Factor analysis. A methodology for data reduction in nerve conduction studies.
Analyzing multiple nerve conduction study parameters individually is statistically problematic. The goal of this study was to develop a useful factor analysis scheme for assessment of nerve conduction study abnormalities in diabetic neuropathy. Hypotheses were: (1) factor analysis produces a few physiologically meaningful factors, (2) there are associations between factors and markers of diabetic severity and (3) clinical impressions are related to factor scores. We studied 165 Japanese-American men: 52 nondiabetic, 66 diabetic and 47 with impaired glucose tolerance. One author (W.C.S.) obtained 28 nerve conduction study parameters in all subjects and factor analysis extracted five factors from these parameters. These factors were related to conduction velocities (factor 1), distal ulnar function (factor 2), sensory amplitudes (factor 3), distal median function (factor 4) and distal peroneal function (factor 5); together, they explain 57% of the variability in the total data. Diabetic factor scores were significantly (P less than 0.05) below that of the controls and correlations with fasting blood sugar were significant at the P less than or equal to 0.001 level. Use of this technique promises to permit sensible analysis of large amounts of data in clinical studies of diabetic and other types of polyneuropathy.
Robinson
L R
LR
Department of Rehabilitation Medicine, University of Washington, Seattle 98195.
Rubner
D E
DE
Wahl
P W
PW
Fujimoto
W Y
WY
Stolov
W C
WC
D000367:Age Factors; D000368:Aged; D001213:Asian; D001827:Body Height; D001831:Body Temperature; D003627:Data Interpretation, Statistical; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology; D003929:Diabetic Neuropathies / Q000503:physiopathology*; D005163:Factor Analysis, Statistical; D006801:Humans; D007564:Japan / Q000208:ethnology; D008297:Male; D008875:Middle Aged; D009431:Neural Conduction