Clinical Characteristics Combined with Craniofacial Photographic Analysis in Children with Obstructive Sleep Apnea

Area of Science:

• Pediatric Pulmonology
• Sleep Medicine
• Craniofacial Medicine

Background:

• Diagnosing obstructive sleep apnea (OSA) in children, especially those at high risk, presents significant clinical challenges.
• Current diagnostic methods like polysomnography can be resource-intensive and inaccessible in certain healthcare settings.

Purpose of the Study:

• To investigate key clinical features and craniofacial photographic analysis for identifying OSA in children.
• To develop and validate a predictive screening model for pediatric OSA.

Main Methods:

• A cohort of 145 children (controls, primary snoring, OSA) underwent clinical assessment and craniofacial photography.
• Logistic regression analysis was employed to identify risk factors and build a prediction model for OSA.
• Statistical comparisons of demographic characteristics and facial morphology were conducted across groups.

Main Results:

• Significant differences in BMI z-score, tonsil hypertrophy, and lower face width were observed in children with OSA.
• The developed screening model demonstrated a classification accuracy of 79.3%, with 64.2% sensitivity and 89.1% specificity.
• The model achieved an area under the curve of 81.0, indicating good predictive performance.

Conclusions:

• A screening model integrating clinical data and craniofacial measurements offers a valuable tool for diagnosing pediatric OSA.
• This approach can assist clinical decision-making, particularly in resource-limited environments where polysomnography is not readily available.