Risk factors for rapid progressive neurological deterioration in patients with cervical spondylotic myelopathy

Zhong, Weiyang; Wang, Lin; Huang, Tianji; Luο, Xingguang

doi:10.1186/s13018-021-02227-6

Cited by 13 publications

(10 citation statements)

References 19 publications

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“…Our investigation revealed that ISI of the spinal cord on T2WI and high degree disc degeneration in the cranial adjacent levels emerged as idependent risk factors affecting the recovery of patients' neurological functions. Remarkably, 90% of patients in the "poor" group exhibited ISI of the spinal cord on T2WI in our study.The ISI of the spinal cord on T2WI mirrors the underlying pathology of spinal cord injury, encompassing edema, gliosis, demyelination, and spinal cord chondromalacia [30] .At the same time, an ISI of the spinal cord on T2WI in might indicate secondary spinal cord edema due to acute spinal cord ischemia, posing as a idependent risk factors for rapid progressive neurological deterioration in patients a icted with cervical spondylosis [16] .Uchida et al [31] elucidated that ISI of the spinal cord on preoperative T2WI signi es a manifestation of severe, potentially irreversible chronic spinal cord injury.…”

Section: Discussionmentioning

confidence: 99%

Risk factors for poor neurological recovery after anterior cervical discectomy and fusion: imaging characteristics

lu,

zhang,

chai

et al. 2024

Preprint

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Background:Poor neurological recovery in patients after anterior cervical discectomy and fusion has been frequently reported; however, there are no studies that analyze the preoperative imaging characteristics of patients to investigate the factors affecting surgical prognosis. The purpose of this study was to investigate the factors influencing patients' preoperative imaging characteristics on poor neurologic recovery after anterior cervical discectomy and fusion. Methods We retrospectively analyzed the clinical data of 89 patients who met the criteria for anterior cervical discectomy and fusion for the treatment of single-level cervical spondylotic myelopathy and evaluated the patients' neurological recovery based on the recovery rate of the Japanese Orthopaedic Association (JOA) scores at the time of the final follow-up visit;patients were categorized into "good" and "poor" groups based on JOA recovery rates of ≥ 50% and < 50%, respectively. Clinical information (age, gender, body mass index, duration of symptoms, JOA score preoperative and at the final follow-up), and imaging characteristics (cervical kyphosis, cervical instability, ossification of the posterior longitudinal ligament(OPLL), calcification of herniated intervertebral discs, increased signal intensity(ISI) of the spinal cord on T2WI, and degree of degeneration of the discs adjacent to the fused levels (cranial and caudal) were collected from the patients.) Univariate and binary logistic regression analyses were used to identify risk factors for poor neurologic recovery. Results The mean age of the patients was 52.56 ± 11.18 years, and the mean follow-up was 26.89±11.14 months. 20 patients (22.5%) had poor neurological recovery. Univariate analysis showed that significant predictors of poor neurological recovery were age (p = 0.019), concomitant OPLL (p = 0.019), concomitant calcification of herniated intervertebral discs (p = 0.019), ISI of the spinal cord on T2WI (p ＜0.05), a high grade of degeneration of the discs of the cranial neighboring levels (p ＜0.05), and a high grade of discs of the caudal neighboring levels (p ＜0.05). Binary logistic regression analysis showed that ISI of the spinal cord on T2WI (p = 0.001 OR = 24.947), and high degree of degeneration of adjacent discs on the cranial side (p = 0.040 OR = 6.260) were independent risk factors for poor neurological prognosis. Conclusion ISI of the spinal cord on T2WI and high degree of cranial adjacent disc degeneration are independent risk factors for poor neurological recovery after anterior cervical discectomy and fusion, and comprehensive analysis of the patients' preoperative imaging characteristics can help in the development of surgical protocols and the management of patients' surgical expectations.

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Section: Discussionmentioning

confidence: 99%

Risk factors for poor neurological recovery after anterior cervical discectomy and fusion: imaging characteristics

lu,

zhang,

chai

et al. 2024

Preprint

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“…Early diagnosis and treatment are still important to preserve as much function as possible since our findings, as well as findings from previous studies have shown that duration of symptoms has some effect as a predictor of surgical outcome. 7,23 Longer duration of symptoms does not, however, always mean that the disease is severe, since some patients live with mild symptoms for years without progression, while others progress quickly to a very severe degree of the disease, 24,25 Furthermore, a long duration of mild symptoms may not have been prioritized for surgical treatment, thus leading to a longer duration of symptoms before treatment. Type of surgery was not a predictor of outcome in accordance with recent studies.…”

Section: Discussionmentioning

confidence: 99%

Patient Reported Data as Predictors of Surgical Outcome in Patients with Degenerative Cervical Myelopathy. Analysis of a National Multicenter Dataset

Gerdhem

Charalampidis

2022

Spine

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Study Design. Retrospective study design on prospectively collected registry data. Objective. To investigate whether improvement after surgery for degenerative cervical myelopathy is associated with preoperative disease severity and to identify predictors of outcome. Summary of Background Data. Degenerative cervical myelopathy is the most common cause of spinal cord compromise in adults and surgery is often the treatment of choice. Identifying predictors may help to improve patient selection. Materials and Methods. This nationwide study from the Swedish spine registry included 901 patients treated surgically for degenerative cervical myelopathy. To investigate improvement in different disease severity groups, the individuals were divided into quartiles based on their preoperative European Myelopathy Scale (EMS) and EuroQol-5 Dimension (EQ-5D) index. Statistical analyses were made with analysis of variance, χ2, McNemar, and t tests. Multivariable linear or logistic regression was used to identify predictors for one-year improvement in EMS and EQ-5D index, and satisfaction at one year. In the regressions, the patient-reported outcome measures were dichotomized at their median, except improvement in EMS. Results. All patient-reported outcome measures improved from baseline to the one-year follow-up (P<0.001). Statistically significant outcome improvements were seen in all disease severity groups. Preoperative low EMS (β=−1.37, P<0.001), long walking distance (<500 vs. >500 m; β=0.44, P=0.030), and low NDI (β=−0.43, P=0.048) were independent predictors of improvement in EMS. R 2 was 0.11 for the multivariable model. Preoperative low EQ-5D index (odds ratio=0.11; 95% confidence interval: 0.07–0.16) and low NDI (0.56; 0.36–0.88) were independent predictors of improvement in EQ-5D index. Preoperative high EMS (1.86; 1.20–2.90) and shorter arm pain duration [<12 vs. >12 months (0.54; 0.33–0.88)] were independent predictors of satisfaction. Conclusions. Postoperative improvement was seen over the whole range of disease severity. Disease severity, symptom duration, and walking distance were predictors of outcome in patients treated surgically for degenerative cervical myelopathy. Level of Evidence. III.

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“…Therefore, it is necessary to conduct physical examinations for patients with suspected CSM. However, the symptoms of CSM are almost always insidious ( 3 ), which makes the diagnosis of CSM very challenging ( 4 ). Currently, imaging is still an important approach for evaluating suspected CSM.…”

Section: Introductionmentioning

confidence: 99%

Voxel- and tensor-based morphometry with machine learning techniques identifying characteristic brain impairment in patients with cervical spondylotic myelopathy

Wang,

Zhao,

Zhu

et al. 2024

Front. Neurol.

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AimThe diagnosis of cervical spondylotic myelopathy (CSM) relies on several methods, including x-rays, computed tomography, and magnetic resonance imaging (MRI). Although MRI is the most useful diagnostic tool, strategies to improve the precise and independent diagnosis of CSM using novel MRI imaging techniques are urgently needed. This study aimed to explore potential brain biomarkers to improve the precise diagnosis of CSM through the combination of voxel-based morphometry (VBM) and tensor-based morphometry (TBM) with machine learning techniques.MethodsIn this retrospective study, 57 patients with CSM and 57 healthy controls (HCs) were enrolled. The structural changes in the gray matter volume and white matter volume were determined by VBM. Gray and white matter deformations were measured by TBM. The support vector machine (SVM) was used for the classification of CSM patients from HCs based on the structural features of VBM and TBM.ResultsCSM patients exhibited characteristic structural abnormalities in the sensorimotor, visual, cognitive, and subcortical regions, as well as in the anterior corona radiata and the corpus callosum [P < 0.05, false discovery rate (FDR) corrected]. A multivariate pattern classification analysis revealed that VBM and TBM could successfully identify CSM patients and HCs [classification accuracy: 81.58%, area under the curve (AUC): 0.85; P < 0.005, Bonferroni corrected] through characteristic gray matter and white matter impairments.ConclusionCSM may cause widespread and remote impairments in brain structures. This study provided a valuable reference for developing novel diagnostic strategies to identify CSM.

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Risk factors for rapid progressive neurological deterioration in patients with cervical spondylotic myelopathy

Cited by 13 publications

References 19 publications

Risk factors for poor neurological recovery after anterior cervical discectomy and fusion: imaging characteristics

Risk factors for poor neurological recovery after anterior cervical discectomy and fusion: imaging characteristics

Patient Reported Data as Predictors of Surgical Outcome in Patients with Degenerative Cervical Myelopathy. Analysis of a National Multicenter Dataset

Voxel- and tensor-based morphometry with machine learning techniques identifying characteristic brain impairment in patients with cervical spondylotic myelopathy

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