Development and validation of a predictive model (CHASE-OSA) for preoperative assessment of moderate-to-severe pediatric obstructive sleep apnea

Purpose Undetected obstructive sleep apnea (OSA) in children increases the likelihood of perioperative respiratory complications. Current screening tools for OSA often lack sensitivity or are overly complex. This study aimed to develop and validate a simplified preoperative predictive model for moderate-to-severe pediatric OSA. Methods The study included children aged 1 to 18 years who underwent either polysomnography or nocturnal pulse oximetry from January 2013 to December 2020. OSA severity was categorized using these tests, and potential predictors were identified using multivariable logistic regression. The outcomes of the tests were used to create a risk-based scoring system. Internal validation was performed using bootstrapping procedures. Results Out of the 1,327 participants, 882 individuals (66.5%) were diagnosed with moderate-to-severe OSA. Predictors considered for developing the scoring system included Craniofacial abnormalities, adenotonsillar Hypertrophy, Age 1-5 years, Snoring > 5 nights/week, Excessive daytime sleepiness, Obesity, Stopping breathing, and Awakening during sleep (CHASE-OSA). The scoring system developed demonstrated an area under the receiver operating characteristic curve of 0.85 (95% CI: 0.83-0.88). The CHASE-OSA score, ranging from 0 to 14, classified scores < 6 as low-risk and >= 6 as high-risk for moderate-to-severe pediatric OSA. This cutoff demonstrated a sensitivity of 86%, specificity of 70%, and positive and negative predictive values of 85% and 71%, respectively. Conclusion The CHASE-OSA predictive model provides a concise and user-friendly preoperative screening tool for identifying moderate-to-severe pediatric OSA. It facilitates risk assessment, enhances perioperative care optimization, and informs postoperative management planning. Further research is needed to comprehensively validate its clinical utility.