Predicting Risk of Obstructive Sleep Apnea in Children with Down Syndrome

Article

Disrupted sleep is prevalent among children and adolescents with Down syndrome and prompt diagnosis and management of the condition are crucial to ensure optimal health and well-being in this population.

Predicting Risk of Obstructive Sleep Apnea in Children with Down Syndrome

Poornima (P.R.) Wijayaratne, PhD candidate

Credit: LinkedIn

Results from recent research revealed the efficacy of a predictive model in determining moderate-severe obstructive sleep apnea (OSA) in children and adolescents with Down syndrome (DS). 1

With the model investigated, the risk factor of patients with DS for experiencing OSA may be accurately identified, therefore streamlining diagnosis and intervention. Specifically when treating patients with DS for OSA, upper airway stimulation can be very effective, especially if implemented early.2

Disrupted sleep is prevalent among children and adolescents with DS and prompt diagnosis and management of the condition are crucial to ensure optimal health and well-being in this population, according to the study. Current clinical guidelines recommend polysomnography (PSG) for all children with DS by the age of 4. 1

However, the investigators explained that access to PSG remains limited, and the testing process can be burdensome for both children and their families. P. R. Wijayaratne, PhD candidate at the Department of Paediatrics, Monash University, and investigators conducted a prospective cross-sectional cohort study to develop a predictive model for OSA in this patient population to assist in triaging patients for PSG.

The team aimed to identify a model capable of predicting OSA in pediatric patients with DS. The proposed model incorporated various demographic, anthropometric, quality of life, and sleep-related variables as potential predictors.

A comprehensive assessment was performed using the sleep-disordered breathing subscale of the Pediatric Sleep Survey Instrument and sleep fragmentation quantified using actigraphy.

The predictive model exhibited efficacy in determining moderate-severe OSA with excellent performance metrics, including high sensitivity (82%), specificity (80%), positive predictive value (75%), and negative predictive value (86%).

In the study, a total of 44 children and adolescents with DS were enrolled between May 2016 - May 2018. The cohort included two groups: those who clinically required a sleep study (n = 20) and those recruited through community advertising (n = 24).

Investigators mentioned the distribution of OSA severity did not differ between these 2 groups. The median age was 8.4 years (IQR, 5.3–12.8), and 57% were female.

Various questionnaires and assessments were completed by the participants and their caregivers. The OSA-18 questionnaire was completed by 66% (n = 29) of the children and adolescents, which provided insights into sleep-related quality of life.

The PSSI was completed by 86% (n = 38) of the participants, assessing sleep-disordered breathing symptoms. The Epworth Sleepiness Scale for Children and Adolescents (ESS-CHAD) data were available for 75% (n = 33) of the cohort, providing information on daytime sleepiness.

The Child Behavior Checklist (CBCL) was completed for 89% (n = 39) of the participants, offering insights into behavioral and emotional problems. The Adaptive Behavior Assessment System, Second Edition (ABAS-II) questionnaire data were available for 86% (n = 38) of the participants, assessing adaptive behavior.

Actigraphy measures, which exhibited objective data on sleep parameters, were available for a subset of the cohort. Time in bed (TIB), total sleep time (TST), sleep onset latency (SOL), sleep efficiency (SE), wake after sleep onset (WASO), and number of awakenings were measured for 66% (n = 29) of the participants.

Fragmentation indices, which quantify sleep fragmentation, were available for 61% (n = 27) of the cohort. The Actiwatch, a device worn on the wrist to collect sleep data, was worn for a median of 6.0 nights (IQR 5.0, 7.0). However, five (11%) children and adolescents did not tolerate wearing the Actiwatch.

Ultimately, these findings indicated the potential of the model to accurately identify individuals at risk of moderate-severe OSA within the DS population, according to the research. The team acknowledged the potential benefit of employing this tool to healthcare professionals in informed decision-making regarding the necessity of PSG.

Further research and validation studies are warranted to assess the generalizability and reproducibility of this model in different populations of children and adolescents with DS. Additionally, efforts should be made to enhance access to PSG and other diagnostic resources to ensure timely and accurate diagnosis of OSA in individuals with DS, aligning with the current clinical guidelines.

References:

  1. Wijayaratne, P. R., Williams, K., Davey, M. J., Horne, R. S. C. & Nixon, G. M. (2023) Prediction of obstructive sleep apnoea in children and adolescents with Down syndrome. Journal of Intellectual Disability Research. https://doi.org/10.1111/jir.13065
  2. Butera A. Upper Airway Stimulation Effective in OSA in Children with Down Syndrome. HCPLive. April 24, 2022. https://www.hcplive.com/view/upper-airway-stimulation-effective-in-osa-in-children-with-down-syndrome-

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