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Statistical Validation of Unsupervised Clustering for Adolescent TMD: A Cross-Sectional Study
1Department of Orofacial Pain and Oral Medicine, College of Dentistry, Dankook University, Cheonan, South Korea.
Oral Diseases
|March 27, 2025
Summary
Unsupervised clustering identified three Temporomandibular disorders (TMD) phenotypes in adolescents: High Impact, Mild Symptoms, and High Catastrophizing. This approach may improve TMD diagnosis and treatment for young patients.
Area of Science:
- Adolescent health
- Biomedical research
- Pain management
Background:
- Temporomandibular disorders (TMD) present varied symptoms in adolescents.
- Current diagnostic methods may not fully capture the complexity of TMD presentations.
- Identifying distinct patient subgroups is crucial for effective treatment.
Purpose of the Study:
- To apply unsupervised clustering to identify distinct Temporomandibular disorders (TMD) phenotypes in adolescents.
- To characterize these clusters based on biopsychosocial features.
- To compare unsupervised clusters with conventional TMD classifications for diagnostic enhancement.
Main Methods:
- Analysis of data from 662 adolescent TMD patients.
- Unsupervised clustering to group patients based on biopsychosocial factors.
- Assessment of pain severity, catastrophizing, psychological distress, and sleep quality.
Main Results:
- Three distinct clusters emerged: High Impact (n=70), Mild Symptoms (n=423), and High Catastrophizing (n=169).
- These clusters differed significantly in pain severity, pain catastrophizing, psychological distress, and sleep disturbances.
- Conventional TMD classifications primarily differentiated subgroups by pain severity alone.
Conclusions:
- Adolescent TMD presentations are highly variable.
- Integrating phenotyping with conventional diagnostics can improve accuracy and treatment outcomes.
- This approach aids in better management of high-risk adolescent TMD patients.
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