Abstract: Introduction: Efficacious screening of severe obstructive sleep apnea (OSA) is important for children with sleep-disordered breathing before time-consuming nocturnal polysomnography. However, the predictive performance of clinical variables, nocturnal unattended pulse oximetry, and snoring sound analysis to screen for severe pediatric OSA has not been comprehensively investigated. Methods: Forty-two consecutive children (11 [26%] girls and 31 [74%] boys; median age, 9 years; median body-mass index of 19.0 kg/m2) with loud snoring were prospectively recruited to undergo standard polysomnography, nocturnal pulse oximetry, and snoring sound analysis. Results: Binary logistic regression models showed that oxygen desaturation index ≥ 3% (> 5.9 events/h), adenoidal‐nasopharyngeal ratio (> 0.782), snoring sound energy of 801-1000 Hz (> 22.1 dB), and tonsil size (> 3) significantly predicted severe OSA, in descending order of odds ratio. Multivariate analysis showed that oxygen desaturation index ≥ 3%, adenoidal‐nasopharyngeal ratio, and tonsil size independently predicted severe OSA, and that their combination best predicted severe OSA (sensitivity = 91%; specificity = 84%; area under the curve = 0.92; p < 0.001). Conclusions: Our results suggested that pulse oximetry is better than snoring sound analysis to screen for severe OSA in children with loud snoring. A combination of oxygen desaturation index ≥ 3%, adenoidal‐nasopharyngeal ratio, and tonsil size can be used to efficiently screen for severe pediatric OSA.

Background: Systemic inflammation and tonsil microbiome have been linked to chronic intermittent hypoxia during sleep in children with obstructive sleep apnea (OSA). However, their relationships have not been comprehensively studied. Here, we investigated the associations between systemic inflammation, tonsil microbiome, OSA severity, and surgical outcome in pediatric OSA patients regarding different weight status. Methods: We recruited 33 children with OSA and non-healthy-weight (cases) and 33 children with OSA and healthy-weight (controls) were prospectively recruited and matched by the proportion of chronic tonsillitis. Each patient underwent adenotonsillectomy and received at least 3-month follow-ups. Systemic inflammatory biomarkers (interleukin [IL]-6, IL-10) were detected in the blood sampled in the morning. Tonsil microbiome was identified with 16S ribosomal RNA gene sequencing. OSA severity was assessed by standard whole-night polysomnography. Results: Differences in systemic inflammatory biomarkers, tonsil phyla, and apnea-hypopnea index were not statistically significant between both groups. After adenotonsillectomy, all OSA severity variables significantly improved; however, apnea-hypopnea index was significantly higher in the non-healthy-weight group and serum level of IL-6 significantly reduced in the healthy-weight group. The percentage changes in IL-6 and minimal pulse oxygen saturation were respectively associated with Deinococcus-Thermus and Eremiobacteraeota in the non-healthy-weight group, whereas the percentage change in IL-6 was associated with Patescibacteria and Cloacimonetes in the healthy-weight group. Furthermore, chronic tonsillitis was related to Chloroflexi, Acidobacteria, Euryarchaeota, Thermotogae, Hydrogenedentes, and Rokubacteria in the non-healthy-weight group. Conclusion: These preliminary findings are novel and provide insight for future research to understand the pathogenesis of the disease and to develop personalized treatments.