0504 Identifying Risk Factors for Developing Sleep Disorders

Amanda Johnson,Vanessa Gonsalves, Brittany Walker,Amanda Santos, Leana Goncalves Araujo,Anael Santos, Akinyemi Ajayi

Sleep(2022)

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摘要
Abstract Introduction Sleep disorders in the pediatric clinical setting are often overlooked and under-screened. The study compared a set of clinical behavior questions and physiological risk factors with potential to increase the risk for sleep disorders within children. Methods A retrospective archive from electronic medical records was analyzed from 695 pediatric patients, 7-14 years old, that visited a pediatric clinic from March-November of 2019. Children or their parents reported on the presence of eight behavioral and physiological factors on the Kids Sleep Screener Questionnaire (KSSQ), which were used as potential risk factors for sleep disorders. The propensity of daytime sleepiness was measured using the Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD). Univariate analysis was performed to find frequencies to summarize the risk factors. Chi square test was used to test for associations between risk factors and ESS-CHAD. Multiple logistic regression (MLR) was used to predict different combinations of factors with ESS-CHAD. Odd ratios (ORs) and 95% CI were used to quantify the level of association. Receiver operating characteristic (ROC) with area under the curve analysis was used to compare three MLR models. Results The risk factors were positively (p<0.05) associated with ESS-CHAD. Excessive daytime sleepiness and increased sleep duration were risk factors with greater potential to predict sleep disorder. They presented 3 times greater (p<0.05) potential to predict sleep disorder than snoring, and 4 times than restless sleep and sleep onset latency. The two combined risk factors with greatest potential to predict sleep disorder are restless sleep with excessive daytime sleepiness, and sleep onset delay with excessive daytime sleepiness.Risk for potential sleep disorders is best assessed when considering the different risk factors with gender. Considering gender, the risk factors with greatest relationship to predict potential sleep disorders were sleep duration, excessive daytime sleepiness, night wakings and the previous discussed combinations (restless sleep with excessive daytime sleepiness, and sleep onset delay with excessive daytime sleepiness). Conclusion The Kids Sleep Screener Questionnaire is a potential tool to predict sleep disorder. Further studies are warranted to explore the behavior and physiological risk factors with potential to increase the risk for sleep disorders. Support (If Any)
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Developmental Surveillance
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