Comparison of Automated versus Traditional Nerve Conduction Study Methods for Median Nerve Testing in a General Worker Population
Supporting Files
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3 2015 ; 3-2015
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Available in CDC Stacks on 2016-03-01T00:00:00Z
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English
Details
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Alternative Title:PM R
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Personal Author:
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Description:Objective ; To investigate the validity of automated nerve conduction studies compared to traditional electrodiagnostic studies (EDS) for testing median nerve abnormalities in a working population. ; Design ; Agreement study and sensitivity investigation from two devices ; Setting ; Field research testing lab ; Participants ; Active workers from several industries participating in a longitudinal study of CTS. ; Methods ; Sixty-two subjects received bilateral median and ulnar nerve conduction testing across the wrist with a traditional device and the NC-stat automated device. We compared intermethod agreement of analogous measurements. ; Main outcome measurement ; Nerve conduction study parameters ; Results ; Median motor and sensory latency comparisons showed excellent agreement (intra-class correlation 0.85 and 0.80 respectively). Areas under the receiver operator characteristic curves were 0.97 and 0.96 respectively, using the optimal thresholds of 4.4ms median motor latency (sensitivity 100%, specificity 86%) and 3.9ms median sensory latency (sensitivity 100%, specificity 87%). Ulnar nerve testing results were less favorable. ; Conclusion ; The automated NC-stat device showed excellent agreement with traditional EDS for detecting median nerve conduction abnormalities in a general population of workers, suggesting that this automated nerve conduction device can be used to ascertain research case definitions of CTS in population health studies. Further study is needed to determine optimal thresholds for defining median conduction abnormalities in populations that are not seeking clinical care.
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Keywords:
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Source:PM R. 2014; 7(3):276-282
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Pubmed ID:25463687
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Pubmed Central ID:PMC4372480
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Document Type:
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Funding:
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Volume:7
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Issue:3
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Main Document Checksum:urn:sha256:7465566c38b477ed7c460eccfe3319d6a57340b611dadea0893bccaedcea5165
Supporting Files
File Language:
English
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