Targeting earlier diagnosis: What symptoms come first in Degenerative Cervical Myelopathy?

Neuromotor decline is associated with gut dysbiosis following surgical decompression for Degenerative Cervical Myelopathy

Degenerative cervical myelopathy (DCM) describes a spectrum of disorders that cause progressive and chronic cervical spinal cord compression. The clinical presentation can be complex and can include locomotor impairment, hand and upper extremity dysfunction, pain, loss of bladder and bowel function, as well as gastrointestinal dysfunction. Once diagnosed, surgical decompression is the recommended treatment for DCM patients with moderate to severe impairment. Our body is composed of a large community of microorganisms, known as the microbiota. Traumatic and non-traumatic spinal cord injuries (SCIs) can induce changes in the gut microbiota and gut microbiota derived metabolites. These changes have been reported as important disease-modifying factors after injury. However, whether gut dysbiosis is associated with functional neurological recovery after surgical decompression has not been examined to date. Here, DCM was induced in C57BL/6 mice by implanting an aromatic polyether material underneath the C5-6 laminae. The extent of gut dysbiosis was assessed by gas chromatography and 16S rRNA sequencing from fecal samples before and after decompression. Neuromotor activity was assessed using the Catwalk test. Our results show that DCM pre- and post- surgical decompression is associated with gut dysbiosis, without altering short chain fatty acids (SCFAs) levels. Significant differences in Clostridia, Verrumicrobiae, Lachnospiracea, Firmicutes, Bacteroidales, and Clostridiaceae were observed between the DCM group (before decompression) and after surgical decompression (2 and 5 weeks). The changes in gut microbiota composition correlated with locomotor features of the Catwalk. For example, a longer duration of ground contact and dysfunctional swing in the forelimbs, were positively correlated with gut dysbiosis. These results show for the first time an association between gut dysbiosis and locomotor deterioration after delayed surgical decompression. Thus, providing a better understanding of the extent of changes in microbiota composition in the setting of DCM pre- and post- surgical decompression.

Flipping the mJOA: Clinical utility of the modified Japanese Orthopaedic Association score as a tool for detecting degenerative cervical myelopathy

Introduction

People with Degenerative Cervical Myelopathy (DCM) often experience diagnostic delay. This could lead to poorer outcomes, including disability.

Research question

Does the modified Japanese Orthopaedic Association scale (mJOA) have clinical utility as an early detection tool for possible DCM?

Materials and methods

This is a prospective study of consecutive adult patients, referred to a National Neurosurgical Centre with a neck problem. Assessing clinicians undertook standard clinical examination and calculated the mJOA score. A consultant radiologist independently reported radiological findings, after which the assessing clinician determined the diagnosis. The sensitivity and specificity of mJOA for DCM at various cut-points was statistically analysed using Receiver Operating Characteristics (ROC) curves.

Results

Of 201 patients (98 male, mean age 52.6 ± 13y) assessed over 13 months, 21 were diagnosed with DCM (prevalence 10.4%). Fifteen (71.4%) had a mJOA score classifying disease severity as mild, 4/21 (19%) had moderate disease and two (9.5%) had severe disease. A mJOA score ≤17 (cutpoint ≥1) showed sensitivity of 95% and specificity of 71% for the clinical diagnosis of DCM. mJOA score ≤16 (cutpoint ≥2) had sensitivity of 62% and specificity of 90%. The ROC area under the curve was 0.885 (95% confidence interval: 0.82 to 0.95). 87% of patients were correctly classified.

Discussion and conclusion

mJOA score ≤16 is 90% specific for a subsequent diagnosis of DCM in people with neck problems and has potential to be used as an early detection tool. Further research is needed to replicate these findings and establish feasibility and acceptability in primary care.

Cost-effectiveness of surgery for degenerative cervical myelopathy in the United Kingdom

PURPOSE

Degenerative cervical myelopathy (DCM) is the commonest cause of adult spinal cord dysfunction worldwide, for which surgery is the mainstay of treatment. At present, there is limited literature on the costs associated with the surgical management of DCM, and none from the United Kingdom (UK). This study aimed to evaluate the cost-effectiveness of DCM surgery within the National Health Service, UK.

MATERIALS AND METHODS

Incidence of DCM was identified from the Hospital Episode Statistics (HES) database for a single year using five ICD-10 diagnostic codes to represent DCM. Health Resource Group (HRG) data was used to estimate the mean incremental surgery (treatment) costs compared to non-surgical care, and the incremental effect (quality adjusted life year (QALY) gain) was based on data from a previous study. A cost per QALY value of <£30,000/QALY (GBP) was considered acceptable and cost-effective, as per the National Institute for Health and Clinical Excellence (NICE) guidance. A sensitivity analysis was undertaken (±5%, ±10% and ±20%) to account for variance in both the cost of admission and QALY gain.

RESULTS

The total number of admissions for DCM in 2018 was 4,218. Mean age was 62 years, with 54% of admissions being of working age (18-65 years). The overall estimated cost of admissions for DCM was £38,871,534 for the year. The mean incremental (per patient) cost of surgical management of DCM was estimated to be £9,216 (ranged £2,358 to £9,304), with a QALY gain of 0.64, giving an estimated cost per QALY value of £14,399/QALY. Varying the QALY gain by ±20%, resulted in cost/QALY figures between £12,000 (+20%) and £17,999 (-20%).

CONCLUSIONS

Surgery is estimated to be a cost-effective treatment of DCM amongst the UK population.

Respiratory dysfunction in degenerative cervical myelopathy: A systematic review

INTRODUCTION

Degenerative cervical myelopathy is a condition of symptomatic cervical spinal cord compression secondary to a range of degenerative spinal pathology. Respiratory symptoms such as shortness of breath are not uncommonly reported by people with DCM and respiratory dysfunction has been described in several DCM studies. The objective of this review was therefore to systematically synthesise the current evidence on the relationship between DCM and respiratory function.

METHODS

The review was registered on PROSPERO and adhered to PRISMA guidelines. Ovid MEDLINE and Embase were searched from inception to 14th March 2023. DCM studies reporting on any measure or outcome relating to respiratory function or disease were eligible. Reference lists of included studies and relevant reviews articles were hand searched. Title, abstract and full text screening, risk of bias and GRADE assessments were completed in duplicate. A quantitative synthesis is presented.

RESULTS

Of 1991 studies identified by literature searching, 13 met inclusion criteria: 3 cohort studies, 5 case-control studies, 1 case series and 4 case studies. Forced vital capacity (FVC), peak expiratory flow rate (PEFR) and maximal voluntary ventilation (MVV) were reported to be lower in DCM patients than controls; there was inconsistency in comparisons of forced expiratory volume in 1 s (FEV1). There was conflicting evidence on whether surgical decompression was associated with improvements in respiratory parameters and on the relationship between level of spinal cord compression and respiratory dysfunction.

CONCLUSION

DCM may be associated with respiratory dysfunction. However, consistency and quality of evidence is currently low. Further work should characterise respiratory dysfunction in DCM patients more rigorously and investigate putative mechanisms such as disruption to cervical nerve roots responsible for diaphragmatic innervation and damage to descending spinal projections from brainstem respiratory centres.

Machine Learning and Symptom Patterns in Degenerative Cervical Myelopathy: Web-Based Survey Study

BACKGROUND

Degenerative cervical myelopathy (DCM), a progressive spinal cord injury caused by spinal cord compression from degenerative pathology, often presents with neck pain, sensorimotor dysfunction in the upper or lower limbs, gait disturbance, and bladder or bowel dysfunction. Its symptomatology is very heterogeneous, making early detection as well as the measurement or understanding of the underlying factors and their consequences challenging. Increasingly, evidence suggests that DCM may consist of subgroups of the disease, which are yet to be defined.

OBJECTIVE

This study aimed to explore whether machine learning can identify clinically meaningful groups of patients based solely on clinical features.

METHODS

A survey was conducted wherein participants were asked to specify the clinical features they had experienced, their principal presenting complaint, and time to diagnosis as well as demographic information, including disease severity, age, and sex. K-means clustering was used to divide respondents into clusters according to their clinical features using the Euclidean distance measure and the Hartigan-Wong algorithm. The clinical significance of groups was subsequently explored by comparing their time to presentation, time with disease severity, and other demographics.

RESULTS

After a review of both ancillary and cluster data, it was determined by consensus that the optimal number of DCM response groups was 3. In Cluster 1, there were 40 respondents, and the ratio of male to female participants was 13:21. In Cluster 2, there were 92 respondents, with a male to female participant ratio of 27:65. Cluster 3 had 57 respondents, with a male to female participant ratio of 9:48. A total of 6 people did not report biological sex in Cluster 1. The mean age in this Cluster was 56.2 (SD 10.5) years; in Cluster 2, it was 54.7 (SD 9.63) years; and in Cluster 3, it was 51.8 (SD 8.4) years. Patients across clusters significantly differed in the total number of clinical features reported, with more clinical features in Cluster 3 and the least clinical features in Cluster 1 (Kruskal-Wallis rank sum test: χ22=159.46; P<.001). There was no relationship between the pattern of clinical features and severity. There were also no differences between clusters regarding time since diagnosis and time with DCM.

CONCLUSIONS

Using machine learning and patient-reported experience, 3 groups of patients with DCM were defined, which were different in the number of clinical features but not in the severity of DCM or time with DCM. Although a clearer biological basis for the clusters may have been missed, the findings are consistent with the emerging observation that DCM is a heterogeneous disease, difficult to diagnose or stratify. There is a place for machine learning methods to efficiently assist with pattern recognition. However, the challenge lies in creating quality data sets necessary to derive benefit from such approaches.