Analyzing and Modeling Gait Patterns in Patients with Coronal and Sagittal Spinal Deformities

Introduction: Adult spinal deformity (ASD) significantly affects patients through chronic back pain and functional limitations. ASD includes both coronal and sagittal deformities, each with distinct clinical features. While these deformities can be identified radiographically, their specific effects on gait remain unclear. This study aimed to analyze gait patterns in patients with coronal and sagittal deformities and those with degenerative spinal conditions, ultimately developing predictive models to differentiate among these presentations.

Methods: Patients with back pain attending a spinal surgical clinic were classified into sagittal deformity, coronal deformity, or degenerative spinal conditions. Inclusion criteria required the ability to walk unaided, age over 18, and lower back pain. Participants walked on a pressure-sensitive walkway to record various gait spatial-temporal parameters and demographic data. Conditions were categorized as sagittal deformity, coronal deformity, mixed deformities, or degenerative lumbar conditions. Cervical deformities were excluded. One-way ANOVA compared gait parameters across groups, and logistic regression predicted deformity types based on ANOVA results, with model accuracy and area under the curve (AUC) assessed.

Results: Eighty-six patients were analyzed: 37 with coronal deformity, 17 with sagittal deformity, 1 with mixed deformities, and 31 with degenerative conditions. Significant differences in gait parameters, including cadence and swing time, were found. Coronal deformity patients showed longer swing times compared to sagittal patients (95% CI: [0.02, 0.07]; P-value: 0.001). The predictive model achieved 80.64% accuracy (AUC: 0.82) for coronal deformity and 72.7% (AUC: 0.78) for sagittal deformity identification.

Conclusion : Coronal deformity patients exhibit distinct gait patterns, specifically longer foot advancement durations. These findings suggest that gait metrics may serve as objective indicators of spinal deformity severity, enhancing the assessment and management of ASD. Integrating gait analysis into clinical practice could provide valuable insights into adult spinal deformities.