Exploration of physical performance, surgical decision-making, and clinical screening for individuals with low back pain
The prevalence of low back pain (LBP) has been steadily increasing in the United States, with current lifetime rates between 80-90%. As a result, LBP is currently the second leading cause of disability in the nation and leading cause of workdays missed. With annual direct and indirect costs estimated between $300-600 billion in the United States alone, there is a growing demand for treatment for individuals with LBP and associated symptoms. Most urgently, there is a need for adequate identification and triage of individuals who would benefit from lumbar surgery, as this population contributes highest to direct and indirect treatment costs. Clinical research evaluating the diagnosis and management of patients with LBP has not kept pace with the growing costs, resulting in a severe lack of high-quality evidence to identify optimal screening, assessment, and treatment. The purpose of the subsequent studies was to aid in the surgical screening process for individuals with LBP by exploring the decision-making of spine physicians and identifying surgical screening tools to help improve efficiency of this process in the future. To this end, a novel screening tool, the functional lumbar index (FLI) was developed by incorporating several commonly utilized physical performance tests into one scoring system. The FLI was validated as an effective tool for identifying individuals who failed conservative management for their LBP using a Poisson regression. Next, five physicians with a high-volume clinical practice of individuals with LBP were interviewed to discuss their individual opinions behind the surgical decision-making process. This data was used to develop the following themes: importance of diagnostic imaging, need for functional assessment, impact of neurologic status, and non-musculoskeletal considerations. The final study prospectively analyzed 50 individuals pre-selected for either surgery (n=25) or conservative care (n=25) on which objective data would best predict pre-determined grouping. Multiple logistic regression analysis was used to identify that the FLI and neurologic status were both significant predictors of pre-determined surgical grouping.