A new approach to evaluate obstructive sleep apnea according to body mass index using breathing diagram

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Abstract
Several studies have investigated predictive factors such as morphological, physiological, and fluid dynamics perspectives for obstructive sleep apnea (OSA) using computed tomography imaging, computer simulations, and experiments. Computational fluid dynamics is used in this study to analyze airflow in the upper airway across different body mass index (BMI) groups to identify suitable factors for predicting OSA. A comparative analysis is conducted on three groups: normal BMI (22.8 ± 1.0), overweight BMI (31.8 ± 1.5), and OSA (28.6 ± 3.3), with nine participants in each group. Geometric parameters were analyzed in addition to fluid dynamics factors. A comparison of the geometric variables revealed that the OSA group had the shortest total airway length (1.5 × 10−1 m) and the smallest volume (5.4 × 10−5 m3). However, t-test results showed low statistical significance for these differences. For fluid dynamics variables, the OSA group experienced the highest pressure drop (−46.8 Pa) and the highest adjusted pressure coefficient (Cp = 0.88) compared to the other two groups. From the analysis of breathing diagrams, the OSA group exhibited the largest area under the breathing power curve (32.6 × 10−3 N m/s) followed by the normal weight (24.9 × 10−3 N m/s) and overweight (21.0 × 10−3 N m/s) groups in descending order. Analysis of fluid dynamics factors indicated that the OSA group exhibited significantly higher pressure drop and pressure coefficient values compared to other groups although the differences between the groups were less significant. Finally, one key finding from this research highlights a new computational approach that relies on the breathing diagram. This new approach could provide more accurate insights into predicting and managing OSA due to their distinctive shapes.
Funding Information
  • Seoul Metropolitan Government Seoul National University Boramae Medical Center (03-2020-15)
  • National Research Foundation (2022R1A2C1093364)

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