Chronic fatigue syndrome (also known as myalgic encephalomyelitis) is a serious, long term condition characterised by extreme, incapacitating fatigue of at least 6 months duration with reduction in activity levels. Other symptoms might include post-exertional malaise lasting at least 24 hours, memory and concentration impairment, tender cervical or axillary lymphadenopathy, muscle pains, sore throat, joint pains without swelling or redness, new pattern type headaches and nonrestorative or unrefreshing sleep (1).
In this essay, we address the question: is chronic fatigue syndrome a sleep disorder. This question can be viewed in several ways. Firstly, could the symptoms of chronic fatigue syndrome be due to an underlying undiagnosed primary sleep disorder? Secondly, could chronic fatigue syndrome be in of itself, a primary sleep disorder? We will look at and evaluate the evidence.
Definitions and differentials
Is there evidence that chronic fatigue syndrome is due to an underlying undetected primary sleep disorder?
The pathogenesis of chronic fatigue syndrome (CFS) is currently unknown. The prominence of fatigue as the key symptom in CFS, combined with the attending symptoms of sleep disturbances have led to early studies examining the association between chronic fatigue syndrome to disordered sleep, and possibly a primary sleep disorder.
Krupp et al reported in his study in 1993 that 62.5% of CFS patients with sleep disturbances had an underlying primary sleep disorder such as apnea, periodic limb movement or narcolepsy (2). In Krupp’s study, CFS patients were found to have a worse level of fatigue and sleep impairment compared to normal controls and even compared to controls with multiple sclerosis. However, the study included patients with primary sleep disorders and therefore these increased symptoms could not be solely attributable to CFS alone. Similar findings were also seen in a second study in 1993 by Morriss et al (3). In Morriss’s study, a diagnosis of a coexisting sleep disorder led to the observation of greater fatigue levels in CFS patients. Prior to 1994, the exclusion of a primary sleep disorder was not necessary in the diagnosis of CFS. In fact, many researchers held the belief that the underlying cause of CFS was a primary sleep disorder. However, even in the 2 studies mentioned, not all patients with CFS defining symptoms had underlying sleep disorders.
In 1994, the Centers for Disease Control and Prevention adopted and revised the case definition and guidelines for CFS. This new definition (also known as the Fukuda criteria) reduced and relaxed the number of diagnostic criteria symptoms required to diagnose CFS. Importantly, this new definition excluded comorbid sleep disorders such as obstructive sleep apnea and narcolepsy.
The question as to whether the presence of primary sleep disorder in a patient with symptoms of CFS should be used as an exclusion criterion for the diagnosis of CFS or be treated as a comorbidity was studied by Libman et al in 2009. This study argued that sleep disordered breathing did not affect the core symptoms of CFS (4). They found that although there was a 68% prevalence of sleep disorder breathing in their group, CFS patients with and without sleep disordered breathing did not differ in subjective sleep variables, psychopathology indexes of anxiety and depression, and quality of life scores as assessed through questionnaires.
Post 1994, Le Bon et al sought to answer the question: “How significant are primary sleep disorders and sleepiness in the chronic fatigue syndrome”. In their study published in 2000, they found that 46% of 46 CFS patients had criteria defining obstructive sleep apnea (apnea-hypopnea index >5). 5% had periodic limb movement disorder. They performed 2 nights of polysomnogram and multiple sleep latency tests on these subjects with controls. Objective and subjective sleepiness did not corelate with the diagnosis of CFS. It was also not correlated in patients with CFS and a primary sleep disorder. This meant that sleepiness was not solely attributable to the primary sleep disorder. Further, 54% of CFS patients had no primary sleep disorder and 69% of CFS patients had no sleepiness. CFS patients with coexisting primary sleep disorder could also not be distinguished from those who had a primary sleep disorder using clinical measures of anxiety, depression, somatisation, physical or mental fatigue or functional status impairment. Therefore the authors concluded that the symptoms of CFS are not due to comorbid primary sleep disorders (5).
If a primary sleep disorder such as sleep apnea was the causation of the symptoms of fatigue seen in CFS, then treating the sleep apnea should resolve the symptoms. Libman et al showed that continuous nasal positive airway pressure therapy in CSF patients with comorbid obstructive sleep apnea did improve symptoms of daytime sleepiness but the symptom scores of fatigue did not differ between the groups who were compliant as compared to those who were not (4). Therefore, there was no resolution of fatigue symptoms after effective treatment of the sleep apnea.
These studies indicate that CFS is unlikely to be due to an underlying primary sleep disorder. A fact recognized in the guidelines proposed by the Fukuda criteria.
A traditional primary sleep disorder
We know consider the possibility that CFS is of itself a primary sleep disorder. If CFS is a primary sleep disorder, there would be detectable changes in the macrostructure and microstructure of sleep compared to normal controls. Polysomnographic studies have been performed in CFS patients looking at different aspects of sleep structure, including traditional sleep architecture parameters such as total sleep time, sleep efficiency, sleep stage composition. We will look at the primary research papers that have compared these sleep parameters in criteria diagnosed CFS patients with normal controls.
Sharpley et al in 1997 studied 20 CSF patients and 20 controls using a 1-night home-based polysomnography and found that CFS patients reported poor quality sleep that was nonrestorative and associated with daytime napping. CFS patients had reduced sleep efficiency, increased time in bed and time awake after sleep onset. However, there were no differences in measured total sleep time (6).
Watson et al in 2003 studied 22 twin pairs discordant for CFS. They performed 2 nights of polysomnography with an administered sleep disorders questionnaire. They found that the CFS twin reported increased insomnia symptoms and poor sleep ratings. However, there was no difference in polysomnographic measures of sleep except for an increase in the amount of REM sleep in the CFS twin (7).
Ball et al in 2004 also looked at 22 monozygotic twin pairs discordant for CFS. 2 nights of polysomnography were performed, and they also found an increase in percentage of REM as well as slow wave sleep in the CFS twins. However, no other objective differences in polysomnographic measurements were seen in the other parameters of sleep architecture (8).
Reeves et al in 2006 looked at 43 CFS patients and 43 healthy controls using 2 nights of polysomnography as well as multiple sleep latency testing (MSLT). They found no difference in both measures of sleep (9).
Majer et al in 2007 studied 35 CFS subjects and 40 normal controls using 2 nights of polysomnography and multiple sleep latency testing. They also applied a subjective sleep quality questionnaire. CFS patients reported poorer quality sleep but the authors found no objective differences in MSLT or polysomnographic parameters between the groups (10).
Neu et al in 2007 looked at 28 CFS patients with 28 age and gender controlled normal controls. They used the Pittsburgh Sleep Quality Index (PSQI), fatigue severity score and polysomnography. Again, the CFS group reported poorer sleep on the PSQI but there was no difference in the polysomnographic sleep parameters between the groups (11).
LeBon et al in 2007 studied 3 populations of patients. There were 28 CFS patients, 27 obstructive sleep apnea patients and 27 healthy controls. They looked at 2 nights of polysomnography as well as NREM sleep distribution. They found that CFS patients had an increase in percentage of NREM sleep and increased ratios of slow wave sleep to light sleep compared to the other 2 groups (12). A similar study was performed in 2009 by Neu et al. They studied 32 CFS patients, 30 obstructive sleep apnea patients and 14 controls. Using 2 nights of polysomnography and analyzing NREM proportions and ratios, they also found an increase in the percentage of NREM sleep and increased ratios of slow wave sleep to light sleep in the CFS group compared to the other 2 groups (17).
Armitage et al in 2007 studied 13 monozygotic twins discordant for CFS. They conducted polysomnographic studies over 3 nights and used power spectral analysis. The first 2 nights were adaptation and baseline studies. On the 3rd night a sleep delay of 4 hours was applied followed by recovery sleep of normal length. They found that there were no differences in polysomnographic measures between the CFS and control groups during baseline sleep. However, they noted a reduction of slow wave activity (delta frequency power density) in the CFS group after the sleep delay challenge. They concluded that CFS may impair sleep homeostasis and sleep propensity (13).
Kishi et al in 2008 conducted an all-female study on 22 CFS patients and 22 controls. They performed overnight polysomnography with sleep stage transition analysis. They found that there was a relative reduced frequency of REM to NREM transitions in CFS subjects. There was also a significant increase in transitions from REM and stage 1 sleep to wake stages. This led to a disruption of the normal continuation of sleep in stage 1 and REM (14).
In 2009, Armitage et al performed another study using monozygotic CFS discordant twins. 14 twins were studied using 2 nights of polysomnography and power spectral analysis. This time no sleep challenge was applied. They found no differences in sleep micro or macro architecture. They concluded that sleep measures were not able to explain the fatigue found in CFS patients (15).
Decker et al in 2009 studied 35 CFS patients and 40 healthy controls using 2 nights of polysomnography with fast Fournier transform (a method of power spectral analysis). They found that CFS patients exhibited reduced delta power during slow wave sleep but there was an increase seen in stage 1 and REM sleep compared to controls (16).
As demonstrated by the studies stated above, there are no consistent differences seen in the sleep parameters measured in polysomnography between CFS patients and healthy controls. Whatever differences that are seen, are variable and non-specific. These variable differences can be explained by the different methodologies employed in the various studies. Some studies used home base polysomnography, and some used only 1 night of polysomnography versus multiple. LeBon et al in 2003 reported that there was a significant first night effect seen in CFS patients with no comorbid sleep disorder (18). Therefore, studies that conducted only 1 night of polysomnography might not have demonstrated an accurate representation of polysomnographic data seen in CFS patients. Many of the abovementioned studies also demonstrate self-reported poor or disturbed sleep in CFS patients. Indeed, there have been studies performed by Morriss et al (3), Fischler et al (19) and Stores et al (20) that have shown a reduction of sleep efficiency and an increase in the number and duration of awakenings during sleep in CFS patients. However, Reeves et al found that when an adaptation night was applied before main data recording, there were no sleep efficiency differences seen between CFS patients and their controls (9).
In an attempt to obtain more reflective data, actigraphy studies have been performed looking at total sleep time, sleep efficiency and sleep onset latency of CFS patients using their normal sleep routines and in their own homes. Ohinata et al in 2008 studied children with CFS and reported actigraphy evidence of disturbed sleep/wake patterns and disturbed sleep on these children (20). More such studies are needed to establish the consistency of these findings. Actigraphy has mostly been used to determine if there are circadian rhythm disturbances and diurnal activity pattern differences in CFS patients compared to normal controls (22). However, more research will be needed as the current findings have no consistent observations (23) (24).
Alpha-delta sleep is an atypical and abnormal electroencephalographic (EEG) pattern seen during NREM sleep. It is characterized by the appearance of prominent alpha activity in NREM sleep and has been postulated to be an intrusion of wakefulness during sleep. This pattern could explain the symptoms of nonrestorative sleep and fatigue. The appearance of alpha-delta sleep during slow wave sleep has been reported in CFS patients (25) (26) in early literature. However, subsequent studies have shown that alpha-delta sleep was found to not be associated with nonrestorative sleep (27). It was also seen in subjects with other disorders that was not associated with CFS and who did not complain of fatigue (28).
As mentioned earlier, slow wave activity and the amount of slow wave sleep was used by Armitage et al to measure differences in sleep homeostasis and sleep propensity in CFS patients (13). Slow wave activity is determined by prior periods of wakefulness. Following sleep deprivation and sleep restriction, the build-up of sleep propensity or pressure leads to an increase in slow wave activity and slow wave sleep. These parameters are therefore used as a measure of sleep homeostasis. In this study, the conclusion drawn by the authors were that CFS was associated with impaired sleep homeostasis and sleep drive. Whether this represents grounds for a primary sleep disorder is unclear. However, sleep regulation and slow wave activity is also affected by other physiological processes. One example is that of cytokine systems. Cytokine systems are involved in sleep regulation with proinflammatory cytokines increasing slow wave sleep as well as slow wave activity (29). The mechanism by which CFS affects slow wave sleep and slow wave activity might be mediated through proinflammatory cytokines and systemic inflammation seen in CFS. More research in this area is needed to establish this theory.
REM sleep has not consistently shown to be different in CFS groups as compared to controls. While some studies have shown a reduction in REM sleep (20) (30) in CFS subjects, other studies have shown an increase in REM sleep relative to controls (26) (7) (8). Reeves et al showed no difference in REM sleep latency in CFS subjects (9). Armitage et al found no differences in REM sleep between monozygotic twins discordant for CFS (15). Therefore, on the weight of the evidence, no REM difference are observed in CFS patients compared to normal controls.
To summarize the above findings, there appears to be few consistent differences seen in the polysomnographic measures of sleep architecture in CFS patients and normal individuals. There seems to be limited evidence that slow wave sleep and slow wave activity may be different in CFS populations, but more studies are required to substantiate this finding. The clearest evidence can be found in the 4 monozygotic twin studies mentioned above. These studies have reduced genetic and environmental confounders. The finding that CFS twins have slow wave sleep and REM sleep differences from their unaffected twins are not consistent across these studies. Therefore, there is no discernable objective sleep disturbance that is seen consistently in all CFS patients. There seems not to be abnormal sleep or abnormal sleep measures in CFS individuals to account for the subjective symptoms of fatigue and nonrestorative sleep. In summary, studies utilizing traditional polysomnographic parameters has not found any evidence that CFS is a primary sleep disorder.
Sleep microstructure
We have looked mainly at traditional polysomnographic measures of sleep and concluded that these measures do not consistently show a difference in CFS patients. Perhaps these macrostructure measures are not capable of discriminating the abnormalities in sleep exhibited in CFS. We will now examine the microstructure measures of sleep in relation to CFS.
As mentioned above, Kishi et al (14) demonstrated the finding of disruption of normal sleep stage transitions. They found that there was a relative reduced frequency of REM to NREM transition in CFS subjects. There was also a significant increase in transitions from REM and stage 1 sleep to wake stages which led to a disruption of the normal continuation of sleep in stage 1 and REM. This disruption of the normal transition of sleep in stage 1 and REM may contribute to the symptoms of nonrestorative sleep and fatigue in CFS. Other studies have also shown differences in stage shifts and stage transitions in CFS patients (19). More research is needed to establish a causal link between these findings and CFS.
Another microstructural measure of sleep is power spectral analysis of EEG quantification. Power spectral analysis using fast Fournier transform (FFT) has been utilized for the study of sleep in CFS patients (15) (16). Decker at al reported in his study a reduction of delta power in slow wave sleep and an increase in delta power in stage 1 and REM sleep seen in 35 CFs patients as compared to normal controls. They also found alpha power reductions in stage 2 sleep, slow wave sleep but most notably during REM sleep. The finding of reduced delta power during slow wave sleep is consistent with the findings in Armitage et al’s 2007 (13) study of reduced slow wave sleep and slow wave activity in CFS twins following a sleep delay challenge. Ironically however, in 2009 Armitage et al found no difference in their FFT EEG analysis of 14 monozygotic twins discordant of CFS (15). Once again, more research is needed to study this aspect of sleep microstructure in CFS patients.
Another postulated mechanism of nonrestorative sleep in CFS is the presence of microarousals not evident on traditional polysomnographic studies (such as the arousal index). This has been supported by studies that have shown that more arousals may exist in CFS patients as compared to their normal controls (17) (31). Cyclic alternating pattern (CAP) is a measure of sleep instability through EEG analysis (32). CAP measures have been used in insomnia and has shown correlation with subjective scores of sleep quality (33). Guilleminault et al (34) in 2006 performed CAP analysis on 14 patients with chronic fatigue without sleepiness and found an increase in CAP rate compared to controls. However, these were not criteria diagnosed CFS patients and a number of these subjects also has flow limitations suggestive of sleep disordered breathing. Once again, more research is needed to evaluate CAP differences in CFS patients.
There seems to be some preliminary evidence of the utility of microstructural measures of sleep in CFS patients beyond traditional polysomnographic measure. However, at this point, there is still little evidence from these studies to indicate that CFS is a sleep disorder.
There are other measures of sleep disturbances that are seen in CFS patients. One of these measures is autonomic activity alterations. This can be measured using heart rate variability. Yamamoto et al in 2003 demonstrated that there was a difference in the heart rate variability in CFS subjects compared to normal controls when an orthostatic challenge was applied via a tilt test (35). These autonomic changes seen in CFS patients during the wakefulness can also be observed during sleep (38). During sleep, the autonomic nervous system in normal healthy subjects demonstrate well characterized patterns of alterations during sleep onset and during different sleep stages (36) (37). Comparative studies on CFS patients have shown a decrease in parasympathetic activity during sleep as evidenced by the presence of significantly reduced heart rate variability (38) (39). A reduction of heart rate variability is currently viewed as being due to a state of autonomic hypervigilance. Burton et al in 2010 assessed 20 CFS patients with 20 normal subjects with heart rate monitoring and subjective sleepiness measures. Using multiple regression analysis, they found that low heart rate variability correlated with sleep quality. They proposed that CFS patients had a persistent state of nocturnal parasympathetic hypervigilance (40).
Another measure of autonomic activity during sleep is that of cardiopulmonary coupling. It has been used as an electrocardiographic measure of sleep stability and quality (41). Using heart rate and respiratory dynamics measurements during sleep, a spectrogram of cardiopulmonary coupling is created. High frequency cardiopulmonary coupling is indicative of high sleep stability and low frequency cardiopulmonary coupling is indicative of low sleep stability. Cardiopulmonary coupling has been used in determining sleep stability in patients with sleep disorders (41) and depression (42). Cunnington et al published in 2011 that there was a difference in cardiopulmonary coupling seen in CFS patients exhibited by a decrease in high frequency coupling and an increase in low frequency coupling indicating reduced sleep stability and quality (43). The use of autonomic activity measures during sleep could possibly uncover a pathophysiological basis for nonrestorative sleep and fatigue seen in CFS patients.
Discussion
One of the diagnostic components of CFS is the presence of nonrestorative sleep. Although this component is not mandatory for the diagnosis of the disease, it implies that there is the presence of disrupted or dysfunctional sleep. However, this relationship has not been easy to prove. Sleep in CFS may then be disrupted either due to an undetected primary sleep disorder. Current evidence shows that although primary sleep disorders may exist as a comorbid condition, CFS exists as a separate clinical entity. Patients who have suspected CFS should be routinely screened for primary sleep disorders. In the presence of a primary sleep disorder, criteria defining CSF cannot be excluded unless there is resolution of the symptoms after treatment of the primary sleep disorder. Therefore, CFS symptoms are not due to a coexisting primary sleep disorder.
Is CFS then a primary sleep disorder. There is currently no polysomnographic evidence of hallmark or disease defining changes seen in CFS patients. There are no consistent patterns seen even in studies comparing monozygotic twins that are discordant for the disease. The idea that traditional polysomnographic measures might not be subtle enough to detect changes in CFS patients have led to microstructural measures such as cyclic alternating pattern, FTT and sleep stage transitions being used. However, even with these tools, there is again no consistent evidence to demonstrate that CFS is a primary sleep disorder in of itself. As for the autonomic changes seen in CFS patients, these exist during wake as well and are unlikely to be caused by the initiation of sleep.
Future research
I would like to suggest some areas for future research. Firstly, randomized controlled interventional trials are needed to determine if primary sleep disorders should be considered an exclusion criterion or a comorbid condition for CFS. Secondly, more work should be done to differentiate the symptoms of fatigue and sleepiness. Objective measures of fatigue are currently unavailable. Thirdly, interventions currently known to improve symptoms for CFS such as cognitive behavioral therapy and graded exercise therapy should be studied in relation to objective assessments of sleep before and after treatment. Fourthly, further studies into sleep homeostasis and slow wave activity is needed to establish the findings of earlier studies. Fifthly, continuing microstructural studies on CFS patients should be performed to elucidate a possible sleep pathogenesis for CFS.
Conclusions:
Although there is no conclusive evidence to support the statement that CFS is a sleep disorder, there remain many unanswered questions regarding the disease and the basis for the symptoms of sleep disturbance and nonrestorative sleep seen in this disease. There exists preliminary evidence that sleep instability, sleep stage transitions, sleep homeostasis and altered autonomic activity during sleep may be responsible for the subjective symptoms of sleep disturbance and nonrestorative sleep. Further research is needed.
References:
Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. The chronic fatigue syndrome: a comprehensive approach to its definition and study. Ann of Intern Med 1994 Dec 15;121(12):953e9.
Krupp LB, Jandorf L, Coyle PK, Mendelson WB. Sleep disturbance in chronic fatigue syndrome. J Psychosom Res 1993;37:325-31
Morriss RK, Sharpe M, Sharpley AL, Cowen PJ, Hawton K, Morris J. Abnormalities of sleep in patients with the chronic fatigue syndrome. BMJ 1993;306:1161-4.
Libman E, Creti L, Baltzan M, Rizzo D, Fichten CS, Bailes S. Sleep apnea and psychological functioning in chronic fatigue syndrome. J Health Psychol 2009;14:1251-67
Le Bon O, Fischler B, Hoffmann G, et al. How significant are primary sleep disorders and sleepiness in the chronic fatigue syndrome? Sleep Res 2000;3:43-8.
Sharpley A, Clements A, Hawton K, Sharpe M. Do patients with pure chronic fatigue syndrome (neurasthenia) have abnormal sleep? Psychosom Med 1997;59:592-6.
Watson NF, Kapur V, Arguelles LM, et al. Comparison of subjective and objective measures of insomnia in monozygotic twins discordant for chronic fatigue syndrome. Sleep 2003;26:324-8
Ball N, Buchwald DS, Schmidt D, Goldberg J, Ashton S, Armitage R. Monozygotic twins discordant for chronic fatigue syndrome: Objective measures of sleep. J Psychosom Res 2004;56:207-12.
Reeves WC, Heim C, Maloney EM, et al. Sleep characteristics of persons with chronic fatigue syndrome and non-fatigued controls: results from a population based study. BMC Neurol 2006;6:41.
Majer M, Jones J, Unger E, et al. Perception versus polysomnographic assessment of sleep in CFS and non-fatigued control subjects: results from a population-based study. BMC Neurol 2007;7:40.
Neu D, Mairesse O, Hoffmann G, et al. Sleep quality perception in the chronic fatigue syndrome: correlations with sleep efficiency, affective symptoms and intensity of fatigue. Neuropsychobiology 2007;56:40-6.
Le Bon O, Neu D, Valente F, Linkowski P. Paradoxical NREMS distribution in “pure” chronic fatigue patients: a comparison with sleep apnea-hypopnea patients and healthy control subjects. J Chronic Fatigue Syndrome 2007;14:2.
Armitage R, Landis C, Hoffmann R, et al. The impact of a 4-hour sleep delay on slow wave activity inb twins discordant for chronic fatigue syndrome. Sleep 2007;30:657-62.
Kishi A, Struzik ZR, Natelson BH, Togo F, Yamamoto Y. Dynamics of sleep stage transitions in healthy humans and patients with chronic fatigue syndrome. Am J Physiol 2008;294:R1980-R7.
Armitage R, Landis C, Hoffmann R, et al. Power spectral analysis of sleep EEG in twins discordant for chronic fatigue syndrome. J Psychosom Res 2009;66:51-7.
Decker M, Tabassum H, Lin J-M, Reeves W. Electroencephalographic correlates of chronic fatigue syndrome. Behav Brain Funct 2009;5:1-8.
Neu D, Cappeliez B, Hoffmann G, Verbanck P, Linkowski P, Le Bon O. High slow-wave sleep and low-light sleep: Chronic fatigue syndrome is not likely to be a primary sleep disorder. J Clin Neurophysiol 2009;26:207-12.
Le Bon O, Minner P, Van Moorsel C, et al. First-night effect in the chronic fatigue syndrome. Psychiatry Res 2003;120:191-9
Fischler B, Le Bon O, Hoffmann G, Cluydts R, Kaufman L, De Meirleir K. Sleep anomalies in the chronic fatigue syndrome. Neuropsychobiology 1997;35:115-22.
Stores G, Fry A, Crawford C. Sleep abnormalities demonstrated by home polysomnography in teenagers with chronic fatigue syndrome. J Psychosom Res 1998;45:85-91.
Ohinata J, Suzuki N, Araki A, Takahashi S, Fujieda K, Tanaka H. Actigraphic assessment of sleep disorders in children with chronic fatigue syndrome. Brain Dev 2008;30:329-33.
Evering RMH, van Weering MGH, Groothuis-Oudshoorn KCGM, VollenbroekHutten MMR. Daily physical activity of patients with the chronic fatigue syndrome: a systematic review. Clin Rehabil 2011;25:112-33.
Tryon WW, Jason L, Frankenberry E, Torres-Harding S. Chronic fatigue syndrome impairs circadian rhythm of activity level. Physiol Behav 2004;82:849-53.
Rahman K, Burton A, Galbraith S, Lloyd AR, Vollmer-Conna U. Sleep-wake behavior in chronic fatigue syndrome. Sleep 2011;34:671-8.
Manu P, Lane TJ, Matthews DA, Castriotta RJ, Watson RK, Abeles M. Alpha-delta sleep in patients with a chief complaint of chronic fatigue. South Med J 1994;87:465-70.
Whelton CL, Salit I, Moldofsky H. Sleep, Epstein-Barr virus infection, musculoskeletal pain, and depressive symptoms in chronic fatigue syndrome. J Rheumatol 1992;19:939.
Stone KC, Taylor DJ, McCrae CS, Kalsekar A, Lichstein KL. Nonrestorative sleep. Sleep Med Rev 2008 Aug;12(4):275e88.
Macfarlane GJ, Moldofsky H. Fibromyalgia and chronic fatigue syndromes. In: Kryger MH, Roth T, Dement CW, editors. Principles and practice of sleep medicine. 5th ed. St. Louis, Mo, USA: Elsevier Saunders; 2011. p. 1422e34.
Madje JA, Krueger JM. Links between the innate immune system and sleep. J Allergy Clin Immunol 2005;116:1188-98.
Togo F, Natelson BH, Cherniack N, FitzGibbons J, Garcon C, Rapoport DM. Sleep structure and sleepiness in chronic fatigue syndrome with or without coexisting fibromyalgia. Arthiritis Res Ther 2008;10:R56.
Neu D, Hoffmann G, Moutrier R, Verbanck P, Linkowski P, Le Bon O. Are patients with chronic fatigue syndrome just ‘tired’ or also ‘sleepy’? J Sleep Res 2008;17:427-31
Terzano MG, Parrino L. Origin and significance of the cyclic alternating pattern (CAP). Sleep Med Rev 2000;4:101-23.
Parrino L, Milioli G, De Paolis F, Grassi A, Terzano MG. Paradoxical insomnia: The role of CAP and arousals in sleep misperception. Sleep Med 2009;10:1139-45
Guilleminault C, Poyares D, Da Rosa A, Kirisoglu C, Almeida T, Lopes MC. Chronic fatigue, unrefreshing sleep and nocturnal polysomnography. Sleep Med 2006;7:513-20.
Yamamoto Y, LaManca JJ, Natelson BH. A measure of heart rate variability is sensitive to orthostatic challenge in women with chronic fatigue syndrome. Exp Biol Med 2003;228:167-74.
Shinar Z, Akselrod S, Dagan Y, Baharav A. Autonomic changes during wake– sleep transition: A heart rate variability based approach. Auton Neurosci 2006;130:17-27
Trinder J, Kleiman J, Carrington M, et al. Autonomic activity during human sleep as a function of time and sleep stage. J Sleep Res 2001;10:253-64.
Boneva RS, Decker MJ, Maloney EM, et al. Higher heart rate and reduced heart rate variability persist during sleep in chronic fatigue syndrome: A population- based study. Auton Neurosci 2007;137:94-101.
Rahman K, Burton A, Galbraith S, Lloyd AR, Vollmer-Conna U. Sleep-wake be- havior in chronic fatigue syndrome. Sleep 2011;34:671-8.
Burton A, Rahman K, Kadota Y, Lloyd A, Vollmer-Conna U. Reduced heart rate variability predicts poor sleep quality in a case–control study of chronic fatigue syndrome. Exp Brain Res 2010;204:71-8
Thomas RJ, Mietus JE, Peng CK, Goldberger AL. An electrocardiogram- based technique to assess cardiopulmonary coupling during sleep. Sleep 2005;28:1151-61.
Yang AC, Yang C-H, Hong C-J, et al. Sleep state instabilities in major depressive disorder: Detection and quantification with electrocardiogram-based cardiopul- monary coupling analysis. Psychophysiol 2011;48:285-91.
Cunnington D, Buccella D, Bastiampillai S, Swieca J. Sleep architecture and sleep stability in chronic fatigue syndrome. J Sleep Res 2011;20:25.