Clinical predictors of EMG-confirmed cervical and lumbosacral radiculopathy
BACKGROUND: Electromyography (EMG) for suspected cervical or lumbosacral root compression is often negative, producing expense and physical discomfort that could have been avoided. To improve patient selection for testing, we sought to identify clinical features that would accurately predict presence of radiculopathy on EMG.
METHODS: Adult patients consecutively evaluated for suspected cervical or lumbosacral root compression at an academic clinical neurophysiology laboratory were prospectively enrolled. Presence of clinical features suggesting root disease (neck or back pain, dermatomal pain or numbness, myotomal weakness, segmental reflex loss, and straight leg-raising) was recorded prior to testing. EMG examination to confirm root compression was conducted per standard protocols. Analysis was based on computation of sensitivity, specificity, predictive values, and accuracy.
RESULTS: A total of 200 patients (55% male; mean age 46.4 years; 38% suspected of cervical and 62% of lumbosacral disease) were included. EMG evidence of root disease was detected in 31% of cervical and 62% of lumbosacral referrals. Dermatomal pain was the most sensitive, and segmental reflex loss and myotomal weakness the most specific individual predictors of root disease. Combined presence of dermatomal pain or numbness with segmental reflex loss and myotomal weakness approached specificities of 78% (lumbosacral disease) and 99% (cervical disease). In all cases, myotomal weakness was the most accurate predictor of root disease.
CONCLUSION: The diverse symptoms and signs of cervical and lumbosacral root compression predict a positive electrodiagnosis of radiculopathy with varying degrees of accuracy, and may be used to guide patient selection for EMG testing.
Canadian Journal of Neurological Sciences
(2013). Clinical predictors of EMG-confirmed cervical and lumbosacral radiculopathy. Canadian Journal of Neurological Sciences, 40(2), 219-224.
Available at: https://ecommons.aku.edu/pakistan_fhs_mc_med_med/543