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The Utility of a Prediction Model Using Neurological Examination Findings for Diagnosing Degenerative Cervical
Masahiro Funaba1, Hiroaki Nakashima2, Lindsay Tetreault3
1Department of Orthopedic Surgery, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan.
Background:
The diagnostic accuracy of neurological examination findings for identifying degenerative cervical myelopathy (DCM) is not apparent, given the paucity of studies with appropriate control groups. In order to address this knowledge gap, we conducted a community cervical spine screening project and examined subjects without DCM or evidence of myelopathy on cervical magnetic resonance imaging (MRI).
Methods:
This study included a total of 229 patients diagnosed with DCM, based on MRI evidence of spinal cord compression and improvement after surgery, and 807 controls without DCM (40 to 79 years of age) enrolled in the screening project. Neurological examination was performed on each subject, including the assessment of deep tendon reflexes at the biceps, triceps, patella, and Achilles tendon and the Hoffmann reflex, Babinski sign, sensory disturbance, and 10-second grip-and-release test. Multiple logistic regression analysis was performed to build a diagnostic model for DCM based on the neurological examination findings.
Results:
Using a stepwise multiple logistic regression analysis method, an almost perfect diagnostic model was designed that comprised sex, age, 10-second grip-and-release test, patellar tendon reflex, Hoffmann reflex, Babinski sign, and sensory disturbance (area under the curve [AUC] in the receiver operating characteristic curve analysis, 0.994). However, given that the last 2 parameters are less commonly evaluated in routine practice, an alternative reduced model was developed for practical use and consisted of sex, age, Hoffmann reflex, patellar tendon reflex, and 10-second grip-and-release test. The reduced model yielded a nearly equivalent AUC of 0.956.
Conclusions:
Both diagnostic prediction models demonstrated excellent accuracy in distinguishing patients with DCM from subjects without DCM, highlighting the importance of combining specific neurological signs and performance measures when evaluating patients with suspected DCM.
Level Of Evidence:
Prognostic Level II . See Instructions for Authors for a complete description of levels of evidence.
