Original Research—Pediatric Otolaryngology
Correlation between REM AHI and Quality-of-Life Scores in Children with Sleep-Disordered Breathing
Otolaryngology– Head and Neck Surgery 2014, Vol. 151(4) 687–691 Ó American Academy of Otolaryngology—Head and Neck Surgery Foundation 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0194599814547504 http://otojournal.org
Cristina Marie Baldassari, MD1, Lyla Alam2, Maria Vigilar3, James Benke3, Charley Martin, MPH4, and Stacey Ishman, MD, MPH5
No sponsorships or competing interests have been disclosed for this article.
Abstract Objectives. Prior research has demonstrated poor correlation between the obstructive apnea-hypopnea index (AHI) on full-night polysomnogram (PSG) and quality-of-life (QOL) scores. We aim to examine the association between rapid eye movement (REM) AHI and QOL scores in children with sleep-disordered breathing (SDB). Study Design. Prospective trial. Setting. Two tertiary children’s hospitals. Subjects and Methods. Children between 3 and 16 years of age with suspected SDB who were undergoing PSG were eligible. Children with craniofacial anomalies were excluded. Subjects’ caregivers completed the Obstructive Sleep Apnea–18 (OSA-18), a validated QOL survey. Power analysis determined a group size of 34. Results. One hundred twenty-seven patients were enrolled. The mean (SD) age was 6.3 (3.3) years. Most subjects (52%) were black and 26% were obese. The mean (SD) obstructive AHI of the subject population was 5.4 (11.9), while the mean (SD) REM AHI was 13.1 (23.7). The mean total OSA-18 score was 65.2, indicating a moderate impact of SDB on QOL. Neither the obstructive AHI (P = .73) nor the REM AHI (P = .49) correlated with total OSA-18 scores. However, lower nadir oxygen saturation was associated with significantly poorer QOL (P = .02). The sleep disturbance OSA-18 subset score significantly correlated with both the obstructive AHI (r2 = 0.22; P = .01) and the REM AHI (r2 = 0.22; P = .01); the remaining 4 subset scores did not correlate with either factor. Conclusion. Neither obstructive AHI nor REM AHI correlates with total OSA-18 QOL scores. With the exception of nadir oxygen saturation, PSG parameters do not reflect the burden of SDB on QOL in children. Keywords obstructive sleep polysomnogram
apnea,
pediatrics,
quality
of
life,
Received April 13, 2014; revised June 18, 2014; accepted July 25, 2014.
O
bstructive sleep apnea (OSA) is a sleep-related breathing disorder that is characterized by intermittent episodes of upper airway collapse during sleep. It is the most severe manifestation of sleep-disordered breathing (SDB) in children and has been linked to metabolic changes, growth inhibition, and cardiovascular sequelae. Obstructive sleep apnea affects 2% to 3% of preschool age children in the United States.1 Furthermore, there is a growing body of literature demonstrating the negative impact of OSA on quality of life (QOL) and cognitive function in children.2 Pediatric OSA has been associated with behavior problems, poor attention, memory and cognitive deficits, and poor school performance.3 The gold standard for diagnosis of pediatric OSA is the full-night polysomnogram (PSG). Recently published guidelines from the American Academy of Pediatrics4 and the American Academy of Sleep Medicine5 recommend routine utilization of PSG in children with symptoms of SDB. Thus, PSGs are being used with increasing frequency in the evaluation of children with suspected OSA. The severity of OSA is categorized according to the obstructive apneahypopnea index (AHI) on PSG. According to the most 1 Department of Otolaryngology–Head and Neck Surgery, Eastern Virginia Medical School, and Department of Pediatric Otolaryngology, Children’s Hospital of the King’s Daughters, Norfolk, Virginia, USA 2 Eastern Virginia Medical School, Norfolk, Virginia, USA 3 Johns Hopkins University School of Medicine, Baltimore, Maryland, USA 4 Eastern Virginia Medical School, Graduate Program in Public Health, Norfolk, Virginia, USA 5 Departments of Pediatric Otolaryngology–Head & Neck Surgery & Pulmonary Medicine, Cincinnati Children’s Hospital Medical Center, and Department of Otolaryngology–Head and Neck Surgery, University of Cincinnati School of Medicine, Cincinnati, Ohio, USA
This article was presented at the American Society of Pediatric Otolaryngology Annual Meeting; May 17, 2014; Las Vegas, Nevada. Corresponding Author: Cristina Marie Baldassari, MD, Department of Otolaryngology–Head and Neck Surgery, Eastern Virginia Medical School, 601 Children’s Lane, 2nd Floor, Norfolk, VA 23507, USA. Email: [email protected]; [email protected]
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commonly used system in children, an obstructive AHI between 1 and 5 indicates mild OSA, while severe OSA is characterized by an obstructive AHI greater than 10.6 Although PSG reliably measures the presence of OSA and provides an objective scale for OSA severity, it fails to quantify the impact of OSA on a child’s general well-being, including emotional and behavioral health. Interestingly, QOL does not correlate with AHI in pediatric patients.7 The rapid eye movement (REM) AHI (the number of apneas and hypopneas occurring during REM sleep) is a parameter frequently included on PSG reports. In children with OSA, respiratory events occur more frequently in REM sleep compared with non-REM sleep.8,9 This can result in sleep fragmentation and may lead to diminished amounts of REM sleep. The impact of REM sleep fragmentation and REM sleep deprivation is still being investigated. In a study of adults with mild OSA (AHI \10) and significant daytime sleepiness, the REM AHI correlated with daytime sleepiness and accounted for 35% of the variance in sleep latency on multiple sleep latency testing (MSLT).10 A REM respiratory disturbance index (RDI) greater than 15 predicted shorter sleep latency on MSLT. To the authors’ knowledge, there have not been any similar studies in children to investigate the impact of REM AHI on daytime sleepiness and QOL. The correlation between the REM AHI and QOL in children with SDB is unknown. The primary objective of this study was to assess if there is an association between REM AHI and QOL scores in children with SDB. We also aimed to determine whether PSG parameters beyond AHI and RDI, such as arousal index and nadir oxygen saturation, affect QOL.
Methods A prospective trial was designed to assess the correlation between REM AHI and QOL in children presenting with SDB. The study was carried out between January and September 2013 at 2 tertiary care children’s hospitals (The Children’s Hospital of The King’s Daughters in Norfolk, Virginia, and Johns Hopkins Children’s Center in Baltimore, Maryland). The research protocol was approved by the institutional review boards at both locations. Subjects were recruited from outpatient pediatric otolaryngology clinics at both locations and from the outpatient sleep clinic at Johns Hopkins Children’s Center. Children were eligible for inclusion if they presented for evaluation of SDB and were between 3 and 16 years of age. All children who were scheduled to undergo full-night PSG as part of their evaluation for SDB were offered participation in the study. Parents, sometimes with input from the child, completed the QOL survey on the date of enrollment. Enrollment occurred at the initial presentation to the otolaryngology clinic. Obese children were included in the study. Subjects with craniofacial abnormalities, cerebral palsy, trisomy 21, or history of adenotonsillar surgery were excluded. Children with non-English-speaking parents were also excluded. An additional exclusion criterion was failure to complete the PSG with less than 4 hours of total sleep time. Since the
majority of obstructive respiratory events in children occur during REM sleep, children with a reduced amount of REM sleep were also excluded. The authors arbitrarily chose a value of REM sleep time less than 10% of total sleep time as an exclusion criterion. A validated instrument, the OSA-18, was used to assess disease-specific QOL. The OSA-18, developed by Franco et al,11 is an 18-item questionnaire that measures the relative severity of sleep-related problems with a Likert scale ranging from 1 (none of the time) to 7 (all of the time). This instrument yields a total score composed of 5 subset scores for sleep disturbance, physical suffering, emotional distress, daytime problems, and caregiver concerns. Total OSA-18 QOL scores between 60 and 80 indicate a moderate QOL impairment. Higher OSA-18 scores are associated with poorer QOL. All PSGs were performed in dedicated pediatric sleep laboratories in accordance with the American Academy of Sleep Medicine (AASM) guidelines and were scored by pediatric sleep medicine specialists.12 Standard procedure included a 6lead electroencephalogram (EEG), bilateral electro-oculogram (EOG) leads, and 1 submental and 2 tibial electromyograms (EMGs). Respiratory measurements were recorded by the following means: chest wall and abdominal movements using inductive plethysmography, airflow using a nasal pressure transducer, oxygen saturation by pulse oximetry, and carbon dioxide using a carbon dioxide sensor. Video and audio recordings were also obtained for each study. Information obtained from PSGs included total sleep time, sleep efficiency, time spent in each sleep stage, number and classification of arousals, periodic limb movements, and oxygen and carbon dioxide levels. Recorded respiratory data included counts and indexes of the following events: obstructive apneas, obstructive hypopneas, central apneas, and mixed apneas recorded in REM sleep and total sleep. Demographic data, including age, sex, ethnicity, and body mass index (BMI) percentiles (calculated according to the Centers for Disease Control and Prevention guidelines), were also recorded.13 Information regarding subjects’ comorbid medical conditions, including a history of asthma and attentiondeficit hyperactivity disorder (ADHD), was obtained from the caregivers on the date of enrollment. A power analysis was conducted prior to undertaking this study. A group size of 34 was deemed sufficient to detect a 20-point difference in OSA-18 QOL scores with 80% power and a .05 significance level. All children for whom complete PSG and QOL survey data were available were included in the analysis regardless of AHI. Descriptive, bivariate, and multivariate analyses were performed using SAS version 9.3 (SAS Institute, Cary, North Carolina) software. Independent samples t test, 1-way analysis of variance (ANOVA), and Pearson correlation coefficients were used to obtain the test statistics and P values. Multiple regression analysis was used to investigate associations between the 2 primary independent variables (REM AHI and obstructive AHI) and the dependent variables (QOL scores) while controlling for covariates. P values less than .05 were considered significant.
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Table 1. Subject Demographic Data (n = 127).a Category Age, mean 6 SD, mo BMI, mean 6 SD BMI percentile, mean 6 SD Underweight Normal weight Overweight Obese Race Black White Other Asthma Prematurity ADHD
Results 75 18.7 70.3 2 68 20 33 66 49 11 44 13 10
6 35.9 6 4.9 6 28.3 (1.6) (55.3) (16.3) (26.8) (52.4) (38.9) (8.7) (36.7) (11.4) (8.4)
Abbreviations: ADHD, attention-deficit hyperactivity disorder; BMI, body mass index. a Values are presented as number (percentage) unless otherwise indicated.
Table 2. Subject Polysomnogram Data and OSA-18 QOL Scores.a Category Mean obstructive AHI OSA classification, No. (%) None (AHI \1) Mild (AHI 1-5) Moderate (AHI 5.1-10) Severe (AHI .10) Mean REM AHI Mean central apnea index Mean nadir oxygen saturation Mean arousal index Mean total OSA-18 QOL score Sleep disturbance subset Physical symptoms subset Emotional distress subset Daytime function subset Caregiver concerns subset
Results 5.4 6 11.9 21 82 13 10 13.1 0.91 89.9 11.2 65.2 17.1 13.6 10.7 10.7 12.8
(16.7) (65.1) (10.3) (7.9) 6 23.7 6 0.9 6 5.2 6 6.9 6 20.5 6 5.3 6 5.4 6 6.0 6 5.0 6 6.9
Abbreviations: AHI, apnea-hypopnea index; OSA, obstructive sleep apnea; QOL, quality of life; REM, rapid eye movement. a Values are presented as mean 6 SD unless otherwise indicated.
Results
Figure 1. Scatter plot showing nadir oxygen saturations and total OSA-18 quality of life (QOL) scores. Lower nadir oxygen saturations were associated with poorer QOL scores in the study population.
subject population was 5.4 (11.9), while the mean (SD) REM AHI was higher at 13.1 (23.7) (Table 2). Sixty-five percent of the children (n = 82) had mild OSA as defined by an obstructive AHI between 1 and 5. The average nadir oxygen saturation while asleep was 90%. The mean (SD) total OSA-18 QOL score was 65.2 (20.5), indicating a moderate impact of SDB on QOL (Table 2). Neither the obstructive AHI (P = .73) nor the REM AHI (P = .49) correlated with the total OSA-18 score. However, lower nadir oxygen saturation during sleep significantly correlated (P = .02) with poorer QOL scores (Figure 1). Race and a history of asthma were also associated with total OSA-18 QOL scores (Table 3). Black children and children with asthma had poorer QOL scores. When the analysis was controlled for common covariates such as sex, age, and race, there was not a significant association between total OSA-18 scores and either the REM AHI (P = .49) or the obstructive AHI (P = .73). The OSA-18 sleep disturbance subscore correlated with both the obstructive AHI (r2 = 0.22; P = .01) and the REM AHI (r2 = 0.22; P = .01). While significant, these correlations were fair in magnitude. The remaining 4 OSA-18 subset scores did not correlate with either factor. Black children had poorer sleep disturbance QOL subset scores than did white children (P = .01). Children with ADHD had significantly poorer QOL scores for the emotional distress subsection (P = .005).
Discussion
Complete QOL scores and PSG data were available for 127 patients. The mean (SD) duration of time between QOL instrument completion and PSG was 29 (27.6) days. The mean (SD) age of the children was 6.3 (3.3) years. Most subjects (52%; n = 66) were black and 26% (n = 33) were obese (Table 1). Asthma was the most common comorbid medical condition in our subject population, affecting 37% of children (n = 44). The mean (SD) obstructive AHI of the
The obstructive AHI is the primary PSG measure used to determine the presence and severity of OSA in children. There are few data, however, regarding the clinical significance of the REM AHI and distribution of respiratory events in REM vs NREM sleep. We hypothesized that the REM AHI would be a better predictor of disease-specific QOL than the obstructive AHI. However, in this multi-institutional, prospective study of children with SDB, neither the obstructive AHI nor the REM
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Table 3. Association between Demographic Factors and Total OSA-18 QOL Scores. Characteristic Age BMI Sex Race ADHD Asthma Prematurity Arousal index Nadir oxygen saturation Central apnea index REM AHI Obstructive AHI
Test Statistic
P Value
–0.10a –0.08a 0.01b 3.20b –1.85b –2.77b –1.35b –0.04a –0.20a 0.01a 0.10a 0.03a
.25 .36 .99 .04c .06 .01c .18 .69 .02c .91 .25 .74
Abbreviations: ADHD, attention-deficit hyperactivity disorder; AHI, apneahypopnea index; BMI, body mass index; QOL, quality of life; REM, rapid eye movement. a Correlation coefficient. b Independent samples t test or analysis of variance. c P \.05.
AHI predicted total OSA-18 scores. We did identify a significant correlation between the sleep disturbance subscore of the OSA-18 and both the obstructive AHI and the REM AHI. Spruyt and Gozal9 reviewed the PSGs of 335 schoolaged children and found that respiratory events were 3.8 times more likely to occur during REM sleep. Only 18.6% of their subject population had a predominance of respiratory events during non-REM (NREM) sleep. Children with a REM predominance of respiratory events had more severe overall OSA disease severity and a higher arousal index. The authors, however, did not examine the association between REM-predominant OSA and QOL or daytime sleepiness. Thus, the impact of REM sleep fragmentation due to respiratory events on daytime function in children was previously unknown. No prior studies have investigated the association between REM AHI and QOL in children with SDB. To this end, relatively few studies have examined the correlation between daytime sleepiness and REM AHI in adults. In a cohort of adults undergoing PSG for suspected SDB, Haba-Rubio et al8 identified 151 patients with REM-predominant OSA (REM AHI/NREM AHI ratio .2). Compared with patients without REM-predominant OSA, those with REM-predominant OSA were younger and had higher BMI scores. There were no significant differences in daytime sleepiness as assessed by either the Epworth Sleepiness Scale or sleep latency on Maintenance of Wakefulness Testing between the 2 groups. These findings are in contrast to the work by Kass et al,10 which demonstrated significant correlation between daytime sleepiness and REM RDI in 34 adults. In this study, a REM RDI greater than 15 was the most accurate predictor of excessive daytime sleepiness as determined by a sleep latency of less than 10 minutes on MSLT.
A recent systematic review of outcome measures for adult OSA advocated for practitioners to routinely measure QOL, sleepiness, and school/occupational performance when assessing disease severity and determining treatment responses.14 The authors of the study cautioned against relying on the AHI as the sole metric of therapeutic effectiveness. Similarly, in children, QOL measures do not correlate with the severity of OSA as assessed by the AHI. Such findings highlight the need to develop outcome measures that can better assess the impact of OSA on patients’ physical symptoms, behavior, emotional state, and family interactions. In this work, we aimed to identify PSG parameters, such as the REM AHI, that could be associated with a child’s QOL and overall health status. In our study, there was not a significant association between REM AHI and QOL scores. Moreover, REM sleep disruption did not correlate with daytime manifestations of OSA, such as daytime sleepiness or poor concentration. The poor association between AHI and QOL demonstrates our lack of understanding the physiology of sleepiness and the daytime behavior impairments seen in children with OSA. Another possible explanation for the lack of correlation between the REM AHI and QOL scores involves the characteristics of our study population. We included all children with SDB symptoms who underwent PSG, regardless of severity of disease as assessed by AHI. Indeed, most children in our study had mild OSA. Perhaps a closer association between REM AHI and QOL scores exists in children with more severe OSA. We also examined additional PSG parameters in an attempt to identify other metrics that might better correlate with QOL in children with SDB. For example, previous research suggests that the number and duration of arousals may contribute to sleep fragmentation and the disruption of sleep architecture.9 Such disruption of sleep may be related to daytime manifestations of SDB such as poor behavior and difficulty with concentration.15 In our study, the only PSG parameter that correlated with total QOL scores was nadir oxygen saturation. Similarly, other authors have also reported that hypoxemia has a measurable negative impact on behavior, cognition, and academic performance. For example, Urschitz et al16 found that impaired academic performance in mathematics in schoolchildren was associated with lower nadir pulse oximetry saturations. The underlying pathophysiologic mechanisms involved in the link between intermittent nighttime oxygen desaturations and poor cognition remain largely unknown. One possible explanation may be found in a 2004 study that demonstrated that intermittent hypoxia increases oxidative stress and nitric oxide levels and leads to cortical and hippocampal cell death in rodents with SDB.17 There were several limitations of the present study. Although sleep position may influence the occurrence of respiratory events in some patients, we did not examine the role of sleep position in this study. Furthermore, data regarding the duration of obstructive symptoms were not routinely collected. On the basis of their work in adults with OSA, Haba-Rubio et al8 postulated that REM-predominant
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OSA is an early manifestation of OSA as opposed to a distinct clinical entity. It is possible that children with higher REM AHIs may be earlier in their disease course, but further research is needed to address this hypothesis. Finally, this study did not examine outcomes following treatment for SDB. Thus, we cannot comment on whether the REM AHI influences responses to therapy. It may be that a higher baseline REM AHI is associated with persistent daytime symptoms following adenotonsillectomy in pediatric patients with OSA. Future research initiatives should include both PSG parameters and validated QOL measures in prospective protocols for the evaluation of children with OSA both pre- and posttreatment.
Conclusion Neither the obstructive AHI nor the REM AHI was associated with QOL scores in this study of children with SDB. With the exception of nadir oxygen saturation, PSG parameters do not reflect the burden of SDB on QOL in children. The lack of correlation between AHI and QOL scores underscores the point that PSG alone cannot be used to determine the impact of OSA on a child’s health. Future research is needed to identify outcome measures that better quantify the impact of SDB on a child’s wellbeing. Author Contributions Cristina Marie Baldassari, study design, drafting of manuscript; Lyla Alam, study design, data acquisition, drafting of manuscript; Maria Vigilar, acquisition of data, editing of manuscript; James Benke, acquisition of data, critical review of manuscript; Charley Martin, data analysis and interpretation, editing manuscript; Stacey Ishman, study design, editing manuscript.
Disclosures Competing interests: None. Sponsorships: None. Funding source: None.
References 1. Katz ES, D’Ambrosio CM. Pediatric obstructive sleep apnea syndrome. Clin Chest Med. 2010;31:221-234. 2. Baldassari CM, Mitchell RB, Schubert C, et al. Pediatric obstructive sleep apnea and quality of life: a meta-analysis. Otolaryngol Head Neck Surg. 2008;138:265-273. 3. Ray R, Bower C. Pediatric obstructive sleep apnea: the year in review. Curr Opin Otolaryngol Head Neck Surg. 2005;13: 360-365.
4. Marcus CL, Brooks LJ, Draper KA, et al. Diagnosis and management of childhood obstructive sleep apnea syndrome. Pediatrics. 2012;130:576-584. 5. Aurora RN, Lamm CI, Karippot A, et al. Practice parameters for the respiratory indications for polysomnography in children. Sleep. 2012;35(11):1467-1473. 6. Wagner MH, Torrez DM. Interpretation of the polysomnogram in children. Otolaryngol Clin North Am. 2007;40:745-759. 7. Mitchell RB, Kelly J. Quality of life after adenotonsillectomy for SDB in children. Otolaryngol Head Neck Surg. 2005;133:569-572. 8. Haba-Rubio J, Janssens J, Rochat T, et al. Rapid eye movements–related disordered breathing clinical and polysomnographic features. Chest. 2005;128:3350-3357. 9. Spruyt K, Gozal D. REM and NREM sleep-stage distribution of respiratory events in habitually snoring school-aged community children. Sleep Med. 2012;13:178-184. 10. Kass JE, Akers SM, Bartter TC, et al. Rapid eye movement specific sleep disordered breathing: a possible cause of excessive daytime sleepiness. Am J Respir Crit Care Med. 1996; 154:167-169. 11. Franco RA, Rosenfeld RM, Rao M. Quality of life for children with obstructive sleep apnea. Otolaryngol Head Neck Surg. 2000;123:9-16. 12. Iber CA, Chesso A, Quan SF. The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications. Darien, IL: American Academy of Sleep Medicine; 2007. 13. Centers for Disease Control and Prevention. Children’s BMI tool for schools. http://www.cdc.gov/healthyweight/assessing/ bmi/childrens_BMI/tool_for_schools.html. Accessed January 10, 2013. 14. Tam S, Woodson BT, Rotenberg B. Outcome measurements in obstructive sleep apnea: beyond the apnea-hypopnea index. Laryngoscope. 2014;124:337-343. 15. Archbold KH, Giordani B, Ruzicka D, et al. Cognitive executive dysfunction in children with mild sleep disordered breathing. Biol Res Nurs. 2004;5:168-176. 16. Urschitz M, Wolff J, Sokollik C, et al. Nocturnal arterial oxygen saturation and academic performance in a community sample of children. Pediatrics. 2005;115:e204-e209. 17. Xu W, Chi L, Row BW, et al. Increased oxidative stress is associated with chronic intermittent hypoxia-mediated brain cortical neuronal cell apoptosis in a mouse model of sleep apnea. Neuroscience. 2004;126:313-323.
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Correlation between REM AHI and Quality-of-Life Scores in Children with Sleep-Disordered Breathing
Otolaryngology– Head and Neck Surgery 2014, Vol. 151(4) 687–691 Ó American Academy of Otolaryngology—Head and Neck Surgery Foundation 2014 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0194599814547504 http://otojournal.org
Cristina Marie Baldassari, MD1, Lyla Alam2, Maria Vigilar3, James Benke3, Charley Martin, MPH4, and Stacey Ishman, MD, MPH5
No sponsorships or competing interests have been disclosed for this article.
Abstract Objectives. Prior research has demonstrated poor correlation between the obstructive apnea-hypopnea index (AHI) on full-night polysomnogram (PSG) and quality-of-life (QOL) scores. We aim to examine the association between rapid eye movement (REM) AHI and QOL scores in children with sleep-disordered breathing (SDB). Study Design. Prospective trial. Setting. Two tertiary children’s hospitals. Subjects and Methods. Children between 3 and 16 years of age with suspected SDB who were undergoing PSG were eligible. Children with craniofacial anomalies were excluded. Subjects’ caregivers completed the Obstructive Sleep Apnea–18 (OSA-18), a validated QOL survey. Power analysis determined a group size of 34. Results. One hundred twenty-seven patients were enrolled. The mean (SD) age was 6.3 (3.3) years. Most subjects (52%) were black and 26% were obese. The mean (SD) obstructive AHI of the subject population was 5.4 (11.9), while the mean (SD) REM AHI was 13.1 (23.7). The mean total OSA-18 score was 65.2, indicating a moderate impact of SDB on QOL. Neither the obstructive AHI (P = .73) nor the REM AHI (P = .49) correlated with total OSA-18 scores. However, lower nadir oxygen saturation was associated with significantly poorer QOL (P = .02). The sleep disturbance OSA-18 subset score significantly correlated with both the obstructive AHI (r2 = 0.22; P = .01) and the REM AHI (r2 = 0.22; P = .01); the remaining 4 subset scores did not correlate with either factor. Conclusion. Neither obstructive AHI nor REM AHI correlates with total OSA-18 QOL scores. With the exception of nadir oxygen saturation, PSG parameters do not reflect the burden of SDB on QOL in children. Keywords obstructive sleep polysomnogram
apnea,
pediatrics,
quality
of
life,
Received April 13, 2014; revised June 18, 2014; accepted July 25, 2014.
O
bstructive sleep apnea (OSA) is a sleep-related breathing disorder that is characterized by intermittent episodes of upper airway collapse during sleep. It is the most severe manifestation of sleep-disordered breathing (SDB) in children and has been linked to metabolic changes, growth inhibition, and cardiovascular sequelae. Obstructive sleep apnea affects 2% to 3% of preschool age children in the United States.1 Furthermore, there is a growing body of literature demonstrating the negative impact of OSA on quality of life (QOL) and cognitive function in children.2 Pediatric OSA has been associated with behavior problems, poor attention, memory and cognitive deficits, and poor school performance.3 The gold standard for diagnosis of pediatric OSA is the full-night polysomnogram (PSG). Recently published guidelines from the American Academy of Pediatrics4 and the American Academy of Sleep Medicine5 recommend routine utilization of PSG in children with symptoms of SDB. Thus, PSGs are being used with increasing frequency in the evaluation of children with suspected OSA. The severity of OSA is categorized according to the obstructive apneahypopnea index (AHI) on PSG. According to the most 1 Department of Otolaryngology–Head and Neck Surgery, Eastern Virginia Medical School, and Department of Pediatric Otolaryngology, Children’s Hospital of the King’s Daughters, Norfolk, Virginia, USA 2 Eastern Virginia Medical School, Norfolk, Virginia, USA 3 Johns Hopkins University School of Medicine, Baltimore, Maryland, USA 4 Eastern Virginia Medical School, Graduate Program in Public Health, Norfolk, Virginia, USA 5 Departments of Pediatric Otolaryngology–Head & Neck Surgery & Pulmonary Medicine, Cincinnati Children’s Hospital Medical Center, and Department of Otolaryngology–Head and Neck Surgery, University of Cincinnati School of Medicine, Cincinnati, Ohio, USA
This article was presented at the American Society of Pediatric Otolaryngology Annual Meeting; May 17, 2014; Las Vegas, Nevada. Corresponding Author: Cristina Marie Baldassari, MD, Department of Otolaryngology–Head and Neck Surgery, Eastern Virginia Medical School, 601 Children’s Lane, 2nd Floor, Norfolk, VA 23507, USA. Email: [email protected]; [email protected]
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commonly used system in children, an obstructive AHI between 1 and 5 indicates mild OSA, while severe OSA is characterized by an obstructive AHI greater than 10.6 Although PSG reliably measures the presence of OSA and provides an objective scale for OSA severity, it fails to quantify the impact of OSA on a child’s general well-being, including emotional and behavioral health. Interestingly, QOL does not correlate with AHI in pediatric patients.7 The rapid eye movement (REM) AHI (the number of apneas and hypopneas occurring during REM sleep) is a parameter frequently included on PSG reports. In children with OSA, respiratory events occur more frequently in REM sleep compared with non-REM sleep.8,9 This can result in sleep fragmentation and may lead to diminished amounts of REM sleep. The impact of REM sleep fragmentation and REM sleep deprivation is still being investigated. In a study of adults with mild OSA (AHI \10) and significant daytime sleepiness, the REM AHI correlated with daytime sleepiness and accounted for 35% of the variance in sleep latency on multiple sleep latency testing (MSLT).10 A REM respiratory disturbance index (RDI) greater than 15 predicted shorter sleep latency on MSLT. To the authors’ knowledge, there have not been any similar studies in children to investigate the impact of REM AHI on daytime sleepiness and QOL. The correlation between the REM AHI and QOL in children with SDB is unknown. The primary objective of this study was to assess if there is an association between REM AHI and QOL scores in children with SDB. We also aimed to determine whether PSG parameters beyond AHI and RDI, such as arousal index and nadir oxygen saturation, affect QOL.
Methods A prospective trial was designed to assess the correlation between REM AHI and QOL in children presenting with SDB. The study was carried out between January and September 2013 at 2 tertiary care children’s hospitals (The Children’s Hospital of The King’s Daughters in Norfolk, Virginia, and Johns Hopkins Children’s Center in Baltimore, Maryland). The research protocol was approved by the institutional review boards at both locations. Subjects were recruited from outpatient pediatric otolaryngology clinics at both locations and from the outpatient sleep clinic at Johns Hopkins Children’s Center. Children were eligible for inclusion if they presented for evaluation of SDB and were between 3 and 16 years of age. All children who were scheduled to undergo full-night PSG as part of their evaluation for SDB were offered participation in the study. Parents, sometimes with input from the child, completed the QOL survey on the date of enrollment. Enrollment occurred at the initial presentation to the otolaryngology clinic. Obese children were included in the study. Subjects with craniofacial abnormalities, cerebral palsy, trisomy 21, or history of adenotonsillar surgery were excluded. Children with non-English-speaking parents were also excluded. An additional exclusion criterion was failure to complete the PSG with less than 4 hours of total sleep time. Since the
majority of obstructive respiratory events in children occur during REM sleep, children with a reduced amount of REM sleep were also excluded. The authors arbitrarily chose a value of REM sleep time less than 10% of total sleep time as an exclusion criterion. A validated instrument, the OSA-18, was used to assess disease-specific QOL. The OSA-18, developed by Franco et al,11 is an 18-item questionnaire that measures the relative severity of sleep-related problems with a Likert scale ranging from 1 (none of the time) to 7 (all of the time). This instrument yields a total score composed of 5 subset scores for sleep disturbance, physical suffering, emotional distress, daytime problems, and caregiver concerns. Total OSA-18 QOL scores between 60 and 80 indicate a moderate QOL impairment. Higher OSA-18 scores are associated with poorer QOL. All PSGs were performed in dedicated pediatric sleep laboratories in accordance with the American Academy of Sleep Medicine (AASM) guidelines and were scored by pediatric sleep medicine specialists.12 Standard procedure included a 6lead electroencephalogram (EEG), bilateral electro-oculogram (EOG) leads, and 1 submental and 2 tibial electromyograms (EMGs). Respiratory measurements were recorded by the following means: chest wall and abdominal movements using inductive plethysmography, airflow using a nasal pressure transducer, oxygen saturation by pulse oximetry, and carbon dioxide using a carbon dioxide sensor. Video and audio recordings were also obtained for each study. Information obtained from PSGs included total sleep time, sleep efficiency, time spent in each sleep stage, number and classification of arousals, periodic limb movements, and oxygen and carbon dioxide levels. Recorded respiratory data included counts and indexes of the following events: obstructive apneas, obstructive hypopneas, central apneas, and mixed apneas recorded in REM sleep and total sleep. Demographic data, including age, sex, ethnicity, and body mass index (BMI) percentiles (calculated according to the Centers for Disease Control and Prevention guidelines), were also recorded.13 Information regarding subjects’ comorbid medical conditions, including a history of asthma and attentiondeficit hyperactivity disorder (ADHD), was obtained from the caregivers on the date of enrollment. A power analysis was conducted prior to undertaking this study. A group size of 34 was deemed sufficient to detect a 20-point difference in OSA-18 QOL scores with 80% power and a .05 significance level. All children for whom complete PSG and QOL survey data were available were included in the analysis regardless of AHI. Descriptive, bivariate, and multivariate analyses were performed using SAS version 9.3 (SAS Institute, Cary, North Carolina) software. Independent samples t test, 1-way analysis of variance (ANOVA), and Pearson correlation coefficients were used to obtain the test statistics and P values. Multiple regression analysis was used to investigate associations between the 2 primary independent variables (REM AHI and obstructive AHI) and the dependent variables (QOL scores) while controlling for covariates. P values less than .05 were considered significant.
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Table 1. Subject Demographic Data (n = 127).a Category Age, mean 6 SD, mo BMI, mean 6 SD BMI percentile, mean 6 SD Underweight Normal weight Overweight Obese Race Black White Other Asthma Prematurity ADHD
Results 75 18.7 70.3 2 68 20 33 66 49 11 44 13 10
6 35.9 6 4.9 6 28.3 (1.6) (55.3) (16.3) (26.8) (52.4) (38.9) (8.7) (36.7) (11.4) (8.4)
Abbreviations: ADHD, attention-deficit hyperactivity disorder; BMI, body mass index. a Values are presented as number (percentage) unless otherwise indicated.
Table 2. Subject Polysomnogram Data and OSA-18 QOL Scores.a Category Mean obstructive AHI OSA classification, No. (%) None (AHI \1) Mild (AHI 1-5) Moderate (AHI 5.1-10) Severe (AHI .10) Mean REM AHI Mean central apnea index Mean nadir oxygen saturation Mean arousal index Mean total OSA-18 QOL score Sleep disturbance subset Physical symptoms subset Emotional distress subset Daytime function subset Caregiver concerns subset
Results 5.4 6 11.9 21 82 13 10 13.1 0.91 89.9 11.2 65.2 17.1 13.6 10.7 10.7 12.8
(16.7) (65.1) (10.3) (7.9) 6 23.7 6 0.9 6 5.2 6 6.9 6 20.5 6 5.3 6 5.4 6 6.0 6 5.0 6 6.9
Abbreviations: AHI, apnea-hypopnea index; OSA, obstructive sleep apnea; QOL, quality of life; REM, rapid eye movement. a Values are presented as mean 6 SD unless otherwise indicated.
Results
Figure 1. Scatter plot showing nadir oxygen saturations and total OSA-18 quality of life (QOL) scores. Lower nadir oxygen saturations were associated with poorer QOL scores in the study population.
subject population was 5.4 (11.9), while the mean (SD) REM AHI was higher at 13.1 (23.7) (Table 2). Sixty-five percent of the children (n = 82) had mild OSA as defined by an obstructive AHI between 1 and 5. The average nadir oxygen saturation while asleep was 90%. The mean (SD) total OSA-18 QOL score was 65.2 (20.5), indicating a moderate impact of SDB on QOL (Table 2). Neither the obstructive AHI (P = .73) nor the REM AHI (P = .49) correlated with the total OSA-18 score. However, lower nadir oxygen saturation during sleep significantly correlated (P = .02) with poorer QOL scores (Figure 1). Race and a history of asthma were also associated with total OSA-18 QOL scores (Table 3). Black children and children with asthma had poorer QOL scores. When the analysis was controlled for common covariates such as sex, age, and race, there was not a significant association between total OSA-18 scores and either the REM AHI (P = .49) or the obstructive AHI (P = .73). The OSA-18 sleep disturbance subscore correlated with both the obstructive AHI (r2 = 0.22; P = .01) and the REM AHI (r2 = 0.22; P = .01). While significant, these correlations were fair in magnitude. The remaining 4 OSA-18 subset scores did not correlate with either factor. Black children had poorer sleep disturbance QOL subset scores than did white children (P = .01). Children with ADHD had significantly poorer QOL scores for the emotional distress subsection (P = .005).
Discussion
Complete QOL scores and PSG data were available for 127 patients. The mean (SD) duration of time between QOL instrument completion and PSG was 29 (27.6) days. The mean (SD) age of the children was 6.3 (3.3) years. Most subjects (52%; n = 66) were black and 26% (n = 33) were obese (Table 1). Asthma was the most common comorbid medical condition in our subject population, affecting 37% of children (n = 44). The mean (SD) obstructive AHI of the
The obstructive AHI is the primary PSG measure used to determine the presence and severity of OSA in children. There are few data, however, regarding the clinical significance of the REM AHI and distribution of respiratory events in REM vs NREM sleep. We hypothesized that the REM AHI would be a better predictor of disease-specific QOL than the obstructive AHI. However, in this multi-institutional, prospective study of children with SDB, neither the obstructive AHI nor the REM
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Table 3. Association between Demographic Factors and Total OSA-18 QOL Scores. Characteristic Age BMI Sex Race ADHD Asthma Prematurity Arousal index Nadir oxygen saturation Central apnea index REM AHI Obstructive AHI
Test Statistic
P Value
–0.10a –0.08a 0.01b 3.20b –1.85b –2.77b –1.35b –0.04a –0.20a 0.01a 0.10a 0.03a
.25 .36 .99 .04c .06 .01c .18 .69 .02c .91 .25 .74
Abbreviations: ADHD, attention-deficit hyperactivity disorder; AHI, apneahypopnea index; BMI, body mass index; QOL, quality of life; REM, rapid eye movement. a Correlation coefficient. b Independent samples t test or analysis of variance. c P \.05.
AHI predicted total OSA-18 scores. We did identify a significant correlation between the sleep disturbance subscore of the OSA-18 and both the obstructive AHI and the REM AHI. Spruyt and Gozal9 reviewed the PSGs of 335 schoolaged children and found that respiratory events were 3.8 times more likely to occur during REM sleep. Only 18.6% of their subject population had a predominance of respiratory events during non-REM (NREM) sleep. Children with a REM predominance of respiratory events had more severe overall OSA disease severity and a higher arousal index. The authors, however, did not examine the association between REM-predominant OSA and QOL or daytime sleepiness. Thus, the impact of REM sleep fragmentation due to respiratory events on daytime function in children was previously unknown. No prior studies have investigated the association between REM AHI and QOL in children with SDB. To this end, relatively few studies have examined the correlation between daytime sleepiness and REM AHI in adults. In a cohort of adults undergoing PSG for suspected SDB, Haba-Rubio et al8 identified 151 patients with REM-predominant OSA (REM AHI/NREM AHI ratio .2). Compared with patients without REM-predominant OSA, those with REM-predominant OSA were younger and had higher BMI scores. There were no significant differences in daytime sleepiness as assessed by either the Epworth Sleepiness Scale or sleep latency on Maintenance of Wakefulness Testing between the 2 groups. These findings are in contrast to the work by Kass et al,10 which demonstrated significant correlation between daytime sleepiness and REM RDI in 34 adults. In this study, a REM RDI greater than 15 was the most accurate predictor of excessive daytime sleepiness as determined by a sleep latency of less than 10 minutes on MSLT.
A recent systematic review of outcome measures for adult OSA advocated for practitioners to routinely measure QOL, sleepiness, and school/occupational performance when assessing disease severity and determining treatment responses.14 The authors of the study cautioned against relying on the AHI as the sole metric of therapeutic effectiveness. Similarly, in children, QOL measures do not correlate with the severity of OSA as assessed by the AHI. Such findings highlight the need to develop outcome measures that can better assess the impact of OSA on patients’ physical symptoms, behavior, emotional state, and family interactions. In this work, we aimed to identify PSG parameters, such as the REM AHI, that could be associated with a child’s QOL and overall health status. In our study, there was not a significant association between REM AHI and QOL scores. Moreover, REM sleep disruption did not correlate with daytime manifestations of OSA, such as daytime sleepiness or poor concentration. The poor association between AHI and QOL demonstrates our lack of understanding the physiology of sleepiness and the daytime behavior impairments seen in children with OSA. Another possible explanation for the lack of correlation between the REM AHI and QOL scores involves the characteristics of our study population. We included all children with SDB symptoms who underwent PSG, regardless of severity of disease as assessed by AHI. Indeed, most children in our study had mild OSA. Perhaps a closer association between REM AHI and QOL scores exists in children with more severe OSA. We also examined additional PSG parameters in an attempt to identify other metrics that might better correlate with QOL in children with SDB. For example, previous research suggests that the number and duration of arousals may contribute to sleep fragmentation and the disruption of sleep architecture.9 Such disruption of sleep may be related to daytime manifestations of SDB such as poor behavior and difficulty with concentration.15 In our study, the only PSG parameter that correlated with total QOL scores was nadir oxygen saturation. Similarly, other authors have also reported that hypoxemia has a measurable negative impact on behavior, cognition, and academic performance. For example, Urschitz et al16 found that impaired academic performance in mathematics in schoolchildren was associated with lower nadir pulse oximetry saturations. The underlying pathophysiologic mechanisms involved in the link between intermittent nighttime oxygen desaturations and poor cognition remain largely unknown. One possible explanation may be found in a 2004 study that demonstrated that intermittent hypoxia increases oxidative stress and nitric oxide levels and leads to cortical and hippocampal cell death in rodents with SDB.17 There were several limitations of the present study. Although sleep position may influence the occurrence of respiratory events in some patients, we did not examine the role of sleep position in this study. Furthermore, data regarding the duration of obstructive symptoms were not routinely collected. On the basis of their work in adults with OSA, Haba-Rubio et al8 postulated that REM-predominant
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OSA is an early manifestation of OSA as opposed to a distinct clinical entity. It is possible that children with higher REM AHIs may be earlier in their disease course, but further research is needed to address this hypothesis. Finally, this study did not examine outcomes following treatment for SDB. Thus, we cannot comment on whether the REM AHI influences responses to therapy. It may be that a higher baseline REM AHI is associated with persistent daytime symptoms following adenotonsillectomy in pediatric patients with OSA. Future research initiatives should include both PSG parameters and validated QOL measures in prospective protocols for the evaluation of children with OSA both pre- and posttreatment.
Conclusion Neither the obstructive AHI nor the REM AHI was associated with QOL scores in this study of children with SDB. With the exception of nadir oxygen saturation, PSG parameters do not reflect the burden of SDB on QOL in children. The lack of correlation between AHI and QOL scores underscores the point that PSG alone cannot be used to determine the impact of OSA on a child’s health. Future research is needed to identify outcome measures that better quantify the impact of SDB on a child’s wellbeing. Author Contributions Cristina Marie Baldassari, study design, drafting of manuscript; Lyla Alam, study design, data acquisition, drafting of manuscript; Maria Vigilar, acquisition of data, editing of manuscript; James Benke, acquisition of data, critical review of manuscript; Charley Martin, data analysis and interpretation, editing manuscript; Stacey Ishman, study design, editing manuscript.
Disclosures Competing interests: None. Sponsorships: None. Funding source: None.
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