ArticleFrontiers in bioengineering and biotechnology2026
Noninvasive prescreening of pediatric adenoid hypertrophy using quantified MFCC statistics and clinical features: development and external validation.
Article in Frontiers in bioengineering and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Adenoid hypertrophy (AH) is a leading cause of pediatric obstructive sleep apnea, yet first-line diagnostics are invasive or resource-intensive. We developed and externally tested a low-cost, noninvasive screening model that fuses quantitative voice features with routine clinical variables for pre-endoscopy and primary-care triage. Methods: In a dual-center cross-sectional study (N = 202), Center 1 (Capital Center for Children's Health, Capital Medical University, n = 161) served as the development cohort and Center 2 (College of Otolaryngology Head and Neck Surgery, The 6th Medical Center, National Clinical Research Center for Otolaryngologic Diseases, Chinese PLA General Hospital, Beijing, China, n = 41) as the independent external cohort. Children produced sustained/a/phonations; Mel-frequency cepstral coefficients (MFCCs) were summarized into fixed statistics and combined with readily available clinical information. Modeling used patient-level aggregation with stratified 10-fold cross-validation in development. The final classifier was selected by a joint criterion of AUC and average precision (AP), then a single Youden-derived locked cutoff was determined in the development set and applied unchanged to the external cohort. Discrimination (AUC/AP), calibration (Brier score, slope, intercept), and clinical utility were evaluated. Results: Internal performance was stable (AUC = 0.81; AP = 0.84). On the small external cohort, discrimination remained (AUC = 0.79; AP = 0.88). At the locked cutoff, the model achieved clinically actionable sensitivity/specificity with balanced F1. Calibration was acceptable (Brier = 0.20, slope = 0.71, intercept = 0.94). Decision-curve analysis showed positive net benefit across a wide range of threshold probabilities versus "treat-all" and "treat-none." SHAP explainability indicated MFCC variability-related features and a subset of airway-symptom clinical variables as leading contributors, aligning with hyponasal resonance changes in AH. Conclusion: A patient-level model with a locked decision threshold showed preservation of discrimination in a small external cohort, supporting a practical pathway for noninvasive, low-overhead AH triage prior to nasoendoscopy. Prospective multicenter studies are warranted.
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