Comparing Patient-Reported Outcomes with Computational Fluid Dynamics-Derived Nasal Airflow After Nasal Airway Surgery: Prioritizing the Patient's Perception of Nasal Obstruction.

Abstract

Background: Some patients report persistent nasal obstruction after surgical treatment despite objective improvement. Objective: To compare patients' perceptions of nasal obstruction after surgery with objective nasal airflow as determined by computational fluid dynamics (CFD) modeling: (1) Is perception driven by a more symptomatic side? (2) Can symptom improvement be predicted with CFD modeling? Methods: Pre/postoperative Nasal Obstruction Symptom Evaluation (NOSE) and visual analog scale (VAS) score were collected for patients undergoing nasal obstruction surgery. Pre/postoperative computed tomography was used to generate patient-specific airway models for CFD simulation at 15 L/min resting inspiration. Results: Ten patients (22-53 years, seven men and three women) underwent septoplasty, turbinate reduction, and/or rhinoplasty. Postoperative NOSE was most correlated with postoperative VAS score from the "affected" side (R² = 0.59, p < 0.01), and postoperative NOSE was strongly predicted by a two-parameter model using parameters only from the "affected" side (R² = 0.84, adjusted R² = 0.80, p < 0.01). Conclusion: The postoperative state of the initially "affected" side drives outcomes after nasal obstruction surgery. Surgeries should prioritize improving the "affected" side. A two-parameter model using the VAS and nasal airflow from only the "affected" side strongly predicts NOSE and is promising for the future using virtual planning to individualize procedures to optimize outcome.