Predicting recovery after lumbar spinal stenosis surgery: A protocol for a historical cohort study using data from the Canadian Spine Outcomes Research Network (CSORN). Issue 4 (21st December 2020)

• Record Type: Journal Article
• Authors: Rowe, Erynne; Hassan, Elizabeth; Carlesso, Lisa; Astephen Wilson, Janie; Gross, Douglas P.; Fisher, Charles; Hall, Hamilton; Manson, Neil; Thomas, Ken; McIntosh, Greg; Drew, Brian; Rampersaud, Raja; Macedo, Luciana
• Is Part Of: Canadian journal of pain =. Volume 4:Issue 4(2020)
• Page Start: 19
• Page End: 25
• Publication Date: 2020-12-21
• Subjects: lumbar spinal stenosis -- back pain -- longitudinal cohort study -- surgery -- partial least squares; Pain -- Periodicals; Pain -- Treatment -- Periodicals; Pain; Pain Management; Periodicals; 616.0472
• DOI: 10.1080/24740527.2020.1734918
• Languages: English
• ISSNs: 2474-0527

Abstract

ABSTRACT: Background : Symptomatic lumbar spinal stenosis (SLSS) is a condition in which narrowing of the spinal canal results in entrapment and compression of neurovascular structures. Decompressive surgery, with or without spinal fusion, is recommended for those with severe symptoms for whom conservative management has failed. However, significant persistent pain, functional limitations, and narcotic use can affect up to one third of patients postsurgery. Aims : The aim of this study will be to identify predictors of outcomes 1-year post SLSS surgery with a focus on modifiable predictors. Methods : The Canadian Spine Outcomes Research Network (CSORN) is a large database of prospectively collected data on pre- and postsurgical outcomes among surgical patients. We include participants with a primary diagnosis of SLSS undergoing their first spine surgery. Outcomes are measured at 12 months after surgery and include back and leg pain, disability (Oswestry Disability Index, ODI), walking capacity (ODI item 4), health-related quality of life, and an overall recovery composite outcome (clinically important changes in pain, disability, and quality of life). Predictors include demographics (education level, work status, marital status, age, sex, body mass index), physical activity level, smoking status, previous conservative treatments, medication intake, depression, patient expectations, and other comorbidities. A multivariate partial least squares model is used to identify predictors of outcomes. Conclusion : Study results will inform targeted SLSS interventions, either for the selection of best candidates for surgery or the identification of targets for presurgical rehabilitation programs.