epilepsy, if any. In patients with OSA, deprivation of rapid eye movement sleep (REMS) phase (known for its strong antiepileptic influence) is relatively more than that non rapid eye movement sleep phase leading to postulation of REMS deprivation as a significant factor in the development of epilepsy as a comorbidity in patients with OSA. Furthermore, OSA and epilepsy both have shown to exercise a bidirectional influence on one another and are also likely to exacerbate each other through a positive feedback mechanism. This is especially based on the reports of improved control of epilepsy upon treatment of comorbid OSA. This brief paper attempts to present an underlying pathophysiological basis of the comorbidity of OSA and epilepsy based upon sleep deprivation and hypoxemia that are characteristic features observed in patients with OSA.

Evaluation of sleep quality in faculty members of Isfahan university of medical sciences

BACKGROUND

Sleep disorders can significantly impair the quality of life and daily functions. Evaluating sleep quality can provide valuable information about working conditions. This study aims to evaluate the sleep quality of faculty members at Isfahan University of Medical Sciences (IUMS).

METHODS

This descriptive-analytic study was conducted from 2020 to 2021, involving 106 faculty members from the medical school. A questionnaire collected demographic information, including age, sex, height, weight, body mass index (BMI), level of education, history of faculty membership, major, working hours during the day and night, residency place, and medical history. The Pittsburgh Sleep Quality Index (PSQI) and Symptom Checklist-25 (SCL-25) questionnaire were used to assess participants' sleep quality. Data were compared between clinicians and basic science faculty members.

RESULTS

PSQI subtypes were examined among the participants. The total PSQI score was 6.20±3.4. A comparison of PSQI scores and subtypes based on age categories did not show any significant differences (P > 0.05 for all). Clinicians had significantly lower total PSQI scores (P=0.044), sleep latency (P=0.024), sleep disturbances (P=0.012), and daytime dysfunction (P=0.022). Additionally, clinicians had a lower severity of sleep latency (P=0.024), sleep disturbances (P=0.012), and total PSQI score (P=0.044). However, clinicians exhibited a higher intensity of daytime dysfunction (P=0.022).

CONCLUSION

Faculty members exhibited a high prevalence of sleep disorders, with the most common disorders being sleep disturbance and high sleep latency. The prevalence of sleep disorders was higher among basic science faculty members compared to clinicians.

The Contribution of Sleep Texture in the Characterization of Sleep Apnea

Obstructive sleep apnea (OSA) is multi-faceted world-wide-distributed disorder exerting deep effects on the sleeping brain. In the latest years, strong efforts have been dedicated to finding novel measures assessing the real impact and severity of the pathology, traditionally trivialized by the simplistic apnea/hypopnea index. Due to the unavoidable connection between OSA and sleep, we reviewed the key aspects linking the breathing disorder with sleep pathophysiology, focusing on the role of cyclic alternating pattern (CAP). Sleep structure, reflecting the degree of apnea-induced sleep instability, may provide topical information to stratify OSA severity and foresee some of its dangerous consequences such as excessive daytime sleepiness and cognitive deterioration. Machine learning approaches may reinforce our understanding of this complex multi-level pathology, supporting patients' phenotypization and easing in a more tailored approach for sleep apnea.

Effects of CPAP treatment on electroencephalographic activity in patients with obstructive sleep apnea syndrome during deep sleep: Preliminary findings of a cross-sectional study

Study objectives: To investigate whether electroencephalographic (EEG) activities during non-rapid eye movement sleep stage 3 (N3) in obstructive sleep apnea syndrome (OSAS) patients were changed with continuous positive airway pressure (CPAP) treatment.Methods: A cross-sectional study of EEG activity during N3 sleep was conducted in 15 patients with moderate to severe OSAS without and with CPAP treatment compared to 15 normal controls. The amplitude, and absolute and relative power of delta, theta, alpha and beta waves as well as the absolute power ratio of slow to fast EEG waves (i.e., absolute power of delta and theta waves/absolute power of alpha and beta waves) and the spectral power density of 0-30 Hz EEG activities were analyzed.Results: CPAP significantly increased N3 sleep, the absolute and relative powers, amplitudes of delta and theta waves, and absolute power ratio of slow to fast EEG waves, but decreased relative alpha and beta powers during N3 sleep. However, there were no significant differences in those parameters between the OSAS patients with CPAP treatment and normal controls.Conclusions: CPAP prolongs N3 sleep and increases the power and amplitude of slow EEG waves during N3 sleep, which indicates an improvement in sleep quality and further provides evidence for recommendation of CPAP treatment for OSAS patients.

Effects of CPAP Treatment on Electroencephalographic Activity in Patients with Obstructive Sleep Apnea Syndrome During Deep Sleep with Consideration of Cyclic Alternating Pattern

Objective

To investigate whether continuous positive airway pressure (CPAP) treatment would change EEG activities associated with cyclic alternating pattern (CAP subtype A1, A2, and A3) and non-CAP (NCAP) during non-rapid eye movement sleep stage 3 (N3) in patients with obstructive sleep apnea (OSA).

Methods

The effects of CPAP treatment on the percentages of sleep stage N3 occupied by the CAP and NCAP, power of EEG waves in the CAP and NCAP were examined in 18 patients with moderate-to-severe OSA undergoing polysomnographic recordings.

Results

Apnea and hypopnea index during sleep stage N3 was positively correlated with ratios of phases A2 and A3 duration to total phase A duration [Phase (A2+A3) /Phase A] and negatively correlated with phase A1/phase A. With CPAP treatment, percentages of sleep stage N3 occupied by total CAPs and subtypes A2 and A3, as well as CAP A2 and CAP A3 indexes were significantly decreased while percentages of sleep stage N3 occupied by NCAP (NCAP/N3) and CAP A1 index were significantly increased. In addition, CPAP treatment significantly decreased percentage of respiratory events associated CAPs and increased percentage of non-respiratory related CAPs. Moreover, absolute and relative delta power was significantly increased during phase A1, unchanged during phase A2 and phase B2, and significantly decreased during phases B1, A3 and B3. The absolute power of faster frequency EEG waves in CAPs showed a general trend of decrease. The absolute and relative power of delta waves with amplitudes ≥75 μV, but not <75 μV, was significantly increased.

Conclusion

CPAP treatment improves the sleep quality in OSA patients mainly by increasing delta power and decreasing power of higher frequency waves during phase A1, and decreasing CAP A2 and A3 indexes as well as increasing NCAP/N3 and power of delta waves with amplitudes ≥75 μV during NCAP.

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.

Sleep-Disordered Breathing Risk with Comorbid Insomnia Is Associated with Mild Cognitive Impairment

Introduction: Few studies have evaluated the combined association between SDB with comorbid insomnia and mild cognitive impairment (MCI). To test the hypothesis that SDB with comorbid insomnia is associated with greater odds of MCI than either sleep disorder independently, we used ADNI data to evaluate cross-sectional associations between SDB risk with comorbid insomnia status and MCI. Methods: Participants with normal cognition or MCI were included. Insomnia was defined by self-report. SDB risk was assessed by modified STOP-BANG. Logistic regression models evaluated associations between four sleep disorder subgroups (low risk for SDB alone, low risk for SDB with insomnia, high risk for SDB alone, and high risk for SDB with insomnia) and MCI. Models adjusted for age, sex, BMI, APOE4 genotype, race, ethnicity, education, marital status, hypertension, cardiovascular disease, stroke, alcohol abuse, and smoking. Results: The sample (n = 1391) had a mean age of 73.5 ± 7.0 years, 44.9% were female, 72.0% were at low risk for SDB alone, 13.8% at low risk for SDB with insomnia, 10.1% at high risk for SDB alone, and 4.1% at high risk for SDB with insomnia. Only high risk for SDB with comorbid insomnia was associated with higher odds of MCI (OR 3.22, 95% CI 1.57–6.60). Conclusion: Studies are needed to evaluate SDB with comorbid insomnia as a modifiable risk factor for MCI.

Sleep EEG Signatures in COVID-19 Survivors

Study Objectives

Effect of COVID-19 on sleep architecture is not known. This study was done to find out EEG changes seen during sleep in COVID-19 survivors.

Methodology

In this prospective single centre study, consecutive patients diagnosed with RTPCR confirmed COVID 19 were included after 4–6 weeks of discharge from hospital. All patients underwent level I PSG. EEG was analysed for presence of abnormal EEG pattern.

Results

Total 189 patients were contacted telephonically for participation in this study. Finally 81 patients (55 males, 26 females) underwent Level I PSG. Total sleep time was 345.1 ± 85.1 min. Sleep efficiency was 76.0 ± 14.2%. Mean time (%) during N1, N2, N3 and Rapid Eye movement (REM) was 16.4%, 59.2%, 7.9% and 18.4% percentage, respectively. Mean AHI was 28.7 ± 22.8 per hour and arousal index was 23.9 ± 13.3. Alpha intrusion was the most common EEG finding (78%), followed by cyclical alternating pattern (59%). REM density was significantly increased in 38% of patients. REM alpha bursts and increased spindles were also seen in 27% and 16%.

Conclusion

Abnormal EEG waves are very commonly seen in COVID-19 survivors. Presence of these abnormal PSG-EEG waves hints that COVID-19 might have similar effects as depression, insomnia on these subjects, at least in short run. Whether these changes are temporary or permanent needs to be evaluated by performing serial polysomnographies in patients with COVID-19 ARDS.

Cyclic alternating patterns and arousals: what is relevant in obstructive sleep apnea? In Memoriam Mario Giovanni Terzano

PURPOSE OF REVIEW

To review main knowledges and gaps in the field of sleep microstructure, represented by the cyclic alternating pattern (CAP), in obstructive sleep apnea (OSA).

RECENT FINDINGS

The (electroencephalographic and autonomic) 'intensity' of arousals in OSA patients, measured through the metrics of CAP, correlate with OSA severity and with disease burden. Continuous positive airway pressure determines variations in sleep architecture (conventional parameters) and at the microstructural level, at different time points.

SUMMARY

CAP is not only an 'attractor' of arousals, but also organizes distribution of K-complexes and delta bursts in non-rapid eye movement sleep. Although attention is always concentrated on the A-phase of CAP, a crucial role is play by the phase B, which reflects a period of transient inhibition. Respiratory events in OSA are a typical example of phase B-associated condition, as they occur during the interval between successive A-phases. Accordingly sleep microstructure provides useful insights in the pathophysiology and estimation of OSA severity and may be exploited to follow-up treatment efficacy. In the complex relationship among sleep fragmentation, excessive daytime sleepiness, cognition and cardiovascular risk the CAP framework can offer an integrative perspective in a multidisciplinary scenario.

Comorbid Insomnia and Sleep Apnea: mechanisms and implications of an underrecognized and misinterpreted sleep disorder

Sleep-disordered breathing (SDB) and insomnia have long been recognized as important sleep disrupters often associated with increased morbidity and mortality. Although they are often seen as divergent conditions, mainly because their cardinal symptoms (excessive daytime sleepiness, and sleep loss) differ, these two sleep disorders present with many common symptoms, which may hinder diagnosis and treatment. In addition to possible bidirectional pathways between SDB and insomnia, other factors such as circadian timing may play a role. In this paper, we review the mechanisms, differential clinical aspects, and implications of Comorbid Insomnia and Sleep Apnea, sometimes termed COMISA.

Cyclic alternating pattern in obstructive sleep apnea: A preliminary study

Obstructive sleep apnea is linked to cardiovascular disease, metabolic disorders and dementia. The precise nature of the association between respiratory events in obstructive sleep apnea, cortical or subcortical arousals, and cognitive, autonomic and oxidative stress consequences remains incompletely elucidated. Previous studies have aimed to understand the relationship between obstructive sleep apnea and arousal patterns, as defined by the cyclic alternating pattern, but results have been inconsistent, in part likely due to the presence of associated comorbidities. To better define this relationship, we analysed cyclic alternating patterns in patients with obstructive sleep apnea without any additional comorbidities. We identified 18 adult male, non-obese subjects with obstructive sleep apnea and no other comorbidities or medication history, who underwent whole-night electroencephalography and polysomnography. Cyclic alternating pattern analysis was performed and verified by certified somnologists. Pairwise linear regression analysis demonstrated an inverse relationship between obstructive sleep apnea severity and cyclic alternating pattern subtype A1, and a direct correlation with cyclic alternating pattern subtype A3. Cyclic alternating pattern subtypes A1 prevail in milder obstructive sleep apnea phenotype, whilst cyclic alternating pattern subtypes A2 and A3 overcome among moderate-to-severe obstructive sleep apnea patients. The milder obstructive sleep apnea group also presented higher sleep efficiency, and increased percentages of non-rapid eye movement stage 3 and rapid eye movement sleep, as well as longer cyclic alternating pattern sequences in N3, while severe obstructive sleep apnea patients spent more time in lighter sleep stages. These results imply/suggest a balance between cyclic alternating pattern's adaptive and maladaptive arousal processes in obstructive sleep apnea of differing severities. In milder obstructive sleep apnea (apnea-hypopnea index < 20), sleep continuity may be reinforced by cyclic alternating pattern subtype A1, whereas in more severe obstructive sleep apnea, decompensation of these sleep-stabilizing mechanisms may occur and more intrusive cyclic alternating pattern fluctuations disrupt sleep circuitry.

Intensity of Respiratory Cortical Arousals Is a Distinct Pathophysiologic Feature and Is Associated with Disease Severity in Obstructive Sleep Apnea Patients

Background: We investigated whether the number, duration and intensity of respiratory arousals (RA) on C3-electroencephalographic (EEG) recordings correlate with polysomnography (PSG)-related disease severity in obstructive sleep apnea (OSA) patients. We also investigated if every patient might have an individual RA microstructure pattern, independent from OSA-severity. Methods: PSG recordings of 20 OSA patients (9 female; age 27–80 years) were analyzed retrospectively. Correlation coefficients were calculated between RA microstructure (duration, EEG-intensity) and RA number and respiratory disturbance index (RDI), oxygen desaturation index (ODI) and arousal index (AI). Intraclass correlations (ICC) for both RA duration and intensity were calculated. Sleep stage-specific and apnea- and hypopnea-specific analyses were also done. The probability distributions of duration and intensity were plotted, interpolated with a kernel which fits the distribution. A Bayesian posterior distribution analysis and pair-wise comparisons of each patient with all other 19 patients were performed. Results: Of the analyzed 2600 RA, strong positive correlations were found between average RA intensity and both RDI and AI. The number of PSG-recorded RA was strongly positively correlated with RDI. Significant correlations between average RA intensity in REM, NREM2 and NREM3 sleep stages and total ODI were identified. No sleep stage-specific correlations of arousal microstructure with age, sex, RDI or AI were identified. Although between-subjects ICC values were <0.25, within-subject ICC values were all >0.7 (all p < 0.05). While apnea-related RA duration did not differ from hypopnea-related RA duration, RA intensity was significantly higher (p = 0.00135) in hypopneas than in apneas. A clear individual pattern of arousal duration for each patient was made distinct. For arousal intensity, a Gaussian distribution was identified in most patients. The Bayesian statistics regarding the arousal microstructure showed significant differences between each pair of patients. Conclusions: Each individual patient with OSA might have an individual pattern of RA intensity and duration indicating a distinct individual pathophysiological feature. Arousal intensity was significantly higher in hypopneic than in apneic events and may be related causally to the diminished (compared to apneas) respiratory distress associated with hypopneas. RA intensity in REM, NREM2 and NREM3 strongly correlated with ODI.

Commonalities and Differences in NREM Parasomnias and Sleep-Related Epilepsy: Is There a Continuum Between the Two Conditions?

Introduction: Differential diagnosis between disorders of arousal (DoA) and sleep-related hypermotor epilepsy (SHE) often represents a clinical challenge. The two conditions may be indistinguishable from a semiological point of view and the scalp video-polysomnography is often uninformative. Both disorders are associated with variable hypermotor manifestations ranging from major events to fragments of a hierarchical continuum of increasing intensity, complexity, and duration. Given their semiological overlap we decided to explore the sleep texture of DoA and SHE seeking for similarities and differences.

Methods: We analyzed sleep macrostructure and CAP (cyclic alternating pattern) parameters in a cohort of 35 adult DoA patients, 40 SHE patients and 24 healthy sleepers, all recorded and scored in the same sleep laboratory. Nocturnal behavioral manifestations included minor motor events, paroxysmal arousals and major attacks in SHE, and simple, rising, or complex arousal movements in DoA.

Results: Compared to healthy controls, DoA and SHE showed similar amounts of sleep efficiency, light sleep, deep sleep, REM sleep, CAP subtypes. Both groups also showed slow wave sleep fragmentation and an increased representation of stage N3 in the second part of the night. The only discriminating elements between the two conditions regarded sleep length (more reduced in DoA) and sleep instability (more elevated in SHE). In DoA recordings, all motor episodes arose from NREM sleep: 37% during light NREM stages and 63% during stage N3 (simple arousal movements: 94%). In SHE recordings, 57% of major attacks occurred during stage N3.

Conclusions: So far, emphasis has been placed on the differentiation of sleep-related epilepsy and NREM arousal disorders. However, the impressive analogies between DoA and SHE suggest the existence of an underestimated continuum across the conditions, linked by increased levels of sleep instability, higher amounts of slow wave sleep and NREM/REM sleep imbalance. Sleep texture is extremely similar in the two conditions, although CAP metrics disclose quantitative differences. In particular, SHE patients show a higher arousal instability compared to DoA subjects. Given their clinical and epidemiological overlap, a common genetic background is also hypothesized. In such a perspective, we suggest that the consolidated dichotomy DoA vs. SHE should be reappraised.

Case Report: Parasomnia Overlap Disorder Induced by Obstructive Sleep Hypopnea Apnea Syndrome: A Case Report and Literature Review

Obstructive sleep apnea hypopnea syndrome (OSAHS) and parasomnia overlap disorder (POD) are types of sleep disorders. When the symptoms of both conditions coexist, the POD symptoms are most likely caused by OSAHS. In these cases, the symptoms of POD will be relieved when OSAHS is effectively treated. We refer to these cases as symptomatic POD (related to OSAHS), which differs in pathophysiology, complications, and treatment from idiopathic POD. It is important to note that the treatment for idiopathic POD may aggravate the symptoms of OSAHS. In this case, we used video polysomnography (v-PSG) on a POD patient with suspected OSAHS to distinguish idiopathic POD from symptomatic POD, to inform the appropriate treatment course. The video results and clinical features lead us to diagnose symptomatic POD, and we treated the patient with auto-set continuous positive airway pressure to address their OSAHS. This course of treatment resolved all POD-related symptoms. Here, we discuss this case and review the relevant literature. This report highlights the importance of the use of v-PSG in the clinical diagnosis, differential diagnosis, and subsequent treatment of POD.

On the use of patterns obtained from LSTM and feature-based methods for time series analysis: application in automatic classification of the CAP A phase subtypes

The cyclic alternating pattern is a marker of sleep instability identified in the electroencephalogram signals whose sequence of transient variations compose the A phases. These phases are divided into three subtypes (A1, A2, and A3) according to the presented patterns. The traditional approach of manually scoring the cyclic alternating pattern events for the full night is unpractical, with a high probability of miss classification, due to the large quantity of information that is produced during a full night recording. To address this concern, automatic methodologies were proposed using a long short-term memory to perform the classification of one electroencephalogram monopolar derivation signal. The proposed model is composed of three classifiers, one for each subtype, performing binary classification in a one versus all procedure. Two methodologies were tested: feed the pre-processed electroencephalogram signal to the classifiers; create features from the pre-processed electroencephalogram signal which were fed to the classifiers (feature-based methods). It was verified that the A1 subtype classification performance was similar for both methods and the A2 subtype classification was higher for the feature-based methods. However, the A3 subtype classification was found to be the most challenging to be performed, and for this classification, the feature-based methods were superior. A characterization analysis was also performed using a recurrence quantification analysis to further examine the subtypes characteristics. The average accuracy and area under the receiver operating characteristic curve for the A1, A2, and A3 subtypes of the feature-based methods were respectively: 82% and 0.92; 80% and 0.88; 85% and 0.86.

Obstructive Sleep Apnea and Its Treatment in Aging: Effects on Alzheimer's disease Biomarkers, Cognition, Brain Structure and Neurophysiology

Here we review the impact of obstructive sleep apnea (OSA) on biomarkers of Alzheimer's disease (AD) pathogenesis, neuroanatomy, cognition and neurophysiology, and present the research investigating the effects of continuous positive airway pressure (CPAP) therapy. OSA is associated with an increase in AD markers amyloid-β and tau measured in cerebrospinal fluid (CSF), by Positron Emission Tomography (PET) and in blood serum. There is some evidence suggesting CPAP therapy normalizes AD biomarkers in CSF but since mechanisms for amyloid-β and tau production/clearance in humans are not completely understood, these findings remain preliminary. Deficits in the cognitive domains of attention, vigilance, memory and executive functioning are observed in OSA patients with the magnitude of impairment appearing stronger in younger people from clinical settings than in older community samples. Cognition improves with varying degrees after CPAP use, with the greatest effect seen for attention in middle age adults with more severe OSA and sleepiness. Paradigms in which encoding and retrieval of information are separated by periods of sleep with or without OSA have been done only rarely, but perhaps offer a better chance to understand cognitive effects of OSA than isolated daytime testing. In cognitively normal individuals, changes in EEG microstructure during sleep, particularly slow oscillations and spindles, are associated with biomarkers of AD, and measures of cognition and memory. Similar changes in EEG activity are reported in AD and OSA, such as "EEG slowing" during wake and REM sleep, and a degradation of NREM EEG microstructure. There is evidence that CPAP therapy partially reverses these changes but large longitudinal studies demonstrating this are lacking. A diagnostic definition of OSA relying solely on the Apnea Hypopnea Index (AHI) does not assist in understanding the high degree of inter-individual variation in daytime impairments related to OSA or response to CPAP therapy. We conclude by discussing conceptual challenges to a clinical trial of OSA treatment for AD prevention, including inclusion criteria for age, OSA severity, and associated symptoms, the need for a potentially long trial, defining relevant primary outcomes, and which treatments to target to optimize treatment adherence.

Matrix of Lags: A tool for analysis of multiple dependent time series applied for CAP scoring

BACKGROUND

Multiple methods have been developed to assess what happens between and within time series. In a particular type of these series, the previous values of the currently observed series are contingent on the lagged values of another series. These cases can commonly be addressed by regression. However, a model selection criteria should be employed to evaluate the compromise between the amount of information provided and the model complexity. This is the basis for the development of the Matrix of Lags (MoL), a tool to study dependent time series.

METHODS

For each input, multiple regressions were applied to produce a model for each lag and a model selection criterion identifies the lags that will populate an auxiliary matrix. Afterwards, the energy of the lags (that are in the auxiliary matrix) was used to define a row of the MoL. Therefore, each input corresponds to a row of the MoL. To test the proposed tool, the heart rate variability and the electrocardiogram derived respiration were employed to perform the indirect estimation of the electroencephalography cyclic alternating pattern (CAP) cycles. Therefore, a support vector machine was fed with the MoL to perform the CAP cycle classification for each input signal. Multiple tests were carried out to further examine the proposed tool, including the effect of balancing the datasets, application of other regression methods and employment of two feature section models. The first was based on sequential backward selection while the second examined characteristics of a return map.

RESULTS

The best performance of the subject independent model was attained by feeding the lags, selected by sequential backward selection, to a support vector machine, achieving an average accuracy, sensitivity, specificity and area under the receiver operating characteristic curve of, respectively, 77%, 71%, 82% and 0.77.

CONCLUSIONS

The developed model allows to perform a measurement of a characteristic marker of sleep instability (the CAP cycle) and the results are in the upper bound of the specialist agreement range with visual analysis. Thus, the developed method could possibly be used for clinical diagnosis.

Correlation of sleep microstructure with daytime sleepiness and cognitive function in young and middle-aged adults with obstructive sleep apnea syndrome

PURPOSE

To compare microstructural features of sleep in young and middle-aged adults with differing severities of obstructive sleep apnea syndrome (OSAS), and to investigate the relationship between sleep microstructural fragmentation and cognitive impairment, as well as daytime sleepiness, in these patients.

METHODS

A total of 134 adults with snoring (mean age, 37.54 ± 7.66 years) were classified into four groups based on apnea-hypopnea index: primary snoring, mild OSAS, moderate OSAS, and severe OSAS. Overnight polysomnography was performed to assess respiratory, sleep macrostructure (N1, N2, N3, and R), and sleep microstructure (arousal, cyclic alternating pattern [CAP]) parameters. Cognitive function and daytime sleepiness were assessed using Montreal Cognitive Assessment (MoCA) and Epworth Sleepiness Scale (ESS).

RESULTS

As OSAS severity increased, MoCA gradually decreased and ESS gradually increased. N1%, N2%, and N3% sleep were significantly different between the severe OSAS group and the primary snoring, mild OSAS, and moderate OSAS groups (all P < 0.05). Overall arousal index, respiratory-related arousal index, CAP time, CAP rate, phase A index, number of CAP cycles, and phase A average time differed significantly in the moderate and severe OSAS groups compared with the mild OSAS and primary snoring groups (all P < 0.05). The strongest correlations identified by stepwise multiple regression analysis were between phase A3 index and the MoCA and ESS scores.

CONCLUSIONS

Sleep microstructure exhibited significant fragmentation in patients with moderate and severe OSAS, which was associated with decreased MoCA and increased ESS scores. This suggests that phase A3 index is a sensitive indicator of sleep fragmentation in OSAS.