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Actigraphic assessment of sleep disorders in children with chronic fatigue syndrome
Brain & Development 30 (2008) 329–333 www.elsevier.com/locate/braindev
Original article
Actigraphic assessment of sleep disorders in children with chronic fatigue syndrome Junko Ohinata *, Nao Suzuki, Akiko Araki, Satoru Takahashi, Kenji Fujieda, Hajime Tanaka Department of Pediatrics, Asahikawa Medical College, Japan Received 14 May 2007; received in revised form 28 September 2007; accepted 3 October 2007
Abstract Children with chronic fatigue syndrome (CFS) often suffer from sleep disorders, which cause many physiological and psychological problems. Understanding sleep characteristics in children with CFS is important for establishing a therapeutic strategy. We conducted an actigraphic study to clarify the problems in sleep/wake rhythm and physical activity in children with CFS. Methods. Actigraphic recordings were performed for 1–2 weeks in 12 CFS children. The obtained data were compared with those of healthy age-matched children used as the control. Results. Sleep patterns were divided into two groups based on subjects’ sleep logs: irregular sleep type and delayed sleep phase type. Compared to the control group, total sleep time was longer and physical activity was lower in both groups of CFS. Continuous sleep for more than 10 h was not uncommon in CFS. In the irregular sleep type, impaired daily sleep/wake rhythms and disrupted sleep were observed. Conclusion. Using actigraphy, we could identify several characteristics of the sleep patterns in CFS children. Actigraphic analysis proved to be useful in detecting sleep/wake problems in children with CFS. Ó 2007 Elsevier B.V. All rights reserved. Keywords: Chronic fatigue syndrome; Sleep disorders; Actigraphy
1. Introduction Chronic fatigue syndrome (CFS) in children has recently become an increasingly recognized problem. The pathophysiology of CFS remains unclear and no biomarker has been validated. The main complaints of these children are physical fatigue or exhaustion, headaches, muscle pain and sleep disorders [1]. Of these, chronic sleep disorder with an impaired sleep/wake cycle causes many problems such as: daytime tiredness or sleepiness, deficits in cognitive performance, memory loss [2–5], and poor attendance at school. Clinical data
*
Corresponding author. Tel.: +81 166 68 2481; fax: +81 166 68 2489. E-mail address: [email protected] (J. Ohinata). 0387-7604/$ - see front matter Ó 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.braindev.2007.10.004
suggest that sleep interventions in patients with CFS may reduce symptoms and improve functional capacity, and sleep management is often included in the behavioral and cognitive treatment of CFS [6]. Garralda et al. also emphasized establishing a sleep routine for the treatment of CFS [1,7]. For the establishment of a sleep routine, understanding of sleep patterns and associated problems with sleep is essential. An actigraph is a device, which patients put on their wrist to record movement. Collected data are downloaded onto a computer for analysis of activity patterns. Using the Sadeh algorithm, sleep–wake scoring can be calculated. Results obtained using this algorithm correlate highly with polysomnography, to differentiate between the state of being asleep and being awake [8–11]. It is also useful for obtaining data recorded at home over an extended period of time [11]. So we used actigraphy to examine
330
J. Ohinata et al. / Brain & Development 30 (2008) 329–333
daily activity patterns. Our study disclosed several characteristics in the sleep/wake activity of children with CFS.
4. Results
2. Subjects
Total daily sleep time in patients with CFS was longer, compared to the control group (Mann–Whitney U-test, P < 0.05). Total daily sleep time of the control group was 7 h and 47 min on average, while for the IR Group and DSP Group, it was 8 h 31 min and 9 h 38 min on average, respectively. The DSP Group exhibited a much longer sleep time than the IR Group (Mann–Whitney U-test, P < 0.05).
Twelve patients, aged 12–16 years, three boys and nine girls, were enrolled in the study. All patients met the diagnostic criteria for CFS, established by the Center for Disease Control in 1994 [12,13] and complained of disturbed sleep. According to the results of a sleep/wake diary and questionnaire, subjects were divided into two groups: irregular sleep type (IR Group) or delayed sleep phase sleep type (DSP Group). Irregular sleep is sleep characterized by no recognizable circadian patterns of sleep onset or waking time. It is also defined as Circadian Rhythm Sleep Disorder, Unspecified Type by DSMIV-TR. Delayed sleep phase is characterized by difficulty in falling asleep at night and the inability to be easily aroused in the morning. It also corresponds to DSMIV-TR: Circadian Rhythm Sleep Disorder, Delayed Sleep Phase Type. In this study, five subjects were enrolled in the IR Group and seven subjects in the DSP Group. To obtain normal data as the control, we recruited seven age-matched children, two boys and five girls, aged 13–16 years, who had no physical or mental problems. We obtained informed consent following a full explanation of the experiments from all subjects we employed in this study.
4.1. Sleep time (Fig. 1)
4.2. Frequency of extremely long sleep (Fig. 2) While the control group exhibited no extremely long sleep, patients in both CFS groups did. It was observed once every two weeks (0.3 times/week on average) in three patients in the IR Group, and 2–6 times every 2 weeks (1.7 times/week on average) in all patients in the DSP Group. 4.3. Activity (Fig. 3) Physical activity while awake was low in both CFS groups (Mann–Whitney U-test, P < 0.01) and there was no statistical difference between the IR and the DSP Group. 4.4. DTA index (Fig. 4) The DTA index was much lower among patients in the IR Group (Mann–Whitney U-test, P < 0.01). No
3. Methods 700
** Total Sleep Time (min./day)
The subjects and the healthy volunteers wore actigraphs (Ambulatory Monitoring Inc., Ardsley, NY, USA) on the non-dominant wrist for 1–2 weeks. Motion was continuously recorded in 1 min epochs using zero crossing mode. The subjects were only allowed to take off the actigraph during bathing, and they were asked to write down the time of bathing. Activity during bathing was omitted, but the bathing time was included as awake time. Collected data were downloaded onto a computer. Sleep measurements obtained through acigraphy were (a) sleep time: total minutes of sleep in a day as indicated by the Sadeh algorithm, (b) frequency of extremely long sleep: frequency of more than 10 h of continuous sleep, (c) activity: average epochs while awake, (d) day time activity index (DTA index): average epochs during the day (from 8 a.m. to 9 p.m.)/average epochs at night (from midnight to 5 a.m.) and (e) very short sleep index (VSS index): percentage of sleep less than 180 min of total sleep time. These measurements obtained from the patients and the controls were evaluated using the Mann–Whitney U-test.
*
*
600
500
400
300 control
IR
DSP
Fig. 1. Total sleep time in a day. In patients with CFS, total daily sleep time was significantly longer than that in control group. Especially, the DSP Group exhibited a much longer sleep time than other two groups. (Mann–Whitney U-test, *P < 0.05; **P < 0.01.)
J. Ohinata et al. / Brain & Development 30 (2008) 329–333
331
4
**
**
30
**
20 2
DTA Index
ELS ( /week)
3
1
10
0 control
IR
DSP 0
Fig. 2. Frequency of extremely long sleep. The DSP Group exhibited extremely long sleep more frequently than the IR Group did. The controls had no extremely long sleep. (Mann–Whitney U-test, **P < 0.01.)
control
DSP
IR
Fig. 4. DTA index. Patients in the IR Group showed significantly low DTA index. (Mann–Whitney U-test, **P < 0.01.)
*
*
30 300
** 250
20
VSS Index
Physical Activity (epochs/min.)
**
200
10
150
0 control
100 control
IR
DSP
Fig. 3. Physical activity while awake. In patients with both groups of CFS, physical activity was lower than that in the control group. (Mann–Whitney U-test, **P < 0.01.)
one in the control group had a DTA index lower than 5, while all subjects in the IR Group did. No statistical difference was observed between the DTA indices of the control and the DSP Group. 4.5. VSS index (Fig. 5) In the IR Group, the VSS index was higher than that of the control and the DSP Group (Mann–Whitney Utest, P < 0.05).
IR
DSP
Fig. 5. VSS index. Patients in the IR Group showed high VSS index. (Mann–Whitney U-test, *P < 0.05.)
5. Discussion Children with CFS frequently complain of sleep disorders such as insomnia and/or disrupted sleep and less frequently, hypersomnia [1]. Many of them describe their sleepiness and fatigue as not being relieved by sleep [6]. They gradually develop disturbances of the circadian rhythm and subsequently present with disturbed endocrinological and autonomical rhythms. Thus, therapeutic intervention for sleep disorders is quite important in the early stage of this syndrome [2]. In this study, we disclosed several characteristics in the sleep disorders of children with CFS. Sleep disorders
332
J. Ohinata et al. / Brain & Development 30 (2008) 329–333
in CFS children could be divided into two groups: irregular sleep type and delayed sleep phase type. Common features of these groups were longer sleep times, the existence of extremely long sleep and lower physical activity. Prolonged sleep was reported as one of symptoms of CFS [1,7,14], but duration of the prolonged sleep had not been mentioned. People who sleep more than 10 h are often called long sleepers. Miike et al. reported that most children with poor school attendance had symptoms of CFS and they needed 10 h sleep [14]. Based on actigraphic findings, we defined extremely long sleep as the sleep that continued for more than 10 h. No extremely long sleep was observed in the control group. However, it was observed in both of the CFS groups, which indicated extremely long sleep was a characteristic of CFS. Sleep quality is not assessed by actigraphy. An overnight EEG study revealed a decrease in deep NREM sleep and delayed latency of REM sleep [14]. Impairment of sleep quality was suspected, but the mechanism of this prolonged sleep is unclear. Adult patients with CFS are reported to be less physically active than their healthy counterparts. They can be more physically active but overall mood and muscle pain worsen with increased activity. They rest more after physical exertion and it is speculated that they have an ‘‘activity limit’’ [15,16]. Our data showed that children with CFS were also less active while awake and their physical activity was not related to their sleep patterns. Brainstem monoaminergic neurons are known to have roles in maintaining arousal and regulating muscle tone [17], and they are under regulation of the hypothalamus. We speculate that children with CFS might have dysfunction of the hypothalamus accompanying the inactivity of noradrenergic and/or serotonergic neurons, and it might cause prolonged sleep and lower physical activity. Some of the patients with CFS are reported to have abnormal hypothalamo–pituitary–adrenal (HPA) axis function, which supposed to be associated with changes in sleep duration and pattern and levels of habitual physical activity [18]. Further investigations are required to clarify the mechanism of sleep and activity problems in CFS. DTA index shows a circadian rhythm of activity. When a subject is active during the day and can rest at night, the DTA index is high. When a subject has a reversed day/night rhythm, the DTA index is below 1. Subjects with a disturbed circadian rhythm have a DTA index around 1. The VSS index is the percentage of very short sleep of total sleep time. When it is high, it means that the subject has disrupted sleep. Children in the IR Group had a very low DTA index compared to the control group and the DSP Group. And the VSS index was high in this group. These results indicated that the CFS children with irregular sleep had an impaired sleep/wake cycle, caused by disrupted night sleep and daytime napping. One home polysomnographic study
showed that people with CFS had higher levels of sleep disruption [19]. Tryon et al. reported lower daytime activity and less regular activity/rest cycles in CFS than in controls [20]. Our data on DTA index and VSS index in the IR Group was compatible with these studies. The children with a delayed sleep phase had a shifted sleep phase, but their DTA index was not always low. And the VSS index was not high in this group. They slept for a long time without disruption. CFS children with hypersomnia described by Garralda et al. [1,7] could be included in this group. Both groups of CFS children shared common features of longer total sleep time and lower physiological activity, but their DTA index and VSS index were not similar. The IR Group had disrupted sleep and impaired circadian rhythm. In contrast, the DSP group kept their circadian rhythm without sleep disruption. For therapeutic intervention of CFS, establishing a sleep routine and a consistent level of activity is more likely to be successful than pharmacological therapy [6,7]. It is known that establishing cycles of sleep/wake and rest/active in the early stage of the disease is necessary for therapy [2] and that is not unusual to need long periods of time to achieve treatment goals [7]. For children with CFS, knowing the problems with sleep and physical activity is important before and throughout treatment. Using actigraphy, we succeeded in measuring sleep/wake rhythm and physical activity objectively. The parameters used in this study give us some insight for the understanding of the characteristics of CFS patients and for evaluating the effectiveness of treatments. References [1] Garralda ME, Rangel LA. Annotation: chronic fatigue syndrome in children and adolescents. J Child Psychol Psychiatry 2002;43:169–76. [2] Miike T. Brain science, education and living environment (in Japanese). No to Hattatsu (Tokyo) 2006;38:85–91. [3] Kheirandish L, Gozal D. Neurocognitive dysfunction in children with sleep disorders. Dev Sci 2006;9:388–99. [4] Martikainen K, Hasan J, Urponen H, Vuori I, Partinen M. Daytime sleepiness: a risk factor in community life. Acta Neurol Scand 1992;86:337–41. [5] Roth T, Roehrs T, Rosenthal L. Hypersomnolence and neurocognitive performance in sleep apnea. Curr Opin Pulm Med 1995;1:488–90. [6] Working Group of the royal Australasian Collage of Physicians. Chronic fatigue syndrome. Clinical practice guidelines – 2002. Med J Aust 2002;6(176):23–56. [7] Garralda ME, Chalder T. Practitioner review: chronic fatigue syndrome in childhood. J Child Psychol Psychiatry 2005;46:1143–51. [8] Sadeh A, Sharkey KM, Crarskadon MA. Activity-based sleep– wake identification: an empirical test of methodological issues. Sleep 1994;17:201–7. [9] Sadeh A, Hauri PJ, Kripke DF, Lavie P. The role of actigraphy in the evaluation of sleep disorders. Sleep 1995;18:288–302. [10] Jean-Louis G, von Gizycki H, Zizi F, Foodson J, Spielman A, Nunes J, et al. Determination of sleep and wakefulness with the actigraph data analysis software (ADAS). Sleep 1996;19:739–43.
J. Ohinata et al. / Brain & Development 30 (2008) 329–333 [11] Ancoli-Israel S, Cole R, Alessi C, Chambers M, Moorcroft W, Pollak C. The role of actigraphy in the study of sleep and circadian rhythms. Sleep 2003;26:342–92. [12] Marshall GS. Report of a workshop on the epidemiology, natural history, and pathogenesis of chronic fatigue syndrome in adolescents. J Pediatr 1999;134:395–405. [13] Reeves WC, Wagner D, Niesenbaum R, Jones JF, Gurbaxani B, Solomon L. Chronic fatigue syndrome – a clinically empirical approach to its definition and study. BMC Med 2005;3:19. [14] Miike T, Tomoda A, Jhodoi T, Iwatani N, Mabe H. Learning and memorization impairment in childhood chronic fatigue syndrome manifesting as school phobia in Japan. Brain Dev 2004;26:442–7. [15] van der Werf SP, Prins JB, Vercoulen JH, van der Meer JW, Bleijenberg G. Identifying physical activity patterns in chronic
[16]
[17] [18] [19]
[20]
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fatigue syndrome using actigraphic assessment. J Psychosom Res 2000;49:373–9. Black CD, O’Connor PJ, McCully KK. Increased daily physical activity and fatigue symptoms in chronic fatigue syndrome. Dyn Med 2005;4:3. Siegel JM. The neurotransmitters in sleep. J Clin Psyciatry 2004;65:4–7. Cleare AJ. The HPA axis and the genesis of chronic fatigue syndrome. Trends Endocrinol Metab 2004;15:55–9. 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. Tryon WW, Jason L, Frankenberry E, Torres-Harding S. Chronic fatigue syndrome impairs circadian rhythm of activity level. Physiol Behav 2004;82:849–53.
Original article
Actigraphic assessment of sleep disorders in children with chronic fatigue syndrome Junko Ohinata *, Nao Suzuki, Akiko Araki, Satoru Takahashi, Kenji Fujieda, Hajime Tanaka Department of Pediatrics, Asahikawa Medical College, Japan Received 14 May 2007; received in revised form 28 September 2007; accepted 3 October 2007
Abstract Children with chronic fatigue syndrome (CFS) often suffer from sleep disorders, which cause many physiological and psychological problems. Understanding sleep characteristics in children with CFS is important for establishing a therapeutic strategy. We conducted an actigraphic study to clarify the problems in sleep/wake rhythm and physical activity in children with CFS. Methods. Actigraphic recordings were performed for 1–2 weeks in 12 CFS children. The obtained data were compared with those of healthy age-matched children used as the control. Results. Sleep patterns were divided into two groups based on subjects’ sleep logs: irregular sleep type and delayed sleep phase type. Compared to the control group, total sleep time was longer and physical activity was lower in both groups of CFS. Continuous sleep for more than 10 h was not uncommon in CFS. In the irregular sleep type, impaired daily sleep/wake rhythms and disrupted sleep were observed. Conclusion. Using actigraphy, we could identify several characteristics of the sleep patterns in CFS children. Actigraphic analysis proved to be useful in detecting sleep/wake problems in children with CFS. Ó 2007 Elsevier B.V. All rights reserved. Keywords: Chronic fatigue syndrome; Sleep disorders; Actigraphy
1. Introduction Chronic fatigue syndrome (CFS) in children has recently become an increasingly recognized problem. The pathophysiology of CFS remains unclear and no biomarker has been validated. The main complaints of these children are physical fatigue or exhaustion, headaches, muscle pain and sleep disorders [1]. Of these, chronic sleep disorder with an impaired sleep/wake cycle causes many problems such as: daytime tiredness or sleepiness, deficits in cognitive performance, memory loss [2–5], and poor attendance at school. Clinical data
*
Corresponding author. Tel.: +81 166 68 2481; fax: +81 166 68 2489. E-mail address: [email protected] (J. Ohinata). 0387-7604/$ - see front matter Ó 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.braindev.2007.10.004
suggest that sleep interventions in patients with CFS may reduce symptoms and improve functional capacity, and sleep management is often included in the behavioral and cognitive treatment of CFS [6]. Garralda et al. also emphasized establishing a sleep routine for the treatment of CFS [1,7]. For the establishment of a sleep routine, understanding of sleep patterns and associated problems with sleep is essential. An actigraph is a device, which patients put on their wrist to record movement. Collected data are downloaded onto a computer for analysis of activity patterns. Using the Sadeh algorithm, sleep–wake scoring can be calculated. Results obtained using this algorithm correlate highly with polysomnography, to differentiate between the state of being asleep and being awake [8–11]. It is also useful for obtaining data recorded at home over an extended period of time [11]. So we used actigraphy to examine
330
J. Ohinata et al. / Brain & Development 30 (2008) 329–333
daily activity patterns. Our study disclosed several characteristics in the sleep/wake activity of children with CFS.
4. Results
2. Subjects
Total daily sleep time in patients with CFS was longer, compared to the control group (Mann–Whitney U-test, P < 0.05). Total daily sleep time of the control group was 7 h and 47 min on average, while for the IR Group and DSP Group, it was 8 h 31 min and 9 h 38 min on average, respectively. The DSP Group exhibited a much longer sleep time than the IR Group (Mann–Whitney U-test, P < 0.05).
Twelve patients, aged 12–16 years, three boys and nine girls, were enrolled in the study. All patients met the diagnostic criteria for CFS, established by the Center for Disease Control in 1994 [12,13] and complained of disturbed sleep. According to the results of a sleep/wake diary and questionnaire, subjects were divided into two groups: irregular sleep type (IR Group) or delayed sleep phase sleep type (DSP Group). Irregular sleep is sleep characterized by no recognizable circadian patterns of sleep onset or waking time. It is also defined as Circadian Rhythm Sleep Disorder, Unspecified Type by DSMIV-TR. Delayed sleep phase is characterized by difficulty in falling asleep at night and the inability to be easily aroused in the morning. It also corresponds to DSMIV-TR: Circadian Rhythm Sleep Disorder, Delayed Sleep Phase Type. In this study, five subjects were enrolled in the IR Group and seven subjects in the DSP Group. To obtain normal data as the control, we recruited seven age-matched children, two boys and five girls, aged 13–16 years, who had no physical or mental problems. We obtained informed consent following a full explanation of the experiments from all subjects we employed in this study.
4.1. Sleep time (Fig. 1)
4.2. Frequency of extremely long sleep (Fig. 2) While the control group exhibited no extremely long sleep, patients in both CFS groups did. It was observed once every two weeks (0.3 times/week on average) in three patients in the IR Group, and 2–6 times every 2 weeks (1.7 times/week on average) in all patients in the DSP Group. 4.3. Activity (Fig. 3) Physical activity while awake was low in both CFS groups (Mann–Whitney U-test, P < 0.01) and there was no statistical difference between the IR and the DSP Group. 4.4. DTA index (Fig. 4) The DTA index was much lower among patients in the IR Group (Mann–Whitney U-test, P < 0.01). No
3. Methods 700
** Total Sleep Time (min./day)
The subjects and the healthy volunteers wore actigraphs (Ambulatory Monitoring Inc., Ardsley, NY, USA) on the non-dominant wrist for 1–2 weeks. Motion was continuously recorded in 1 min epochs using zero crossing mode. The subjects were only allowed to take off the actigraph during bathing, and they were asked to write down the time of bathing. Activity during bathing was omitted, but the bathing time was included as awake time. Collected data were downloaded onto a computer. Sleep measurements obtained through acigraphy were (a) sleep time: total minutes of sleep in a day as indicated by the Sadeh algorithm, (b) frequency of extremely long sleep: frequency of more than 10 h of continuous sleep, (c) activity: average epochs while awake, (d) day time activity index (DTA index): average epochs during the day (from 8 a.m. to 9 p.m.)/average epochs at night (from midnight to 5 a.m.) and (e) very short sleep index (VSS index): percentage of sleep less than 180 min of total sleep time. These measurements obtained from the patients and the controls were evaluated using the Mann–Whitney U-test.
*
*
600
500
400
300 control
IR
DSP
Fig. 1. Total sleep time in a day. In patients with CFS, total daily sleep time was significantly longer than that in control group. Especially, the DSP Group exhibited a much longer sleep time than other two groups. (Mann–Whitney U-test, *P < 0.05; **P < 0.01.)
J. Ohinata et al. / Brain & Development 30 (2008) 329–333
331
4
**
**
30
**
20 2
DTA Index
ELS ( /week)
3
1
10
0 control
IR
DSP 0
Fig. 2. Frequency of extremely long sleep. The DSP Group exhibited extremely long sleep more frequently than the IR Group did. The controls had no extremely long sleep. (Mann–Whitney U-test, **P < 0.01.)
control
DSP
IR
Fig. 4. DTA index. Patients in the IR Group showed significantly low DTA index. (Mann–Whitney U-test, **P < 0.01.)
*
*
30 300
** 250
20
VSS Index
Physical Activity (epochs/min.)
**
200
10
150
0 control
100 control
IR
DSP
Fig. 3. Physical activity while awake. In patients with both groups of CFS, physical activity was lower than that in the control group. (Mann–Whitney U-test, **P < 0.01.)
one in the control group had a DTA index lower than 5, while all subjects in the IR Group did. No statistical difference was observed between the DTA indices of the control and the DSP Group. 4.5. VSS index (Fig. 5) In the IR Group, the VSS index was higher than that of the control and the DSP Group (Mann–Whitney Utest, P < 0.05).
IR
DSP
Fig. 5. VSS index. Patients in the IR Group showed high VSS index. (Mann–Whitney U-test, *P < 0.05.)
5. Discussion Children with CFS frequently complain of sleep disorders such as insomnia and/or disrupted sleep and less frequently, hypersomnia [1]. Many of them describe their sleepiness and fatigue as not being relieved by sleep [6]. They gradually develop disturbances of the circadian rhythm and subsequently present with disturbed endocrinological and autonomical rhythms. Thus, therapeutic intervention for sleep disorders is quite important in the early stage of this syndrome [2]. In this study, we disclosed several characteristics in the sleep disorders of children with CFS. Sleep disorders
332
J. Ohinata et al. / Brain & Development 30 (2008) 329–333
in CFS children could be divided into two groups: irregular sleep type and delayed sleep phase type. Common features of these groups were longer sleep times, the existence of extremely long sleep and lower physical activity. Prolonged sleep was reported as one of symptoms of CFS [1,7,14], but duration of the prolonged sleep had not been mentioned. People who sleep more than 10 h are often called long sleepers. Miike et al. reported that most children with poor school attendance had symptoms of CFS and they needed 10 h sleep [14]. Based on actigraphic findings, we defined extremely long sleep as the sleep that continued for more than 10 h. No extremely long sleep was observed in the control group. However, it was observed in both of the CFS groups, which indicated extremely long sleep was a characteristic of CFS. Sleep quality is not assessed by actigraphy. An overnight EEG study revealed a decrease in deep NREM sleep and delayed latency of REM sleep [14]. Impairment of sleep quality was suspected, but the mechanism of this prolonged sleep is unclear. Adult patients with CFS are reported to be less physically active than their healthy counterparts. They can be more physically active but overall mood and muscle pain worsen with increased activity. They rest more after physical exertion and it is speculated that they have an ‘‘activity limit’’ [15,16]. Our data showed that children with CFS were also less active while awake and their physical activity was not related to their sleep patterns. Brainstem monoaminergic neurons are known to have roles in maintaining arousal and regulating muscle tone [17], and they are under regulation of the hypothalamus. We speculate that children with CFS might have dysfunction of the hypothalamus accompanying the inactivity of noradrenergic and/or serotonergic neurons, and it might cause prolonged sleep and lower physical activity. Some of the patients with CFS are reported to have abnormal hypothalamo–pituitary–adrenal (HPA) axis function, which supposed to be associated with changes in sleep duration and pattern and levels of habitual physical activity [18]. Further investigations are required to clarify the mechanism of sleep and activity problems in CFS. DTA index shows a circadian rhythm of activity. When a subject is active during the day and can rest at night, the DTA index is high. When a subject has a reversed day/night rhythm, the DTA index is below 1. Subjects with a disturbed circadian rhythm have a DTA index around 1. The VSS index is the percentage of very short sleep of total sleep time. When it is high, it means that the subject has disrupted sleep. Children in the IR Group had a very low DTA index compared to the control group and the DSP Group. And the VSS index was high in this group. These results indicated that the CFS children with irregular sleep had an impaired sleep/wake cycle, caused by disrupted night sleep and daytime napping. One home polysomnographic study
showed that people with CFS had higher levels of sleep disruption [19]. Tryon et al. reported lower daytime activity and less regular activity/rest cycles in CFS than in controls [20]. Our data on DTA index and VSS index in the IR Group was compatible with these studies. The children with a delayed sleep phase had a shifted sleep phase, but their DTA index was not always low. And the VSS index was not high in this group. They slept for a long time without disruption. CFS children with hypersomnia described by Garralda et al. [1,7] could be included in this group. Both groups of CFS children shared common features of longer total sleep time and lower physiological activity, but their DTA index and VSS index were not similar. The IR Group had disrupted sleep and impaired circadian rhythm. In contrast, the DSP group kept their circadian rhythm without sleep disruption. For therapeutic intervention of CFS, establishing a sleep routine and a consistent level of activity is more likely to be successful than pharmacological therapy [6,7]. It is known that establishing cycles of sleep/wake and rest/active in the early stage of the disease is necessary for therapy [2] and that is not unusual to need long periods of time to achieve treatment goals [7]. For children with CFS, knowing the problems with sleep and physical activity is important before and throughout treatment. Using actigraphy, we succeeded in measuring sleep/wake rhythm and physical activity objectively. The parameters used in this study give us some insight for the understanding of the characteristics of CFS patients and for evaluating the effectiveness of treatments. References [1] Garralda ME, Rangel LA. Annotation: chronic fatigue syndrome in children and adolescents. J Child Psychol Psychiatry 2002;43:169–76. [2] Miike T. Brain science, education and living environment (in Japanese). No to Hattatsu (Tokyo) 2006;38:85–91. [3] Kheirandish L, Gozal D. Neurocognitive dysfunction in children with sleep disorders. Dev Sci 2006;9:388–99. [4] Martikainen K, Hasan J, Urponen H, Vuori I, Partinen M. Daytime sleepiness: a risk factor in community life. Acta Neurol Scand 1992;86:337–41. [5] Roth T, Roehrs T, Rosenthal L. Hypersomnolence and neurocognitive performance in sleep apnea. Curr Opin Pulm Med 1995;1:488–90. [6] Working Group of the royal Australasian Collage of Physicians. Chronic fatigue syndrome. Clinical practice guidelines – 2002. Med J Aust 2002;6(176):23–56. [7] Garralda ME, Chalder T. Practitioner review: chronic fatigue syndrome in childhood. J Child Psychol Psychiatry 2005;46:1143–51. [8] Sadeh A, Sharkey KM, Crarskadon MA. Activity-based sleep– wake identification: an empirical test of methodological issues. Sleep 1994;17:201–7. [9] Sadeh A, Hauri PJ, Kripke DF, Lavie P. The role of actigraphy in the evaluation of sleep disorders. Sleep 1995;18:288–302. [10] Jean-Louis G, von Gizycki H, Zizi F, Foodson J, Spielman A, Nunes J, et al. Determination of sleep and wakefulness with the actigraph data analysis software (ADAS). Sleep 1996;19:739–43.
J. Ohinata et al. / Brain & Development 30 (2008) 329–333 [11] Ancoli-Israel S, Cole R, Alessi C, Chambers M, Moorcroft W, Pollak C. The role of actigraphy in the study of sleep and circadian rhythms. Sleep 2003;26:342–92. [12] Marshall GS. Report of a workshop on the epidemiology, natural history, and pathogenesis of chronic fatigue syndrome in adolescents. J Pediatr 1999;134:395–405. [13] Reeves WC, Wagner D, Niesenbaum R, Jones JF, Gurbaxani B, Solomon L. Chronic fatigue syndrome – a clinically empirical approach to its definition and study. BMC Med 2005;3:19. [14] Miike T, Tomoda A, Jhodoi T, Iwatani N, Mabe H. Learning and memorization impairment in childhood chronic fatigue syndrome manifesting as school phobia in Japan. Brain Dev 2004;26:442–7. [15] van der Werf SP, Prins JB, Vercoulen JH, van der Meer JW, Bleijenberg G. Identifying physical activity patterns in chronic
[16]
[17] [18] [19]
[20]
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