Development of a pediatric obstructive sleep apnea triage algorithm

Abstract

Introduction Diagnosis and treatment of obstructive sleep apnea (OSA) in children is often delayed due to the high prevalence and limited physician and sleep testing resources. As a result, children may be referred to multiple specialties, such as pediatric sleep medicine and pediatric otolaryngology, resulting in long waitlists. Method We used data from our pediatric OSA clinic to identify predictors of tonsillectomy and/or adenoidectomy (AT). Before being seen in the clinic, parents completed the Pediatric Sleep Questionnaire (PSQ) and screening questionnaires for restless leg syndrome (RLS), nasal rhinitis, and gastroesophageal reflux disease (GERD). Tonsil size data were obtained from patient charts and graded using the Brodsky-five grade scale. Children completed an overnight oximetry study before being seen in the clinic, and a McGill oximetry score (MOS) was assigned based on the number and depth of oxygen desaturations. Logistic regression, controlling for otolaryngology physician, was used to identify significant predictors of AT. Three triage algorithms were subsequently generated based on the univariate and multivariate results to predict AT. Results From the OSA cohort, there were 469 eligible children (47% female, mean age = 8.19 years, SD = 3.59), with 89% of children reported snoring. Significant predictors of AT in univariate analysis included tonsil size and four PSQ questions, (1) struggles to breathe at night, (2) apneas, (3) daytime mouth breathing, and (4) AM dry mouth. The first triage algorithm, only using the four PSQ questions, had an odds ratio (OR) of 4.02 for predicting AT (sensitivity = 0.28, specificity = 0.91). Using only tonsil size, the second algorithm had an OR to predict AT of 9.11 (sensitivity = 0.72, specificity = 0.78). The third algorithm, where MOS was used to stratify risk for AT among those children with 2+ tonsils, had the same OR, sensitivity, and specificity as the tonsil-only algorithm. Conclusion Tonsil size was the strongest predictor of AT, while oximetry helped stratify individual risk for AT. We recommend that referral letters for snoring children include graded tonsil size to aid in the triage based on our findings. Children with 2+ tonsil sizes should be triaged to otolaryngology, while the remainder should be referred to a pediatric sleep specialist. Graphical abstract

The role of artificial intelligence in the treatment of obstructive sleep apnea

“…The study demonstrated that children with mild symptoms could avoid AT and outlined an approach to more accurately predict who should be treated with AT [ 31 ]. Another study focused on pediatric OSA developed an algorithm to predict the need for AT and highlighted that tonsil size was the strongest predictor of AT [ 32 ]. ML has also be applied in the setting of deciding whether children need postoperative overnight monitoring following AT [ 33 ].…”

Considerations in Surgical Management of Pediatric Obstructive Sleep Apnea: Tonsillectomy and Beyond

“…Other measures for determining OSA in lieu of PSG have been examined. These surrogate measures of OSA include tonsil size [13,24,25] clinical assessment, questionnaires [24,26], sleep videos [23], and overnight oximetry [14,24,27], with notable variables and often contested capacity to accurately identify children with OSA. As such, there is currently little consensus on the best way to define pediatric OSA that is widely applicable, accessible, successful, and cost effective when considering surgical management to treat the disease.…”

Barriers of artificial intelligence implementation in the diagnosis of obstructive sleep apnea

“…A study showed how the implications of adherence may challenge CPAP as the gold-standard, and demonstrated that surgery should also be considered in the context of an individual’s anatomical features, OSA severity and treatment goals [ 24 ]. This concept of considering individual anatomy guiding treatment is also evident in a study which developed a pediatric OSA algorithm and demonstrated that tonsil size was the strongest predictor of adenotonsillectomy (AT) [ 25 ]. Myofunctional therapy (MT) is another treatment option which involves oropharyngeal exercises and has been shown to decrease AHI by 50% in adults [ 26 , 27 ].…”