title: A diagnostic algorithm for carpal tunnel syndrome based on Bayes's theorem.
abstract: OBJECTIVE
  To construct a diagnostic algorithm based on Bayes's theorem and using simple clinical tests to allow accurate diagnosis without resort to nerve conduction studies.
  
  
  METHODS
  A cohort of patients being referred with possible carpal tunnel syndrome had clinical and electrophysiological testing, from which the simple calculations for sensitivity, specificity and prevalence were made and subsequently used in the formula of Bayes's theorem. The algorithm was then tested prospectively in a further cohort of similarly referred patients.
  
  
  RESULTS
  The algorithm proved to be reliable when tested prospectively, and was similar to nerve conduction studies in diagnostic accuracy.
  
  
  CONCLUSIONS
  A simple algorithm of clinical tests can identify patients without resort to nerve conduction studies, facilitating early treatment.
authors.affiliation: Department of Rheumatology, Norfolk, UK.
authors.forename: D
authors.initials: D
authors.lastname: O'Gradaigh
authors.forename: P
authors.initials: P
authors.lastname: Merry
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002349:Carpal Tunnel Syndrome / Q000175:diagnosis*; D006801:Humans