Prospective validation of a brief questionnaire for predicting the severity of pediatric obstructive sleep apnea

Abstract

IntroductionPediatric obstructive sleep apnea (OSA) is diagnosed and stratified by polysomnography. However, due to cost and inaccessibility, up to 90% of children undergo tonsillectomy and adenoidectomy (T&A) solely based on clinical criteria. We previously developed a data-driven brief screening questionnaire (‘Selected Features,’ SF) that predicted OSA severity than alternatives. The SF asks the parent whether a child: (i) has had breath-holding spells at night over the past 4 weeks, (ii) is a mouth-breather during the day, (iii) has stopped growing at a normal rate any time since birth, and (iv) is overweight. This study sought prospectively validate the SF questionnaire. MethodsWe conducted a prospective assessment of the predictive accuracy of SF compared to the Pediatric Sleep Questionnaire—Sleep Related Breathing Disorder (PSQ-SRBD) scale in otherwise healthy children with sleep disordered breathing referred for T&A. We compared the model fits of PSQ-SRDB and SF for (i) a linear regression model for the prediction of OSA, and (ii) a logistic regression model for severe OSA, defined as apnea hypopnea index (AHI) > 10. P < 0.05 was significant. ResultsA total of 124 patients were included. The average age was 7.3 years (95% confidence interval, 6.6–8.0) and 66 (54%) were male. The racial composition was 54 (44%) black, 41 (33%) white, and 28 (23%) other. The median AHI was 4.8 (interquartile range 12) and 43 (35%) of patients had severe OSA. In linear and logistic regression models, SF outperformed the PSQ-SRBD and null models as measured by Akaike Information Criteria. The overall accuracy in predicting AHI >10 for PSQ-SRBD was 0.65 (0.56–0.73, P = 0.54) compared to 0.73 (0.64–0.80, P = 0.04) for SF. ConclusionBy eliminating redundancy, we have developed a questionnaire with improved prediction of OSA and its severity, in children with high pre-test probability of the condition. While multi-site validation is necessary, SF demonstrates value in screening children prior to T&A in resource-limited environments.