title: Electrodiagnosis of ulnar neuropathy at the elbow (Une): a Bayesian approach.
abstract: BACKGROUND
  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.
authors.affiliation: Department of Neurology, Box 673, 601 Elmwood Avenue, University of Rochester Medical Center, Rochester, New York, 14642, USA.
authors.forename: Eric L
authors.initials: EL
authors.lastname: Logigian
authors.forename: Raissa
authors.initials: R
authors.lastname: Villanueva
authors.forename: Paul T
authors.initials: PT
authors.lastname: Twydell
authors.forename: Bennett
authors.initials: B
authors.lastname: Myers
authors.forename: Marlene
authors.initials: M
authors.lastname: Downs
authors.forename: David C
authors.initials: DC
authors.lastname: Preston
authors.forename: Milind J
authors.initials: MJ
authors.lastname: Kothari
authors.forename: David N
authors.initials: DN
authors.lastname: Herrmann
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000328:Adult; D000368:Aged; D001499:Bayes Theorem; D004550:Elbow / Q000294:innervation*; D004568:Electrodiagnosis / Q000379:methods*; D004576:Electromyography; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000503:physiopathology; D009431:Neural Conduction / Q000502:physiology; D012372:ROC Curve; D014459:Ulnar Nerve / Q000473:pathology*; D020424:Ulnar Neuropathies / Q000175:diagnosis*; D055815:Young Adult
keywords: Bayes theorem; ROC curve; electrodiagnosis; nerve conduction; ulnar neuropathy