In the study, we found that the main EDS cause was OSA and almost all recruited patients were discovered retrospectively by PSG to be suffering from OSA, this is agreement with the literature that the most common cause of EDS in a clinical setting is obstructive sleep apnea (OSA) . Almost all our study demonstrations will be about EDS due to OSA.
Our cases group included 20 cases (4 females and 16 males). This higher male percentage is in, historical, agreement with Chan et al. (2003) study that reported the prevalence (which is the proportion of the whole affected subjects) of OSA according to gender was two to threefolds major risk for men compared with women in most of the population-based studies . Also found higher prevalence of OSA in men than women until after the age of 50 years, when both genders became at equal risk for the disease. Regarding OSA incidence, Strohl et al. (1996) reported that the overall incidence of moderate-to-severe OSA over a 5-year period was 11.1% in men and 4.9% in women .
Our cases age ranged from 32 to 58 years with a mean age of 45.45 ± 7.6 years. This age range of our study group was near to the age group of Tishler et al. (2003) in their study of 1190 patients suffering from increased sleepiness during daily normal activities which was 36–50 years . This age group was also near to many studies as Newman et al. (2005) .
The risk of having OSA increases with age . This may be due to increased length of the soft palate, fat deposition in the parapharyngeal region and changes in body structures that surround the pharyngeal tissue, yet its still observational and needs more research . As for the BMI, its mean in our cases was 31.97 ± 4.26 (kg/m2) and ranged from (32.0 to 58.0 kg/m2) which is in agreement with Punjabi et al. (2008) study that found that the prevalence of OSA is higher in overweight people (BMI > 25 kg/m2). This comes in agreement with the worldwide epidemiologic studies about body weight, which was considered as the strongest risk factor for obstructive sleep apnea . In addition, it was stated by Martikainen et al. (1992) that every 10% increase in the body weight leaded to an increase of the AHI by 32% and a sixfold increase in the risk of developing moderate to severe OSA .
Regarding QEEG results, our QEEG analysis it surprisingly showed statistically significant reduction of delta waves in the central (Cz) as well as the temporal electrodes in the cases, while controls did not show this reduction it showed only increase in the delta waves in the temporal electrodes. Therefore, likely, patients experiencing EDS due to their fragmented night sleep and non-restorative sleep which was presented in the form of reduction of the centro-temporal delta power and occipital alpha power in Eikermann et al. (2007) .
The suggested mechanism that demonstrated the reduction of delta power in EDS patients secondary to OSA after sleep could be attributed to hypoxemia and/or hypercapnia during OSA as detected by Tufik et al. (2010) who found a correlation between the severity of hypoxemia and hypercapnia during the OSA and changes in delta power .
The reduction in the central and temporal delta power of the EEG in our cases after sleep supported the idea of non-restorative sleep in EDS patients secondary to OSA. According to the synaptic homeostasis hypothesis theory of sleep function which stated that learning activities and synaptic plasticity acquired during wakefulness state as a result, to an increase in the duration of slow wave activity in the following night sleep. This theory makes restorative sleep which is reflected in the form of increased duration of the central slow waves is important for the synaptic strength and its nutrient supply, important for grey matter consumption and preservation of learning and memory .
In OSA patients, because of night sleep deprivation and fragmentation, they lost this sleep regulation function leading to “cerebral overloading” and in turn impairment of their memory and learning abilities. So that these changes in delta power in our cases were suggested to be a contributor to daytime symptoms of non-alertness and non-attentiveness in OSA patients .
Our control group showed increase in the absolute delta power in the temporal electrodes in comparing EEG after with before sleep. This finding agreed also with synaptic homeostasis hypothesis; being had a normal restorative night sleep , the control group had normal synaptic homeostasis, preventing cerebral overloading and so that they had normal day neurobehavioral functions.
In contrast to our study results regarding delta power spectral analysis in EDS patients—secondary to OSA—during wakefulness, was Morisson et al. (1998) study that investigated changes of waking EEG in OSA patients over 24 h of sustained wakefulness in comparison to healthy controls and found that the absolute delta power was higher in OSA patients than controls , the same was found also by Tononi et al. (2003) in OSA patients but after 40 h of extended wakefulness in comparison to controls . This increase in delta power could be demonstrated by a theory stating that disturbance of the restorative power of sleep in OSA patients leading to increase in the low frequency bands activity during wakefulness, inducing drowsiness and EDS, especially at the end of the 24-h period of sustained wakefulness. This QEEG finding may be due to the presence of combined effects of both acute and chronic sleep deprivation in OSA patients in such study with augmentation of sleepiness effects in those patients . This is not the case in our study that investigated the chronic night sleep deprivation and fragmentation effects in EDS patients secondary to OSA.
We also found a significant decrease in the occipital alpha power in cases (P = 0.03) and positive correlation (P = 0.022) in the cases between the difference of average occipital (O) alpha power (between before and after sleep) and ESS score explaining un wakefulness of the cases on the other day of non-restorative sleep, while Grenèche et al. (2008), who studied the correlation between ESS score and alpha relative power in OSA patients and recorded the EEG during wakefulness in the morning found that ESS score was negatively correlated with alpha relative power; as the patient’s sleepiness level increased, the ESS score also increased and in turn the alpha relative power decreased . This negative correlation of the author’s results was different from our positive one. This might be attributed to the use of the relative alpha power in QEEG analysis in his study instead of the absolute alpha power that we used in ours.
Another statistically significant positive correlation was found in the cases group of our study between the difference of average occipital alpha power (between before and after sleep) with KSS before sleep (P = 0.005). This is aligning with D'Rozario et al. (2013) study; in which QEEG assessment was done for patients with OSA during oral intake of Modafinil with acute withdrawal of continuous positive airway pressure CPAP for 2 days (CPAP was used for the first night and then withdrawn for 2 subsequent nights). It showed significant positive correlation of KSS (subjective alertness assessment) with Alpha/Delta ratio (absolute alpha power/delta power) and fast ratio (Power ratio of (alpha beta)/ (delta theta) but not with any of the individual frequency bands . The significance of our study lies in its predicting of EDS cases that are functioning during the day in critical professions, as example driving and healthcare. During the last decade, lots of literature focused on instantaneous diagnosis of hypo vigilance in such professions using various electrophysiological modalities, For example hypo vigilance could be detected by heart rate variability (HRV) , driver drowsiness detector using the Eyelid closure degree (ECD) as a video-based method or using EEG sensors instead of video based method as ECD exhibits a linear relationship with changes of the occipital EEG . BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements . Combined EEG-fMRI studies have suggested a close association of fMRI-defined resting state networks with EEG microstates [36, 37]. As well combination of EEG and NIRS, to detect driver drowsiness. EEG, EOG, ECG and NIRS signals .
Limitations and recommendations
Sample size could have been larger, yet the patients had to spend a whole night at the lab for PSG, which made the patients less interested to continue the research.
We are recommending expansion of the study of pre/vs/post sleep QEEG extensive analysis to reach the most valid methodology suggestive of non-restorative sleep.