Karthik R Krishnan1,2, Darryl B Sneag1,2,3, Joseph H Feinberg1, Steve K Lee1,2, Scott W Wolfe1,2. 1. Center for Brachial Plexus and Traumatic Nerve Injury, Hospital for Special Surgery, New York, NY, USA. 2. Weill Cornell Medicine, New York, NY, USA. 3. Department of Radiology and Imaging, Hospital for Special Surgery, New York, NY, USA.
Abstract
Background: Assessing the extent and specific location of brachial plexus injuries can be difficult given the variety of mechanisms of injury and anatomic complexity of the plexus. We developed a program to accurately assess the location of a patient's neurologic injury based on electromyographic data. Purpose: We sought to test our hypothesis that the location of traumatic brachial plexopathies could be accurately assessed with a novel program that processed electromyogram (EMG) and mechanism of injury data. Methods: This retrospective diagnostic cohort study was carried out with a novel diagnostic algorithm developed with the Python programming language. The program accepts user input of muscles demonstrating decreased motor unit recruitment, positive sharp waves, or fibrillation potentials. The testing data set was derived from a registry of brachial plexus injuries treated at our center. The primary outcome was the percent concordance of the algorithm's diagnosis with the surgical diagnosis. Results: Ninety-five cases met the inclusion criteria. Median time from injury onset to EMG examination was 4 months; median time from EMG examination to surgery was 1.2 months. The program diagnosis matched the surgical diagnosis in 92 out of 95 (97%) of cases, including cases with multilevel injuries and additional peripheral nerve injuries. Conclusion: This program accurately localized brachial plexopathies in nearly all cases, including those involving polytrauma or complex patterns of injury. This algorithm may be valuable as an aid to complete electrodiagnostic examinations, a diagnostic adjunct when planning treatment of severe plexus palsies, or an educational tool.
Background: Assessing the extent and specific location of brachial plexus injuries can be difficult given the variety of mechanisms of injury and anatomic complexity of the plexus. We developed a program to accurately assess the location of a patient's neurologic injury based on electromyographic data. Purpose: We sought to test our hypothesis that the location of traumatic brachial plexopathies could be accurately assessed with a novel program that processed electromyogram (EMG) and mechanism of injury data. Methods: This retrospective diagnostic cohort study was carried out with a novel diagnostic algorithm developed with the Python programming language. The program accepts user input of muscles demonstrating decreased motor unit recruitment, positive sharp waves, or fibrillation potentials. The testing data set was derived from a registry of brachial plexus injuries treated at our center. The primary outcome was the percent concordance of the algorithm's diagnosis with the surgical diagnosis. Results: Ninety-five cases met the inclusion criteria. Median time from injury onset to EMG examination was 4 months; median time from EMG examination to surgery was 1.2 months. The program diagnosis matched the surgical diagnosis in 92 out of 95 (97%) of cases, including cases with multilevel injuries and additional peripheral nerve injuries. Conclusion: This program accurately localized brachial plexopathies in nearly all cases, including those involving polytrauma or complex patterns of injury. This algorithm may be valuable as an aid to complete electrodiagnostic examinations, a diagnostic adjunct when planning treatment of severe plexus palsies, or an educational tool.
Authors: Vasileios I Sakellariou; Nikolaos K Badilas; George A Mazis; Nikolaos A Stavropoulos; Helias K Kotoulas; Stamatios Kyriakopoulos; Ioannis Tagkalegkas; Ioannis P Sofianos Journal: ISRN Orthop Date: 2014-02-09