The Relationship Between Objective and Subjective Sleep Quality in Pediatric Obstructive Sleep Apnea
Open Access
- Author:
- Divincenzo, Marcella Marie
- Area of Honors:
- Nursing
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Amy M Sawyer, Thesis Supervisor
Harleah Graham Buck, Thesis Honors Advisor - Keywords:
- sleep apnea
obstructive sleep apnea
sleep quality
sleep fragmentation
sleep architecture
pediatric
children - Abstract:
- Background: There is a paucity of research that specifically addresses sleep quality impairment in children with obstructive sleep apnea (OSA). This study will describe objective and subjective sleep quality in children with OSA and explore the relationship between objective and subjective measures of sleep quality. Theoretical Framework: Increased frequency of respiratory-event related arousals and fragmentation of sleep in OSA disrupt normal sleep architecture, such that the homeostatic process of sleep is not sufficient and sleep quality is poor, as supported by the Two-Process Model of Sleep Regulation. Methods: A post-hoc, descriptive analysis of data from a parent study of children with OSA (n=28). Inclusion criteria: (1) male or female children aged 5-18 years, and (2) OSA diagnosis (apnea hypopnea index [AHI] ≥ 1 event/hr). Exclusion criteria: neuromuscular disease or chronic respiratory failure. Data was extracted from source documents (EMR and polysomnogram [PSG] acquisition system database). Data accrual was complete if a diagnostic PSG report was available. Objective sleep quality variables from PSG include: AHI, O2 saturation nadir, total sleep time, arousal index, respiratory effort related arousal index, wake after sleep onset, sleep efficiency, and sleep stage distribution (N1-N3; REM); subjective sleep quality measured by a single self-report item was assessed the morning after PSG. Descriptive statistics, graphical examination of variable distribution, and correlational procedures for objective and subjective sleep quality relationship are reported. Results: The sample of children and adolescents (mean age [yrs], 12.03± 3.43) with complete data for the analysis (n=28) included primarily males (61%) with severe OSA (mean AHI, 20.95 events/hour ± 25.53). The sample demonstrated objective disrupted sleep, as measured by PSG. In contrast, subjects rated their sleep quality primarily as good or average. No relationship existed between objective sleep quality, defined by respiratory event related arousals (RERAs), and self-reported subjective sleep quality though a possible increasing monotonic trend was identified via scatter plot. An exploratory correlational analysis between self-reported subjective sleep quality and objective sleep quality, measured as sleep efficiency by PSG revealed a significant increasing monotonic relationship (Spearman’s r = 0.69, p = 0.00), also verified by scatter plot. Conclusions & Implication: Overall sleep quality assessment by a simplistic survey item is not sensitive or specific to OSA in children. Screening for OSA in children cannot be reliably or accurately assessed by simplistic self-report of sleep quality. Rather, OSA screening should include use of validated OSA screening tools, such as STOP-BANG for children tool, to identify possible OSA; with a positive screening, follow up by PSG is necessary.