Title: Palatal Height Predicts Pharyngeal Airway Volume in a Multi-Variate Model
Erin Yoshida (Presenter)
UMKC School of Dentistry
Vandana Kumar, UMKC School of Dentistry
JoAnna Scott, UMKC School of Dentistry
Shankar Rengasamy Venugopalan, University of Missouri - Kansas City
Objectives: Obstructive sleep apnea (OSA) is a common disorder that when left untreated is associated with comorbidities such as systemic hypertension, depression, stroke, angina, and also an increased risk of mortality. Certain orofacial characteristics and a smaller airway volume have been shown to potentiate OSA. Objective: The aim of this study is to investigate the craniofacial predictors of pharyngeal airway volume using Cone Beam Computed Tomography (CBCT) in a multi-variate model.
Methods: This retrospective study was approved by the UMKC Institutional Review Board (#17-167). CBCT scans from the private practice of UMKC Oral Radiology Faculty were used for this study. All patient related information was de-identified prior to the start of the study. The inclusion criteria of this study were: (1) Full head scans, (2) No obvious pathology, and (3) patients have completed growth (16+ years). The study consists of 42 CBCT scans. Airway volume, palatal height, and palatal width were measured using InVivoDental software. Orthogonal lateral cephalometric radiographs were constructed from the CBCT scans and uploaded into Dolphin Imaging Software for cephalometric tracing. Bivariate tests of association of the cephalometric variables with airway volume were completed using linear regression. Variables with P<0.1 were included in multivariate regression analysis and a multivariate model for airway volume was created.
Results: Bivariate analysis identified six cephalometric variables associated with airway volume at the 0.1 level: palatal height, length of mandibular base, lower face height, total face height, mandibular length, and corpus length. After multivariate analysis, only palatal height was significantly associated with airway volume (p=0.023).
Conclusions: There are craniofacial predictors of pharyngeal airway volume that can be evaluated using CBCT. Skeletal class and position of the mandible did not have a significant association with pharyngeal airway volume, as previously reported, in our model. Palatal height has a significant positive association with airway volume and can be used as a predictor. This study was supported by the UMKC School of Dentistry Summer Scholars Program.