Utility of overnight oximetry indices in the evaluation of children with snoring and suspected obstructive sleep apnea

Study Objectives: Optimal cutoff values of oximetry indices that differentiate obstructive sleep apnea (OSA) from primary snoring (PS) are not well-established. Our study aimed to assess the utility of overnight oximetry indices in differentiating PS from OSA and assessing OSA severity, compared to polysomnography, in children with suspected OSA. Methods: This was a retrospective study of children (1-18 years of age) with snoring who underwent polysomnography. Patients with Down syndrome, craniofacial anomalies, known genetic syndromes, neuromuscular conditions, or a central apnea index >= 5 were excluded. Demographic data, polysomnography variables, and oximetry indices (eg, oxygen desaturation index [ODI3, defined as number of >= 3% desaturation episodes/h of artifact-free recording time, and SpO2 nadir]) were collected. Results: Of 1,203 children (mean age 9.1 +/- 3.9 years, 67.7% males), 91.8% (847/923) <= 12 years and 84.3% (236/280) > 12 years of age had OSA. The optimal cutoff of ODI3 for differentiating PS from OSA was 2.4 (sensitivity [Se]: 78.8% [75.9-81.6%]; specificity [Sp]: 80.5% [69.9-88.7%]) in children <= 12 years of age and 3.6 (Se: 71.1% [64.8-76.8%]; Sp: 91.1% [78.8-97.5%]) in children > 12 years of age. The optimal cutoffs of ODI3 for differentiating PS from mild, moderate, and severe OSA categories were 2.0 (Se: 70.1% [65.3-74.5%]; Sp: 70.1% [58.6-80.0%]), 3.7 (Se: 82.3% [76.6-87.1%]; Sp: 94.8% [87.2-98.6%]), and 4.3 (Se: 99.1% [96.8-99.9%]; Sp: 98.7% [93.0-100.0%]) in children <= 12 years of age and 1.9 (Se: 78.8% [75.9-81.6%]; Sp: 80.5% [69.9-88.7%]), 4.1 (Se: 85.4% [72.2-93.9%]; Sp: 91.1% [78.8-97.5%]), and 6.9 (Se: 98.4% [91.2-100.0%]; Sp: 97.8% [88.2-99.9%]) in children > 12 years of age, respectively. Conclusions: This study provides optimal cutoff values for ODI3 in differentiating PS from OSA and assessing OSA severity in children. Because oximetry is cheaper and widely available, ODI3 has the potential to be incorporated into cost-effective clinical decision-making algorithms, especially in resource-limited settings.