Document Detail


Clinical Predictors of EMG-confirmed Cervical and Lumbosacral Radiculopathy.
MedLine Citation:
PMID:  23419571     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
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.
Authors:
Ali Hassan; Bilal Hameed; Muhammad Islam; Bhojo Khealani; Mustafa Khan; Saad Shafqat
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The Canadian journal of neurological sciences. Le journal canadien des sciences neurologiques     Volume:  40     ISSN:  0317-1671     ISO Abbreviation:  Can J Neurol Sci     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-02-19     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0415227     Medline TA:  Can J Neurol Sci     Country:  Canada    
Other Details:
Languages:  eng     Pagination:  219-24     Citation Subset:  IM    
Affiliation:
Section of Neurology, Department of Medicine, Aga Khan University Medical College, Karachi, Pakistan.
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