Source: American Journal of the Medical Sciences Vol. 333, #2, pp 78-84 Date: February 2007 URL: http://www.amjmedsci.com/pt/re/ajms/home.htm http://www.amjmedsci.com/pt/re/ajms/issuelist.htm http://www.amjmedsci.com/pt/re/ajms/toc.00000441-200702000-00000.htm Defining the Occurrence and Influence of Alpha-Delta Sleep in Chronic Fatigue Syndrome Elke Van Hoof, PhD; Pascale De Becker, PhD; Charles Lapp, MD; Raymond Cluydts, PhD; Kenny De Meirleir, PhD >From the Department of Human Physiology (EVH, PDB, KDM) and the Department of Psychology (EVH, RC), Vrije Universiteit, Brussels, Belgium; and from the Hunter-Hopkins Center, Charlotte, North Carolina (CL). Submitted May 11, 2006; accepted in revised form September 11, 2006. Correspondence: Elke Van Hoof, Vakgroep COBI, Faculty of Psychological and Educational Sciences, Pleinlaan 2, 1050 Brussels, Belgium (E-mail: Elke.Van.Hoof@vub.ac.be). ABSTRACT Background Patients with chronic fatigue syndrome (CFS) present a disordered sleep pattern and frequently undergo polysomnography to exclude a primary sleep disorder. Such studies have shown reduced sleep efficiency, a reduction of deep sleep, prolonged sleep initiation, and alpha-wave intrusion during deep sleep. Deregulation of the 2-5A synthetase/RNase L antiviral pathway and a potential acquired channelopathy are also found in a subset of CFS patients and could lead to sleep disturbances. This article compiles a large sleep study database on CFS patients and correlates these data with a limited number of immune parameters as it has been thought that RNase L could be associated with these sleep disturbances. Methods Forty-eight patients who fulfilled 1994 Centers for Disease Control and Prevention criteria for CFS underwent extensive medical evaluation, routine laboratory testing, and a structured psychiatric interview. Subjects then completed a complaint checklist and a two-night polysomnographic investigation. RNase L analysis was performed by gel electrophoresis using a radiolabeled 2',5'-oligoadenylate trimer. Basic descriptive statistical parameters were calculated. Results Patients experienced a prolonged sleep latency, showed a low sleep efficiency index, and had a low percentage of slow wave sleep. The present alpha-delta intrusion correlated with anxiety; no correlations appeared, however, between alpha-delta sleep and immunologic parameters, including RNase L. Conclusions The main findings are 1) validation of sleep latency problems and other sleep disturbances as already suggested by several authors; 2) alpha-delta intrusion seems associated with anxiety; and 3) elevated RNase L did not correlate with alpha-delta sleep. KEY INDEXING TERMS Alpha-delta sleep; Median-split; Anxiety; Specificity; CFS. Chronic fatigue syndrome (CFS) is a clinically defined syndrome that is characterized by chronic fatigue and a constellation of other symptoms and physical findings.1-3 In our sample in Brussels, CFS is diagnosed using a clinical case definition established by the Centers for Disease Control and Prevention (CDC) in 19881 that was revised in 1994.4 The major distinguishing symptom is debilitating fatigue of more than 6 months' duration associated with a marked decrease in daily activity that cannot be attributed to any known medical cause. Other nonspecific symptoms including joint pain, night sweats, visual disturbances, exaggerated allergic reactions, memory loss, emotional lability, and sleep problems such as unrefreshing sleep, accompany the fatigue.4 Patients with CFS describe a disordered sleep pattern with difficulty getting to sleep, frequent awakenings, and, less commonly, early morning wakening. Sleep is nonrestorative, with most patients more aware of their symptoms in the mornings and improving slightly as the day progresses.5-7 In the diagnostic process, patients undergo a polysomnographic investigation to exclude a primary sleep disorder. The use of electroencephalographic (EEG) techniques to investigate the sleeping brain reveals a wealth of electrical activity in a seemingly passive body.8 Sleep is divided into rapid eye move- ment (REM) sleep and non-REM sleep. In turn, non-REM sleep is divided into stages 1, 2, 3, and 4, with slow delta waves comprising stages 3 and 4.8,9 In practice, the alpha rhythm normally occurs during quiet wakefulness and is located over the posterior part of the scalp. The onset of sleep is characterized by the disappearance of this rhythm and the appearance of other EEG frequencies such as theta (3-7 Htz), K-complexes, sleep spindles (12-15 Htz), and later, delta or slow waves (0.5-2.5 Htz) or stages 3 and 4 non-REM sleep. Polysomnographic studies in CFS have shown reduced sleep efficiency, a reduction of REM sleep, and a longer sleep initiation.5,7,10-15 CFS patients have a significantly lower percentage of stage 4 sleep and alpha wave intrusion in deep sleep or alpha-delta sleep.10,11,13 Alpha-delta sleep is an abnormal sleep EEG rhythm characterized by alpha activity that is superimposed on delta waves of slow wave sleep stages 3 and 4.16 This activity was first reported by Hauri and Hawkins in 1973 in 9 psychiatric patients with somatic malaise and fatigue.17 Now, alpha sleep has been broadened to include alpha intrusion into all stages of non-REM sleep.18 However, it seems not to be specific for CFS and has been seen in fibromyalgia,19,20 rheumatoid arthritis,21 and other conditions associated with chronic pain.22,23 In sleep architecture, specific reductions in REM sleep have been reported. Due to this reduction, interferences in daily functioning seem inevitable.10,15 Also, CFS patients have a reduced percentage of delta sleep in their non-REM period.14 Chronic fatigue syndrome is associated with several immunologic abnormalities or discrepancies.24 An intracellular immune deregulation is also widely reported in patients with CFS. After the discovery by Suhadolnik and colleagues, the deregulation of the 2-5A synthetase/RNase L antiviral pathway is frequently found in a subset of CFS patients.5 The hyperactivation of RNase L has been reported at length in the scientific literature,5-8 but also the discovery of the abnormal low molecular weight RNase L (37 kDa) in patients with CFS5 was confirmed by several other researchers.7-9 It had been thought that RNase L level gives a clear picture of immune deregulation and that the suggested acquired channelopathy that occurs as a consequence will lead to central fatigue and sleep disturbances.25 Increased RNase L activity creates interaction of ABC transporters with the ankyrin fragment of RNase L upon its release by proteolytic cleavage.26 Subsequently, it is thought that improper ion channel function will develop, leading toward an ac- quired channelopathy of the ABC transporters. This suggested acquired channelopathy with loss of intracellular potassium will lead to metabolic and intracellular abnormalities, including central fatigue and sleep disturbances such as alpha-delta intrusion.25 This article subjects alpha-delta sleep to an indepth study. First of all, the occurrence of alpha-delta sleep in a randomized study group is examined. If alpha-delta sleep is present in this study population, a median split will be used to check whether more alpha-delta sleep is equivalent with more subjective complaints and more immunologic deviances. Correlation analysis may reveal associations between the subjective feeling of unrefreshing sleep, total sleep time, immunologic parameters, and alpha-delta sleep. After the theory presented by Englebienne and De Meirleir, it has been thought that RNase L would be associated with alpha-delta intrusion and other self-reported as well as objective sleep parameters.25,26 If any of the parameters (RNase L, NK-cells, T-cells, total sleep time, or unrefreshing sleep) correlated significantly with alpha-delta sleep, then a regression analysis might reveal the exact associations between the parameters and alpha-delta in CFS patients. Methods Recruitment of CFS Patients Study subjects were recruited from the outpatient fatigue clinic, Vrije Universiteit Brussels between October and February 2003. Generally, patients are referred by their general practitioner to the outpatient fatigue clinic. To fulfill the 1994 CDC criteria for CFS, clinically evaluated, unexplained, persistent, or relapsing chronic fatigue that is of new or definite onset should result in a substantial reduction in previous levels of occupational, educational, social, or personal activities.2 Furthermore, at least 4 of the following symptoms must have persisted or recurred during 6 or more consecutive months and must not have predated the fatigue: impairment in short-term memory or concentration, tender cervical or axillary lymph nodes, muscle pain, multijoint pain, headaches, unrefreshing sleep, and postexertional malaise lasting more than 24 hours.2 Any active medical condition that may explain the presence of chronic fatigue prohibits the diagnosis of CFS. Hence, all subjects underwent an extensive medical evaluation, consisting of a standard physical examination, medical history, exercise capacity test, and routine laboratory tests. The laboratory tests included a complete blood cell count, determination of the erythrocyte sedimentation rate, serum electrolyte panel, measures of renal, hepatic and thyroid function, and rheumatic and viral screens. If the patients' medical history did not exclude a psychiatric problem at the time of disease onset, a structured psychiatric interview, based on the Diagnostic Statistical Manual for Psychiatric Disorders (DSM), was performed. In a number of cases, further neurologic, gynecologic, endocrine, cardiac, and gastrointestinal evaluations were performed. The medical records were also reviewed to determine whether patients suffered from organic or psychiatric illness that could explain their symptoms. If any of the laboratory or additional analyses revealed any active medical or psychiatric condition that could explain the presence of the patient's symptoms, then CFS could not be diagnosed and those patients were excluded from the study. During a 2-night polysomnographic investigation, blood samples were taken. Only CFS patients who completed a 2-night polysomnographic investigation and had a diagnosis of CFS according to the CDC criteria4 were included in the study. Polysomnography Patients spent 2 nights in the sleep unit, with the first night being considered as a habituation night and followed by an all-night polysomnography examination on the second night. Subjects were prepared for the polysomnographic recordings between 10:00 and 11:00 PM and were allowed to retire when they wished (good night time). They were awakened around 7:30 AM if they did not arise spontaneously (good morning time). Polysomnography involved an electroencephalogram, which was recorded from C4-A1, C3-A2, Fpz2-A1, Fpz1-A2, O2-A1, O1-A2 sites, as well as an electrooculogram, a submental electromyogram, and an anterior tibialis electromyogram. Nasal and oral airflow, respiratory effort (thoracic and abdominal belt), and arterial oxygen saturation were recorded during the second night. The sleep recordings were recorded on Nicolet Ultrasom and visualized on screen and scored by trained sleep technicians in 30-second epochs according to standard criteria. The technicians scored during their routine clinical activities, without knowledge of the aims of the study. The studied sleep variables were: slow-wave sleep (min) (SWS), REM sleep (min) (STGE-REM), time awake (min) (awake) from good night time to good morning time, sleep latency (LAPSTGE2), sleep quality index (SE%), micro-awakenings (MAI) (n/h), total sleep time (TST) (min), REM latency (REMLATN) (min), number of shifts between stages (STSHIFTS), percentage time awake in bed (A%TIB), percentage slow-wave sleep (SWS%TIB), percentage of non-REM sleep (Nrem%TIB), percentage total sleep time (TST%TIB), and alpha-intrusion in slowwave sleep (SWS%AI). Patients were excluded if the TST of 1 night was less than 120 minutes. Immunological Data (Immunophenotyping) Anticoagulated blood (EDTA) was collected between 9:00 and 11:00 AM and used for white blood cell enumeration, differential counts (Celldyn 4000, Abbott Laboratories, Abbott Park, IL) and flow cytometric studies. Lymphocyte populations were analysed with dual color direct immunofluorescence on a EPICS xl flow cytometer (Coulter, Miami, FL), with aid of the System I computer software. A collection of 100 muL of whole blood was incubated with the appropriate combination of monoclonal antibodies for 25 minutes at 4&C. Red blood cells were then lysed using lysis buffer (Becton Dickinson) for 7 minutes, centrifuged, and washed once with 2 mL phosphate buffered saline. Resuspension was immediately followed by cell analysis. Commercially available (Becton-Dickinson) phycoerythrin or fluorescein isothiocyanate labeled monoclonal antibodies were used (Table 1). Estimates of absolute numbers of lymphocyte subsets were determined by multiplying peripheral lymphocyte counts by the percentage of each surface marker. Assessment of peripheral blood mononuclear cells, cell extracts, and serum and quantification of 37-kDa 2-5A-BP in peripheral blood mononuclear cell extracts were performed in a similar fashion as the method described by Demettre et al.26 Subjective Complaints A complaint checklist was presented to the patients. They were asked to complete the checklist and rate their complaints on a Likert scale from 0 (absent) to 3 (commonly present). Fatigue, postexertional fatigue, depressive feelings, anxiety, self-perceived personality changes, emotional lability, muscle aches, joint aches, sleep problems, and nonrefreshing sleep were completed. No psychometric parameters are known. Statistical Analyses Basic descriptive statistical parameters are reported. A onetailed Kolmogorov-Smirnov test was performed to check normal distribution. For the reporting of the location and spread of the distribution of the various variables in this study, the median is more appropriate, as most of the data are either ordinal or continous, but skewed. The mean, standard deviation, and range are also reported as additional information, to make a comparison with other studies possible. The relationship between the different variables was quantified using the nonparametric Spearman rank correlation coefficient for the same distributional reasons as given previously. Kendall's tau was also computed but was not reported in the paper because the results were very much in line with the Spearman coefficient. To assess the significance of the correlations, the P-value for the correlation coefficients was determined. Because of the many correlations, a Bonferoni correction was applied to keep the type I error under control. Therefore correlations are considered to be significant when the P-value is less than 0.002 instead of 0.05. The above statistical computations were performed using the SPSS statistical package [SPSS 2000, SPSS Syntax reference 12.0 SPSS Inc. Chicago, Il] Results Subjects Forty-eight patients were included in this study, of which 19 were male (40%) and 29 were female (60%). The mean age of the patients was 45 years (p/m 10.46 years). The mean number of years the pa- tients experienced symptoms was 8.98 (p/m 7.71 years). The mean scores on the immune parameters are presented in Table 2. None of the immune variables fell outside their reference score. Rnase L The mean RNase L was 4.47 (p/m 0.71) with a median of 2.80. The deregulation of the RNase L pathway can be quantified by dividing the amount of 37 kDa RNase L by 83 kDa RNase L, and multiplying this quotient by 10. The outcome of this formula, frequently referred to as RNase L ratio, is considered normal when it remains below 0.5. In any other case, the RNase L ratio is considered increased, suggestive of deregulation of the 2.5A synthetase RNase L pathway.27 Thirty-nine patients (86.67%) presented an increased RNase L ratio. Subjective Complaints Sixty percent of the patients reported significant fatigue. The mean score of fatigue on a scale from 0 to 3 was 2.56 (p/m 0.58). Almost 75% of patients suffered from post-exertional fatigue, with a mean score of 2.66 (p/m 0.70). Almost 75% reported signifi- cant sleep problems with a mean score of 2.09 (p/m 1.04) and significant nonrefreshing sleep with a mean score of 1.94 (p/m 1.17). The other symptoms are summarized in Table 1. Sleep Continuity Table 3 describes the group variables for the sleep parameters. The sleep latency or the time from lights-off until stage 2 was 61.40 minutes (p/m 7.35 minutes). Table 4 shows the results from Fischler et al,13 who also used a Belgian population. Sleep latency time was lower than in our population. The sleep efficiency index shows 72.35% (p/m 2.15), which is lower than the results presented by Fischler et al13 (Table 4). Our population presented 9.53 (p/m 1.10) micro-awakenings per hour. Again the results in the study performed by Fischler et al13 were relatively lower (Table 4). Sleep Architecture The patients spent 71.49% (p/m 2.19) of the time in sleep. The patients had 70.19 minutes (p/m 5.02) of slow wave sleep or delta-sleep. On average the REM sleep time was 261.96 minutes (p/m .31). The total sleep time was 326.21 minutes (p/m 10.46), which is approximately 5.5 hours of sleep. The test showed a mean number of shifts between stage of 67.29 times (p/m 4.55). The percentage slow wave sleep was 22.49% (p/m 1.71) with a mean non-REM sleep percentage of 80.90% (p/m 1.31). The percentage of alpha waves in slow wave sleep appeared to be 4.32% (p/m 0.80) (Table 3). Alpha-Delta Intrusion A median split was performed on the percentage of alpha waves in slow wave sleep (SWS%AI). A median split was performed to examine whether a high percentage of alpha-delta intrusion results in more subjective complaints or alteration in immune parameters. This method could shed more light on the potential importance of the influence of the alpha-delta intrusion. The median was 2. The meanage of the group with few alpha-delta intrusion was 44.73 years of age (p/m 2.18) and a mean onset of symptoms with a mean of 8.73 years (p/m 1.56). The group with the most alpha-delta intrusion had a mean age of 45.32 years of age (p/m 2.11) with a mean onset of 9.27 years (p/m 1.62). There was no significant difference between the ages of the two groups (chi^X2=2.8; P=0.196). No significant difference could be identified for the onset of both groups (U=268.00, Z=0.374, P=0.708). Table 5 shows the significant differences in subjective complaints and immunologic parameters. Only "subjectively perceived anxiety" differed significantly between the group with high alpha-delta intrusion and low alpha-delta intrusion. The high alpha-delta intrusion group reported the most self-reported anxiety (Table 4). Correlations Alpha-delta intrusion correlated with anxiety, although this was just a statistical trend (R=0.317; P=0.03). No other correlations revealed significant information (data not shown). Because no significant correlations could be found, no regression analyses were performed to reveal exact associations. Discussion Sleep architecture variables demonstrated significantly different sleep onset latency and sleep disturbances in CFS patients (Table 4). Because of the resemblance between the CFS patients used by Fischler et al13 and Fossey et al15 and our CFS population, their results may apply to our sample, although no healthy control group was used. Similar results were already reported by several other authors, such as Whelton et al10 and Stough and Withers.14 CFS patients present less sleep continuity. Patients experience problems falling asleep, represented by the large sleep latency. The low sleep efficiency index and the high number of micro-awakenings objectify the subjectively presented complaints of a distorted sleep pattern and a nonrestorative sleep.5-7 The patients slept about 5.5 hours. They spent almost 30% of the time awake in bed. Interestingly, a lot of shifts between stages are apparent. Again, the results of the sleep architecture underscore the distorted sleep pattern and an unrefreshing sleep. Alpha-delta intrusion is present although a wide range of the percentage of this intrusion indicates its nonspecific nature. This sleep anomaly is thought to be accompanied by indications of vigilance during sleep and the subjective experience of unrefreshing sleep. The latter seems not solely associated with alpha-delta intrusion because no differences in feelings of fatigue and unrefreshing sleep could be found between CFS patients with low or high alpha-delta intrusion. Our results emphasize the nonspecific nature of alpha-delta sleep in CFS patients, a suggestion made by several authors.19-23 For instance, Manu and associates found no correlation between alpha-delta sleep and CFS, fibromyalgia, major depression, primary sleep disorders, or Lyme disease but did find that alpha-delta sleep was more common among chronic fatigue patients without major depressive disorders.23 Although the sample showed high RNase L, no differences were apparent between patients with low and high alpha-delta intrusion. Furthermore, no correlations appeared between alpha-delta sleep and immunologic parameters, including RNase L. So far, it has been thought that a potential acquired channelopathy, a consequence of immune deregulation through RNase L, leads to sleep disturbances including alpha-delta sleep.25,26 Our results suggests that RNase L and the subsequent channelopathy are not associated with alpha-delta intrusion. Moreover, none of the self-reported sleep problems, nor the objective sleep parameters, are associated with RNase L. This result questions at least a part of the suggested hypothesis proposed by Englebienne and De Meirleir.25 The suggested acquired channelopathy with loss of intracellular potassium should lead to metabolic and intracellular abnormalities, including central fatigue and sleep disturbances such as alpha-delta intrusion. Our results do not support the inclusion of sleep disturbances including alpha-delta intrusion in the list of potential consequences of the suggested channelopathy. The results the deregulation of the 2-5A synthetase/RNase L pathway are similar to those of previous studies.27,28 It is still unclear, however, whether the 37 kDa RNase L ratio is representative of the CFS population in general, and whether the 37 kDa RNase L ratio is characteristic of a particular stage in the course of the illness or if it fluctuates over time (as is the case with symptom severity in the majority of CFS patients). Recent research suggest the ratio could be associated with (the severity) of the experienced complaints and its associated clinical causes.25 For instance, the deregulation of the 2-5A synthetase/RNase L pathway appears to accompany different aspects of immune dysfunction in CFS patients. A reduced number and activity (cytotoxicity) of NK-cells have been reported in patients with CFS.29-31 In addition, a negative correlation between the RNase L ratio and both the number and percentage of NK-cells was observed in CFS patients. In our study, no deviant NK-cells percentages were found. Moreover, no correlations were found between the RNase L ratio and the NK-cells. To be a biological gradient, a correlation between the biological parameter of interest (i.e., impairment of the RNase L pathway) and the clinical severity of the disorder of interest (i.e., CFS) is required. No significant correlations regarding self-reported complaints, objective sleep parameters, and immune parameters were found in this study. For interpreting a correlation analysis, however, one should focus on the correlation coefficient rather than interpreting the P-value. Correlation coefficients as low as 0.2, regardless of the P-value, suggest no association is present. Although no significant associations were found, some correlation coefficients suggested possible relationships. The Bonferroni-corrections and the small sample size could prevent any significant results. Further research is necessary to clarify possible associations. Using our present results, no significant findings appeared, casting into question the biological gradient of the RNase L ratio regarding the NK-cells and sleep disturbances. Anxiety differed between low and high alpha-delta sleep. People suffering from high alpha-delta intrusion experience more anxiety. Anxiety could be the result of the higher vigilance in slow wave sleep. The major clinical importance of this study is that because of alpha wave intrusion in phase 3 and 4 of the non-REM sleep, full benefit is not taken from the recuperative function of slow wave sleep. This study had several limitations. First, the study was done retrospectively and therefore strong causal relations were difficult to make. Second, a limited number of CFS patients were enrolled and there was no healthy control group, although the results were similar to those of Fischler et al13 and Fossey et al,15 who did include a healthy control group. Therefore, more research is needed, not only with a increased number of CFS patients that would give more accurate results, but also with the same polysomnographic protocol and adequate control subjects, including patients with non-CFS-induced fatigue. The relatively small number of CFS patients in this study was due to recent changes in polysomnographic protocols; only 41 CFS patients were found to have completed a similar 2-night polysomnographic protocol. Moreover, 1-night polysomnographic protocols should be avoided due to the first-night effect.32 In summary, one obvious limitation of the present study is the lack of power due to a small sample size. However, the well-documented expense related to laboratory sleep research,33 as well as the difficulties regularly encountered with subject attrition in such extensive, demanding, and lengthy investigations make small sample size an unfortunate but common consequence. Nevertheless, the comprehensive data collected make an important contribution to CFS research and should form the basis for future investigations. Summarizing, the main findings of this study are as follows: 1) The existence of sleep latency problems and other sleep disturbances are validated, as already suggested by several authors. 2) Alpha-delta-intrusion seems associated with anxiety. 3) An elevated RNase L-ratio did not correlate with alpha-delta sleep. 4) The results from the correlation analysis questions RNase L as a biological gradient. To our knowledge, this is the first study in which immune parameters were correlated to polysomnographic variables in CFS patients. More research is undoubtedly necessary to state causal relationships, although some interesting suggestions have been made. Acknowledgments Our Department would like to thank Kim Borremans in collecting the appropriate data and Nancy Reichenbach for her help in academic writing. Tables Table 1. Subjective Symptoms Reported by the Patients -------------------------------------------------------------------------------- Variable 0-Absent 1 2 3-Present X (SD) all the time -------------------------------------------------------------------------------- Depressive feelings 23% 25% 33% 19% 1.48 (1.05) Anxiety 44% 10% 31% 15% 1.17 (1.16) Self-perceived 46% 17% 27% 10% 1.02 (1.08) personality changes Emotional lability 19% 19% 33% 29% 1.73 (1.09) Muscle aches 23% 6% 27% 42% 1.89 (1.20) Joint aches 31% 10% 29% 27% 1.53 (1.21) -------------------------------------------------------------------------------- Table 2. Group Variables of Immune Parameters -------------------------------------------------------------------------------- Item Reference, % Patients, n Mean SD Median Range -------------------------------------------------------------------------------- RNAse L -- 45 4.47 0.71 2.80 21 CFS marker CD3HLADR 2-9 44 4.55 0.43 4.00 12 CD8 23-41 44 26.73 1.08 26.00 32 CD19 CD5+ 1-4 44 2.15 0.25 2.00 8 CD3-CD16CD56+ 4-22 44 7.07 0.85 5.50 32 CD4/CD8 0.9-2.6 44 2.22 0.13 2.13 4 -------------------------------------------------------------------------------- Table 3. Group Variables for the Sleep Parameters -------------------------------------------------------------------------------- Item Description Mean SD Median Range -------------------------------------------------------------------------------- SWS Slow wave sleepDelta sleep (min) 70.19 5.02 67.50 134 STGE-REM REM-sleep (min) 261.96 7.31 265.50 221 LAPSTGE2 Sleep latency (from lights-off 61.40 7.35 47.00 269 until stage 2) (min) SE% Sleep quality index (%) 72.35 2.15 75.65 56.2 MAI#/u Micro-awakenings (n/u) 9.53 1.10 8.35 28.6 TST Total sleep time (min) 326.21 10.46 334.50 387 STSHIFTS Number of shifts between stages 67.29 4.55 67.50 120 A%TST % Awake time in bed 46.28 5.54 32.25 160.8 SWS%TST % Slow wave sleep 22.49 1.71 20.95 52.7 NREM%TST % Non-REM sleep 80.90 1.31 81.05 42 TST%TIB % Total sleep time 71.49 2.19 75.05 56.2 SWS%AI % Alpha-waves in slow wave sleep 4.32 0.80 2.00 21 -------------------------------------------------------------------------------- Table 4. Comparison with Data of Fischler et al., 1997 (means) -------------------------------------------------------------------------------- Item Fischler's Fischler's CFS Our Controls Patients Population -------------------------------------------------------------------------------- Sleep latency 21.5^a 39^a 61.40 Micro-awakenings 2.8 3.2 9.53 Total sleep time 382a 339a 326.21 REM latency 89.5 96.0 -- Sleep efficiency, % 87.8^a 76.5^a 72.35 Number of shifts 21.9^a 28.7^a 67.29 Stage 1 sleep, % 9.0 13.9 -- Stage 2 sleep, % 45.5^a 38.2^a -- Stage 3 sleep, % 9.0 11.0 -- Stage 4 sleep, % 14.6 8.8 -- SWS% 23.6 19.8 -- REM sleep, % 14.1 12.0 -- -------------------------------------------------------------------------------- ^a Statistically significant at 0.001 Table 5. Differences in Subjective Complaints and Immunologic Parameters Using a Median Split in Alpha-Delta Intrusion -------------------------------------------------------------------------------- Variable Alpha-delta Alpha-delta P-Value^a < Median (SD) > Median(SD) -------------------------------------------------------------------------------- Immunological parameters RNase L 3.62 (0.71) 5.44 (1.28) 0.645 CD4/CD8 2.15 (0.17) 2.29 (0.21) 0.892 CD3-CD16CD56 5.91 (0.70) 8.33 (1.59) 0.371 CD3 HLADR 4.48 (0.60) 4.62 (62) 0.777 CD19 CD5 1.89 (0.35) 2.43 (0.36) 0.169 Subjective complaints Fatigue 2.46 (0.11) 2.68 (0.12) 0.174 Postexertional fatigue 2.60 (0.16) 2.73 (0.12) 0.807 Depressive feelings 1.35 (0.21) 1.64 (0.22) 0.366 Anxiety 0.77 (0.22) 1.64 (0.22) 0.009 Self-perceived personality 0.88 (0.20) 1.18 (0.24) 0.380 changes Emotional lability 1.65 (0.21) 1.82 (0.23) 0.597 Muscle aches 1.80 (0.26) 2.00 (0.24) 0.769 Joint aches 1.56 (0.27) 1.50 (0.24) 0.762 Sleep problems 2.08 (0.20) 2.09 (0.24) 0.809 Nonrefreshing sleep 2.12 (0.22) 1.73 (0.27) 0.297 -------------------------------------------------------------------------------- ^a Statistical significance (Bonferroni-correction): 0.002 References 1. 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