Suppr超能文献

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

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

作者信息

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

机构信息

School of Biomedical Engineering, McMaster University, Hamilton, Ontario, Canada.

Department of Mechanical Engineering, McMaster University, Hamilton, Ontario, Canada.

出版信息

Can J Pain. 2020 Dec 30;4(4):19-25. doi: 10.1080/24740527.2020.1734918.

Abstract

: 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. : The aim of this study will be to identify predictors of outcomes 1-year post SLSS surgery with a focus on modifiable predictors. : 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. : 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.

摘要

症状性腰椎管狭窄症(SLSS)是一种椎管狭窄导致神经血管结构受压的疾病。对于保守治疗失败且症状严重的患者,建议进行减压手术,可选择是否进行脊柱融合术。然而,高达三分之一的患者术后会出现严重的持续性疼痛、功能受限和使用麻醉药物的情况。本研究的目的是确定SLSS手术后1年预后的预测因素,重点关注可改变的预测因素。加拿大脊柱预后研究网络(CSORN)是一个大型数据库,前瞻性收集了手术患者术前和术后预后的数据。我们纳入了首次接受脊柱手术且初步诊断为SLSS的参与者。在术后12个月测量预后,包括背部和腿部疼痛、残疾程度(奥斯维斯特里残疾指数,ODI)、行走能力(ODI第4项)、健康相关生活质量以及总体恢复综合结果(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特征(教育程度、工作状态、婚姻状况、年龄、性别、体重指数)、身体活动水平、吸烟状况、既往保守治疗、药物摄入、抑郁、患者期望以及其他合并症。使用多元偏最小二乘模型来确定预后的预测因素。研究结果将为有针对性的SLSS干预提供依据,无论是为手术选择最佳候选人,还是为术前康复计划确定目标。

相似文献

本文引用的文献

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验