Recurrence Quantification Analysis of F-Waves and the Evaluation of XXXX .

@entity1 @entity6 @entity16 @entity3949 @entity51
Electrodiagnostic (EDX) patterns of @entity51 have been based on axonal/demyelinating criteria requiring prior assumptions. This has not produced classifications of desired sensitivity or specificity. Furthermore, standard nerve conduction studies have limited reproducibility. New methodologies in EDX seem important. Recurrent Quantification Analysis (RQA) is a nonlinear method for examining patterns of recurrence. RQA might provide a unique method for the EDX evaluation of @entity16 . RQA was used to analyze F-wave recordings from the abductor hallucis muscle in 61 @entity1 with @entity16 . Twenty-nine of these @entity1 had @entity6 as the sole cause of their @entity16 . In the other 32 @entity1 , the etiologies of the @entity16 were diverse. Commonly used EDX variables were also recorded. RQA data could separate the 29 @entity1 with @entity3949 from the other 32 @entity1 (P < 0.009). Statistically significant differences in two EDX variables were also present: compound muscle action potential amplitudes (P < 0.007) and F-wave persistence (P < 0.001). RQA analysis of F-waves seemed able to distinguish @entity3949 from the other @entity16 studied, and this separation was associated with specific physiological abnormalities. This study would therefore support the idea that RQA of F-waves can distinguish between types of @entity51 based on EDX data alone without prior assumptions.
