Electrodiagnosis of ulnar neuropathy at the elbow (Une): A bayesian approach

Eric L. Logigian, Raissa Villanueva, Paul T. Twydell, Bennett Myers, Marlene Downs, David C. Preston, Milind J. Kothari, David N. Herrmann

Research output: Contribution to journalArticle

11 Scopus citations


Introduction: In ulnar neuropathy at the elbow (UNE), we determined how electrodiagnostic cutoffs [across-elbow ulnar motor conduction velocity slowing (AECV-slowing), drop in across-elbow vs. forearm CV (AECV-drop)] depend on pretest probability (PreTP). Methods: Fifty clinically defined UNE patients and 50 controls underwent ulnar conduction testing recording abductor digiti minimi (ADM) and first dorsal interosseous (FDI), stimulating wrist, below-elbow, and 6-, 8-, and 10-cm more proximally. For various PreTPs of UNE, the cutoffs required to confirm UNE (defined as posttest probability=95%) were determined with receiver operator characteristic (ROC) curves and Bayes Theorem. Results: On ROC and Bayesian analyses, the ADM 10-cm montage was optimal. For PreTP=0.25, the confirmatory cutoffs were >23 m/s (AECV-drop), and <38 m/s (AECV-slowing); for PreTP=0.75, they were much less conservative: >14 m/s, and <47 m/s, respectively. Conclusions: (1) In UNE, electrodiagnostic cutoffs are critically dependent on PreTP; rigid cutoffs are problematic. (2) AE distances should be standardized and at least 10 cm.

Original languageEnglish (US)
Pages (from-to)337-344
Number of pages8
JournalMuscle and Nerve
Issue number3
Publication statusPublished - Jan 1 2014


All Science Journal Classification (ASJC) codes

  • Physiology
  • Clinical Neurology
  • Cellular and Molecular Neuroscience
  • Physiology (medical)

Cite this

Logigian, E. L., Villanueva, R., Twydell, P. T., Myers, B., Downs, M., Preston, D. C., ... Herrmann, D. N. (2014). Electrodiagnosis of ulnar neuropathy at the elbow (Une): A bayesian approach. Muscle and Nerve, 49(3), 337-344. https://doi.org/10.1002/mus.23913