Quantitative analysis of the effects of slow wave sleep deprivation during the first 3 h of sleep on subsequent EEG power density

Summary The relation between EEG power density during slow wave sleep (SWS) deprivation and power density during subsequent sleep was investigated. Nine young male adults slept in the laboratory for 3 consecutive nights. Sepctral analysis of the EEG on the 2nd (baseline) night revealed an exponential decline in mean EEG power density (0.25–15.0 Hz) over successive nonrapid eye movement — rapid eye movement sleep cycles. During the first 3 h of the 3rd night the subjects were deprived of SWS by means of acoustic stimuli, which did not induce wakefulness. During SWS deprivation an attenuation of EEG power densities was observed in the delta frequencies, as well as in the theta band. In the hours of sleep following SWS deprivation both the power densities in the frequency range from 1 to 7 Hz and the amount of SWS were enhanced, relative to the same period of the baseline night. Both the amount of EEG energy accumulating subsequent to SWS deprivation and its time course could be predicted accurately from the EEG energy deficit caused by SWS deprivation. The data show that the level of integral EEG power density during a certain period after sleep onset depends on the amount of EEG energy accumulated during the preceding sleep rather than on the time elapsed since sleep onset. In terms of the two-process model of sleep regulation (Borbély 1982; Daan et al. 1984) this finding indicates that EEG power density reflects the rate of decay of the regulating variable, S, rather than S itself, as was originally postulated.     

Effect of sleep deprivation on sleep and EEG power spectra in the rat

EEG power spectra of the rat were computed for consecutive 4-s epochs of the daily light period and matched with the scores of the vigilance states. Sleep was characterized by a progressive decline of low frequency spectral values (i.e. slow wave activity) in non-rapid eye movement (non-REM) sleep, and a progressive increase in the amount of REM sleep. During recovery from 24-h total sleep deprivation (TSD) the following changes were observed: an increase of slow wave activity in non REM sleep with a persisting declining trend; an enhancement of theta activity (7.25-10.0 Hz) both in REM sleep and waking; a decrease of non-REM sleep and an increase of REM sleep. In addition, a slow wave EEG pattern prevailed in the awake and behaving animal during the initial recovery period. In selective sleep deprivation paradigms, either REM sleep or slow wave activity in non-REM sleep was prevented during a 2-h period following upon 24-h TSD. During both procedures, non-REM sleep spectra in the lowest frequency band showed no increase. There was no evidence for a further enhancement of slow wave activity after its selective deprivation. The results indicate that: (1) slow wave activity in non-REM sleep and theta activity in REM sleep may reflect sleep intensity; and (2) REM sleep and active waking, the two states with dominant theta activity, may be functionally related.     

The diagnostic value of the short sleep EEG and other provocative methods following sleep deprivation

Summary One hundred and eighty-five EEGs recorded after deprivation of sleep for 24h were evaluated. Valuable diagnostic information was found in 59% of the EEG recordings; 24% of the EEGs contained seizure activity. The duration of the stages of sleep and the frequency of seizure activity, paroxysmal sharp wave groups and localizing findings were analyzed. The sleep stages A to C (based on the Loomis scale) were reached for about equal duration by an EEG recording of 30–40 min; sleep stage D was reached only shortly and stage E was not observed. Pathological EEG findings appeared for the most part in the sleep stages A and B. Localized findings were pronounced in stage C. No significant differences pertaining to the occurrence and form of EEG patterns were found between patient groups with primary generalized seizures, psychomotor seizures or those with unclarified disturbances of consciousness. The combination of the short sleep EEG following 24h of sleep deprivation with subsequent use of the additional provocative methods of hyperventilation, photostimulation and hydration, yielded, in all, new information in 50% of the patients. Each of these additional methods contributed nearly equally to this information.

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Zusammenfassung Es wurden 185 EEGs nach 24h Schlafentzug ausgewertet. Hiervon enthielten 110 EEGs (59%) diagnostisch weiterführende Befunde. In 24% fand sich Krampfaktivität. Es wurden die Dauer der Schlafstadien, die Häufigkeit des Auftretens von Krampfaktivität, paroxysmalen Steilwellengruppen und Lokalbefunden analysiert. Die Schlaftiefen A bis C (nach Loomis) wurden während einer EEG-Ableitung von 30–40 min gleichmäßig lang, Stadium D nur kurz, Stadium E nicht erreicht. Pathologische EEG-Befunde traten überwiegend in den Schlafstadien A und B auf. Lokalbefunde fanden sich besonders im Stadium C. Zwischen den Patientengruppen mit primär generalisierten Anfällen, psychomotorischen Anfällen sowie Zuständen ungeklärter Bewußtseinsstörung fand sich kein signifikanter Unterschied hinsichtlich Auftreten und Ausprägung der EEG-Veränderungen. Die regelmäßig durchgeführte Hyperventilation und Fotostimulation und die Flüssigkeitsbelastung, die nur bei negativen Vorbefunden zusätzlich durchgeführt wurde, ergaben zusammen in 50% eine neue Information.

     

Obstructive sleep apnea in epilepsy patients: the Sleep Apnea scale of the Sleep Disorders Questionnaire (SA-SDQ) is a useful screening instrument for obstructive sleep apnea in a disease-specific population

OBJECTIVE: To determine useful cutoffs on the Sleep Apnea scale of the Sleep Disorders Questionnaire (SA-SDQ) in an epilepsy population. BACKGROUND: Epilepsy and obstructive sleep apnea (OSA) frequently coexist, and treating OSA in epilepsy patients may reduce seizure frequency and improve daytime sleepiness. The SA-SDQ, a 12-item validated measure of sleep-related breathing disorders, may be a useful tool to screen epilepsy patients for OSA, although appropriate cutoff points have not been established in this population. Previously suggested SA-SDQ cutoff points for OSA in a non-epilepsy population were 32 for women and 36 for men. PATIENTS AND METHODS: One hundred twenty-five subjects with epilepsy undergoing polysomnography completed a survey about their sleep, including the 12-item SA-SDQ scale. Receiver-operating characteristics curves were constructed to determine optimal sensitivity and specificity. RESULTS: Sixty-nine of the 125 subjects (45%) had apnea-hypopnea indices greater than five, indicating OSA. The area under the curve was 0.744 for men and 0.788 for women. For men, an SA-SDQ score of 29 provided a sensitivity of 75% and a specificity of 65%. For women, an SA-SDQ score of 26 provided a sensitivity of 80% and a specificity of 67%. CONCLUSIONS: The SA-SDQ is a useful screening instrument for OSA in an epilepsy population. Our results indicate that the previously suggested cutoffs for OSA (36 for men and 32 for women) may be too high for this specific population. We suggest screening cutoffs of 29 for men and 26 for women.     

Obstructive sleep apnea in psychiatric outpatients. A clinic-based study

Psychiatric diseases and symptoms are common among patients with obstructive sleep apnea (OSA). However, only a few studies have examined OSA in psychiatric patients. At the outpatient clinic of the Uusikaupunki Psychiatric Hospital, Finland, we used a low referral threshold to a diagnostic sleep study. An ambulatory cardiorespiratory polygraphy was performed in 114 of 221 patients. 95 patients were referred by the psychiatric clinic and 19 were examined in other clinical settings. We reviewed the medical files and retrospectively assessed the prevalence of OSA and the effect of gender, age, obesity, hypertension, type 2 diabetes, alcohol abuse, and symptoms suggesting OSA. 58 of the 221 patients (26.2%), 30 of 85 men (35.3%) and 28 of 136 women (20.6%), had OSA as determined by an apnea–hypopnea index (AHI) of 5/h or more. 20 patients (12 men and 8 women) had moderate or severe OSA (AHI ≥ 15/h). 46 patients (including 11 patients with moderate or severe OSA) were identified in the psychiatric clinic. In univariate analysis, a high body mass index, male gender, hypertension, snoring, and a history of witnessed apneas during sleep were associated with the presence of OSA. In multivariate analysis, a history of witnessed apneas did not remain significant. Age, type 2 diabetes, alcohol abuse, excessive daytime sleepiness (EDS), and fatigue did not associate with the presence of OSA. Our findings suggest that in psychiatric outpatients OSA is common but underdiagnosed. Presentation is often atypical, since many patients with OSA do not report witnessed apneas or EDS.     

A comparative study of the diagnostic value of drug-induced sleep EEGs and sleep EEGs following sleep deprivation in patients with complex partial seizures

Summary The purpose of the study was to investigate whether the sleep EEG after sleep deprivation has a stronger provocative effect than the drug-induced sleep EEG. For this purpose a sleep EEG, induced by 2 mg/kg body weight of promazine hydrochloride, was recorded. On the following day a sleep EEG of the same patient was recorded after sleep deprivation of 24–26 h. If only patients whose wake EEGs were free from epileptic activity are considered, the rate of provocation was 58%. As epileptic activity could be recorded even in the sleep EEG without sleep deprivation in 45%, the advantage gained by recording a sleep EEG after sleep deprivation (52%) is only relatively small. The occurrence of epileptic activity was shown to be significantly more frequent amongst women and those who developed epilepsy at a younger age. For practical purposes it is recommended that for those patients whose wake EEGs are free from epileptic activity, a sleep EEG—possibly drug-induced—should be recorded. Only in instances where epileptic activity can not then be recorded should a wake EEG after sleep deprivation be carried out, and followed immediately, if necessary, by a sleep EEG.Supported by the Deutsche Forschungsgemeinschaft     

The impact of obstructive sleep apnea and daytime sleepiness on work limitation

BACKGROUND: Many patients with obstructive sleep apnea (OSA) participate in the work force. However, the impact of OSA and sleepiness on work performance is unclear. METHODS: To address this issue, we administered the Epworth Sleepiness Scale (ESS), the Work Limitations Questionnaire (WLQ), and an occupational survey to patients undergoing full-night polysomnography for the investigation of sleep-disordered breathing. Of 498 patients enrolled in the study, 428 (86.0%) completed the questionnaires. Their mean age+/-standard deviation (SD) was 49+/-12 years, mean body mass index (BMI) was 31+/-7 kg/m(2) mean apnea hypopnea index (AHI) was 21+/-22 events/h, and mean ESS score was 10+/-5. Subjects worked a mean of 39+/-18 h per week. The first 100 patients to complete the survey were followed up at two years. RESULTS: In the group as a whole, there was no significant relationship between severity of OSA and the four dimensions of work limitation. However, in blue-collar workers, significant differences were detected between patients with mild OSA (AHI 5-15/h) and those with severe OSA (AHI>30/h) with respect to time management (limited 23.1% of the time vs. 43.8%, p=0.05) and mental/personnel interactions (17.9% vs. 33.0%, p=0.05). In contrast, there were strong associations between subjective sleepiness (as assessed by the ESS) and three of the four scales of work limitation. That is, patients with an ESS of 5 had much less work limitation compared to those with an ESS 18 in terms of time management (19.7% vs. 38.6 %, p<0.001), mental-interpersonal relationships (15.5% vs. 36.0%, p<0.001) and work output (16.8% vs. 36.0%; p<0.001). Of the group followed up, 49 returned surveys and 33 who were using continuous positive airway pressure (CPAP) showed significant improvements between the initial and second follow-up in time management (26% vs. 9%, p=0.0005), mental-interpersonal relationships (16% vs. 11.0%, p=0.014) and work output (18% vs. 10%; p<0.009). CONCLUSION: We have demonstrated a clear relationship between excessive sleepiness and decreased work productivity in a population referred for suspected sleep-disordered breathing. Screening for sleepiness and sleep-disordered breathing in the workplace has the potential to identify a reversible cause of low work productivity.     

Dynamics of the EEG slow-wave synchronization during sleep

OBJECTIVE: To study the dynamics of spatial synchronization of the slow-wave activity recorded from different scalp electrodes during sleep in healthy normal controls. METHODS: We characterized the different levels of EEG synchronization during sleep (in the 0.25-2.5 Hz band) of five healthy subjects by means of the synchronization likelihood (SL) algorithm and analyzed its long-range temporal correlations by means of the detrended fluctuation analysis (DFA). RESULTS: We found higher levels of interregional synchronization during 'cyclic alternating pattern' (CAP) sleep than during nonCAP with a small but significant difference between its A and B phases. SL during CAP showed fluctuations probably corresponding to the single EEG slow-wave elements. DFA showed the presence of two linear scaling regions in the double-logarithmic plot of the fluctuations of SL level as a function of time scale. This indicates the presence of a characteristic time scale in the underlying dynamics which was very stable among the different subjects (1.23-1.33 s). We also computed the DFA exponent of the two scaling regions; the first, with values approximately 1.5, corresponded to fluctuations with period 0.09-0.75 s and the second, with values approximately 1, corresponded to fluctuations with period 1.5-24.0 s. Only the first exponent showed different values during the different sleep stages. CONCLUSIONS: All these results indicate a different role for each sleep stage and CAP condition in the EEG synchronization processes of sleep which show a complex time structure correlated with its neurophysiological mechanisms. SIGNIFICANCE: Very slow oscillations in spatial EEG synchronization might play a critical role in the long-range temporal EEG correlations during sleep which might be the chain of events responsible for the maintenance and correct complex development of sleep structure during the night.     

Sleep and libido in men with obstructive sleep apnea syndrome

ObjectivesThe objectives of this study were to investigate the relationship between a low libido and objective sleep parameters as well as mood disturbances in patients with obstructive sleep apnea syndrome (OSA).MethodsWe enrolled 436 untreated patients who were newly diagnosed with OSA (all male, mean age 42.8 years). Patients completed the Symptom checklist-90-Revised (SCL-90-R), Epworth Sleepiness Scale (ESS), Beck Depression Inventory-II (BDI), and Beck Anxiety Inventory (BAI). Patients were divided into low-libido and normal-libido groups according to their response to the statement “Loss of sexual interest or pleasure” on the SCL-90-R.ResultsApproximately 23% of patients reported a low libido. Patients with a low libido were older (47.5 ± 9.0 vs. 41.4 ± 11.1 years; p < 0.001), had more nocturia (33.3% vs. 16.6%; p < 0.001), higher BDI (9.0 (5.0–14.0) vs. 5.0 (2.0–9.0); p < 0.001) and BAI score (11.0 (6.3–16.8) vs. 5.0 (2.0–10.0); p < 0.001). These patients had a lower non-REM sleep stage 3 (N3) % (0.1 (0–4.0) vs. 2.3 (0.1–7.9); p < 0.001). Multivariate analysis revealed that older age and higher BDI score were independent factors associated with a low libido.ConclusionsMen with untreated OSA suffered from a low libido. Older age and depressed mood were the most important factors of low libido in middle-aged men with OSA.     

Obstructive sleep apnea,sleep duration and chronic kidney disease in patients with coronary artery disease

BackgroundLimited evidence is available addressing the potential role of sleep disorders on renal function. Here, we aimed to explore the associations of obstructive sleep apnea (OSA) and sleep duration (SD) with renal function in subjects with high cardiovascular risk.MethodsConsecutive subjects with coronary artery disease (CAD) underwent clinical evaluation, sleep study to define OSA and one-week wrist actigraphy to objectively measure SD. OSA was defined by an apnea-hypopnea index (AHI) of ≥15 events/hour. The estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI equation. We analyzed the associations of OSA and SD with continuous eGFR values and according to the presence of CKD (eGFR<60 mL/min/1.73 m²) after adjusting for multiple confounding factors.ResultsWe studied 242 subjects (62.8% men). The frequency of OSA was 55.4% and the median SD was 412.8 (363.4–457.25) min. There was no difference in the eGFRs between participants with and without OSA (69.3 ± 19.1 vs. 74.6 ± 19.3 mL/min/1.73 m², p = 0.72) and the rate of eGFR <60 mL/min/1.73 m² (34.3% vs. 25.9%; p = 0.21). Similarly, we did not find differences in patients in eGFR for those with SD ≥ 6 h versus SD < 6 h (72.5 ± 20.3 vs. 71.4 ± 19.1 mL/min/1.73 m², p = 0.72). In the linear regression analysis, AHI was independently associated with an eGFR<60 mL/min/1.73 m² in the unadjusted model [−0.15 (-0.27 to −0.04)], (P = 0.01), but not in the adjusted models. Analyses of continuous SD or the stratification in SD ≥ 6 h or <6 h also revealed neutral results on eGFR.ConclusionOSA severity and SD were not independently associated with CKD in subjects with CAD.     

Obstructive sleep apnea is associated with cancer mortality in younger patients

ObjectiveThe association between obstructive sleep apnea (OSA) and cancer mortality has scarcely been studied. The objective of this study was to investigate whether OSA is associated with increased cancer mortality in a large cohort of patients with OSA suspicion.MethodsThis was a multicenter study in consecutive patients investigated for suspected OSA. OSA severity was measured by the apnea–hypopnea index (AHI) and the hypoxemia index (% night-time spent with oxygen saturation <90%, TSat₉₀). The association between OSA severity and cancer mortality was assessed using Cox’s proportional regression analyses after adjusting for relevant confounders.ResultsIn all, 5427 patients with median follow-up of 4.5 years were included. Of these, 527 (9.7%) were diagnosed with cancer. Log-transformed TSat₉₀ was independently associated with increased cancer mortality in the entire cohort (hazard ratio [HR], 1.21; 95% confidence interval [CI], 1.03–1.42), as well as in the group of patients with cancer (HR, 1.19; 95% CI, 1.02–1.41). The closest association was shown in patients <65 years in both the AHI (continuous log-transformed AHI: HR, 1.87; 95% CI, 1.1–3.2; upper vs lower AHI tertile: HR, 3.98; 95% CI, 1.14–3.64) and the TSat₉₀ (continuous log-transformed TSat₉₀: HR, 1.73; 95% CI, 1.23–2.4; upper vs lower TSat₉₀ tertile: HR, 14.4; 95% CI, 1.85–111.6).ConclusionsOSA severity was associated with increased cancer mortality, particularly in patients aged <65 years.     

Varenicline administration for smoking cessation may reduce apnea hypopnea index in sleep apnea patients

Objective/Background: Varenicline (VAR) is used for smoking cessation as it inhibits nicotine for binding on its receptors reducing nicotine dependence. VAR administration has been reported to affect sleep. The aim of this study was to evaluate possible changes in polysomnography (PSG) during VAR treatment (SmokeFreeBrain) in healthy smokers and smokers with obstructive sleep apnea (OSA). Patients/Methods: Thirty smokers (21 men) with 15.3 ± 10.2 PY, aged 32.8 ± 4.5 years, with BMI 28.6 ± 4 kg/m², 16 without and 14 with OSA (92% males) were studied with PSG (Embletta MPR-Master) before treatment with VAR while smoking and 20–30 days during VAR administration and smoking cessation for at least 5 days. Results: No significant differences were observed in sleep macro architecture (N1, N2, N3, REM, Sleep Efficiency, Total Sleep Time) during VAR treatment apart from prolongation of sleep latency, N2 and N3 latency in both smokers with and without OSA. Apnea hypopnea index (AHI) was reduced in OSA smokers and especially during REM with a borderline increase of arousal index (ArI) and reduction of sleep efficiency (SE). Conclusion: VAR treatment worsened sleep quality as a prolongation of sleep latency, N2 and N3 latency was observed. A marginal reduction of AHI was found in OSA patients, more significantly during REM. Due to the small sample size, further studies are needed to distinguish between the adverse reactions of VAR treatment and smoking cessation effects and to evaluate whether VAR may play a role in OSA treatment.     

Two-group classification of patients with obstructive sleep apnea based on analysis of brain recurrence

ObjectiveTo demonstrate that the severity of obstructive sleep apnea (OSA) could be predicted algorithmically by means of recurrence analysis of the sleep-staged electroencephalogram (EEG).MethodsA randomly selected cohort of 20 sleep-staged patients with OSA (apnea–hypopnea index (AHI) 5–30) was divided into mild and moderate sub-cohorts (AHI 5–15, 16–30, respectively), and the sleep EEG (C3) was analyzed using analysis of brain recurrence (ABR) (LSU cohort). Twenty distinct but related markers for sleep depth and fragmentation were computed from four ABR variables, and a marker function capable of classifying each patient into one of the two sub-cohorts was determined by linear discriminant analysis. Classification accuracy of individual patients was evaluated using area under the receiver operator characteristics curve (AUROC). As a control procedure, 20 additional sleep-staged patients with OSA whose polysomnographic data was obtained from an independent database were also evaluated (SHHS cohort).ResultsOn average, markers for sleep depth were reduced and those for sleep fragmentation were increased in the patients with moderate OSA, as expected. All patients in both cohorts were correctly classified using as few as 5–6 markers.SignificanceThe degree of severity of OSA was reflected in objective changes in the sleep EEG. Recurrence analysis of the EEG potentially has uses beyond identification of the degree of OSA.     

Alterations in sympathetic and parasympathetic brain networks in obstructive sleep apnea

Objective/backgroundObstructive sleep apnea (OSA) patients experience hypoxia and, potentially, autonomic impairments stemming from neural damage. In this study, the executive control networks (ECNs), salience networks (SNs), and default mode networks (DMNs) of adult OSA patients, as well as their relationships with autonomic impairment, were investigated through independent component analysis (ICA).Patients/methodsA total of 41 OSA patients and 19 healthy controls volunteers were recruited and subjected to polysomnography to ascertain their degree, if any, of sleep apnea. Each participant also underwent a cardiovascular autonomic survey, with the participant's baroreflex sensitivity (BRS) being determined based on heart rate and blood pressure alterations. The resting fMRI data of the participants was separated using probabilistic ICA, and six autonomic resting-state networks were established for group comparisons. The differences in autonomic parameters, autonomic functional connectivity (FC), and clinical severity were then correlated.ResultsThe OSA group had significantly worse BRS values than the controls, as well as lower FC in the posterior and anterior SNs, bilateral ECNs, and the ventral DMN, and higher FC in the left ECN. These intrinsic connectivity networks showed dissociable correlations with greater baroreflex impairment and clinical disease severity. The higher FC in the left ECN was associated with the lower FC in the ventral DMN.ConclusionsOur findings suggest that autonomic dysfunction in OSA might be accompanied by central autonomic network alterations. The stronger sympathetic-associated regions in ECNs and the weaker parasympathetic-associated regions in DMNs may represent intrinsic neural architecture fluctuations underlining their consequent processes in OSA.     

Comparison of obstructive sleep apnea patients with and without leg edema

BackgroundTo determine the proportion of patients with obstructive sleep apnea (OSA) who have leg edema, and to identify differences between edematous and non-edematous OSA patients.MethodsRetrospective, cross-sectional study of 378 patients with OSA (apnea/hypopnea index [AHI] ⩾15) who had neither heart failure nor chronic lung disease.ResultsThirty-five percent (133/378) of the subjects with OSA had bilateral leg edema. Eighty-one percent (108/133) of the edematous subjects had mild pitting that was 1+. Compared to the non-edematous OSA subjects, the edematous subjects were older (age = 51 ± 13 versus 45 ± 13 years, p = 0.001), more obese (body mass index = 39 ± 9 versus 33 ± 8 kg/m², p = 0.001), had more severe OSA (AHI = 46 ± 71 versus 27 ± 29, p = 0.004), spent a greater proportion of sleep time with an oxygen saturation <90% (20 ± 26 versus 11 ± 18%, p = 0.001), and were more likely to have diabetes mellitus (11% versus 3%, p = 0.001) and hypertension (32% versus 10%, p = 0.001). Age, obesity, hypertension and diabetes mellitus correlated significantly with edema status. After adjusting for these confounding variables, the AHI means remained different between the edema and non-edema groups (41 ± 5 versus 28 ± 3, p = 0.04).ConclusionsApproximately one-third of OSA patients have edema. Edematous OSA patients are older, more obese, more likely to have diabetes mellitus and hypertension, and have more severe OSA than OSA patients who lack edema.     

Cerebral autoregulation in patients with obstructive sleep apnea syndrome during wakefulness

Background and purpose:  Obstructive sleep apnea syndrome (OSAS) is an independent risk factor for stroke. Impairment of cerebral autoregulation may play a potential role in the pre-disposition to stroke of OSAS patients. In this study, we aimed to assess dynamic cerebral autoregulation (DCA) during wakefulness in OSAS patients and a group of matched controls.
Methods:  Patients and controls were examined in the morning after an overnight complete polysomnography. Mean cerebral blood flow velocity (CBFV) in the middle cerebral artery and mean arterial blood pressure (ABP) were continuously recorded using transcranial Doppler and Finapres. DCA was assessed using the Mx autoregulatory index. Mx is a moving correlation coefficient between mean CBFV and mean ABP. More positive value of Mx indicates worse autoregulation.
Results:  Eleven OSAS patients (mean age ± SD; 52.6 ± 7.9) and 9 controls (mean age ± SD; 49.1 ± 5.3) were enrolled. The mean apnea–hypopnea index (AHI) in the OSAS group was of 22.7 ± 11.6. No significant difference was found between the two groups as for age, body mass index, mean ABP and endtidal CO₂ pressure. Cerebral autoregulation was impaired in OSAS patients compared with controls (Mx index: 0.414 ± 0.138 vs. 0.233 ± 0.100; P  = 0.009). The severity of autoregulation impairment correlated to the severity of the sleep respiratory disturbance measured by the AHI ( P  = 0.003).
Conclusion:  Cerebral autoregulation is impaired in patients with OSAS during wakefulness. Impairment of cerebral autoregulation is correlated with the severity of OSAS.     

Diurnal variation in daytime sleepiness of patients with sleep apnea syndrome

Diurnal variations in daytime sleepiness were studied in 26 men with sleep apnea syndrome (SAS) [age, 41.7 +/- 9.9 years (mean +/- SD); body mass index, 30.0 +/- 6.2 kg/m2; Epworth Sleepiness Score, 8.7 +/- 4.1; apnea-hypopnea index, 50.2 +/- 22.0]. Sleep latencies measured at 09.00 h, 11.00 h, 13.00 h, 15.00 h, and 17.00 h were 3.4 +/- 3.6 min, 4.7 +/- 5.5 min, 5.2 +/- 4.4 min, 5.3 +/- 5.4 min, and 9.3 +/- 7.2 min, respectively (ANOVA, P < 0.05). Daytime sleepiness in patients with SAS was more pronounced in the morning than in the afternoon and evening.     

Obstructive sleep apnea in Parkinson's disease: a study in 239 Chinese patients

ObjectiveOur objective was to explore the clinical characteristics of Parkinson's disease (PD) comorbidity with obstructive sleep apnea (OSA), explore the correlation between OSA and PD features and identify factors that are independent predictors of OSA in PD patients.MethodsIn sum, 239 PD patients were divided into two groups according to the presence of OSA (apnea–hypopnea index (AHI) score ≥5) (PD-OSA vs PD-non-OSA). Blinded to sleep apnea status, participants underwent an extensive assessment to determine demographic features, concomitant disease, disease severity, polysomnography (PSG) characteristics and non-motor symptoms (NMSs).ResultsOf the 239 patients, 66 (27.62%) had an AHI score ≥5, including 14.2% (34/239) with mild, 6.7% (16/239) with moderate, and 6.7% (16/239) with severe sleep apnea. The binary logistic regression analyses indicated that age and male gender were risk factors for OSA, while rapid eye movement (REM) sleep disorder (RBD) and higher Levodopa equivalent dose (LED) were protective factors for OSA. PD-OSA patients had higher Epworth Sleepiness Scale (ESS) scores than those of PD-non-OSA patients. No differences were found for other NMSs between groups.ConclusionOur data suggest that OSA in PD was lower in patients with RBD and higher LED. RBD and higher LDEs were significant protective factors for OSA in PD. OSA in PD was increased with age and male gender. Age and male gender were risk factors for OSA in PD. OSA can aggravate excessive daytime somnolence in PD patients but is not associated with other NMSs.     

Investigating the interaction between heart rate variability and sleep EEG using nonlinear algorithms

Background

The multi-mode modulation is a key feature of sleep EEG. And the short-term fractal property reflects the sympathovagal modulation of heart rate variability (HRV). The properties of EEG and HRV strongly correlated with sleep status and are interesting in clinic diagnosis.

New method

19 healthy female subjects were included for over-night standard polysomnographic study. Hilbert Huang transform (HHT) was used to characterize the temporal features of slow- and fast-wave oscillations decomposed from sleep EEG at different stages. Masking signals were used for solving the mode-mixing problem in HHT. On the other hand, detrended fluctuation analysis (DFA) was used to assess short-term property of HRV denoted as DFA α1, which reflects the temporal activity of autonomic nerve system (ANS). Thus, the dynamic interaction between sleep EEG and HRV can be examined through the relationship between the features of sleep EEG and DFA α1 of HRV.

Results

The frequency feature of sleep EEG serves as a good indicator for the depth of sleep during non-rapid eye movement (NREM) sleep, and amplitude feature of fast-wave oscillation is a good index for distinguishing rapid eye movement (REM) from NREM sleep.

Comparison with existing method

The relationship between DFA α1 of HRV and the mean amplitude of fast-wave oscillation of sleep EEG affirmed with Pearson correlation coefficient is more significant than the correlation verified by the traditional spectral analysis.

Conclusion

The dynamic properties of sleep EEG and HRV derived by EMD and DFA represent important features for cortex and ANS activities during sleep.