Related Experiment Video
Updated: Jan 14, 2026
Drug-Induced Sleep Endoscopy DISE with Target Controlled Infusion TCI and Bispectral Analysis in Obstructive Sleep Apnea
Published on: December 6, 2016
Development of an explainable prediction model for the risk of moderate-to-severe obstructive sleep apnea in children
Fuzhi Lin1, Yufei Peng2, Xiaowei Chen1
1Department of Otorhinolaryngology-Head and Neck Surgery, Children's Hospital of Zhejiang University School of Medicine, No. 3333 Binsheng Road, Binjiang District, Hangzhou, 310051, Zhejiang Province, China.
Insights
A new nomogram helps identify children with moderate-to-severe obstructive sleep apnea (OSA) using clinical and inflammatory markers. This tool aids early diagnosis and intervention when polysomnography (PSG) is unavailable.
Area of Science:
- Pediatric Sleep Medicine
- Biomarker Discovery
- Clinical Prediction Modeling
Background:
- Polysomnography (PSG) is the gold standard for diagnosing pediatric obstructive sleep apnea (OSA), but its limited accessibility hinders early identification of severe cases.
- Accurate and timely diagnosis is crucial for effective intervention in children with moderate-to-severe OSA.
Purpose of the Study:
- To develop an interpretable clinical prediction model for early identification of moderate-to-severe pediatric OSA.
- To distinguish moderate-to-severe pediatric OSA from mild OSA using accessible clinical and inflammatory biomarkers.
Main Methods:
- Retrospective study of 164 children diagnosed with OSA via PSG.
- Least Absolute Shrinkage and Selection Operator (LASSO) regression to select predictive features.
- Multivariable logistic regression model presented as an interpretable nomogram, validated with bootstrap analysis.
Main Results:
- Eight core predictors identified: female sex, tonsil size (grades 3-4), adenoid-to-nasopharynx ratio (A/N ratio), IgE, IL-4, IL-6, and IL-10.
- The final model achieved a bootstrap-corrected AUC of 0.763 (95% CI 0.690-0.836).
- Decision curve analysis confirmed the model's clinical utility for risk assessment.
Conclusions:
- An explainable nomogram was developed integrating upper airway anatomy, allergic status, sex, and inflammatory cytokines (IL-4, IL-6, IL-10).
- This tool offers a practical, non-invasive method for individualized risk assessment of moderate-to-severe OSA in children.
- Facilitates prioritized diagnosis and intervention for children with moderate-to-severe OSA.
Abstract:
Early identification of children at high risk for moderate-to-severe obstructive sleep apnea (OSA) is crucial for timely intervention, yet is often hindered by limited access to polysomnography (PSG). We aimed to develop an interpretable clinical prediction model using easily obtainable clinical and inflammatory biomarkers to distinguish moderate-to-severe from mild pediatric OSA. We conducted a retrospective study of 164 children diagnosed with OSA by PSG. From multiple biomarkers and clinical variables, least absolute shrinkage and selection operator (LASSO) regression was employed to select the most predictive features. A multivariable logistic regression model was built and presented as an interpretable nomogram. Model performance was evaluated via bootstrap validation assessing discrimination, calibration, and clinical utility. The LASSO algorithm identified eight core predictors: female, tonsil size grades 3 and 4, adenoid-to-nasopharynx ratio (A/N ratio), IgE, IL-4, IL-6, and IL-10. The final model demonstrated robust performance, with a bootstrap-corrected AUC of 0.763 (95%CI 0.690-0.836). Decision curve analysis confirmed the model's clinical utility.
Conclusion:
We developed an explainable nomogram that integrates upper airway anatomy, allergic, sex, and specific inflammatory cytokines. This tool provides clinicians with a practical, non-invasive method for individualized risk assessment, facilitating the identification of children with moderate-to-severe OSA who may benefit from prioritized diagnosis and intervention.
What Is Known:
• Polysomnography(PSG) is the gold standard for diagnosing pediatric obstructive sleep apnea (OSA) but has limited accessibility, hindering the early identification of children at risk for moderate-to-severe disease.
What Is New:
• We developed an explainable nomogram that integrates sex, tonsil size, adenoid hypertrophy, allergy (IgE), and specific inflammatory cytokines (IL-4, IL-6, IL-10) to provide a practical, noninvasive tool for individualized risk assessment of moderate-to-severe OSA in children.
Related Concept Videos
01:21Sleep Apnea
The condition is more prevalent among...
01:17Other Pulmonary Disorders