Berlin Connor, Marino Alexandria C, Mummaneni Praveen V, Uribe Juan, Tumialán Luis M, Turner Jay, Wang Michael Y, Park Paul, Bisson Erica F, Shaffrey Mark, Gottfried Oren, Than Khoi D, Fu Kai-Ming, Foley Kevin, Chan Andrew K, Bydon Mohamad, Alvi Mohammed Ali, Upadhyaya Cheerag, Coric Domagoj, Asher Anthony, Potts Eric A, Knightly John, Meyer Scott, Buchholz Avery
1Department of Neurosurgery, University of Virginia, Charlottesville, Virginia.
2Department of Neurological Surgery, University of California, San Francisco, California.
J Neurosurg Spine. 2022 Jun 17;37(5):758-766. doi: 10.3171/2022.5.SPINE211425. Print 2022 Nov 1.
While surgical decompression is an important treatment modality for cervical spondylotic myelopathy (CSM), it remains unclear if the severity of preoperative myelopathy status affects potential benefit from surgical intervention and when maximum postoperative improvement is expected. This investigation sought to determine if retrospective analysis of prospectively collected patient-reported outcomes (PROs) following surgery for CSM differed when stratified by preoperative myelopathy status. Secondary objectives included assessment of the minimal clinically important difference (MCID).
A total of 1151 patients with CSM were prospectively enrolled from the Quality Outcomes Database at 14 US hospitals. Baseline demographics and PROs at baseline and 3 and 12 months were measured. These included the modified Japanese Orthopaedic Association (mJOA) score, Neck Disability Index (NDI), quality-adjusted life-years (QALYs) from the EQ-5D, and visual analog scale from the EQ-5D (EQ-VAS). Patients were stratified by preoperative myelopathy severity using criteria established by the AO Spine study group: mild (mJOA score 15-17), moderate (mJOA score 12-14), or severe (mJOA score < 12). Univariate analysis was used to identify demographic variables that significantly varied between myelopathy groups. Then, multivariate linear regression and linear mixed regression were used to model the effect of severity and time on PROs, respectively.
For NDI, EQ-VAS, and QALY, patients in all myelopathy cohorts achieved significant, maximal improvement at 3 months without further improvement at 12 months. For mJOA, moderate and severe myelopathy groups demonstrated significant, maximal improvement at 3 months, without further improvement at 12 months. The mild myelopathy group did not demonstrate significant change in mJOA score but did maintain and achieve higher PRO scores overall when compared with more advanced myelopathy cohorts. The MCID threshold was reached in all myelopathy cohorts at 3 months for mJOA, NDI, EQ-VAS, and QALY, with the only exception being mild myelopathy QALY at 3 months.
As assessed by statistical regression and MCID analysis, patients with cervical myelopathy experience maximal improvement in their quality of life, neck disability, myelopathy score, and overall health by 3 months after surgical decompression, regardless of their baseline myelopathy severity. An exception was seen for the mJOA score in the mild myelopathy cohort, improvement of which may have been limited by ceiling effect. The data presented here will aid surgeons in patient selection, preoperative counseling, and expected postoperative time courses.
虽然手术减压是治疗脊髓型颈椎病(CSM)的重要治疗方式,但术前脊髓病状态的严重程度是否会影响手术干预的潜在益处以及何时预期术后改善最大仍不清楚。本研究旨在确定对前瞻性收集的CSM手术后患者报告结局(PROs)进行回顾性分析时,按术前脊髓病状态分层是否存在差异。次要目标包括评估最小临床重要差异(MCID)。
从美国14家医院的质量结局数据库中前瞻性纳入了1151例CSM患者。测量了基线人口统计学数据以及基线、3个月和12个月时的PROs。这些指标包括改良日本骨科协会(mJOA)评分、颈部残疾指数(NDI)、EQ-5D的质量调整生命年(QALYs)以及EQ-5D的视觉模拟量表(EQ-VAS)。根据AO脊柱研究组制定的标准,将患者按术前脊髓病严重程度分层:轻度(mJOA评分15 - 17)、中度(mJOA评分12 - 14)或重度(mJOA评分<12)。采用单因素分析确定脊髓病组间有显著差异的人口统计学变量。然后,分别使用多因素线性回归和线性混合回归对严重程度和时间对PROs的影响进行建模。
对于NDI、EQ-VAS和QALY,所有脊髓病队列的患者在3个月时均取得了显著的最大改善,12个月时无进一步改善。对于mJOA,中度和重度脊髓病组在3个月时表现出显著的最大改善,12个月时无进一步改善。轻度脊髓病组的mJOA评分没有显著变化,但与病情更严重的脊髓病队列相比,总体上确实保持并获得了更高的PRO评分。mJOA、NDI、EQ-VAS和QALY在3个月时所有脊髓病队列均达到了MCID阈值,唯一的例外是轻度脊髓病队列在3个月时的QALY。
通过统计回归和MCID分析评估,脊髓型颈椎病患者在手术减压后3个月时,无论其基线脊髓病严重程度如何,其生活质量、颈部残疾、脊髓病评分和整体健康状况均有最大程度的改善。轻度脊髓病队列的mJOA评分是个例外,其改善可能受到天花板效应的限制。本文提供的数据将有助于外科医生进行患者选择、术前咨询以及预期术后病程的判断。