Skip to main content
NCBI home page
Sleep logoLink to Sleep
. 2007 Jul 1;30(7):837–843. doi: 10.1093/sleep/30.7.837

Relationship Between Rem Density, Duty Cycle, and Obstructive Sleep Apnea in Children

Laurie Karamessinis 1, Patricia Galster 1,2, Brian Schultz 1, Joanne Elliott 1, Thornton A Mason II 1, Lee J Brooks 1, Paul R Gallagher 2, Carole L Marcus 1,✉
PMCID: PMC1978365  PMID: 17682653

Abstract

Study Objectives:

The pattern and distribution of rapid eye movement (REM) sleep changes during development, yet there have been few studies of REM density in children. Although children with obstructive apnea syndrome (OSAS) obstruct primarily during REM sleep, the relationship between REM density and obstructive apnea has not been established for this population. We hypothesized that (i) REM density and REM cycle duration increases over the course of the night in children, (ii) the duty cycle (inspiratory time divided by respiratory cycle time) increases over the course of the night in children with suspected OSAS, and (iii) the increase in REM density over the course of the night is associated with increased severity of obstructive apnea.

Design:

REM density and respiratory parameters were measured during polysomnography.

Setting:

Sleep laboratory

Patients:

76 children with suspected OSAS.

Interventions:

NA

Measurements and Results:

REM density and the duration of REM cycles increased over the course of the night until the fifth REM cycle, and then stabilized. The duty cycle increased across the first 6 REM cycles. However, the apnea hypopnea index (AHI) did not increase across REM cycles, and was not affected by the changes in REM density or duty cycle. We speculate that the increase in the duty cycle is a compensatory response to increased upper airway loads during sleep, and that this may lead to ventilatory or upper airway muscle fatigue.

Citation:

Karamessinis L; Galster P; Schultz B et al. Relationship between rem density, duty cycle, and obstructive sleep apnea in children.

Keywords: Duty cycle, REM cycle, progression of apnea

INTRODUCTION

THE PATTERN AND DISTRIBUTION OF RAPID EYE MOVEMENT (REM) SLEEP CHANGES WITH AGE AND DEVELOPMENT. THE FUNCTION OF REM SLEEP IS UNKNOWN, but it has been speculated that REM sleep is important for memory and learning.1 It is therefore not surprising that infants and young children have more REM sleep than older subjects, and have a different distribution of REM sleep.2 The intensity of tonic REM sleep has been measured using such parameters as the duration of REM sleep and REM latency, whereas the intensity of phasic REM sleep is typically measured by assessing the REM density, i.e., the number of rapid eye movements per unit time.3 Despite the importance of REM sleep in children, there have been few studies evaluating the intensity of REM sleep in the pediatric age group.

Obstructive sleep apnea syndrome (OSAS) is common during childhood, occurring in approximately 2% of young children.4 In children, the overwhelming majority of obstructive events occur during REM.5,6 It has been shown that the severity of obstructive apnea in children is increased in the last third of the night compared to the first third.5 The mechanisms for this are unclear, but it was postulated that this could be due to changes in REM density,5 as phasic REM sleep is associated with central inhibition of ventilation.7,8 Theoretically, muscle hypotonia and central inhibition of breathing may be worse during more intense portions of REM. Alternatively, the worsening of obstructive apnea over the course of the night could be due to increasing upper airway fatigue.5

We therefore hypothesized that: (i) REM density as well as REM cycle duration increases over the course of the night in children; (ii) the duty cycle (inspiratory time [TI] divided by total respiratory cycle time [TT], or TI/TT, a factor that can lead to muscle fatigue9) increases over the course of the night in children with suspected OSAS; and (iii) the increase in REM density over the course of the night is associated with increased severity of obstructive apnea. We therefore measured REM density and cycle duration and respiratory parameters over the course of the night in children with suspected OSAS.

METHODS

Studies were performed in children undergoing polysomnography for suspected OSAS. Routine polysomnography was performed, with the addition of extra electrooculogram leads as described below. REM density, TI/TT, and the apnea hypopnea index (AHI) were calculated for each REM cycle, and the change in these parameters over the course of the night was measured.

Study Group

Children with suspected OSAS, aged 2–12 years, were recruited from the Sleep Center at Children's Hospital of Philadelphia. The younger age limit was chosen to exclude infants and very young children, who have more REM than older children. The upper age limit was used to exclude most children in the later stages of puberty, as sex hormones can affect OSAS.10,11 The suspicion of OSAS was based on a presenting complaint of habitual snoring associated with additional symptoms, such as labored breathing during sleep or excessive daytime sleepiness. Children with significant, chronic medical conditions other than suspected OSAS secondary to adenotonsillar hypertrophy or obesity were excluded, except for those with mild asthma requiring only intermittent albuterol therapy. Thus, children with genetic syndromes, craniofacial anomalies and neurologic disease were excluded. Children with a history of previous upper airway surgery or previous treatment for OSAS, those on medications known to affect REM sleep, and those with a history of blindness or serious injury to one or both eyes, were also excluded. Subjects were considered obese if their body mass index was greater than the 95th percentile for age, height, and race.12

Written informed consent was obtained from the parents/legal guardians. In addition, assent was obtained from children ≥7 years of age. The study was approved by the Institutional Review Board of Children's Hospital of Philadelphia, and studies were performed according to the Declaration of Helsinki.

Polysomnography

Overnight polysomnography commenced between 20:00–21:00 and ended at 06:00. The following parameters were recorded (using Rembrandt, Medcare, Buffalo, NY): electroencephalogram (C3/A2, C4/A1, O1/A2, O2/A1); submental electromyogram (EMG); tibial EMG; electrocardiogram; chest and abdominal wall motion by respiratory inductance plethysmography (Respitrace Systems, Ambulatory Monitoring Inc, Ardsley, NY); airflow by nasal pressure (Pro-Tech Services, Inc, Mukilteo, WA) and 3-pronged thermistor (Pro-Tech Services, Inc, Mukilteo, WA); end-tidal PCO2 by capnography (Novametrix 7000; Novametrix, Wallingford, CT); arterial oxygen saturation (Novametrix 7000 or Masimo, Irvine, CA), oximeter pulse waveform, and digital video.

Four electrooculographic (EOG) gold cup electrodes (Grass, West Warwick, RI) were placed to detect eye movements. Right and left EOG leads were placed 1 cm lateral to the outer canthus of each eye, in the horizontal plane. Vertical EOG leads were placed 1 cm above and below the right eye.13,14 All 4 leads were used to assess eye movements. EOG changes were scored as eye movements if they met the following criteria: amplitude >25 μV, velocity >50°/sec, deflection >3° and at least 200 ms between each eye movement.15

Sleep architecture and arousals from sleep were analyzed using standard techniques.16,17 Respiratory parameters were scored using standard pediatric criteria,18,19 i.e., obstructive apneas of any length were scored. Hypopneas were scored if there was a qualitative decrease in oronasal airflow ≥50% associated with paradoxical respiratory efforts, desaturation ≥3%,20 and/or arousal. The obstructive apnea hypopnea index was defined as the number of obstructive apneas, mixed apneas, and obstructive hypopneas per unit time. Central apneas were also scored,18 but as very few central apneas occurred, these data are not presented.

Data Analysis

REM was divided into 1-second mini-epochs. The number of eye movements in each mini-epoch and the number of obstructive apneas originating within that epoch were manually calculated, as described in the literature.13 REM density was defined as the number of eye movements per each 30-second epoch of REM sleep. REM cycles of <2 minutes duration were not included in the analysis. For the purpose of analysis, REM cycles interrupted by <5 minutes of wakefulness or NREM sleep were considered to be part of the same REM cycle. Subjects with fewer than 3 REM cycles during the night were excluded. The obstructive apnea duration was defined as the sum of the duration of all obstructive apneas and hypopneas during each REM cycle. The inspiratory time and total respiratory cycle duration were obtained from the respiratory inductance plethysmographic signal. TI and TT were measured for each breath during the first and last minute of each REM cycle.

Statistical Analysis

The number of apneas and hypopneas in the first third of the night compared to the last third of the night was compared using the Wilcoxon signed rank test. The difference in REM density (averaged across all REM cycles) between subjects with an AHI <1/hr and those with an AHI >1 /hr was performed using the Mann-Whitney rank sum test. The Spearman correlation coefficient was used for correlational analyses. The effect of REM cycle on the various outcomes as measured repeatedly across REM cycles was analyzed based on a longitudinal mixed effects approach. In order to allow for the possibility that change across REM cycles has a curvilinear component, terms for quadratic time and cubic time were included in each model. If these terms were found to be nonsignificant, they were subsequently dropped from the final models. In order to explore the study hypotheses, various models involving time-varying or time-dependent covariates were also examined. For example, the effect of REM density changing across REM cycle on AHI changing across REM cycle was examined by including REM density as a time-dependent covariate and specifying the repeating measures of AHI as the outcome variable. In this study, using several measurements from different REM cycles across the night, the compound symmetry covariance matrix structure was assumed. SAS Proc Mixed models were used.21

RESULTS

Study Group

Seventy-nine subjects were studied. Three subjects were excluded as they had <3 REM cycles during the night. Thus, data were evaluated for 76 subjects. The mean age was 6 ± 3 (SD) years, range 2–12 years. Fifty-six percent were female, and 29% were obese. Polysomnography results are shown in Table 1. Subjects had a wide range of severity of OSAS, as shown in Figure 1. AHI ranged from 0–57/hr, with a median AHI of 1.9/hr.

Table 1.

Sleep Architecture

Total recording time (min) 534 ± 33
    Range 466 – 615
Total sleep time (min) 459 ± 41
    Range 320 – 530
Sleep efficiency (%) 86 ± 9
    Range 33 – 98
Sleep latency (min) 29 ± 28
    Range 2 – 191
Wake after sleep onset (min) 37 ± 24
    Range 4 – 121
Stage 1 (%TST) 7 ± 5
    Range 1 – 27
Stage 2 (%TST) 46 ± 8
    Range 29 – 66
Slow wave sleep (%TST) 26 ± 6
    Range 10 – 41
REM sleep (%TST) 20 ± 5
    Range 11 – 33
REM latency (min) 118 ± 55
    Range 35 – 286
REM cycles (N) 5 ± 1
    Range 3 – 8
Arousal index (N/hr) 15 ± 9
    Range 5 – 64
Apnea hypopnea index (N/hr)
    Median 1.9
    Range 0 – 57
Mean obstructive apnea duration(s) 11.7 ± 3.2
Mean hypopnea duration(s) 13.2 ± 3.9
Arterial oxygen saturation nadir (%) 88 ± 8
    Range 66 – 98
Peak end-tidal PCO2 (mm Hg) 51 ± 5
    Range 37 – 64
Open in a new tab

Data displayed as mean ± SD and range, except for the apnea hypopnea index, which was not normally distributed and is displayed as median and range. TST, total sleep time.

Figure 1.

Figure 1

Open in a new tab

The apnea hypopnea index for each of the 76 subjects is shown.

REM Architecture

With the exception of the 3 subjects excluded from the study because they had <3 REM cycles, subjects had 3–8 REM cycles during the night; 5 (7%) subjects had 7 REM cycles, and only 1 (1%) subject had 8 cycles. REM density changed significantly across the REM cycles, with significant linear and quadratic time effects (P = 0.0017 and 0.0245, respectively), indicating a linear increase and an eventual leveling of REM density by the fifth REM cycle (Figure 2).

Figure 2.

Figure 2

Open in a new tab

The mean (SD) REM density is shown as a function of REM cycles across the course of the night. Note that few subjects had >6 REM cycles.

There was no correlation between REM density (computed as the mean REM density per subject) and age (r = 0.11, P = 0.37; Figure 3). In order to compare this study to previous data in the literature, the correlation between REM density and age was reevaluated in those children ≥6 years of age. There was a slightly stronger relationship, but this still did not reach significance (r = 0.29, P = 0.11). There was no significant difference in mean REM density between children with an AHI <1/hr and children with an AHI >1/hr (P = 0.83).

Figure 3.

Figure 3

Open in a new tab

The relationship between REM density and age is shown.

REM duration changed across the REM cycles, with significant linear and quadratic time effects (P <0.0001 for both linear and quadratic time effects), again indicating a linear increase and an eventual leveling at the fifth cycle (Figure 4).

Figure 4.

Figure 4

Open in a new tab

The mean (SD) duration of each REM cycle is shown as a function of REM cycles across the course of the night. Note that few subjects had >6 REM cycles.

Duty Cycle

TI/TT increased significantly across the REM cycles of the night in a linear fashion (P = 0.0033). This is shown in Figure 5. Note that very few subjects had more than 6 REM cycles; thus, the apparent decrease in TI/TT in cycles 7 and 8 was not significant.

Figure 5.

Figure 5

Open in a new tab

The mean (SD) duty cycle is shown as a function of REM cycles across the course of the night. Note that few subjects had >6 REM cycles. TI, inspiratory time; TT, total respiratory cycle time.

Apnea Hypopnea Index

The AHI and obstructive apnea duration variables were severely skewed, with a preponderance of values of zero, and could not be normalized using transformation techniques. Despite the fact that the number of REM obstructive apneas and hypopneas was greater during the last third of the night than the first third (first third, median 0, interquartile range 0–2; last third median 1, interquartile range 0–6.5; P <0.001), there was no significant change in the AHI across the REM cycles of the night (P = 0.052 for raw AHI and P = 0.45 for log AHI; Figure 6); nor was there a change in total obstructive apnea duration across the REM cycles of the night (P = 0.13 for raw values and P = 0.33 for log transformed values).

Figure 6.

Figure 6

Open in a new tab

The apnea hypopnea index for subjects with an AHI ≥1/hr is shown as a function of REM cycles across the course of the night. The boundaries of the boxes indicate the 25th and 75th percentiles, the line within the boxes marks the medians, the whiskers indicate the 90th and 10th percentiles, and the points represent the outliers.

The change in AHI across REM cycles was reevaluated for those subjects who had any degree of airway obstruction, i.e., after excluding those with an AHI = 0. Under these circumstances, log transformation helped to normalize the AHI distribution. There was still no statistically significant change in AHI across the REM cycles over the course of the night (P = 0.0751 for raw values; P = 0.12 for log values). Similarly, when only children with moderate OSAS (AHI ≥5/hr) were evaluated, there was no statistically significant change in AHI across REM cycles (P = 0.17 for raw values; P = 0.24 for log values). There were 2 subjects who were outliers, with very severe OSAS. One subject with an AHI of 42/hr had 4 REM cycles; her REM AHI for each cycle, respectively, was 131, 120, 77, and 107/hr. The second outlier, with an AHI of 57/hr, had 3 REM cycles, with a REM AHI of 14, 122, and 32/hr, respectively. Thus, neither of the most severely affected subjects had a pattern of worsening during the last REM cycle.

The correlations between AHI and REM density, and AHI and REM duration, were not significant (r = −0.05, P = −0.69; and r = −0.03, P = 0.80; respectively).

Relationship Between REM Density, Duty Cycle, and AHI

Although REM density changed across REM cycles, this change in REM density did not have an effect on TI/TT changing across REM cycles. There was no relationship between the changes in either REM density or TI/TT and changes in the AHI across REM cycles.

Obesity

There were no significant correlations between body mass index z-scores, which serve as an index of obesity, and AHI (P = 0.19), mean REM density (P = 0.60), or mean TI/TT (P = 0.23) (all parameters computed as the average of the means for each REM cycle).

DISCUSSION

This study has shown that REM density and the duration of REM cycles changed over the course of the night in children, with an increase until the fifth REM cycle and then a plateau. The TI/TT increased across REM cycles. However, in contrast to our initial hypothesis, neither the change in REM density nor the change in TI/TT affected the AHI.

Changes in REM Sleep with Age

We have shown that both REM duration and REM density increase over the course of the night in preschool-aged children and school-aged children. REM sleep distribution is known to change with age and development. Newborns have a predominance of active sleep, a state analogous to REM sleep, and frequently enter sleep through this stage.22 The proportion of REM then decreases during childhood, and continues to decrease further during adulthood and old age.2 Although REM density has been shown to increase over the course of the night in adults,3,14 REM density has not been well studied in children. Coble et al23 evaluated REM density, for the first 4 cycles of the night only, in a somewhat older group of children (6–16 years). They found that REM density tended to increase over the first 4 REM cycles of the night. Our study confirmed this finding in younger children and showed a highly significant increase in REM density across all REM cycles. Coble et al also noted a trend towards increased REM density in younger children, although this was only significant for the first and third REM cycles. Hoffman et al24 evaluated REM density in a small sample of females which included 2 prepubertal and 6 pubertal adolescents, and noted increased REM density in the prepubertal compared to the pubertal subjects. We found no relationship between age and REM density when evaluating a younger group of children, although there was a slight trend towards an increased REM density in younger children when only school-aged children were evaluated. Thus, in young children, there is no correlation between REM density and age.

The subjects in the current study had sleep architecture similar to that of a large, somewhat younger, normal population recently reported by Montgomery-Downs et al,25 with a similar total sleep time (459 minutes in the current study compared to 472–475 minutes in the Montgomery-Downs study), a similar percentage of REM sleep (20% in the current study compared to 20%–21% in the Montgomery-Downs study), and a similar number of REM cycles. This is not surprising, as many studies have shown no difference in sleep architecture between children with OSAS and normal controls,5 or children with OSAS before and after treatment.26,27 The duration of REM cycles across the night increased in the current study, similar to that reported by Montgomery-Downs. However, the Montgomery-Downs study did not evaluate REM density.

Apnea Hypopnea Index

A previous study showed an increase in the REM AHI in the last third of the night compared with the first third of the night.5 In that study, the night was arbitrarily divided into thirds, and only the first and last thirds of the night were evaluated, i.e., there was no evaluation of the intervening third. In contrast, the current study used sophisticated analytic techniques to evaluate the entire night. Although the current study found that the number of REM obstructions was greater during the last third of the night compared to the first third, when the intervening REM cycles were taken into account, the AHI did not change significantly across REM cycles. It is most likely that the difference between the 2 studies is due to the different analytic techniques used. Alternatively, the difference may be secondary to the inclusion of subjects with a wide distribution of AHI, as compared with the previous study, which evaluated subjects with more severe disease. However, this is less likely, as the results were similar when only subjects with an AHI >5/hr were studied. In addition, neither of the 2 subjects with very severe OSAS had their highest REM AHI during the last REM cycle. The variability in their patterns of AHI illustrates the importance of examining all REM cycles during the night.

Duty Cycle

The duty cycle (TI/TT) increased significantly across REM cycles. All of the subjects in this study presented with symptoms of OSAS and a history of habitual nightly snoring. Thus, all of the subjects had varying degrees of increased inspiratory resistance loading during sleep, ranging from snoring alone to obstructive sleep apnea.28 A prolonged TI has been shown to occur as a compensatory response to increased inspiratory resistance loading. This response has been shown to occur during both REM and NREM sleep,29,30 although the response during sleep is less than during wakefulness. Little is known about the relative contributions of upper airway and ventilatory pump muscles to breathing during sleep in children. In adults during wakefulness, it was recently suggested that the forces generated by these 2 sets of muscles are linearly related,31 but this may not apply during sleep. The TI/TT ratio probably represents the combined action of both upper airway muscles and ventilatory pump muscles. It is possible that inspiratory muscle (upper airway and pump) tone decreases as the night progresses, resulting in increased upper airway resistance. This can lead to a compensatory increase in TI/TT In support of this theory, we have previously shown that normal children have a dramatic decrease in tidal volume in response to inspiratory resistance loading during sleep, accompanied by an increase in TI/TT30 In contrast to adults,32 children manifest little recovery over time.30

An increased TI/TT may lead to ventilatory muscle fatigue.9 This could occur from continued work against an inspiratory load. Although previous studies (in adults) did not find evidence of diaphragmatic fatigue during sleep in patients with OSAS, these studies were all limited to NREM sleep.33,34 Furthermore, no studies have evaluated the upper airway muscles for fatigue over time. However, in the current study, the increased TI/TT across REM cycles was not associated with an increase in AHI, even in the more severely affected subjects, suggesting that clinically relevant muscle fatigue did not occur. It is possible that the increase in TI/TT across REM cycles was due to REM-related changes in upper airway neuromotor control or central regulation of ventilation. The latter appears unlikely. Animal studies using the carbachol model for REM sleep have shown a decrease in both inspiratory and expiratory time in response to carbachol injection,35 whereas studies in normal adults without sleep disordered breathing showed a decrease in expiratory time and TT in relation to REM density, but little change in TI.36 These studies are in contrast to the present study, which demonstrated an increase in TI/TTOT.

Limitations

It should be noted that polysomnograms were terminated at 06:00, due to laboratory scheduling issues. It is likely that some children would have had more REM cycles if they had been allowed to sleep until spontaneous awakening. However, total sleep time, proportion of REM time, and the number of REM cycles were similar to those previously reported for a large cohort of normal children,25 so it is unlikely that this had a major impact on our results.

Children with OSAS may have a pattern of persistent partial upper airway obstruction associated with hypercapnia, rather then discrete obstructive events. This has been termed obstructive hypoventilation.18 We did not analyze the relationship between hypercapnia and REM density, as this would have required analyzing the end-tidal PCO2 on a breath-by-breath basis. Future studies of this relationship would be of interest.

Conclusions

In conclusion, we have shown that REM density and the duty cycle (TI/TT) increase across REM cycles during the night in children. Despite this, the degree of obstructive apnea does not change significantly across REM cycles.

ACKNOWLEDGMENTS

Dr. Marcus was supported by NIH grants #HL58585, MO1-RR-000240 and U54 RR023567 and research support from Respironics, Inc. that funded a research technician. Dr. Mason was supported by K23 RR16566.

We thank all of the Children's Hospital of Philadelphia sleep laboratory technologists who helped conduct this study. We are grateful to the children and their families for their enthusiastic participation in this study.

Footnotes

Disclosure Statement

This was not an industry supported study. Dr. Brooks has participated in research supported by Cephalon. Dr. Marcus has received research support and use of equipment from Respironics. Ms. Karamessinis, Ms. Galster, Mr. Schultz, Ms. Elliott, Dr. Mason, and Mr. Gallagher have reported no financial conflicts of interest.

REFERENCES

  • 1.Fu J, Li P, Ouyang X, et al. Rapid eye movement sleep deprivation selectively impairs recall of fear extinction in hippocampus-independent tasks in rats. Neuroscience. 2007;144:1186–92. doi: 10.1016/j.neuroscience.2006.10.050. [DOI] [PubMed] [Google Scholar]
  • 2.Roffwarg HP, Muzio JN, Dement WC. Ontogenetic development of the human sleep-dream cycle. Science. 1966;152:604–19. doi: 10.1126/science.152.3722.604. [DOI] [PubMed] [Google Scholar]
  • 3.Takahashi K. Intensity of REM sleep. In: Mallick BN, Inoue S, editors. Rapid eye movement sleep. New York: Marcel Dekker, Inc; 1999. pp. 382–92. [Google Scholar]
  • 4.Redline S, Tishler PV, Schluchter M, Aylor J, Clark K, Graham G. Risk factors for sleep-disordered breathing in children. Associations with obesity, race, and respiratory problems. Am J Respir Crit Care Med. 1999;159:1527–32. doi: 10.1164/ajrccm.159.5.9809079. [DOI] [PubMed] [Google Scholar]
  • 5.Goh DY, Galster P, Marcus CL. Sleep architecture and respiratory disturbances in children with obstructive sleep apnea. Am J Respir Crit Care Med. 2000;162:682–6. doi: 10.1164/ajrccm.162.2.9908058. [DOI] [PubMed] [Google Scholar]
  • 6.Morielli A, Ladan S, Ducharme FM, Brouillette RT. Can sleep and wakefulness be distinguished in children by cardiorespiratory and videotape recordings? Chest. 1996;109:680–7. doi: 10.1378/chest.109.3.680. [DOI] [PubMed] [Google Scholar]
  • 7.Millman RP, Knight H, Kline LR, Shore ET, Chung DC, Pack AI. Changes in compartmental ventilation in association with eye movements during REM sleep. J Appl Physiol. 1988;65:1196–1202. doi: 10.1152/jappl.1988.65.3.1196. [DOI] [PubMed] [Google Scholar]
  • 8.Smith CA, Henderson KS, Xi L, Chow C, Eastwood PR, Dempsey JA. Neural-mechanical coupling of breathing in REM sleep. J Appl Physiol. 1997;83:1923–32. doi: 10.1152/jappl.1997.83.6.1923. [DOI] [PubMed] [Google Scholar]
  • 9.Bellemare F, Grassino A. Effect of pressure and timing of contraction on human diaphragm fatigue. J Appl Physiol. 1982;53:1190–5. doi: 10.1152/jappl.1982.53.5.1190. [DOI] [PubMed] [Google Scholar]
  • 10.Schneider BK, Pickett CK, Zwillich CW, et al. Influence of testosterone on breathing during sleep. J Appl Physiol. 1986;61:618–23. doi: 10.1152/jappl.1986.61.2.618. [DOI] [PubMed] [Google Scholar]
  • 11.Zwillich CW, Natalino MR, Sutton FD, Weil JV. Effects of progesterone on chemosensitivity in normal men. J Lab Clin Med. 1978;92:262–9. [PubMed] [Google Scholar]
  • 12.Rosner B, Prineas R, Loggie J, Daniels SR. Percentiles for body mass index in U. S. children 5 to 17 years of age. J Pediatr. 1998;132:211–22. doi: 10.1016/s0022-3476(98)70434-2. [DOI] [PubMed] [Google Scholar]
  • 13.Ktonas PY, Bes FW, Rigoard MT, Wong C, Mallart R, Salzarulo P. Developmental changes in the clustering pattern of sleep rapid eye movement activity during the first year of life: a Markov-process approach. Electroencephalogr Clin Neurophysiol. 1990;75:136–40. doi: 10.1016/0013-4694(90)90166-h. [DOI] [PubMed] [Google Scholar]
  • 14.Witzenhausen C, Bes FW, Schulz H. Evidence for a circadian distribution of eye movement density during REM sleep in humans. Sleep Res Online. 2001;4:59–66. [Google Scholar]
  • 15.Lucidi F, Devoto A, Violani C, De Gennaro L, Mastracci P, Bertini M. Rapid eye movements density as a measure of sleep need: REM density decreases linearly with the reduction of prior sleep duration. Electroencephalogr Clin Neurophysiol. 1996;99:556–61. doi: 10.1016/s0013-4694(96)95671-0. [DOI] [PubMed] [Google Scholar]
  • 16.Rechtschaffen A, Kales A. A manual of standardized terminology: Techniques and scoring systems for sleep stages of human subjects. Bethesda, MD: NINDB Neurological Information network (US); 1968. [Google Scholar]
  • 17.Sleep disorders atlas task force. Guilleminault C. C. EEG arousals: scoring rules and examples. Sleep. 1992;15:173–84. [PubMed] [Google Scholar]
  • 18.American Thoracic Society. Standards and indications for cardiopulmonary sleep studies in children. Am J Respir Crit Care Med. 1996;153:866–78. doi: 10.1164/ajrccm.153.2.8564147. [DOI] [PubMed] [Google Scholar]
  • 19.Marcus CL, Omlin KJ, Basinki DJ, et al. Normal polysomnographic values for children and adolescents. Am Rev Respir Dis. 1992;146(5 Pt 1):1235–9. doi: 10.1164/ajrccm/146.5_Pt_1.1235. [DOI] [PubMed] [Google Scholar]
  • 20.Sleep-related breathing disorders in adults: recommendations for syndrome definition and measurement techniques in clinical research. The Report of an American Academy of Sleep Medicine Task Force. Sleep. 1999;22:667–89. [PubMed] [Google Scholar]
  • 21.SAS/STAT User's Guide. Cary, NC: SAS Institute Inc; 1999. [Google Scholar]
  • 22.Sadeh A. Maturation of normal sleep patterns from childhood through adolescence. In: Loughlin GM, Carroll JL, Marcus CL, editors. Sleep and breathing in children: a developmental approach. New York: Marcel Dekker, Inc; 2000. pp. 63–78. [Google Scholar]
  • 23.Coble PA, Reynolds CF, III, Kupfer DJ, Houck P. Electroencephalographic sleep of healthy children. Part II: Findings using automated delta and REM sleep measurement methods. Sleep. 1987;10:551–62. [PubMed] [Google Scholar]
  • 24.Hoffmann G, Petre-Quadens O. Maturation of REM-patterns from childhood to maturity. Waking Sleeping. 1979;3:255–62. [PubMed] [Google Scholar]
  • 25.Montgomery-Downs HE, O'Brien LM, Gulliver TE, Gozal D. Polysomnographic characteristics in normal preschool and early school-aged children. Pediatrics. 2006;117:741–53. doi: 10.1542/peds.2005-1067. [DOI] [PubMed] [Google Scholar]
  • 26.Frank Y, Kravath RE, Pollak CP, Weitzman ED. Obstructive sleep apnea and its therapy; clinical and polysomnographic manifestations. Pediatrics. 1983;71:737–42. [PubMed] [Google Scholar]
  • 27.Marcus CL, Carroll JL, Koerner CB, Hamer A, Lutz J, Loughlin GM. Determinants of growth in children with the obstructive sleep apnea syndrome. J Pediatr. 1994;125:556–62. doi: 10.1016/s0022-3476(94)70007-9. [DOI] [PubMed] [Google Scholar]
  • 28.American Academy of Sleep medicine. 2nd ed. Westchester, IL: American Academy of Sleep Medicine; 2005. The International Classification of Sleep Disorders. [Google Scholar]
  • 29.Wiegand L, Zwillich CW, White DP. Sleep and the ventilatory response to resistive loading in normal men. J Appl Physiol. 1988;64:1186–95. doi: 10.1152/jappl.1988.64.3.1186. [DOI] [PubMed] [Google Scholar]
  • 30.Marcus CL, Moreira GA, Bamford O, Lutz J. Response to inspiratory resistive loading during sleep in normal children and children with obstructive apnea. J Appl Physiol. 1999;87:1448–54. doi: 10.1152/jappl.1999.87.4.1448. [DOI] [PubMed] [Google Scholar]
  • 31.Shepherd KL, Jensen CM, Maddison KJ, Hillman DR, Eastwood PR. Relationship between upper airway and inspiratory pump muscle force in obstructive sleep apnea. Chest. 2006;130:1757–64. doi: 10.1378/chest.130.6.1757. [DOI] [PubMed] [Google Scholar]
  • 32.Badr MS, Skatrud JB, Dempsey JA, Begle RL. Effect of mechanical loading on expiratory and inspiratory muscle activity during NREM sleep. J Appl Physiol. 1990;68:1195–1202. doi: 10.1152/jappl.1990.68.3.1195. [DOI] [PubMed] [Google Scholar]
  • 33.Montserrat JM, Kosmas EN, Cosio MG, Kimoff RJ. Lack of evidence for diaphragmatic fatigue over the course of the night in obstructive sleep apnoea. Eur Respir J. 1997;10:133–8. doi: 10.1183/09031936.97.10010133. [DOI] [PubMed] [Google Scholar]
  • 34.Cibella F, Cuttitta G, Romano S, Bellia V, Bonsignore G. Evaluation of diaphragmatic fatigue in obstructive sleep apnoeas during non-REM sleep. Thorax. 1997;52:731–5. doi: 10.1136/thx.52.8.731. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Kimura H, Kubin L, Davies RO, Pack AI. Cholinergic stimulation of the pons depresses respiration in decerebrate cats. J Appl Physiol. 1990;69:2280–9. doi: 10.1152/jappl.1990.69.6.2280. [DOI] [PubMed] [Google Scholar]
  • 36.Neilly JB, Gaipa EA, Maislin G, Pack AI. Ventilation during early and late rapid-eye-movement sleep in normal humans. J Appl Physiol. 1991;71:1201–15. doi: 10.1152/jappl.1991.71.4.1201. [DOI] [PubMed] [Google Scholar]

RESOURCES