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Practice Parameter: Evaluation of distal symmetric polyneuropathy: Role of laboratory and genetic testing (an evidence-based review): Report of the American Academy of Neurology, American Association of Neuromuscular and Electrodiagnostic Medicine, and American Academy of Physical Medicine and Rehabilitation

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England, J. D., Gronseth, G. S., Franklin, G., Carter, G. T., Kinsella, L. J., Cohen, J. A., Asbury, A. K., Szigeti, K., Lupski, J. R., Latov, N., Lewis, R. A., Low, P. A., Fisher, M. A., Herrmann, D. N., Howard, J. F., Lauria, G., Miller, R. G., Polydefkis, M., Sumner, A. J.·2009·Neurology

Abstract

BACKGROUND: Distal symmetric polyneuropathy (DSP) is the most common variety of neuropathy. Since the evaluation of this disorder is not standardized, the available literature was reviewed to provide evidence-based guidelines regarding the role of laboratory and genetic tests for the assessment of DSP. METHODS: A literature review using MEDLINE, EMBASE, and Current Contents was performed to identify the best evidence regarding the evaluation of polyneuropathy published between 1980 and March 2007. Articles were classified according to a four-tiered level of evidence scheme and recommendations were based upon the level of evidence. RESULTS AND RECOMMENDATIONS: 1) Screening laboratory tests may be considered for all patients with polyneuropathy (Level C). Those tests that provide the highest yield of abnormality are blood glucose, serum B12 with metabolites (methylmalonic acid with or without homocysteine), and serum protein immunofixation electrophoresis (Level C). If there is no definite evidence of diabetes mellitus by routine testing of blood glucose, testing for impaired glucose tolerance may be considered in distal symmetric sensory polyneuropathy (Level C). 2) Genetic testing should be conducted for the accurate diagnosis and classification of hereditary neuropathies (Level A). Genetic testing may be considered in patients with cryptogenic polyneuropathy who exhibit a hereditary neuropathy phenotype (Level C). Initial genetic testing should be guided by the clinical phenotype, inheritance pattern, and electrodiagnostic features and should focus on the most common abnormalities which are CMT1A duplication/HNPP deletion, Cx32 (GJB1), and MFN2 mutation screening. There is insufficient evidence to determine the usefulness of routine genetic testing in patients with cryptogenic polyneuropathy who do not exhibit a hereditary neuropathy phenotype (Level U).

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Metadata

Authors
England, J. D., Gronseth, G. S., Franklin, G., Carter, G. T., Kinsella, L. J., Cohen, J. A., Asbury, A. K., Szigeti, K., Lupski, J. R., Latov, N., Lewis, R. A., Low, P. A., Fisher, M. A., Herrmann, D. N., Howard, J. F., Lauria, G., Miller, R. G., Polydefkis, M., & Sumner, A. J.
Venue
Neurology
Published
2009-01-13
Volume
72
Issue
2
Pages
185-192
ISSN
  • 0028-3878 (ISSN-L)
  • 1526-632X
OpenAlex
W2138863939
Cited by
272
References
2
FWCI
4.14
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Practice Parameter: Evaluation of distal symmetric polyneuropathy: Role of laboratory and genetic testing (an evidence-based review): Report of the American Academy of Neurology, American Association of Neuromuscular and Electrodiagnostic Medicine, and American Academy of Physical Medicine and Rehabilitation. https://app.cochat.ai/papers/10.1212/01.wnl.0000336370.51010.a1
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England, J. D., Gronseth, G. S., Franklin, G., Carter, G. T., Kinsella, L. J., Cohen, J. A., Asbury, A. K., Szigeti, K., Lupski, J. R., Latov, N., Lewis, R. A., Low, P. A., Fisher, M. A., Herrmann, D. N., Howard, J. F., Lauria, G., Miller, R. G., Polydefkis, M., & Sumner, A. J. (2009). Practice Parameter: Evaluation of distal symmetric polyneuropathy: Role of laboratory and genetic testing (an evidence-based review): Report of the American Academy of Neurology, American Association of Neuromuscular and Electrodiagnostic Medicine, and American Academy of Physical Medicine and Rehabilitation. Neurology. https://doi.org/10.1212/01.wnl.0000336370.51010.a1

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.