Premium
Issue & Opinions: Receiver operating characterist curve anic analysis in the prediction of carpal tunnel syndrome: A model for reporting Electrophysiological data
Author(s) -
Eisen Andrew,
Schulzer Michael,
Pant Bhanu,
MaCneil Maureen,
Stewart Heather,
Trueman Sandra,
Mak Edwin
Publication year - 1993
Publication title -
muscle and nerve
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.025
H-Index - 145
eISSN - 1097-4598
pISSN - 0148-639X
DOI - 10.1002/mus.880160715
Subject(s) - carpal tunnel syndrome , receiver operating characteristic , medicine , linear discriminant analysis , latency (audio) , electrophysiology , area under the curve , electrodiagnosis , audiology , physical medicine and rehabilitation , surgery , cardiology , statistics , mathematics , telecommunications , computer science
Receiver operating characteristic (ROC) curves were used to predict the risk of carpal tunnel syndrome (CTS). Patients were classified clinically as (1) normal exam and no symptoms (169 hands); (2) having a motor and/or sensory deficit typical of CTS (115 hands); (3) having a history characteristic of CTS (156 hands); and (4) nondiagnostic symptomatology (122 hands). Electrophysiological studies consisted of median and ulnar motor, sensory, and palmar measurements. Group mean values for group 1 differed significantly from groups 2 and 3 (not 4) for all measurements, but values overlapped considerably. Median distal motor latency (DMML) combined with median‐ulnar palmar latency differences (MUPLD) had significantly superior discriminant power than other measurements and correlated highly for all groups ( r values = 0.71–0.73). These variables were used to construct ROC curves and prediction tables. The approach used allows one to assign a percentage risk of having a CTS and can be used in outcome studies.