Role of Neurologists and Diagnostic Tests on the Management of Distal Symmetric Polyneuropathy

Callaghan, Brian C.; Kerber, Kevin A.; Lisabeth, Lynda; Morgenstern, Lewis B.; Longoria, Ruth; Rodgers, Ann; Longwell, P. J.; Feldman, Eva L.

doi:10.1001/jamaneurol.2014.1279

Cited by 102 publications

(75 citation statements)

References 29 publications

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“…Even in patients with type 2 diabetes, glycemic control has only a small effect on the prevention of peripheral neuropathy 6. Furthermore, a significant proportion of patients with peripheral neuropathy have no known underlying cause 7, 8, 9, 10. Therefore, a better understanding of the underlying causes is needed to inform the development of new disease modifying treatments.…”

Section: Introductionmentioning

confidence: 99%

Diabetes and obesity are the main metabolic drivers of peripheral neuropathy

Callaghan

Gao

Li³

et al. 2018

Ann Clin Transl Neurol

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ObjectiveTo determine the associations between individual metabolic syndrome (MetS) components and peripheral neuropathy in a large population‐based cohort from Pinggu, China.MethodsA cross‐sectional, randomly selected, population‐based survey of participants from Pinggu, China was performed. Metabolic phenotyping and neuropathy outcomes were performed by trained personnel. Glycemic status was defined according to the American Diabetes Association criteria, and the MetS using modified consensus criteria (body mass index instead of waist circumference). The primary peripheral neuropathy outcome was the Michigan Neuropathy Screening Instrument (MNSI) examination. Secondary outcomes were the MNSI questionnaire and monofilament testing. Multivariable models were used to assess for associations between individual MetS components and peripheral neuropathy. Tree‐based methods were used to construct a classifier for peripheral neuropathy using demographics and MetS components.ResultsThe mean (SD) age of the 4002 participants was 51.6 (11.8) and 51.0% were male; 37.2% of the population had normoglycemia, 44.0% prediabetes, and 18.9% diabetes. The prevalence of peripheral neuropathy increased with worsening glycemic status (3.25% in normoglycemia, 6.29% in prediabetes, and 15.12% in diabetes, P < 0.0001). Diabetes (odds ratio [OR] 2.60, 95% CI 1.77–3.80) and weight (OR 1.09, 95% CI 1.02–1.18) were significantly associated with peripheral neuropathy. Age, diabetes, and weight were the primary splitters in the classification tree for peripheral neuropathy.InterpretationSimilar to previous studies, diabetes and obesity are the main metabolic drivers of peripheral neuropathy. The consistency of these results reinforces the urgent need for effective interventions that target these metabolic factors to prevent and/or treat peripheral neuropathy.

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Section: Introductionmentioning

confidence: 99%

Diabetes and obesity are the main metabolic drivers of peripheral neuropathy

Callaghan

Gao

Li³

et al. 2018

Ann Clin Transl Neurol

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159

110

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“…2,3 Guideline discordant neuroimaging overuse appears to be common for headache 4,5 and peripheral neuropathy. [6][7][8] At the same time, underuse of neuroimaging in some highrisk headache patients 9 and diagnostic laboratory testing 10 in neuropathy patients likely exists. 6 The Veterans Affairs (VA) health system is a single-payer health system that is largely separate from the private sector health care system.…”

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confidence: 99%

Neuroimaging overuse is more common in Medicare compared with the VA

et al. 2016

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Objective: To inform initiatives to reduce overuse, we compared neuroimaging appropriateness in a large Medicare cohort with a Department of Veterans Affairs (VA) cohort.Methods: Separate retrospective cohorts were established in Medicare and in VA for headache and neuropathy from 2004 to 2011. The Medicare cohorts included all patients enrolled in the Health and Retirement Study (HRS) with linked Medicare claims (HRS-Medicare; n 5 1,244 for headache and 998 for neuropathy). The VA cohorts included all patients receiving services in the VA (n 5 93,755 for headache and 183,642 for neuropathy). Inclusion criteria were age over 65 years and an outpatient visit for incident neuropathy or a primary headache. Neuroimaging use was measured with Current Procedural Terminology codes and potential overuse was defined using published criteria for use with administrative data. Increasingly specific appropriateness criteria excluded nontarget conditions for which neuroimaging may be appropriate.Results: For both peripheral neuropathy and headache, potentially inappropriate imaging was more common in HRS-Medicare compared with the VA. Forty-nine percentage of all headache patients received neuroimaging in HRS-Medicare compared with 22.1% in the VA (p , 0.001) and differences persist when analyzing more specific definitions of overuse. A total of 23.7% of all HRS-Medicare incident neuropathy patients received neuroimaging compared with 9.0% in the VA (p , 0.001), and the difference persisted after excluding nontarget conditions. Conclusions:Overuse of neuroimaging is likely less common in the VA than in a Medicare population.Better understanding the reasons for the more selective use of neuroimaging in the VA could help inform future initiatives to reduce overuse of diagnostic testing. Neurology ® 2016;87:792-798 GLOSSARY HRS 5 Health and Retirement Study; ICD-9 5 International Classification of Diseases-9; NCS 5 nerve conduction studies; SPEP 5 serum protein electrophoresis; VA 5 Veterans Affairs.

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“…Speculation considers the variability in the results of ST treatment as a result of heterogeneity in pain syndromes, patient selection criteria, pain diagnosis, pain locations, and range of pain intensity [23][24][25]. Hence, more strict inclusion criteria will be needed in future studies to determine which pain syndromes yield the best response to ST treatment.…”

Section: Discussionmentioning

confidence: 99%