Jensen Rikke K, Kent Peter, Jensen Tue S, Kjaer Per
Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark.
Medical Department, Spine Centre of Southern Denmark, Lillebaelt Hospital, Middelfart, Denmark.
BMC Musculoskelet Disord. 2018 Feb 20;19(1):62. doi: 10.1186/s12891-018-1978-x.
Research into the clinical importance of spinal MRI findings in patients with low back pain (LBP) has primarily focused on single imaging findings, such as Modic changes or disc degeneration, and found only weak associations with the presence of pain. However, numerous MRI findings almost always co-exist in the lumbar spine and are often present at more than one lumbar level. It is possible that multiple MRI findings are more strongly associated with LBP than single MRI findings. Latent Class Analysis is a statistical method that has recently been tested and found useful for identifying latent classes (subgroups) of MRI findings within multivariable datasets. The purpose of this study was to investigate the association between subgroups of MRI findings and the presence of LBP in people from the general population.
To identify subgroups of lumbar MRI findings with potential clinical relevance, Latent Class Analysis was initially performed on a clinical dataset of 631 patients seeking care for LBP. Subsequently, 412 participants in a general population cohort (the 'Backs on Funen' project) were statistically allocated to those existing subgroups by Latent Class Analysis, matching their MRI findings at a segmental level. The subgroups containing MRI findings from the general population were then organised into hypothetical pathways of degeneration and the association between subgroups in the pathways and the presence of LBP was tested using exact logistic regression.
Six subgroups were identified in the clinical dataset and the data from the general population cohort fitted the subgroups well, with a median posterior probability of 93%-100%. These six subgroups described two pathways of increasing degeneration on upper (L1-L3) and lower (L4-L5) lumbar levels. An association with LBP was found for the subgroups describing severe and multiple degenerative MRI findings at the lower lumbar levels but none of the other subgroups were associated with LBP.
Although MRI findings are common in asymptomatic people and the association between single MRI findings and LBP is often weak, our results suggest that subgroups of multiple and severe lumbar MRI findings have a stronger association with LBP than those with milder degrees of degeneration.
对腰痛(LBP)患者脊柱MRI检查结果临床重要性的研究主要集中在单一影像学表现,如Modic改变或椎间盘退变,且发现其与疼痛存在之间仅有微弱关联。然而,众多MRI表现几乎总是在腰椎同时存在,且常在多个腰椎节段出现。多个MRI表现可能比单一MRI表现与LBP的关联更强。潜在类别分析是一种统计方法,最近经过测试,发现可用于识别多变量数据集中MRI表现的潜在类别(亚组)。本研究的目的是调查MRI表现亚组与普通人群中LBP存在之间的关联。
为识别具有潜在临床相关性的腰椎MRI表现亚组,首先对631名因LBP寻求治疗的患者的临床数据集进行潜在类别分析。随后,通过潜在类别分析将普通人群队列(“Funen背部”项目)中的412名参与者按节段水平匹配其MRI表现,统计分配到现有的那些亚组中。然后将包含普通人群MRI表现的亚组组织成假设的退变途径,并使用精确逻辑回归测试途径中亚组与LBP存在之间的关联。
在临床数据集中识别出六个亚组,普通人群队列的数据与这些亚组拟合良好,后验概率中位数为93%-100%。这六个亚组描述了上腰椎(L1-L3)和下腰椎(L4-L5)水平退变加重的两条途径。在下腰椎水平描述严重和多发退变MRI表现的亚组与LBP存在关联,但其他亚组均与LBP无关联。
尽管MRI表现在无症状人群中很常见,且单一MRI表现与LBP之间的关联通常较弱,但我们的结果表明,多个和严重的腰椎MRI表现亚组与LBP的关联比退变程度较轻的亚组更强。