PEDIATRICS Vol. 108 No. 3 September 2001, pp. 693-697

Objective Sleepiness Measures in Pediatric Obstructive Sleep Apnea

David Gozal, MD, FAAP, Mei Wang, PhD, and Dennis W. Pope Jr, REPSGT

From the Kosair Children's Hospital Sleep Medicine and Apnea Center, Division of Pediatric Sleep Medicine, Department of Pediatrics, University of Louisville, Louisville, Kentucky.

	ABSTRACT

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Objectives.  Excessive daytime sleepiness (EDS) occurs frequently in adult patients with obstructive sleep apnea (OSA). However, the incidence of EDS in children with OSA is unknown.

Methods.  To determine overall daytime sleepiness in pediatric OSA, 54 children with OSA, 14 children with primary snoring (PS), and 24 controls (C) underwent an overnight diagnostic polysomnogram followed the next day by a multiple sleep latency test.

Results.  The mean apnea index was 15.1 ± 9.5 standard deviation in OSA, 1.1 ± 0.5 in PS, and 0.1 ± 0.3 in C. Mean sleep latencies were 23.7 ± 3.0 minutes in C, 23.7 ± 3.1 minute in PS, and 20.0 ± 7.1 minute in OSA patients. However, only 7 children with OSA had mean sleep latencies <10 minutes. In addition, shorter sleep latencies were more likely to occur in more obese OSA patients and those with more severe apnea index, and oxyhemoglobin desaturation.

Conclusions.  Shortened sleep latencies occur in children with OSA, but EDS is infrequent and tends to develop among more severe and/or obese patients.  Key words:  sleepiness, sleep apnea, obstructive hypoventilation, intermittent hypoxia, arousal.

It has become clear that adults with obstructive sleep apnea (OSA) frequently exhibit excessive daytime sleepiness (EDS).^1,2 However, it remains unclear whether EDS is a frequent manifestation of OSA in prepubertal children. Indeed, although earlier clinical reports of OSA in children indicated that EDS was a frequent feature of OSA in children,^3,4 more recent assessment of this issue using parental questionnaires suggested that EDS is only present in a minority of pediatric OSA patients,⁵ and that subjective EDS tends to be clustered among the more obese children.⁶ However, EDS was not objectively measured and the earlier parental reports may have reflected more severely affected children.

Multiple sleep latency test (MSLT) constitutes one of the better established tests for assessment of daytime sleepiness.^7-9 In prepubertal children, daytime sleep propensity as assessed by MSLT is reduced compared with pubertal children,¹⁰ and sleep latencies <10 minutes are unusually found among healthy prepubertal children.¹¹ Although sleepiness is a rather unusual feature in young children during daytime, its manifestations can be subtle,¹² and therefore the identification of EDS by parents and school teachers may be difficult.

We conducted the present study to more objectively examine the frequency of EDS among prepubertal children with suspected sleep disordered breathing attributable to enlarged tonsils and adenoids.

	PATIENTS AND METHODS

Prepubertal children clinically followed at the Tulane or Kosair Children's Hospital Comprehensive Sleep Medicine Center were invited to participate in the study, which received institutional experimental human subject committee approval. Participants were eligible if they had no medical conditions apart from suspected obstructive sleep apnea syndrome (OSAS) secondary to adenotonsillar hypertrophy, based on history and a disease-oriented questionnaire, and were referred for a sleep study to rule out OSA. All patients with suspected gastroesophageal reflux (ie, requiring studies with pH probes), a history of previous treatment of OSAS (including tonsillectomy and adenoidectomy), or referred for titration of continuous positive airway pressure therapy attributable to sleep-disordered breathing therapy were excluded. Patients were compared with age-matched, asymptomatic, nonsnoring control children who were previously recruited from the community as control participants for other ongoing research studies.

The parents of all participants filled a previously validated questionnaire that inquired on the frequency of snoring, breathing problems during sleep, and daytime sleepiness.¹³

A standard overnight, multichannel, polysomnographic evaluation was performed at the sleep laboratory within Kosair Children's Hospital or Tulane Hospital for Children. Children were studied for at least 8 hours in a quiet, darkened room with an ambient temperature of 24^oC in the company of 1 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, which also provided breath-by-breath assessment of end-tidal carbon dioxide levels (P_ETCO₂; PryonSC-300, Menomonee Falls, WI), as well as a nasal pressure transducer (Braebon, Canada) and/or a thermistor. Arterial oxygen saturation (SaO₂) was assessed by pulse oximetry (Nellcor N 100; Nellcor Inc, Hayward, CA), with simultaneous recording of the pulse wave form. The bilateral electro-oculogram, 8 channels of electroencephalogram, chin and anterior tibial electromyograms, and analog output from a body position sensor were also monitored. All measures were digitized using a commercially available polysomnography system (Stellate Systems, Montreal, Canada). Tracheal sound was monitored with a microphone sensor and a digital time-synchronized video recording was performed.

The morning after the polysomnographic study, a MSLT was performed to evaluate the effect of sleep disordered breathing on sleepiness. The MSLT was conducted at 10:00, 12:00, 14:00, and 16:00 hours, and standard procedures were followed,⁸ except that the children were given 30-minute opportunities to fall asleep, and thereby reduce the likelihood of missing differences across conditions.^11,14 Parents were requested to stay in the room with their child to eliminate any external apprehension. Each latency test was abrogated after 3 successive 30-second epochs of stage 1 sleep or one epoch of any other stage sleep. The sleep latency for each trial was calculated as the time elapsed from "lights out" to the first epoch of sleep. If no sleep occurred during a nap, the sleep latency for that nap was assigned a value of 30 minutes

Sleep studies were interpreted according to recently published pediatric criteria.¹⁵ The apnea index (AI) was defined as the number of obstructive and mixed apneas, of at least 2 respiratory cycles duration, per hour of total sleep time.^15,16 For this study purpose, hypopneas were not quantified because of the lack of standard definition of hypopneas in children.¹⁵ For assessment of arterial oxygen saturation, the SaO₂ nadir and mean SaO₂ were determined. SaO₂ measurements associated with a poor pulse waveform were discounted. An SaO₂ nadir <92% was considered abnormal.¹⁷ The mean and peak end-tidal PCO₂ (P_ETCO₂) were determined. P_ETCO₂ measurements associated with a poor waveform were discounted. Obstructive hypoventilation was assessed by measuring the percentage of total sleep time with P_ETCO₂ 48 mm Hg.¹⁸ Sleep architecture was scored in 30-second epochs according to the criteria outlined by Rechtschaffen and Kales.¹⁹ Because there is no consensus on definitions for pediatric arousals, arousals were defined according to the standard American Sleep Disorders Association criteria.²⁰ Arousals were further classified as respiratory-related (occurring immediately after an apnea or during alveolar hypoventilation associated with increasing respiratory efforts), technician-induced (related to external disturbances), or spontaneous (not associated with any of the above). The arousal index was calculated as the number of respiratory and spontaneous arousals per hour of total sleep time.

Data Analysis

Participants' body mass index (BMI) was calculated using a standard formula and expressed as percentile using recently developed norms.²¹ For the purposes of this, study children were defined as primary snorers (PS) if the AI was 2 apnea/hr percentage of total sleep time (TST). Children with AI >2 were considered to represent OSA. Sleep latencies for each time point during the day were compared across groups using 2-tailed t tests or analysis of variance followed by posthoc tests as appropriate. Linear regression analysis was performed to evaluate potential relationships between sleep latency, age, AI, BMI, TST spent in alveolar hypoventilation, percentage of TST spent with SaO₂ <90%, and arousal index. Mean sleep latency was defined as the dependent variable, and we first ascertained that it was normally distributed using univariate procedures of skewness and kurtosis. After univariate regression analysis was completed, stepwise multivariate regression procedures were applied to identify independent variables primarily contributing to decreases in mean sleep latency in the OSA cohort. A P value <.05 was considered to achieve statistical significance.

	RESULTS

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Fifty-four children with OSA, 14 children with PS, and 24 controls (C) completed the study. Participant characteristics are shown in Table 1. In OSA, the mean AI was 15.1 ± 9.4, 1.1 ± 0.5 in PS, and 0.1 ± 0.3 in C (P < .0001 vs PS or C; PS vs C: P < .001). The severity of apnea index was positively correlated with BMI (r: 0.63, P < .0001), but not with age.

Mean daytime sleep latencies were 23.7 ± 3.0 minutes in C, 23.7 ± 3.1 minutes in PS, and 20.0 ± 7.1 minutes in OSA patients (P < .01 analysis of variance vs PS or C). The evolution of sleep latencies throughout the day is shown in Fig 1 for the 3 groups, and illustrates the early afternoon increase in sleep propensity in all study groups. Only 7 children with OSA (13%) had mean sleep latencies <10 minutes. Of note, only 4 parents indicated daytime sleepiness in the questionnaire (7.5%), and of these, only 1 had MSLT <10 minutes. Sleep latencies were more likely to be shorter in OSA patients with more severe apnea index (Fig 2; r: 075; P < .0001), with higher arousal index (r: 0.69, P < .001), with higher percent of total sleep time spent with SaO₂ below 90% (r: 0.70; P < .001) and with higher BMI (r: 0.78, P < .0001). There were no significant linear relationships between age and the degree of obstructive hypoventilation and MSLT in this cohort of OSA patients. After univariate regression analyses, stepwise multivariate regression procedures were conducted in an attempt to identify which independent variables primarily contributed to decreases in mean sleep latency in the OSA cohort. A significant model emerged (F2,49 = 63 820, P < .0005), in which apnea index (: 0.509, P < .0005) and BMI (: 0.431, P < .0005) were the only 2 independent variables contributing significantly to prediction of the mean sleep latency.

View larger version (18K): [in this window] [in a new window]   Fig. 1.   Mean (± standard error) sleep latencies in 54 OSA patients (), 14 PS children (), and 24 control () children. (OSA vs PS or C: P < .01).

View larger version (20K): [in this window] [in a new window]   Fig. 2.   Scatterplot of individual sleep latencies in 54 OSA patients (), 14 PS children (), and 24 control () children plotted against corresponding apnea indices. Linear regression analysis (dotted line) revealed a significant negative correlation between sleep latency and apnea index in 54 OSA patients (r: 075; P < .0001). However, such relationship was not present in control or children with PS. The horizontal lines show that the effect of EDS definition criteria on the prevalence of EDS in the cohort with OSA. If EDS is defined as a mean sleep latency of 15 minutes (upper horizontal line), 22% (12 of 54) of OSA children would be defined as excessively sleepy whereas only 7 children (13%) will have EDS when the criterion is set at <10 minutes (lower horizontal line).

	DISCUSSION

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This study shows that excessive daytime sleepiness as defined by a mean sleep latency <10 minutes occurs in a small proportion of children with OSA, and that sleep latencies are mildly, albeit significantly reduced in OSA patients. The increase in daytime sleep propensity exhibited linear dependencies on apnea index, arousal index, degree of nighttime hypoxemia, and BMI, but was not related to patient age and degree of obstructive hypoventilation.

Before we discuss the potential implications of our findings, some technical considerations deserve comment. Although it has become clear that the MSLT is a reliable and objective measure of sleep tendency, this test is not widely applied in young prepubertal children, such that extrapolation of our findings to those of others is relatively arduous. Notwithstanding such limitations, our findings are similar to those reported by several authors. Indeed, Palm et al¹¹ reported a mean sleep latency of 26.4 ± 2.8 minutes (standard deviation) in 18 prepubertal normal children using a similar nap duration approach to the one used in this study. Of interest, only 1 child fell asleep in <10 minutes, and this occurred only during 1 trial.¹¹ Furthermore, Randazzo and colleagues¹³ in 16 children ages 10 to 14 years found a mean MSLT of 23.5 minutes, a strikingly similar mean latency to that reported herein for both control participants and for primary snoring children. More recently, Lecendreux and colleagues²² used the more conventionally adopted 20-minute nap approach in 21 control children and found a mean MSLT of 18.9 ± 3.0 minutes. However, only 1 to 3 children fell asleep at any of the 4 nap 20-minute trials, such that the mean sleep latency found by these investigators represents in fact an underestimate of true sleep latency.²² Thus, it becomes evident from all the above studies and the present one, that mean sleep latencies <10 minutes and even <15 minutes are exceedingly rare in normal prepubertal children, and clearly separate between sleepy and nonsleepy children. It is also important to note in this context that because all the children were prepubertal at the time of their study, the potential bias that may be introduced by puberty-associated increases in daytime sleep tendency was avoided.¹⁰ Another important technical point involves the usefulness of capnography in pediatric studies, which allows for identification of extended periods of high upper airway resistance during the night in the absence of apnea.²³ Despite such valuable contributions to detection of gas exchange abnormalities during sleep, we found no correlation between hypercapnia and sleepiness in this study.

In adult patients with OSA, EDS is a primary daytime clinical manifestation of the disease,²⁴ and is positively correlated with the number of arousals, but not with the respiratory disturbance index or degree of hypoxemia.²⁵ However in an elderly population, Ancoli-Israel and colleagues²⁶ found significant differences between subjectively sleepy and nonsleepy OSA patients, and the degree of sleepiness correlated with oxyhemoglobin saturation indices rather than with the number of nighttime awakenings. Chervin and Aldrich²⁷ performed a retrospective analysis of risk factors for EDS in 1146 adult patients evaluated for sleep disordered breathing in whom overnight polysomnography and MSLT were conducted. In this large cohort, the investigators identified obstructive apnea index and the minimum oxygen saturation as independent variables significantly accounting for approximately 15% of the variance in mean sleep latency.²⁷ In a more recent study, Punjabi et al²⁸ examined the potential relationships between polysomnographic parameters and the degree of hypersomnolence in 741 adult patients with obstructive apnea. As in the previous studies, apnea-hypopnea index, nocturnal hypoxemia, and sleep fragmentation were found to be independent determinants of EDS in patients with sleep-disordered breathing.²⁸ However, it needs to be stressed that accurate separation of the relative contributions of nocturnal hypoxemia and sleep fragmentation to EDS is probably impossible in OSA patients, particularly when one considers the multiplicity of intercorrelations existing between somatic characteristics and respiratory and sleep disturbances. In this study of children with OSA, robust relationships between sleepiness and apnea index emerged, and in fact accounted for approximately 50% of the variance in mean sleep latency. In contrast, although the cumulative degree of hypoxemia was significantly correlated to sleepiness as an isolated independent variable, it did not provide any additional predictive value to changes in mean sleep latency. Furthermore, the degree of obstructive hypoventilation was not contributory. This is important in light of the findings reported in the adult population, and because EDS in children as defined by mean sleep latencies <10 minutes appears to occur only when the apnea index is very high (>15 apnea/hr TST). Thus, although it has been rather surprising that EDS is not a more frequent finding in children, and that a clinical history compatible with EDS is only occasionally elicited,⁵ there could be several possible explanations for such observations which are now confirmed by more objective methodology in the present study: 1) Assuming similar susceptibility in adults and children, the overall diminished severity of hypoxemia and the reduced density of apneic events that is usually present in children with abnormal sleep studies¹⁶ would in turn impose less of an impact on daytime sleep tendency; 2) There is recent evidence that in pediatric OSA, sleep architecture is preserved and that although the arousal index is elevated, only ~50% of respiratory events will be associated with arousal when the latter is scored as defined for adult subjects by a consensus panel.^20,29 Thus, in the presence of equivalent susceptibility between adults and children, reduced number of adult-like arousals would logically lead to reduced EDS, if indeed arousals are a major contributor to EDS. A note of caution should however be introduced at this stage, because there is no consensus as to the definition of arousal in children,^18,30 and clearly such definition would have major implications for correlational analyses between arousal and daytime sleepiness. In addition, there is experimental evidence that inspiratory loads are less likely to induce arousal in pediatric OSA patients.³¹ On the other hand, even in the absence of arousal that fulfills adult criteria, dynamic changes in electroencephalogram spectral characteristics do emerge during the course of an obstructive apneic event, and could be of importance in generation of EDS,^{32, 33} (iii) Although unlikely, the possibility that children have differential susceptibility to the pathophysiological elements underlying daytime sleepiness can not be excluded. In fact, it could account for the different EDS frequencies recorded in adults and children with OSA. Notwithstanding such considerations, our study shows for the first time that a high apnea index needs to be present in children with OSA such as to be associated with EDS. Thus, although much lower apnea indices are considered to represent the upper limit of normal respiratory pattern during sleep,¹⁶ only much more severe respiratory abnormalities during sleep appear to be associated with EDS as an adverse outcome in children with OSA.

In the absence of more definitive answers to above mentioned hypothetical scenarios, a major issue arising from this and previous studies addresses the clinical implications inherent to the overall infrequent occurrence of excessive sleepiness in children with OSA. Indeed, <15% of children with OSA exhibited EDS (MSLT<10 minutes), such that the neurocognitive and behavioral consequences of excessive sleepiness would also be expected to be rare in pediatric OSA patients. However, the opposite clinical picture emerges, whereby behavioral and learning problems are clearly very prevalent among children with OSA.^1334-37 Thus, daytime externalizing behavior problems either alone or in combination with MSLT, could in fact provide more reliable estimates of daytime sleepiness and sleep deprivation or fragmentation in school-aged children,^38,39 rather than reliance on parental perception or laboratory measurement of EDS. In other words, it is possible that the MSLT provides a relatively insensitive testing procedure to identification of EDS in young children, and improved understanding of the causes for such lack of sensitivity may lead to refinements in the definition of EDS in this age population.

Our study closely concurs with that of Marcus and colleagues⁶ who found close relationships between obesity and apnea index, degree of oxyhemoglobin desaturation, and daytime sleepiness. It remains unclear whether obese children are more susceptible to develop sleepiness in the presence of OSA or whether the consequences of sleep-disordered breathing in obese children are more likely to manifest as sleepiness rather than more physically demanding externalizing behavior problems such as hyperactivity and restlessness. However, in contrast with a recent study by Goh and colleagues,²⁹ we found evidence for mild disruption of sleep architecture in the OSA group as evidenced by a reduction in rapid eye movement sleep, without much alterations in non-rapid eye movement distribution.

	CONCLUSION

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Pathologic daytime sleepiness defined in this study as a mean sleep latency <10 minutes is seldom present in young children with OSA, although the latter will be associated with significant albeit modest increases in sleepiness. However, obesity and more severe respiratory disturbance seem to be important risk factors for development of EDS in pediatric OSA patients.

	ACKNOWLEDGMENTS

This study was supported by grants from the National Institutes of Health (HL-65 270 and HL-63 912), and the American Heart Association (AHA- 0050442N).

We thank the children and families for their patience and cooperation and the sleep technologists for their dedicated work.

	FOOTNOTES

Received for publication Dec 27, 2000; accepted Mar 9, 2001.

Reprint requests to (D.G.) Kosair Children's Hospital Research Institute, University of Louisville School of Medicine, 570 S Preston St, Suite 321, Louisville, KY 40202. E-mail:david.gozal{at}louisville.edu

	ABBREVIATIONS

OSA, obstructive sleep apnea; EDS, excessive daytime sleepiness; MSLT, multiple sleep latency test; OSAS, obstructive sleep apnea syndrome; P_ETCO₂, end tidal carbon dioxide; SaO₂, arterial oxygen saturation; AI, apnea index; BMI, body mass index; PS, primary snoring; TST, total sleep time; C, controls.

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