Clinical biomarkers differentiate myelitis from vascular and other causes of myelopathy

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Abstract

Objective

To assess the predictive value of the initial clinical and paraclinical features in the differentiation of inflammatory myelopathies from other causes of myelopathy in patients with initial diagnosis of transverse myelitis (TM).

Methods

We analyzed the clinical presentation, spinal cord MRI, and CSF features in a cohort of 457 patients referred to a specialized myelopathy center with the presumptive diagnosis of TM. After evaluation, the myelopathies were classified as inflammatory, ischemic/stroke, arteriovenous malformations/fistulas, spondylotic, or other. A multivariable logistic regression model was used to determine characteristics associated with the final diagnosis and predictors that would improve classification accuracy.

Results

Out of 457 patients referred as TM, only 247 (54%) were confirmed as inflammatory; the remaining 46% were diagnosed as vascular (20%), spondylotic (8%), or other myelopathy (18%). Our predictive model identified the temporal profile of symptom presentation (hyperacute <6 hours, acute 6–48 hours, subacute 48 hours–21 days, chronic >21 days), initial motor examination, and MRI lesion distribution as characteristics that improve the correct classification rate of myelopathies from 67% to 87% (multinomial area under the curve increased from 0.32 to 0.67), compared to only considering CSF pleocytosis and MRI gadolinium enhancement. Of all predictors, the temporal profile of symptoms contributed the most to the increased discriminatory power.

Conclusions

The temporal profile of symptoms serves as a clinical biomarker in the differential diagnosis of TM. The establishment of a definite diagnosis in TM requires a critical analysis of the MRI and CSF characteristics to rule out non-inflammatory causes of myelopathy.

Classification of evidence

This study provides Class IV evidence that for patients presenting with myelopathy, temporal profile of symptoms, initial motor examination, and MRI lesion distribution distinguish those with inflammatory myelopathies from those with other causes of myelopathy.

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