Diagnosis and Management of Childhood Obstructive Sleep Apnea Syndrome

Ward, Sally Davidson; Lehmann, Christopher; Jones, Jacqueline; Schechter, Michael S.; Sheldon, Stephen H.; Marcus, Lena; Brooks, Lee J.; Draper, Kari A.; Gozal, David; Carol, Ann

doi:10.1542/peds.2012-1671

Cited by 1,544 publications

(752 citation statements)

References 19 publications

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“…This was the case even when controlling for neighborhood income, BMI, and adenotonsillectomy, factors that have previously been associated with OSA in young children. 18,34 This finding parallels previous research showing increased OSA symptoms (ie, snoring and sleep-disordered breathing) among Black children relative to White children. [18][19][20] Seasonal allergies and asthma have been shown to increase risk for OSA 16 ; however, rates of these risk factors did not differ by race in this sample.…”

supporting

confidence: 84%

“…Identifying these genetic factors, and how they may interact with environmental effects to produce OSA onset in early childhood is especially important given the broad developmental risks that OSA poses to young children. 26,27,34 Further, despite Black preschoolers having sleep patterns similar to those of White children in this sample, a greater proportion of White children presented for difficulty falling/ staying asleep concerns and were given a diagnosis of pediatric insomnia. This difference was present even when we controlled for caregiver-child bed-sharing.…”

mentioning

confidence: 75%

“…We calculated time in bed (ie, sleep opportunity) using bedtime and wake time. We also abstracted medical information, including whether the patient had a history of adenotonsillectomy, as this surgery is the first-line treatment for OSA 34 and thus could affect whether children presented with OSA-related concerns. Other relevant medical information abstracted from the consultation note included risk factors for OSA 16 (ie, perinatal/birth complications and history of asthma or seasonal allergies) and current use of melatonin as a sleep aid.…”

Section: Methodsmentioning

confidence: 99%

“…We additionally entered in previous adenoid or tonsil removal surgery as a covariate in OSA-related models, given that this surgery is the first-line treatment for pediatric OSA in the context of adenoid or tonsillar hypertrophy. 34 Alpha level for logistic regressions was set at .05.…”

Section: Analysesmentioning

confidence: 99%

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Differences in Sleep Patterns and Problems by Race in a Clinical Sample of Black and White Preschoolers

Williamson

Rubens

Patrick

et al. 2017

Journal of Clinical Sleep Medicine

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Study Objectives: Community-based research indicates that Black preschoolers tend to have more bedtime difficulties and are at higher risk for obstructive sleep apnea (OSA) compared to White preschoolers. This study examined differences in sleep patterns and problems by race among a clinical sample of Black and White preschoolers at an outpatient sleep clinic. Methods: Data were collected from electronic medical records for 125 children ages 2-5 years (mean = 3.37 years, 64.0% White, 36.0% Black; 59.2% male) presenting at a pediatric sleep clinic in an academic medical center. Neighborhood income data were based on ZIP codes entered into the United States Census Bureau's American Fact Finder. Results: Black patients (51.1%) were significantly more likely than White patients (20.0%) to bed-share with a caregiver (χ 2 = 12.99, P ≤ .001). There were no other significant differences in presenting sleep patterns (bed/wake times, sleep onset latency, naps, night awakenings, or sleep opportunity). Logistic regressions showed that White patients were more likely to present with difficulty falling/staying asleep and receive an insomnia diagnosis, and Black patients were more likely to present with OSA-related concerns and receive a diagnosis of suspected OSA, even when controlling for relevant sociodemographic covariates. Conclusions: In contrast to community-based research, Black and White children showed similar sleep patterns. However, there were differences by race in referral questions and diagnoses. Findings suggest the need to consider caregiver perceptions and other sociocultural factors that may contribute to differential rates of presentation for sleep services, as well as potential health disparities in this regard. I NTRO DUCTI O NAlthough sleep problems affect 20% to 30% of infants, preschoolers, and kindergarteners, 1,2 recent research indicates that young children from non-White racial/ethnic backgrounds are at increased risk of experiencing sleep difficulties compared to non-Hispanic/Latino White youth (hereafter the term "White" will be used to reference non-Hispanic/Latino White racial/ ethnic background). Specifically, studies comparing Black and White children have found that racial/ethnic background is a significant predictor of variation in preschoolers' sleep regularity, duration, and quality.3-5 Community-based studies have shown that Black preschoolers are more likely than their White peers to exhibit symptoms of behavioral sleep disturbances, such as increased bedtime resistance, longer sleep onset latency, and shorter total sleep duration.5-8 Aspects of sleep routines and the sleep environment also differ by race, with Black children showing later bedtimes and decreased likelihood of following a regular bedtime routine, 5,6,8,9 as well as higher rates of parent-child bed-sharing. 10,11 Later bedtimes and less regular bedtime routines have been associated with increased child sleep disturbances, 2,12,13 and research on the effect of bed-sharing on child sleep is mixed.11 Some families may choos...

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supporting

confidence: 84%

mentioning

confidence: 75%

Section: Methodsmentioning

confidence: 99%

Section: Analysesmentioning

confidence: 99%

See 2 more Smart Citations

Differences in Sleep Patterns and Problems by Race in a Clinical Sample of Black and White Preschoolers

Williamson

Rubens

Patrick

et al. 2017

Journal of Clinical Sleep Medicine

View full text Add to dashboard Cite

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“…However, a clinically optimal predictive model that included other known demographic risk factors could not be determined. These study findings are important, as they demonstrate that PSG reliably provides information that can help clinicians prepare for potential adverse events related to postoperative respiratory recovery, but the decision to admit patients postoperatively for monitoring should also include physician clinical judgment based on the patient's other risk factors and social situations.The literature and recent guidelines have been more consistent in their recommendations for postoperative overnight monitoring based on demographic risk factors rather than OSAS 2,3,5,10,13,14,18,19,[25][26][27][28][29] Specifically, both AAP and AAO-HNSF guidelines agree that children should be admitted postoperatively if they have high-risk factors including age <3 years, obesity, and/or various comorbidities. 2,3,5,10,13,14,18 In the current study, only some demographic characteristics were found to be significantly associated with adverse major respiratory events (age <3 years and presence of FTT [regardless of age]), but we did not find this to be true for children who had a history of prematurity, other comorbidities, or obesity.…”

mentioning

confidence: 99%