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Neurology Research International
Volume 2015, Article ID 183608, 6 pages
http://dx.doi.org/10.1155/2015/183608
Research Article

Recurrence Quantification Analysis of F-Waves and the Evaluation of Neuropathies

1Department of Neurology, Hines VAH, Hines, IL 60141, USA
2Department of Neurology, Loyola University Stritch School of Medicine, Maywood, IL 60153, USA
3Department of Physiology, Loyola University Stritch School of Medicine, Maywood, IL 60153, USA

Received 21 September 2015; Revised 27 October 2015; Accepted 2 November 2015

Academic Editor: Mamede de Carvalho

Copyright © 2015 Morris A. Fisher et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Electrodiagnostic (EDX) patterns of neuropathic dysfunction 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 neuropathies. RQA was used to analyze F-wave recordings from the abductor hallucis muscle in 61 patients with neuropathies. Twenty-nine of these patients had diabetes as the sole cause of their neuropathies. In the other 32 patients, the etiologies of the neuropathies were diverse. Commonly used EDX variables were also recorded. RQA data could separate the 29 patients with diabetic neuropathies from the other 32 patients (). Statistically significant differences in two EDX variables were also present: compound muscle action potential amplitudes () and F-wave persistence (). RQA analysis of F-waves seemed able to distinguish diabetic neuropathies from the other neuropathies 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 neuropathic dysfunction based on EDX data alone without prior assumptions.