Gregor Omejec1, Simon Podnar2. 1. Institute of Clinical Neurophysiology, Division of Neurology, University Medical Center Ljubljana, Slovenia. Electronic address: gregor.omejec@kclj.si. 2. Institute of Clinical Neurophysiology, Division of Neurology, University Medical Center Ljubljana, Slovenia. Electronic address: simon.podnar@kclj.si.
Abstract
OBJECTIVE: To determine what causes ulnar neuropathy at the elbow (UNE) by analyzing patients' clinical, electrodiagnostic (EDx) and ultrasonographic (US) findings. METHODS: In prospectively recruited patients with definite UNE, four blinded examiners took a history and performed neurologic, EDx and US examinations. A multivariate logistic regression model was used to investigate the association between UNE location and patient variables. RESULTS: We included 117 patients; 73% with lesions in the retroepicondylar (RTC) groove and 27% under the humeroulnar aponeurotic arcade (HUA). In our multivariate model, hard manual labor (OR=152; 95% CI 12-1847; p<0.001), dominant arm involvement (OR=4.12; 95% CI 1.01-16.72; p=0.048), and age (OR=1.10; 95% CI 1.03-1.18; p=0.004) were predictive of ulnar neuropathy at HUA. CONCLUSION: Our data suggest that UNE at HUA is related to years of hard labor affecting mainly dominant hands, and is caused by work-related changes in the HUA. By contrast, UNE in the RTC groove affects mainly the non-dominant arms of younger administrative workers and is caused by external compression of the ulnar nerve. SIGNIFICANCE: We believe that our findings will help to improve the diagnosis and treatment of UNE patients, hopefully leading to improved clinical outcomes.
OBJECTIVE: To determine what causes ulnar neuropathy at the elbow (UNE) by analyzing patients' clinical, electrodiagnostic (EDx) and ultrasonographic (US) findings. METHODS: In prospectively recruited patients with definite UNE, four blinded examiners took a history and performed neurologic, EDx and US examinations. A multivariate logistic regression model was used to investigate the association between UNE location and patient variables. RESULTS: We included 117 patients; 73% with lesions in the retroepicondylar (RTC) groove and 27% under the humeroulnar aponeurotic arcade (HUA). In our multivariate model, hard manual labor (OR=152; 95% CI 12-1847; p<0.001), dominant arm involvement (OR=4.12; 95% CI 1.01-16.72; p=0.048), and age (OR=1.10; 95% CI 1.03-1.18; p=0.004) were predictive of ulnar neuropathy at HUA. CONCLUSION: Our data suggest that UNE at HUA is related to years of hard labor affecting mainly dominant hands, and is caused by work-related changes in the HUA. By contrast, UNE in the RTC groove affects mainly the non-dominant arms of younger administrative workers and is caused by external compression of the ulnar nerve. SIGNIFICANCE: We believe that our findings will help to improve the diagnosis and treatment of UNE patients, hopefully leading to improved clinical outcomes.
Authors: Tobias Rossmann; Ulrike M Heber; Stefan Heber; Lukas F Reissig; Wolfgang Grisold; Wolfgang J Weninger; Stefan Meng Journal: Muscle Nerve Date: 2021-09-10 Impact factor: 3.852