Predictive effect of cervical spinal cord compression and corresponding segmental paravertebral muscle degeneration on the severity of symptoms in patients with cervical spondylotic myelopathy

Lin, Taotao; Wang, Zhenyu; Chen, Gang; Liu, Wenge

doi:10.1016/j.spinee.2021.03.030

Cited by 14 publications

(9 citation statements)

References 24 publications

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“…Although the current study has demonstrated a correlation between CR, ISI, and CSM severity, 35,36 the measurement of CR is subject to subjectivity, and there is also variability in the measurement results between doctors 37–39 . While dMRI is less affected by subjectivity, 8,28,40 it remains controversial whether dMRI can preoperatively predict postoperative CSM patient outcomes 8,18,21 .…”

Section: Discussionmentioning

confidence: 72%

“…In other words, the pathological changes represented by multiple variables will jointly affect the treatment effect of the patients after surgery. Consequently, the multifactor regression model is more suitable for Although the current study has demonstrated a correlation between CR, ISI, and CSM severity, 35,36 the measurement of CR is subject to subjectivity, and there is also variability in the measurement results between doctors. [37][38][39] While dMRI is less affected by subjectivity, 8,28,40 it remains controversial whether dMRI can preoperatively predict postoperative CSM patient outcomes.…”

Section: Discussionmentioning

confidence: 95%

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Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy

Wen

Zhang

et al. 2023

Magnetic Resonance Imaging

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BackgroundDiffusion magnetic resonsance imaging (dMRI) can potentially predict the postoperative outcome of cervical spondylotic myelopathy (CSM).PurposeTo explore preoperative dMRI parameters to predict the postoperative outcome of CSM through multifactor correlation analysis.Study TypeProspective.PopulationPost‐surgery CSM patients; 102 total, 73 male (52.42 ± 10.60 years old) and 29 female (52.0 ± 11.45 years old).Field Strength/Sequence3.0 T/Turbo spin echo T1/T2‐weighted, T2*‐weighted multiecho gradient echo and dMRI.AssessmentSpinal cord function was evaluated using modified Japanese Orthopedic Association (mJOA) scoring at different time points: preoperative and 3, 6, and 12 months postoperative. Single‐factor correlation and t test analyses were conducted based on fractional anisotropy (FA), mean diffusivity, intracellular volume fraction, isotropic volume fraction, orientation division index, increased signal intensity, compression ratio, age, sex, symptom duration and operation method, and multicollinearity was calculated. The linear quantile mixed model (LQMM) and the linear mixed‐effects regression model (LMER) were used for multifactor correlation analysis using the combinations of the above variables.Statistical TestsDistance correlation, Pearson's correlation, multiscale graph correlation and t tests were used for the single‐factor correlation analyses. The variance inflation factor (VIF) was used to calculate multicollinearity. LQMM and LMER were used for multifactor correlation analyses. P < 0.05 was considered statistically significant.ResultsThe single‐factor correlation between all variables and the postoperative mJOA score was weak (all r < 0.3). The linear relationship was stronger than the nonlinear relationship, and there was no significant multicollinearity (VIF = 1.10–1.94). FA values in the LQMM and LMER models had a significant positive correlation with the mJOA score (r = 5.27–6.04), which was stronger than the other variables.Data ConclusionThe FA value based on dMRI significantly positively correlated with CSM patient postoperative outcomes, helping to predict the surgical outcome and formulate a treatment plan before surgery.Evidence Level1Technical EfficacyStage 2

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Section: Discussionmentioning

confidence: 72%

Section: Discussionmentioning

confidence: 95%

Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy

Wen

Zhang

et al. 2023

Magnetic Resonance Imaging

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“…[13] Taotao Lin et al demonstrated that the severity of the degeneration of cervical PSMs in CR was associated with the cervical sagittal parameters and neck pain but not with paresthesia, limb weakness, gait disturbance, neurological dysfunction, and bladder/intestinal dysfunction. [9] Due to the differences in the function of the neck flexors and extensors, clinical presentations of CR may also differ, indicating that some muscles may not be associated with CR. Elliott et al reported that in CR patients exhibiting occult neck pain, symptom duration and NDI score were not associated with cervical extensor muscles.…”

Section: Risk Factors In Assessing Cr Based On Imaging Characteristicsmentioning

confidence: 99%

“…Lin et al found that age was inversely associated with symptom severity in patients under the age of 50 years but positively associated with patients older than 60, suggesting that older age was associated with more severe symptoms. [9] We used the ROC curve method to assess the ability of age and flexors alone and in combination to predict CR and found that the combination of both indicators exerted the best effect. Furthermore, to clarify the clinical significance of age and cervical flexors in CR, we constructed a clinical predictive model.…”

Section: Age Cervical Flexors and Crmentioning

confidence: 99%

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Age and flexors as risk factors for cervical radiculopathy: A new machine learning method

Pan,

Liu,

Chen

et al. 2024

Medicine

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This study aimed to investigate the risk factors for cervical radiculopathy (CR) along with identifying the relationships between age, cervical flexors, and CR. This was a retrospective cohort study, including 60 patients with CR enrolled between December 2018 and June 2020. In this study, we measured C2 to C7 Cobb angle, disc degeneration, endplate degeneration, and morphology of paraspinal muscles and evaluated the value of predictive methods using receiver operating characteristic curves. Next, we established a diagnostic model for CR using Fisher discriminant model and compared different models by calculating the kappa value. Age and cervical flexor factors were used to construct clinical predictive models, which were further evaluated by C-index, receiver operating characteristic curve, calibration curve, and decision curve analysis. Multivariate analysis showed that age and cervical flexors were potential risk factors for CR, while the diagnostic model indicated that both exerted the best diagnostic effect. The obtained diagnostic equation was as follows: y1 = 0.33 × 1 + 10.302 × 2–24.139; y2 = 0.259 × 1 + 13.605 × 2–32.579. Both the C-index and AUC in the training set reached 0.939. Moreover, the C-index and AUC values in the external validation set reached 0.961. We developed 2 models for predicting CR and also confirmed their validity. Age and cervical flexors were considered potential risk factors for CR. Our noninvasive inspection method could provide clinicians with a more potential diagnostic value to detect CR accurately.

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Prevalence of sleep disturbance in patients with cervical radiculopathy and an analysis of risk factors: a cross-sectional study

Shi

Chen

et al. 2023

Eur Spine J

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Predictive effect of cervical spinal cord compression and corresponding segmental paravertebral muscle degeneration on the severity of symptoms in patients with cervical spondylotic myelopathy

Cited by 14 publications

References 24 publications

Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy

Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy

Age and flexors as risk factors for cervical radiculopathy: A new machine learning method

Prevalence of sleep disturbance in patients with cervical radiculopathy and an analysis of risk factors: a cross-sectional study

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