Hallands Sjukhus Varberg, Varberg, Sweden.
Department of Surgery and Orthopaedics, Alingsås Lasarett, Alingsås, Sweden.
BMC Musculoskelet Disord. 2024 Aug 21;25(1):654. doi: 10.1186/s12891-024-07714-5.
Patients surgically treated for lumbar spinal stenosis or cervical radiculopathy report improvement in approximately two out of three cases. Advancements in Machine Learning and the utility of large datasets have enabled the development of prognostic prediction models within spine surgery. This trial investigates if the use of the postoperative outcome prediction model, the Dialogue Support, can alter patient-reported outcome and satisfaction compared to current practice.
This is a prospective, multicenter clinical trial. Patients referred to a spine clinic with cervical radiculopathy or lumbar spinal stenosis will be screened for eligibility. Participants will be assessed at baseline upon recruitment and at 12 months follow-up. The Dialogue Support will be used on all participants, and they will thereafter be placed into either a surgical or a non-surgical treatment arm, depending on the decision made between patient and surgeon. The surgical treatment group will be studied separately based on diagnosis of either cervical radiculopathy or lumbar spinal stenosis. Both the surgical and the non-surgical group will be compared to a retrospective matched control group retrieved from the Swespine register, on which the Dialogue Support has not been used. The primary outcome measure is global assessment regarding leg/arm pain in the surgical treatment group. Secondary outcome measures include patient satisfaction, Oswestry Disability Index (ODI), EQ-5D, and Numeric Rating Scales (NRS) for pain. In the non-surgical treatment group primary outcome measures are EQ-5D and mortality, as part of a selection bias analysis.
The findings of this study may provide evidence on whether the use of an advanced digital decision tool can alter patient-reported outcomes after surgery.
The trial was retrospectively registered at ClinicalTrials.gov on April 17th, 2023, NCT05817747.
Clinical multicenter trial.
接受腰椎管狭窄症或颈椎神经根病手术治疗的患者，约有三分之二的患者报告症状得到改善。机器学习的进步和大型数据集的应用，使得脊柱外科中的预后预测模型得以开发。本试验旨在研究使用术后结局预测模型——Dialogue Support 是否可以改变患者报告的结局和满意度，与当前的治疗方法相比。
这是一项前瞻性、多中心的临床试验。颈椎神经根病或腰椎管狭窄症患者在脊柱门诊就诊时，将进行筛选以确定其是否符合纳入标准。参与者将在招募时进行基线评估，并在 12 个月时进行随访。所有参与者都将使用 Dialogue Support，根据患者和外科医生之间的决策，他们将被分为手术治疗或非手术治疗组。基于诊断为颈椎神经根病或腰椎管狭窄症，将对手术治疗组进行单独研究。手术组和非手术组将与从 Swespine 注册中心检索的回顾性匹配对照组进行比较，Dialogue Support 未在此注册中心使用。手术治疗组的主要结局测量指标是腿部/手臂疼痛的总体评估。次要结局测量指标包括患者满意度、Oswestry 残疾指数 (ODI)、EQ-5D 和疼痛的数字评定量表 (NRS)。非手术治疗组的主要结局测量指标是 EQ-5D 和死亡率，作为选择偏倚分析的一部分。
本研究的结果可能提供有关使用先进的数字决策工具是否可以改变手术后患者报告的结局的证据。
该试验于 2023 年 4 月 17 日在 ClinicalTrials.gov 进行了回顾性注册，NCT05817747。
临床多中心试验。
