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Sleep Medicine 7 (2006) 513–520
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Original article
Chronic fatigue, unrefreshing sleep and nocturnal polysomnography
Christian Guilleminault a,*, Dalva Poyares a,b, Agostinho da Rosa b, Ceyda Kirisoglu a,
Tatiana Almeida b, Maria Cecilia Lopes a
a
Stanford University Sleep Disorders Clinic, 401 Quarry road, suite 3301, Stanford, CA 94305, USA
Department of Psychobiology, Sleep Institute, Federal University of Sao Paulo, Sao Paulo, Brazil
b
Received 2 January 2006; received in revised form 28 February 2006; accepted 6 March 2006
Abstract
Background and purpose: To investigate the complaint of unrefreshing sleep with study of sleep electroencephalogram (EEG) in patients
with chronic fatigue.
Patients and methods: Fourteen successively seen patients (mean age: 41.1 9.8) who complained of chronic fatigue but denied sleepiness and
agreed to participate were compared to 14 controls (33.6G10.2 years) who were monitored during sleep recorded in parallel. After
performing conventional sleep scoring we applied Fast Fourier Transformation (FFT) for the delta 1, delta 2, theta, alpha, sigma 1, sigma 2,
beta EEG frequency bands. The presence of non-rapid eye movement (NREM) sleep instability was studied with calculation of cyclic
alternating pattern (CAP) rate. Two-way analysis of variance (ANOVA) was performed to analyze FFT results and Mann–Whitney U-test to
compare CAP rate in both groups of subjects.
Results: Slow wave sleep (SWS) percentage and sleep efficiency were lower, but there was a significant increase in delta 1 (slow delta)
relative power in the chronic fatigue group when compared to normals (P!0.01). All the other frequency bands were proportionally and
significantly decreased compared to controls. CAP rate was also significantly greater in subjects with chronic fatigue than in normals (PZ
0.04). An increase in respiratory effort and nasal flow limitation were noted with chronic fatigue.
Conclusions: The complaints of chronic fatigue and unrefreshing sleep were associated with an abnormal CAP rate, with increase in slow
delta power spectrum, affirming the presence of an abnormal sleep progression and NREM sleep instability. These specific patterns were
related to subtle, undiagnosed sleep-disordered breathing.
q 2006 Elsevier B.V. All rights reserved.
Keywords: Chronic fatigue; Unrefreshing sleep; Slow wave sleep; Cyclic alternating pattern; Slow delta; Sleep-disordered breathing
1. Introduction
Complaints of chronic fatigue are common in general
medical clinics, and relating the complaint to a specific
medical entity is often difficult. Effort has been made to define
‘Chronic Fatigue Syndrome (CFS)’ to better investigate these
patients. CFS is estimated to affect approximately 0.2–0.7% of
the population in Western countries [1] and up to 800,000
Americans [2]. It is a medically unexplained illness and
represents a socio-economical burden [2]. In association with
the complaint of fatigue, sleep, musculoskeletal and somatic
symptoms [3,4] are the most prevalent symptoms in CFS.
* Corresponding author. Tel.: C1 650 723 6601; fax: C1 650 725 89 10.
E-mail address: [email protected] (C. Guilleminault).
1389-9457/$ - see front matter q 2006 Elsevier B.V. All rights reserved.
doi:10.1016/j.sleep.2006.03.016
Despite these clear symptoms, the pathophysiology underlying the complaint of chronic fatigue, or the so-called
‘chronic fatigue syndrome’ is still unclear. Immune system
activation [5–8], neurocognitive and mental alterations
[4,9,10], evidence of oxidative stress [8,11] and involvement
of hypothalamic–pituitary axes (HPA) have also been
described [1,5,6,12,13]. However, none of these findings are
sufficient to fully explain the symptoms of chronic fatigue.
Even the HPA alterations seem to be multifactorial and are not
the primary cause of CFS. Rather they appear to be a
consequence of the persistence of the symptomatology linked
to CFS [12]. A recent study showed that the most prevalent
complaint among subjects with idiopathic chronic fatigue is
unrefreshing sleep [14]; however, using a Sleep Disorders
Questionnaireq (SDQ), the study did not find any increased
association between the complaint of chronic fatigue and
excessive daytime somnolence or sleep apnea. The reported
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C. Guilleminault et al. / Sleep Medicine 7 (2006) 513–520
prevalence of an association between an undiagnosed primary
sleep disorder and the diagnosis of CFS varies between 0 and
50% [14,15]. Fisher [15] and Unger [14] emphasized the
importance of excluding a treatable primary sleep disorder
when evaluating patients with the complaint of chronic
fatigue. Furthermore, clear controversies exist regarding the
presence of specific abnormal sleep patterns in patients
presenting with unexplained chronic fatigue. Several studies
have described a sleep electroencephalogram (EEG) pattern
known as ‘alpha–delta’ sleep (better called ‘delta–alpha’
based on successive appearance of the EEG frequencies) in
patients suffering from CFS [16,17]. However, many believe
that the ‘delta–alpha’ sleep pattern is not a specific marker of
CFS [18] but instead is a non-specific pattern [19], and its
association with CFS has been questioned [20,21].
Patients seen in a subdivision of rheumatology dealing
with the complaint of unexplained chronic fatigue were
regularly referred for objective investigation of their sleep
once all other possible etiologies for their complaint of
chronic fatigue had been ruled out. Clinical sleep evaluation
obtained for these patients did not reveal any abnormalities
that could explain their subjective complaints. The only
consistent finding in the polysomnograph recordings have
been a decrease in slow wave sleep (SWS), despite the fact
that an increase in stage 4 NREM sleep has been mentioned
in at least one report [22], but this finding is non-specific.
We have performed several investigations using the cyclic
alternating pattern (CAP) scoring system in other patients
with abnormal SWS findings. Based on these preliminary
clinical findings of the other patients with abnormal slow
wave sleep, this study was designed as a prospective
investigation of the potential relationship between the
complaint of chronic fatigue, unrefreshing sleep and
abnormal slow wave sleep (SWS). The study was based
on one night of polysomnography and specifically evaluated
SWS. Prior to this study we performed several investigations using the CAP scoring system in patients with
abnormal SWS findings. The goal of this study was to
compare the CAP rate seen in patients with fatigue to
matched controls and to explore the relationship between
CAP pattern and quantitative EEG measured during the
same night as one of the central EEG derivations (C4/A1).
This report presents the results of this investigation on
subjects referred to the sleep clinic with an unexplained
complaint of chronic fatigue and unrefreshing sleep, who
agreed to undergo all steps of the investigation. All who
enrolled signed informed consent forms for anonymous
usage of their data for research.
2. Methods
2.1. Subjects
Fourteen patients (3 men and 11 women), with a mean
age of 41.1G9.8, who had been evaluated by the specialized
rheumatologic clinic and found to have unexplained chronic
fatigue, were referred for sleep investigation. They were
compared to 14 controls (3 men and 11 women) aged 33.6G
10.2-year-old (PZ0.06) recruited from the community; the
controls were professionals and had a socio-economic
background that was similar to those presented by the
patients. Controls were matched for gender and age as
closely as possible. The need to monitor patients and
controls nearly simultaneously to avoid effect of seasonal
change with variable light intensity, time change, respiratory allergy, school schedule for children, etc. was in part
responsible for a small discrepancy in age between groups.
Controls were excluded if they had a complaint of chronic
fatigue or suffered from a sleep disorder. Additionally,
controls had to report that they were in good health and took
no medications, and sign the informed consent form.
2.2. Evaluation
Patients and controls underwent the same evaluation.
They all filled out standard questionnaires, including the
Epworth sleepiness scale (ESS) [23] and the fatigue severity
scale (FFS) [23]. The former is a scale with eight questions
and four possible responses evaluating degree of sleepiness
in specific situations. The latter is a validated fatigue scale
designed to assess functional outcomes related to fatigue. It
is a 9-item scale scored from 1 to 7, where 1 indicates no
impairment and 7 indicates severe impairment. Its clinical
utility, reliability and validation criteria have been reported.
Higher scores suggest greater fatigue [23]. Fatigue in CFS
patients and in disorders of sleep continuity have been
associated with increased scores on the FFS [24,25]. Sleep
logs indicating bed time, wake time, and sleep interruption
were obtained for 15 days prior to the recording and
included 2 weekend or days off each week. Patients were
given pre-stamped envelopes and were asked to mail their
sleep logs every 3 days.
Medical data obtained from evaluation at the chronic
fatigue/fibromyalgia clinic in the rheumatology division
was reviewed, and blood tests were repeated if they had
been obtained more than 2 months prior to the sleep clinic
investigation. All patients and controls had normal blood
tests, and no evidence of infections or immunologic
disorders.
2.3. PSG recording
Every subject went to bed at the usual bedtime and had a
minimum of 7 1/2 h of PSG recordings. The following sleep
variables were collected and stored using a dedicated
computerized 32-channel sleep system with a sampling rate
of 256 Hz per channel: a total of 20 EEG leads, two electrooculogram (EOG) channels, two electromyogram (EMG)
channels (chin and both legs), and an electrocardiogram
(ECG) channel. Respiration was monitored with a nasal
cannula-pressure transducer system, mouth thermocouple,
C. Guilleminault et al. / Sleep Medicine 7 (2006) 513–520
two channels for chest and abdominal efforts with calibrated
inductive respiratory plethysmography, esophageal pressure
(Pes), neck microphone, and pulse oximetry with a
Nellcore (Alameda, CA, USA) oximeter. Standard evening
and morning questionnaires were filled out before lights-out
time and after lights-on.
2.4. EEG fast Fourier transformation (FFT) analysis
Once visual scoring had been performed, EEG spectral
analysis was applied on the C4-A1 channel, with a sampling
rate of 256 Hz per channel. Visual inspection eliminated
movement artifacts and awakening segments longer than
10 s. Absolute and relative power was assessed for each
classical EEG frequency bands, defined by delta 1 (0.25–
2 Hz), delta 2 (2.25–4 Hz), theta (4.25–8) Hz, alpha (8.25–
12) Hz, sigma 1 (12.25–14), sigma 2 (14.25–16), and beta
(16–20). Results were given in relative power. The FFTs
were performed on averaged, non-overlapping, four-second
windows, with a Hanning window, free of artifacts and
arousals O10 s of EEG segments during the total PSG
recording. The window results were averaged to obtain a 60s value, and analysis covered the total sleep.
2.5. Data analysis
2.5.1. Scoring criteria
All records were to be scored following the international
sleep scoring criteria of Rechtshaffen and Kales [26]. Short
EEG arousals and respiratory events were also defined using
the American Sleep Disorders Association (ASDA) and
American Academy of Sleep Medicine (AASM) recommendations [27,28]. Monitoring of respiratory variables
allowed recognition and typification of sleep apneas and
hypopneas. A hypopnea is defined as a decrease of nasal
cannula pressure transducer signal by at least 30%
associated with an oxygen drop of 3% or an EEG arousal
of 3 s or longer. Flow limitation is defined as a drop of nasal
flow compared to prior recording between 3 and 30% with a
‘flattening’ of the curve as described, for at least four
breaths, associated with changes in Pes. An abnormal
respiratory effort was identified with the presence of Pes
crescendos or continuous sustained effort, terminated by an
abrupt return to normal effort which is referred to as a Pes
reversal [29]. Visual scoring of sleep stages and recognition
of respiratory events were performed blindly on both
patients and controls. This scoring process also included
identification of all sleep phenomena such as body or leg
movements. The different respiratory criteria allowed
scoring of an apnea–hypopnea index (AHI) based on the
calculation of apneas and hypopneas per hour of sleep, and a
respiratory disturbance index (RDI) with integration of flow
limitation events, respiratory event-related arousal, and Pes
events terminated by a Pes reversal [29].
515
2.5.2. Cyclic alternating pattern (CAP)
Automatic detection of CAP [30,31] was applied to C4A1 and visually corrected, based on the international atlas
rules [32]. A CAP [31,33] is formed by electrocortical
events indicated by periodic EEG activity occurring during
non-rapid eye movement (NREM) sleep, and characterized
by transitory events that recur at regular intervals in the
range of seconds during NREM sleep. These events are
clearly distinct from the background EEG rhythm as abrupt
frequency shifts or amplitude changes. Two phases (A and
B) are present that are part of a CAP cycle and recur within
2–60 s. When none of the phases (A and B) are identifiable,
sleep has reached a new stable state [32,33]. Phase A is
identified by transient events typically observed in NREM
sleep. It includes EEG patterns of higher voltage, slower
frequency and faster-lower voltage than the background
EEG (with an increase in amplitude by at least 1/3 compared
to the background EEG). Phase A has been subdivided into
three subtypes based on the presence in association with
high amplitude slow waves (delta waves) and the presence
of faster and lower amplitude activity that can mimic for
phase A3 what has been described as delta–alpha EEG
pattern. Phase B, which follows, is defined by an EEG
pattern of less EEG amplitude with EEG figures of stages 1,
2 NREM sleep. If there is difficulty reaching a new stable
state during NREM sleep passing from wake to REM sleep,
the CAP rate will increase with the greater the number of
cycles (i.e. the greater the number of Phases A and B, or
CAP rate) signifying a greater instability of NREM sleep.
Phase A was analyzed as a whole; i.e. subtypes of phase
A were not considered in this study. Main sleep EEG
patterns recognized in this detection were delta bursts, also
called delta-cluster, sequences of K-complexes, vertex
sharp wave, and polyphasic bursts of slow and fast
frequencies. The parameters analyzed were CAP rate
(time occupied by CAP sequences over total NREM sleep
time expressed in percent) and CAP time.
2.6. Statistical analysis
One-way analysis of variance (ANOVA) was performed
to compare sleep stages and demographic parameters
between fatigue and controls. Comparison of relative and
absolute power between patients and controls was done with
t-test, and comparison of CAP rate and CAP time with
Mann–Whitney U-test (after Kolmogorov–Smirnov test).
3. Results
3.1. Patient history, subjective complaints, sleep logs,
and scales
Social variables: all patients and controls worked outside
of the home. Three women in the patient group and four in
the controls worked part-time only. Three chronic fatigue
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and three control subjects had no children. There was a
difference between the two groups in the age of the patients’
children, with the youngest child in the chronic fatigue
group being 9-year-old compared to the youngest child
being 2-year-old in the control group. Overall the youngest
child in the family tended to be younger in controls than in
chronic fatigue patients, despite the fact that if all ages of
children were tabulated no significant difference between
groups could be shown, as large SD existed.
Chronic fatigue patients had complaints of continuous
fatigue during the day, which impaired their social and
professional life and had been present for a mean of 6G4.3
years (range 2–12 years). This fatigue was present upon
awakening and was associated with a feeling of unrefreshing sleep. Fatigue was present on weekdays as well as
weekends and did not diminish after a longer time was spent
in bed, which usually occurred on weekends.
On their 15-day sleep logs, chronic fatigue patients
reported 7.38 hG24 min of time in bed during weekdays
but spent as much as 12 h in bed on weekends. The reported
time in bed during weekdays was not significantly different
in chronic fatigue patients than controls (7.14 hG35 min).
However, on weekends, time spent in bed was much greater
in patients with fatigue than in controls (mean difference on
weekend: 190G29 min). Eleven chronic fatigue subjects
had a complaint of nocturnal disrupted sleep, and sleep logs
indicated a mean of 1.8G.9 episodes of awakening during
sleep. The mean duration of these reported awakenings was
14G9 min. None of the chronic fatigue patients considered
themselves an ‘insomniac’, but six of them mentioned
muscle pain at awakening. Four had nocturia, but related it
to a prior awakening.
With regard to their complaint of fatigue, 12 chronic
fatigue patients reported difficulty concentrating during the
daytime and at work. Seven of them believed that their
fatigue was responsible for limitation in job performance,
and all reported great curtailment in social activities due to
their symptoms. None of the patients smoked and 8/14
reported they did not consume alcohol. The remaining six
patients stated they consumed alcohol only on social
occasions, with one alcoholic beverage every 4–6 weeks.
Caffeine intake was variable but always limited to morning
hours and was usually limited to 1–2 cups of coffee or tea.
Chronic fatigue patients had all previously consulted
internists in search of a solution for their problems, and had
tried to live as ‘healthy’ as possible with regular schedules
to improve their condition. None of the patients took any
medications for the prior 10 months. Chronic fatigue
patients who had tried pharmacotherapy in the past
(10/14) had used polyvitamins, or specific vitamin
supplements, preparation such as ATP, 5-HTP, calcium or
magnesium supplements. No benefit was derived from any
of these therapies and all had been discontinued. In addition,
6/14 had previously been placed on a low dosage of a
Tricyclics or selective serotonin reuptake inhibitors (SSRI)
from their general practitioners for symptomatic treatment.
Two men had undergone treatment with a low dosage of
testosterone for unclear reasons, as their endocrinologic
evaluation was normal. Despite the variety of pharmaceutical agents, none of these medications had any positive
effect on symptoms. As mentioned, all medication intakes
had been stopped many months before the referral.
Krupp et al.’s FSS scores [24] were 4.9G1.2 and 2.1G
0.8, P!0.01 for fatigue patients versus controls, indicating
the presence of abnormal fatigue in chronic fatigue patients.
Though two women with chronic fatigue had signs and
symptoms for fibromyalgia, they did not fulfill the
examination criteria for this condition.
At clinical evaluation, body mass index (BMI) was
similar for both groups (24.6G2.4; 22.1G4.5 kg/m2,
fatigue and controls, respectively; PZ0.14). No explanation
for chronic fatigue had been found after in-depth evaluations at the rheumatologic clinic, which included normal
endocrine and immunological tests.
3.2. Sleep, sleep stages and, respiratory parameters
Pre- and post-sleep questionnaires obtained in the
laboratory indicated that all chronic fatigue patients felt
that their day had been of poor quality, with constant
fatigue, which impaired their professional activities. In the
morning, these patients reported the presence of awakenings
which matched polysomnography findings. In addition, they
reported very unrefreshing sleep with significant tiredness
which was equal or greater to what they felt at the previous
bedtime. Despite the impression of their sleep being of poor
quality, none complained of ‘insomnia’.
Sleep stage analyses: as shown in Table 1, patients with
complaint of chronic fatigue had a significantly lower
percentage of Stages 3, 4 NREM sleep, lower sleep
efficiency, and a similar AHI (0.9G0.6 versus 0.7G0.9,
pZns) but higher RDI compared to normal subjects
(Table 1).
Table 1
Main PSG data and Epworth sleepiness score for fatigue and control
subjects
PSG parameters
RDI
Lowest O2
Saturation
TST (min)
Sleep efficiency
REM sleep (%)
Stages 3, 4
NREM sleep (%)
Arousal index/
hour of sleep
Epworth sleepiness scale
Fatigue
(nZ14)
Controls
(nZ14)
F(1,27)
P
4.7G3.3a
92.6G2.8
1.0G1.4
92.0G2.1
11.8
0.34
0.01
n.s.
398.8G72
84.1G9.4a
17.2G6.1
13.9G7.2a
377.2G75.5
90.6G4.6
19.4G4.7
25.4G6.7
2.8
4.2
0.88
15.1
n.s.
0.06
n.s.
0.01
9.5G3.8
9.3G5.2
0.006
n.s.
10.3G4.7
8.9G2.4
0.37
n.s.
RDI, respiratory disturbance index; TST, total sleep time; Fatigue: chronic
fatigue patients; Number of subject involved: 28.
a
One-way ANOVA.
C. Guilleminault et al. / Sleep Medicine 7 (2006) 513–520
Table 2
CAP parameters and NREM sleep duration for chronic fatigue and control
subjects
CAP parameters
Fatigue
(nZ14)
CAP time
(min)
CAP rate
171.1G89.3a
Slow wave
sleep (min)
NREM
sleep (min)
Controls
(nZ14)
U
P
91.3G97.6
39
0.04
50.9G32.0a
27.0G26.2
55.43G28.7b
95.8G25.3
37.5
F(1,26)
15.1
0.04
P
0.01
331.5G68.3
304.0G46.3
1.4
n.s.
CAP, cyclic alternating pattern; fatigue: chronic fatigue patients; total
number of subjects, 28.
a
Mann–Whitney U-test.
b
One-way ANOVA.
3.3. CAP parameters
CAP time and CAP rate were significantly higher in
chronic fatigue patients despite similar NREM sleep time
(as measured in minutes) in both subject groups. (Table 2)
Further phase A analyses were not performed.
3.4. Sleep EEG spectral power frequencies
There was a significant increase in slow delta (delta 1)
power in chronic fatigue patients compared to normal
controls as shown in Tables 3A and 3B. This was found
when considering relative and absolute power (Tables 3A
and 3B and Fig. 1).
4. Discussion
We studied subjects complaining of unexplained fatigue
and unrefreshing sleep lasting for several years. In many
reports, patients with ‘chronic fatigue syndrome’ have
normal sleep including sleep stage distribution by polysomnography despite their sleep complaints [34]. Others
have reported sleep stage changes, with increase in stage 2
NREM sleep and decreases or increases in slow wave sleep
[22,35,36]. A sleep pattern called ‘delta–alpha’ has also been
Table 3A
Sleep EEG frequency bands relative power
EEG frequencies
Fatigue (nZ13)
Controls (nZ14)
P
Delta 1 (%)
Delta 2 (%)
Theta (%)
Alpha (%)
Sigma 1 (%)
Sigma 2 (%)
Beta (%)
0.74G0.14a
0.15G0.07a
0.07G0.04a
0.02G0.03a
0.01G0.02a
0.01G0.01a
0.003G0.009a
0.47G0.18
0.26G0.09
0.12G0.04
0.06G0.03
0.04G0.03
0.03G0.09
0.01G0.01
!0.01
!0.01
!0.01
!0.01
!0.01
!0.01
!0.01
t-Test; Total number of subjects, nZ27 (one CD-ROM with recording data
unreadable).
a
Significantly different with t-Test analysis.
517
Table 3B
Sleep EEG frequency bands absolute power (mV2)
EEG frequencies
Delta 1
Delta 2
Theta
Alpha
Sigma 1
Sigma 2
Beta
Fatigue (nZ13)
a
1459.3G1113.2
294.0G154.1
89.3G41.8
41.7G18.0
35.0G24.8
22.3G17.6
6.7G3.3
Controls (nZ14)
P
516.7G394.2
247.5G129.7
127.57G59
57.33G24.75
37.0G20
16.7G13.2
14.36G7.05a
!0.01
n.s.
n.s.
n.s.
n.s.
n.s.
!0.01
t-Test (one CD with recording data unreadable, nZ27). Fatigue, chronic
fatigue patients.
a
Significantly different with t-Test analysis.
associated with fibromyalgia and fatigue, but publications
reporting it have been criticized due to lack of specificity of
this pattern [19]. The real issue, we believe, is not the
specificity of the polysomnographic pattern: It is the fact that
patients with chronic fatigue syndrome have an abnormal
sleep EEG pattern of shorter duration than the one used for
sleep staging. This abnormal sleep EEG pattern is not
recognized by the conventional scoring methods of polysomnography, and critics of the finding should have raised
the question of the underlying problems behind the presence
of delta–alpha sleep disturbances [14].
Our study addressed the question of unrefreshing sleep
using new tools. None of our patients had secondary gain to
their claim of fatigue, and all were greatly handicapped by
their syndrome. These patients tried to treat their fatigue by
staying in bed on weekends and days off, despite the
negative impact it had on their social and family lives. They
denied ‘sleepiness’, and their ESS was borderline normal.
Several of the sleep logs showed some nocturnal sleep
disruption, though all patients denied having ‘insomnia’,
defined as difficulty falling asleep at sleep onset or difficulty
returning to sleep if awakened during the night. The major
complaint of the patients was of ‘unrefreshing sleep’ and a
continuous feeling of fatigue that was described as
‘exhaustion’ by a few, which was already present at the
time of morning awakening. In our study the subjective
investigations did not yield important findings. Sleep
staging analyses did not account for the reported fatigue.
Though there were subtle abnormalities, a decrease in sleep
efficiency and a decrease in stages 3, 4 NREM sleep (SWS)
compared to normal controls as already mentioned by others
[36], these findings are interesting but are not specific.
Additionally, experiments with short-term sleep deprivation
and recovery have shown that sleep duration appears to be
more important for daytime alertness than SWS content [37]
and total sleep time, which were similar in our fatigue
patients and controls. We also failed to demonstrate
alterations in sleep consolidation and fragmentation
parameters. Our fatigue patients had similar arousal indices
compared to normals. Notably, this study did not find an
increase in alpha EEG frequencies (fast frequencies),
primary components of delta–alpha pattern and of arousals
from sleep. The lack of sleep fragmentation may explain
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C. Guilleminault et al. / Sleep Medicine 7 (2006) 513–520
Fig. 1. EEG relative power in fatigue (nZ13) and controls subjects (nZ14). Significant differences are indicated in Table 3A: all bands were significantly
different between controls and patients (P!0.01).
why these patients were not sleepy during the daytime but
complained only of chronic fatigue.
However, the CAP analyses and quantitative EEG
analyses changes were significant compared to controls.
These changes suggest one should analyze the polysomnograms of patients complaining of fatigue differently. In our
chronic fatigue patients, there was a significant increase in
slow delta power despite an overall decrease in SWS
compared to normals. Some of the findings are close to
those observed with parasomnias [38–42], including an
increase in CAP rate and CAP time as observed here. Such
increases are associated with complaint of unrefreshing
sleep and sleep disorders [31,33,43]. In our analysis we did
not dissociate the different phases A of CAP because we
believe that the important question here is not related to
types of phase A but instead to the following: why are the
phases A interrupted and why is there a return to phase B
instead of a normal progression toward consolidated SWS?
The presence of an increase in slow delta indicates presence
of ‘delta burst’ or ‘delta-cluster waves’ [44]; however, the
decrease in overall delta power and slow wave sleep
indicates that the ‘delta stage’ cannot be maintained during
NREM sleep, leading to ‘instability of NREM sleep’ as
emphasized by Terzano et al. [32,33]. Instability of NREM
sleep has been seen with a variety of different syndromes
and is a non-specific finding but raises the question of why
such instability is present. We believe NREM sleep
instability suggests an impairment of the normal homeostatic process.
Increase in CAP rate is associated with the presence of
increased respiratory effort and of flow limitation events as
shown with nasal cannula and esophageal pressure
measurements. With these combined recording techniques,
which are not routinely used in most sleep laboratories, we
found a significant increase in the RDI (an index very
different from the well-known AHI calculated in obstructive
sleep apnea) in chronic fatigue subjects compared to
controls. The main complaint of patients, particularly premenopausal women, with upper airway resistance syndrome
(UARS [45]) is ‘chronic fatigue’. The difference between
patients labeled ‘chronic fatigue’ or UARS appears mainly
dependant on the referral route of patients rather than their
clinical complaint. Initially, UARS patients were sent to the
sleep clinic because of snoring, but it is well-known that
UARS may be present without snoring [45]. The main
complaint of patients in this study was ‘chronic fatigue’,
which led them to be referred and evaluated by rheumatologists. Despite the diagnosis ‘chronic fatigue’ or ‘UARS’
both groups of patients share similar sleep disturbances that
result in similar consequences. There are now a series of
reports that show abnormal breathing without obstructive
apneas, and hypopneas may be associated with changes in
sleep EEG. Chervin et al. showed that in both children and
adults [46,47] EEG changes may be seen with each
abnormal breath and each increase in respiratory effort by
utilizing a much more sophisticated technique than visual
sleep stage scoring. There is now an array of reports that
demonstrate the importance of intact sensory input from the
oro-pharynx and upper larynx to avoid the development of
the obstructive sleep apnea syndrome [48]. The presence of
a local neuropathy appears to be associated with OSAS, but
persistence of normal local sensory input seems to be
inducing UARS, with its cortege of daytime fatigue [48],
abnormal CAP rate and changes of sleep EEG at
quantitative EEG analyses.
In 1999, Lentz et al. showed that SWS sleep disruption
resulting in an increase in fatigue and a decrease in pain
threshold [49]. Vergara et al. [50] reported that an important
predictor of subjective quality of sleep and sleep depth is
related to delta maximum power measured with quantitative
EEG analysis. Instability of NREM sleep is associated with
changes in delta power from the first to the last NREM–
REM cycle as demonstrated in investigation of chronic
sleepwalkers [42]. Subtle sleep-disordered breathing
(UARS type) leads to these changes in delta power. The
challenges now are to understand why similar breathing
disorders during sleep lead to different clinical presentations, why subjects with similar sleep disturbances have
C. Guilleminault et al. / Sleep Medicine 7 (2006) 513–520
different types of parasomnia, or just a complaint of chronic
fatigue. Could it be that the type of anatomical problem
presented by these patients (nasal impairment versus base of
tongue impairment, versus pharyngeal impairment) plays a
role on the severity of the sleep EEG disturbance? Is an
increase in nasal resistance more detrimental in creating an
anxiety response than a base of tongue narrowing? These
are unanswered questions but are important to consider as
the types and number of sensory receptors are very different
depending on the region of the upper airway that is the
primary site of narrowing. The projections of these sensors
and their association with certain regions of the brain may
also be important: again an abnormality in the nose passage
may not have the same impact as one behind the base of
tongue. There will also be the need to explore whether
subtle disruption of other biological functions leads to some
subtle disturbances of sleep and complaints of chronic
fatigue due to the impact on SWS and appearance of NREM
sleep instability. In the recent past, the use of investigative
approaches such as quantitative EEG, CAP scoring, or
complex algorithms such as the one used by Chervin et al.
[46,47], have demonstrated that much more information
could be extracted from the sleep EEG of patients with
complaint of ‘fatigue’, and these approaches may reveal
much more than simple sleep staging.
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