预测腰椎管狭窄手术后的恢复:一项使用加拿大脊柱结局研究网络(CSORN)数据的历史队列研究方案。

Erynne Rowe, Elizabeth Hassan, Lisa Carlesso, Janie Astephen Wilson, Douglas P Gross, Charles Fisher, Hamilton Hall, Neil Manson, Ken Thomas, Greg McIntosh, Brian Drew, Raja Rampersaud, Luciana Macedo
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引用次数: 1

摘要

背景:症状性腰椎管狭窄症(SLSS)是指椎管狭窄导致神经血管结构的夹持和压迫。对于那些症状严重且保守治疗失败的患者,推荐进行减压手术,伴或不伴脊柱融合。然而,显著的持续性疼痛、功能限制和麻醉使用可影响多达三分之一的术后患者。目的:本研究的目的是确定SLSS手术后1年预后的预测因素,重点是可修改的预测因素。方法:加拿大脊柱预后研究网络(CSORN)是一个大型数据库,收集了手术患者术前和术后预后的前瞻性数据。我们纳入了初步诊断为SLSS并进行首次脊柱手术的参与者。在手术后12个月测量结果,包括背部和腿部疼痛、残疾(Oswestry残疾指数,ODI)、行走能力(ODI项目4)、健康相关生活质量和总体恢复综合结果(疼痛、残疾和生活质量的临床重要变化)。预测因素包括人口统计学(教育水平、工作状况、婚姻状况、年龄、性别、体重指数)、体力活动水平、吸烟状况、既往保守治疗、药物摄入、抑郁、患者期望和其他合并症。多变量偏最小二乘模型用于确定结果的预测因子。结论:研究结果将为有针对性的SLSS干预提供信息,无论是选择最佳手术候选人还是确定手术前康复计划的目标。
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Predicting recovery after lumbar spinal stenosis surgery: A protocol for a historical cohort study using data from the Canadian Spine Outcomes Research Network (CSORN).

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.

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来源期刊
CiteScore
3.70
自引率
12.50%
发文量
36
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