Sleep Pressure Score: a New Index of Sleep Disruption in Snoring Children
Riva Tauman, MD; Louise M. O’Brien, PhD; Cheryl R. Holbrook, MAT, RPSGT; David Gozal, MD
Kosair Children’s Hospital Research Institute, and Division of Pediatric Sleep Medicine, Department of Pediatrics, University of Louisville, Kentucky
increases relative to AHI, reaching a plateau at an AHI of 30 to 40 per hour
of total sleep time. Furthermore, SPS values were significantly higher
among African American and obese children (P < .0001).
Conclusions: Sleep architecture is not preserved in children with SDB.
An algorithm allowing for calculation of sleep propensity and disturbed
sleep homeostasis in children who snore is proposed and may be of practical value in the assessment of sleepiness.
Key Words: sleep architecture, arousal, sleep fragmentation, sleepiness,
snoring, sleep-disordered breathing
Abbreviations: AHI, Apnea-hypopnea Index; Artot, Total arousal; ARtotI,
Total arousal index; BMI, Body mass index; EDS, Excessive daytime
sleepiness; OSA, Obstructive sleep apnea; RAI, Respiratory Arousal
Index; REM, Rapid eye movement; SAI, Spontaneous Arousal Index;
SDB, Sleep-disordered breathing; SWS, Slow-wave sleep; TST, Total
sleep time; SpO2, Arterial oxygen saturation measured by pulse oximetry;
SPS, Sleep pressure score
Citation: Tauman R; O’Brien LM; Holbrook CR; Gozal D. Sleep pressure
score: a new index of sleep disruption in snoring children. SLEEP 2004;
27(2):274-8.
Study Objectives: Excessive daytime sleepiness (EDS), as measured by
objective criteria, is infrequent in snoring children despite a high prevalence of EDS-related behavioral manifestations. We hypothesized that
sleep architecture and arousal indexes may be altered relative to the
severity of sleep-disordered breathing (SDB).
Design: Retrospective and prospective study.
Setting: Questionnaires were distributed through sleep clinic or school
program; polysomnograms were performed at Kosair Children’s Hospital
in Louisville, Kentucky.
Participants: To examine this issue, 182 children with SDB, 163 children
with primary snoring, and 214 control children with a mean age of 6.9 ±
2.6 years underwent polysomnographic evaluation in the laboratory.
Measurements and Results: Significant increases in slow-wave sleep
(percentage of total sleep time) and decreases in rapid eye movement
sleep (percentage of total sleep time) occurred in the SDB group (P <
.0001). Spontaneous and respiratory arousal indexes and the apneahypopnea index (AHI) displayed negative and positive correlations,
respectively, suggesting reciprocal interactions. Based on these observations, a sleep pressure score (SPS) was derived as a surrogate numeric
measure for disrupted sleep homeostasis. The SPS exhibited linear
INTRODUCTION
SUBJECTS AND METHODS
SLEEP-DISORDERED BREATHING (SDB) IS A FREQUENT CONDITION AFFECTING BOTH CHILDREN AND ADULTS.1-4 In adults,
SDB is associated with substantial sleep fragmentation and with
decreases in the percentages of slow-wave sleep (SWS) and rapid eye
movement (REM) sleep.5-8 In contrast, sleep fragmentation appears to be
an unusual feature in children with SDB.9-11 Consequently, excessive
daytime sleepiness (EDS), a major symptom in adults with SDB,12 is
also infrequent in children,13,14 even if EDS-like morbidity may be present. Indeed, school and behavior problems similar to those observed in
children with attention-deficit/hyperactivity disorder have been repeatedly reported in children with SDB15-18 and are reversed, at least partially, after treatment of SDB.19-21 The dichotomy between preserved sleep
architecture in children with SDB and the frequent occurrence of neurobehavior manifestations attributable to EDS in these children suggests
that current measures of sleepiness are inadequate and that subtle
changes in sleep homeostasis may occur during childhood when SDB is
present. To further examine these possibilities, we hypothesized that
sleep-stage distribution and the various arousal indexes may change as a
function of SDB severity.
A retrospective chart review of consecutive snoring children who
were evaluated for the presence of SDB at Kosair Children’s Hospital
Sleep Medicine Center from July 2001 to January 2003 were included in
the study. In addition, children were prospectively recruited from a community survey of sleep habits. The study was approved by the University
of Louisville Human Research Committee and the Jefferson County
Public Schools Board, and parental informed consent and child assent,
in the presence of a parent, were obtained. A standard overnight multichannel polysomnographic evaluation was performed in the sleep laboratory. Children were studied for up to 12 hours in a quiet darkened room
with an ambient temperature of 24oC in the company of one of their parents. No drugs were used to induce sleep. The following parameters
were measured: chest and abdominal wall movement by respiratory
impedance or inductance plethysmography, heart rate by electrocardiogram, air flow was monitored with a sidestream end-tidal capnograph
that also provided breath-by-breath assessment of end-tidal carbon dioxide levels (PETCO2; BCI SC-300, Menomonee Falls, Wis), and a thermistor. Arterial oxygen saturation (SpO2) was assessed by pulse oximetry (Nellcor N 100; Nellcor Inc, Hayward, Calif), with simultaneous
recording of the pulse waveform. The bilateral electrooculogram, 8
channels of electroencephalogram, chin and anterior tibial electromyograms, and analog output from a body-position sensor (Braebon Medical
Corporation, NY) were also monitored. All measures were digitized
using a commercially available polysomnography system (Rembrandt,
MedCare Diagnostics, Amsterdam, Holland). Tracheal sound was monitored with a microphone sensor (Sleepmate, Va), and a digital time-synchronized video recording was performed.
Sleep architecture was assessed by standard techniques.22 The proportion of time spent in each sleep stage was expressed as percentage of
total sleep time (%TST). Awakenings were defined as a sustained
arousal lasting for at least 15 seconds. Sleep efficiency was defined as
TST divided by total recording time. The apnea index was defined as the
number of apneas per hour of TST. Central, obstructive, and mixed
apneic events were counted. Obstructive apnea was defined as the
Disclosure Statement
This study was supported by National Institutes of Health grant HL-65270,
Department of Education Grant H324E011001, Centers for Disease Control and
Prevention Grant E11/CCE 422081-01, and The Commonwealth of Kentucky
Research Challenge Trust Fund. Riva Tauman was supported by a Kosair Charities
Research Fellowship and a Ohio Valley American Heart Association Fellowship.
Submitted for publication June 2003
Accepted for publication October 2003
Address correspondence to: David Gozal, MD, Kosair Children’s Hospital
Research Institute, University of Louisville School of Medicine, 571 S. Preston
Street Suite 321, Louisville, KY 40202; Tel: 502-852-2323; Fax: 502-852-2215;
E-mail: david.gozal@louisville.edu
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Sleep Pressure in Children—Tauman et al
absence of airflow with continued chest-wall and abdominal movement
for duration of at least 2 breaths.23-24 Hypopneas were defined as a
decrease in nasal flow of at least 50% with a corresponding decrease in
SpO2 of at least 4%, an arousal, or both.24 The obstructive apnea-hypopnea index (AHI) was defined as the number of apneas and hypopneas per
hour of TST. Children with an AHI of at least 1 but less than 5 per hour
of TST were considered to have mild SDB (mild group), while children
with an AHI of at least 5 per hour of TST were considered to have clinically significant SDB, or obstructive sleep apnea (OSA group). Control
children were defined as children with an AHI less than 1 per hour of
TST. Periodic leg movements during sleep were scored if there were at
least 4 movements of 0.5- to 5-seconds duration and between 5 and 90
seconds apart. A periodic leg movements index of at least 5 per hour of
sleep is generally considered as exceeding the normal range in children.25 Periodic leg movement-associated arousals were also scored.
The mean SpO2 in the presence of a pulse waveform signal void of
motion artifact and the SpO2 nadir were recorded. Because criteria for
arousals have not yet been developed for children, arousals were defined
as recommended by the American Sleep Disorders Association Task
Force report26 using the 3-second rule, the presence of movement
arousal, or both.27 Arousals were divided into 2 types: spontaneous
arousals and respiratory arousals, the latter occurring within 3 seconds
following an apnea, hypopnea, or snore. The total number of arousals
(ArTOT) was also calculated and included the sum of respiratory arousals,
spontaneous arousals, periodic leg movement-associated arousals, and
technical arousals. The corresponding arousal indices were calculated as
a function of TST duration and are expressed as per hour of TST (total
arousal index [ARtotI], spontaneous arousal index [SAI], and respiratory arousal index [RAI]). Children with TST less than 4 hours or with no
SWS or REM sleep were excluded.
Data Analysis
Data are presented as means ± SD unless otherwise indicated.
Comparisons of demographics and sleep variables according to group
assignment were made with independent t tests (continuous variables)
with P values adjusted for unequal variances when appropriate
(Levene’s test for equality of variances) or χ2 analyses with Fisher exact
test (dichotomous outcomes). Correlations between arousals indexes and
AHI were performed using polynomial regressions aiming to optimize
Table 1—Demographic and polysomnographic characteristics of 559
children correlated with apnea-hypopnea index
AHI < 1
Controls
n = 214
Age, y
6.8 ± 1.4
(2-15)
Sex, boys:girls
112:102
2
Body mass index, kg/m
17.7 ± 5.0
(11.6-43.3)
Total sleep time (TST), min
444.9±52.6
Sleep efficiency, %
88.5 ± 8.4
Awakenings, no.
5.4 ± 4.8
Stage 1, percentage of TST
9.0 ± 6.9
Stage 2, percentage of TST
44.5 ± 8.6
SWS, percentage of TST
23.5 ± 7.6
REM sleep, percentage of TST 22.3 ± 7.0
Total Arousal Index
9.8 ± 4.4
Spontaneous Arousal Index
8.4 ± 3.7
Respiratory Arousal Index
0.8 ± 0.1
SpO2 nadir, %
89.7 ± 7.2
PLM index
2.47 ± 0.4
PLMA index
0.14 ± 0.1
AHI 1-5
Mild SDB
n = 183
AHI > 5
OSA
n = 162
6.6 ± 2.1
(1-14)
103:80
18.9 ± 5.7
(11.8-46.4)
446.9±60.9
89.3 ± 8.9
6.3 ± 6.9
8.7 ± 8.1
41.5 ± 11.6
25.9 ± 10.7‡
21.4 ± 6.9
11.0 ± 4.2‡
8.5 ± 3.6
2.0 ± 0.2‡
90.9 ± 4.6
1.59 ± 0.2
0.52 ± 0.1
7.4 ± 3.8*
(1-18)
99:63
23.2 ± 10.0*†
(7.14-67.3)
415.2±71.7*†
86.7 ± 11.5
12.2 ± 9.7*†
8.0 ± 6.8
40.8 ± 31.9
28.8 ± 11.4†
17.3 ± 7.5§†
20.9 ± 15.1*†
5.3 ± 3.9*†
14.5 ± 1.2*†
84.4 ± 12.7§†
2.15 ± 0.4
1.1 ± 0.3
Data are given as mean ± SD (range). AHI refers to apnea-hypopnea index; SDB, sleepdisordered breathing; OSA, obstructive sleep apnea; REM, rapid eye movement; PLM,
periodic limb movements of sleep; PLMA, PLM associated with arousal.
*P < .05 OSA vs controls; †P < .005 OSA vs mild SDB; ‡P < .05 Mild SDB vs controls;
§P < .005 OSA vs controls
SLEEP, Vol. 27, No. 2, 2004
Figure 1—Scatterplots of total arousal index ([ArtotI] upper panel), spontaneous arousal
index ([SAI] middle panel), and respiratory arousal index ([RAI] lower panel) in 559 children. Linear regression lines are shown (see text for details). AHI refers to apnea-hypopnea
index.
275
Sleep Pressure in Children—Tauman et al
goodness of fit, followed by calculation of correlation coefficients.
Multivariate analysis was conducted to determine any relationship of
sleep pressure score (SPS) to ethnicity using AHI, BMI, and sex as
covariates. All P values reported are 2-tailed with statistical significance
set at <.05.
ostasis in this cohort and could potentially represent an index of sleep
pressure (ie, SPS).
We propose the following formula as best representing this concept as
follows: SPS = RAI/ARtotI * (1 - SAI/ARtotI). When the SPS was calculated in relation to the 2 curve-fitting functions delineated above,
increases in SPS followed a predicted trajectory, displaying increased
SPS as a function of log AHI (Figure 3). Based on this model, the SPS
corresponding to the point at which spontaneous arousals/ARtotI and
RAI/ARtotI are identical was calculated at 0.25 and selected as the cutoff point for increased sleep pressure (Figure 3). Of note, the AHI corresponding to the SPS cutoff value was calculated at approximately 7 per
hour of TST.
To further verify this presumption, the SPS was calculated for each of
the study participants and plotted against the corresponding AHI (Figure
4). The SPS exhibited substantial increases as a function of AHI until it
reached a plateau in the vicinity of an AHI between 30 and 40 per hour
of TST (Figure 4). No differences in the mean SPS values were apparent
in relation to sex or age. However, at any given level of AHI, mean SPS
values were significantly higher among African American children compared to Caucasian children (P < .0001, corrected for AHI, BMI, and
sex). In addition, the SPS for the whole group was significantly correlated with BMI (r = .52, P < .0001).
RESULTS
A total of 559 children (314 boys) with valid sleep recordings were
included in the study. Of these, 162 children (99 boys) were found to
have OSA, 183 children (103 boys) had mild SDB, and 214 children
(112 boys) were in the control group. Subject characteristics are shown
in Table 1.
The BMI was higher in the OSA group compared to the control and
mild SDB groups (P < .001). The TST was significantly shorter in the
OSA group compared to both mild SDB and control groups (P = .003
and P = .0.008, respectively). However, there were no significant differences in sleep efficiency between the 3 groups. After adjusting for TST,
a significant increase in the percentage of SWS was found in the OSA
group and in the mild SDB group compared to controls (P < .001 and P
= .03, respectively). Conversely, significant reductions in REM-sleep
percentage were observed in the OSA group compared to both mild SDB
and control groups (P < .0001).
A higher ARtotI and increased frequency of awakenings during the
night occurred in the OSA group compared to both mild SDB and control groups (P < .0001). For the total cohort, ARtotI showed a positive
linear relationship with AHI (Figure 1; r = 0.80; P < .0001). Similarly,
the RAI showed a significant relationship with AHI (Figure 1; r=0.88; P
< .0001). However, the slope of the latter was steeper than that for
ARtotI (0.68 versus 0.59). In contrast, the SAI showed an inverse relationship with AHI (Figure 1; r = -0.31; P < .0001).
Based on these findings, we further examined whether these reciprocal relationships between AHI, SAI, and RAI would persist when
expressed as a function of the ARtotI. When individual values for
SAI/ARtotI were plotted against their corresponding log AHI values, a
2-factor exponential curve-fitting function significantly improved the
goodness of fit (Figure 2; r2 = 0.76). RAI/ARtotI could also be
expressed as a 2-factor exponential curve fitting function (Figure 2; r2 =
0.77). From the equations derived from these data, a model was created
and clearly displays the reciprocal interaction between SAI/ARtotI and
RAI/ARtotI (Figure 3). Based on these relationships, we formulated the
hypothesis that a function incorporating all 3 arousal indexes would
allow for description of a surrogate measure of disrupted sleep home-
DISCUSSION
Our study shows that significant dynamic changes occur in sleep
architecture and manifest as increases in SWS and decreases in REM
sleep, as well as changes in arousal indexes. Furthermore, these changes
in arousal exhibit dose dependency in relation to the severity of SDB.
Thus, contrary to published reports, sleep is not strictly preserved in children with SDB, but, rather, compensatory mechanisms most likely aiming to preserve sleep homeostasis lead to declines in spontaneous arousal
that parallel and partially compensate for the reciprocal increase in respiratory arousals. We further show that these relationships can be incorporated into a single equation yielding a factor that we have termed SPS
that accounts for such reciprocal changes in arousal. This factored number appears to represent the anticipated increases in sleep pressure that
occur with SDB. Indeed, the SPS correlated linearly with AHI until
reaching a plateau at an AHI corresponding to extremely severe SDB in
children.
The increase in SWS found in this study contrasts with previous
reports on smaller cohorts.9-11 The reason for such discrepancies is
unclear and may reflect differences in the population studied or in sleep-
Figure 2—Left Panel: Scatterplot of the ratio between spontaneous arousal index (SAI) and total arousal index (ARtotI) plotted against log apnea-hypopnea index (AHI) in 559 children.
Polynomial fitting procedures revealed the following function: y = 0.84031 - 0.28606 x - 0.1972 x2 + 0.06025 x3 (r2, -0.77; P < .00001). The regression line is shown. Right Panel: Scatterplot
of the ratio between respiratory arousal index (RAI) and ARtotI plotted against log AHI in 559 children. Polynomial fitting procedures revealed the following function: y = 0.09852 + 0.27605
x+0.20837 x2-0.05588 x3 (r2, -0.76; P < .00001). The regression line is shown.
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Sleep Pressure in Children—Tauman et al
Figure 3—Left Panel: Polynomial functions derived from 559 children for spontaneous arousal index (SAI) and respiratory arousal index (RAI) plotted against log apnea-hypopnea index
(AHI) (see Figure 2). The reciprocal relationships between SAI and RAI as a function of total arousal index (ARtotI) are shown. Arrow indicates the value of the sleep pressure score (SPS)
at the intersection of the 2 functions (see text for details). Right Panel: The SPS derived from the polynomial equations and calculated as SPS = RAI/ARtotI*(1-SAI/ARtotI) is plotted against
log AHI. A progressive increase in SPS with increasing AHI is apparent.
adults.10,32 However, such an assumption is not supported by the marked
and at least partially reversible neurocognitive and behavioral morbidities found in children with SDB, the latter further suggesting that the
morbidities may result from the presence of sleep disturbance. Indeed,
subtle changes in electroencephalographic characteristics occur during
obstructive apneic events even in the absence of visually recognizable
arousals.33 In a study by Goh and colleagues,10 the indexes for spontaneous arousals and for respiratory arousals were exceedingly low, even
lower than those found in normal children,14 despite the presence of relatively severe SDB in their cohort. It is unclear whether the criteria used
for definition of arousal differed from those used in the present study.
The different and reciprocal changes in the distribution of spontaneous and respiratory arousals in relation to the severity of SDB
expressed as AHI support the notion that, with increasing SDB severity,
children will develop compensatory neural mechanisms that attenuate
the responsiveness and elevate the arousal threshold to nonrespiratory
triggers, most possibly in an effort to compensate for the increase in respiratory-related arousals. In support of this notion, Fewell et al reported
changes in arousal latency during repeated upper-airway obstruction in
lambs.34-35 It is possible that this decrease in the nonrespiratory fraction
of arousals represents an effort to preserve sleep homeostasis in children
with SDB. Taking advantage of the reciprocal relationships that emerged
in our large cohort between SAI and RAI, we found that the SPS factor
was closely correlated with AHI. Based on the intersection of the 2 exponential fitting functions that accounted for the best fit for spontaneous
and respiratory arousals in relation to AHI, the predicted cutoff point for
SPS was calculated at 0.25 and corresponded to an AHI of approximately 7 per hour of TST. This is clearly a lower AHI than the one we previously reported when measuring sleep propensity using Multiple Sleep
Latency Test, whereby an AHI greater than 15 to 20 per hour of TST was
necessary to detect EDS in children.14 However, these 2 findings are not
contradictory; rather, they suggest that SPS may be a more sensitive correlate of sleepiness than is Multiple Sleep Latency Test in children who
snore. Indeed, at an AHI greater than 15 per hour of TST, only 2 children
had an SPS less than 0.25 (Figure 4). As previously reported using subjective36 and objective criteria,14 higher SPS values were more likely to
occur in obese children, suggesting that the latter may be more vulnerable to sleep fragmentation. Similarly, ethnic-related differences in SPS
emerged, with African American children having higher SPS values at
any given level of AHI, thereby corroborating our previous findings
(Gozal D, unpublished observations). In a companion manuscript, we
further examine the neurobehavioral implications of SPS and show that
Figure 4—Sleep pressure score (SPS) calculated for each participant plotted against corresponding obstructive apnea-hypopnea index (AHI) in 559 children. The arrow and lines
used for the proposed SPS cutoff of 0.25 are also shown. The SPS increases with increasing AHI until a plateau is reached at approximately 30 to 40 events per hour of total sleep
time.
scoring practices. It is possible that the increased duration of SWS in
children with SDB will not only elevate their arousal threshold, but also
reflect the increased sleep pressure associated with REM-sleep disruption, the sleep state in which the preponderance of respiratory events will
occur. Thus, increases in SWS could represent a strategy to preserve
sleep homeostasis in the context of a relative inability to preserve REM
sleep, since the majority of respiratory events occur in REM sleep in
children.10,14,28-30 Of note, even children with mild SDB exhibit significant, albeit smaller, reductions in REM sleep than do controls (Table 1).
In marked contrast to adult patients with SDB, children who snore
and are referred for evaluation of SDB infrequently have EDS as a presenting complaint.13,30 In fact, hyperactivity and behavior disturbances
appear to be more indicative of underlying sleepiness in children with
SDB18,31 than is the presence of EDS using either subjective13,30 or objective criteria such as the Multiple Sleep Latency Test.14 The initial
assumption following these findings was that children with SDB do not
arouse from their respiratory events during sleep as often as adults do
and that, therefore, sleep architecture is better preserved than in
SLEEP, Vol. 27, No. 2, 2004
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Sleep Pressure in Children—Tauman et al
this numeric factor provides a sensitive and independent correlate of
cognitive and behavioral morbidity in children who snore.
In summary, in a large cohort of normal and snoring children, sleep
architecture is not preserved and undergoes substantial SDB severity
dependent changes, particularly in SWS and REM-sleep distribution as
well as in arousal subtype frequencies. Such changes in sleep structure
may reflect activation of homeostatic sleep mechanisms and their relative failure with increasing SDB severity. We further propose a new
numeric factor, the SPS, which may provide an easy and potentially useful estimate of sleep pressure in children who snore.
erwise healthy children. Pediatr Pulmonol 1999;27:403-409.
31. O'Brien LM, Gozal D. Behavioural and neurocognitive implications of snoring and
obstructive sleep apnoea in children: facts and theory. Paediatr Respir Rev 2002;3:3-9.
32. McNamara, F., F. G. Issa, and C. E. Sullivan. Arousal pattern following central and
obstructive breathing abnormalities in infants and children. J Appl Physiol
1996;81:2651-7.
33. Bandla HPR, Gozal D. Dynamic changes in EEG spectra during obstructive apnea in
children. Pediatr Pulmonol 2000;29:359-65.
34. Fewell JE, Williams BJ, Szabo JS, Taylor BJ. Influence of repeated upper airway
obstruction on the arousal and cardiopulmonary response to upper obstruction in lambs.
Pediatr Res 1988;23:191-5.
35. Fewell JE. The effect of short-term sleep fragmentation produced by intense auditory
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36. Marcus CL, Curtis S, Koerner CB, Joffe A, Serwint JR, Loughlin GM. Evaluation of
pulmonary function and polysomnography in obese children and adolescents. Pediatr
Pulmonol 1996;21:176-83.
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