Degenerative Cervical Myelopathy (DCM) is the most common cause of spinal cord injury in the elderly population in the developed world, and it significantly impacts on quality of life of patients and their caregivers. Surgical treatment remains the treatment option able to halt the disease progression and provide neurological recovery in most of the patients. While it remains challenging to predict exactly who will improve after surgery, increasingly it has been shown that clinical, imaging and electrophysiological factors can predict, with relatively good capacity, those who are more likely to benefit. Clinically, baseline neurological impairment appears to be strongly related with outcome, and MRI, with T1-hypointensity and the length of T2-hyperintensity, appears to be most prognostic. In this context, electrophysiology (both motor and sensory evoked potentials, MEPs and SEPs) have shown some predictive capacity, but large studies are lacking. While multivariate models have been conducted using clinical and MRI data, there remains no multimodal prediction models which encompass the predictive capacity from clinical, imaging and electrophysiological data. In the present review, the rationale for clinical, imaging and electrophysiological utilization in clinical practice are examined, and a model of multimodal assessment for the management of DCM is discussed.
|Number of pages||7|
|Publication status||Published - 2020|
All Science Journal Classification (ASJC) codes
- Clinical Neurology