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Original Investigation |

Tests and Expenditures in the Initial Evaluation of Peripheral Neuropathy FREE

Brian Callaghan, MD; Ryan McCammon, AB; Kevin Kerber, MD; Xiao Xu, PhD; Kenneth M. Langa, MD, PhD; Eva Feldman, MD, PhD
[+] Author Affiliations

Author Affiliations: Departments of Neurology (Drs Callaghan, Kerber, and Feldman), Internal Medicine (Mr McCammon and Dr Langa), and Obstetrics and Gynecology (Dr Xu), University of Michigan, Ann Arbor; and VA Center for Clinical Management Research, Ann Arbor (Dr Langa).


Arch Intern Med. 2012;172(2):127-132. doi:10.1001/archinternmed.2011.1032.
Text Size: A A A
Published online

Background Peripheral neuropathy is a common disorder in which an extensive evaluation is often unrevealing.

Methods We sought to define diagnostic practice patterns as an early step in identifying opportunities to improve efficiency of care. The 1996-2007 Health and Retirement Study Medicare claims–linked database was used to identify individuals with an incident diagnosis of peripheral neuropathy using International Classification of Diseases, Ninth Revision, codes and required no previous neuropathy diagnosis during the preceding 30 months. Focusing on 15 relevant tests, we examined the number and patterns of tests and specific test utilization 6 months before and after the incident neuropathy diagnosis. Medicare expenditures were assessed during the baseline, diagnostic, and follow-up periods.

Results Of the 12 673 patients, 1031 (8.1%) received a new International Classification of Diseases, Ninth Revision, diagnosis of neuropathy and met the study inclusion criteria. Of the 15 tests considered, a median of 4 (interquartile range, 2-5) tests were performed, with more than 400 patterns of testing. Magnetic resonance imaging of the brain or spine was ordered in 23.2% of patients, whereas a glucose tolerance test was rarely obtained (1.0%). Mean Medicare expenditures were significantly higher in the diagnostic period than in the baseline period ($14 362 vs $8067, P < .001).

Conclusions Patients diagnosed as having peripheral neuropathy typically undergo many tests, but testing patterns are highly variable. Almost one-quarter of patients receiving neuropathy diagnoses undergo high-cost, low-yield magnetic resonance imaging, whereas few receive low-cost, high-yield glucose tolerance tests. Expenditures increase substantially in the diagnostic period. More research is needed to define effective and efficient strategies for the diagnostic evaluation of peripheral neuropathy.

Figures in this Article

Peripheral neuropathy is a common and debilitating condition with a prevalence of 2% to 7% in the general population.1,2 The prevalence increases significantly in older adults, with a prevalence of approximately 15% in those older than 40 years.3 Distal symmetric polyneuropathy (DSP) is the most common subtype of neuropathy.4 Previous research suggests that a focused and directed evaluation is the optimal diagnostic approach in this patient population.5 The best evidence for diagnostic testing in DSP was recently summarized in a systematic review by the American Academy of Neurology (AAN).4 Fasting glucose levels, vitamin B12 levels, serum protein electrophoresis (SPEP), and 2-hour oral glucose tolerance tests (GTTs) were supported by the literature based on the yield of these tests and the potential for subsequent interventions.4 A fasting glucose level is the most frequently used test to diagnose diabetes, which is the most common cause of DSP.6 Vitamin B12 deficiency causes a potentially treatable neuropathy with different characteristics than those in idiopathic neuropathy.7 The use of GTTs and SPEP is supported by evidence810 that patients with neuropathy have a substantially increased prevalence of these abnormalities compared with control groups. Evidence to support other diagnostic tests in the evaluation of DSP is lacking.

Even after an extensive evaluation, the cause of many peripheral neuropathy cases remains unknown.11 Furthermore, even when a specific cause is identified, only a few therapies exist. The most common etiology for DSP is diabetes, which is treated with glycemic control. Immunosuppressive medications are used for certain rare subtypes of neuropathy, such as chronic inflammatory demyelinating polyradiculoneuropathy and mononeuritis multiplex. However, there are few disease-modifying therapies for patients with DSP, and pain management becomes paramount regardless of etiology. Because DSP composes most peripheral neuropathy, many of these cases are idiopathic, and few treatments are available; efficient diagnostic testing is particularly important in this population.

No previous studies, to our knowledge, have described the evaluation of peripheral neuropathy in routine clinical care. This information is important because it can provide insights into opportunities for optimizing care and setting future research priorities. In this study, we used a large, nationally representative health survey, the Health and Retirement Study (HRS), that is linked to Medicare claims data to identify a cohort with incident peripheral neuropathy and to determine evaluation practices by all physicians.

POPULATION

Data for this analysis came from respondents to 1 or more waves of the HRS biennial interview between January 1998 and December 2006, with linked Medicare Standard Analytical Files data. This database combines the rich demographic detail from the HRS with the extensive health care utilization data available in Medicare claims. We identified individuals with incident peripheral neuropathy, defined as persons who had an International Classification of Diseases, Ninth Revision (ICD-9), diagnosis of peripheral neuropathy and no previous diagnosis during the preceding 30 months (incident diagnoses range from March 1998–June 2007). All the ICD-9 codes for peripheral neuropathy were included (354.5, 356.0-9, and 357.0-9). Individuals were included if they were at least 65 years old at the start of the baseline period, were continuously enrolled in Medicare parts A and B fee-for-service from 30 months preceding the index diagnosis through 6 months after the index diagnosis, and completed an HRS interview within 3 years before the diagnosis date. We also identified a matched comparison group using a propensity score method (eMethods).

DEMOGRAPHICS AND HEALTH MEASURES

Key demographic variables that were identified from the HRS interview included age, sex, race/ethnicity, educational level, body mass index, alcohol intake, and limitations in activities of daily living. The Medicare claims database provided the diabetes status of the patient based on the Chronic Condition Data Warehouse definition (≥1 inpatient, skilled nursing, or home health claim or 2 outpatient or carrier claims with diagnostic codes 249.x, 250.x, 357.2, 362.01, 362.02, or 366.31 during the 2-year matching period).12 Moreover, ICD-9 diagnosis codes identified patients with diabetic complications other than neuropathy. Medicare claims also provided information on chronic kidney disease, rheumatoid arthritis and osteoarthritis, and cancer.

DIAGNOSTIC TESTS

Tests were identified by Current Procedural Terminology codes and included fasting glucose level, hemoglobin A1c level, GTT, SPEP, B12 level, antinuclear antibody test, erythrocyte sedimentation rate, thyrotropin level, complete blood cell count, and comprehensive metabolic panel. Electrodiagnostic tests and magnetic resonance imaging (MRI) studies (brain, cervical, thoracic, or lumbosacral spine) were also identified. These tests were selected based on their relevance to the diagnostic evaluation of DSP.

MEDICARE EXPENDITURES

Medicare payment information was obtained from the Medicare Standard Analytical Files and included all payments found in the Medicare Provider Analysis and Review, outpatient, carrier, home health, hospice, and durable medical equipment files. We evaluated expenditures during the baseline (6-18 months before diagnosis), diagnostic (6 months before and after diagnosis), and follow-up (6-18 months after diagnosis) periods.

STATISTICAL ANALYSIS

The number and patterns of testing were assessed during the diagnostic period (6 months before and after the index diagnosis). This time frame was chosen because tests are frequently ordered for this condition before the firm establishment of a diagnosis. Medicare expenditures were calculated during the baseline, diagnostic, and follow-up periods. T tests were used when comparing continuous variables. Sensitivity analyses were conducted after the exclusion of patients with a diagnosis of mononeuritis multiplex, demyelinating neuropathy, or hereditary neuropathy. All the analyses were performed using a commercially available software program (SAS, version 9.1; SAS Institute, Inc).

POPULATION

Of the 12 673 patients in the HRS-Medicare claims database, 1031 (8.1%) received a new ICD-9 diagnosis of peripheral neuropathy during the 10-year study and met the inclusion criteria. Demographic and other characteristics of the population are given in the Table. The mean age of this population was 77.6 years, and 54.0% were female. Twelve percent of the patients were non-Hispanic black and 8.0% were Hispanic; 41.5% met the Chronic Condition Data Warehouse definition of diabetes and 16.3% had other diabetic complications. Demographics and clinical variables from a matched comparison group are given in eTable 1.

Table Graphic Jump LocationTable. Demographic and Clinical Variables in 1031 Patients With Neuropathy

In patients with diabetes, the most common ICD-9 neuropathy diagnosis was polyneuropathy in diabetes (44.4%), followed by different idiopathic classifications (47.8%). In addition, 6.6% of patients with diabetes were classified as having neuropathy due to other diseases (including toxins, drugs, and inflammatory conditions), 1.4% as having hereditary neuropathies, and 0.2% as having acute inflammatory demyelinating polyradiculoneuropathy. Of patients without diabetes, 80.0% had an ICD-9 diagnosis of idiopathic neuropathy, followed by 11.7% with neuropathy due to other diseases, 4.7% with hereditary neuropathies, 3.5% with diabetes (new diagnosis of diabetes), 1.0% with mononeuritis multiplex, 1.0% with acute inflammatory demyelinating polyradiculoneuropathy, and 0.3% with chronic inflammatory demyelinating polyradiculoneuropathy.

TEST UTILIZATION

Of the 15 relevant tests assessed, the median number of tests performed per patient was 4 (interquartile range, 2-5). There were more than 400 patterns of testing in this population, with no single pattern occurring in more than 4.8% of patients. Furthermore, no particular test was common to all the top patterns.

A fasting glucose level was ordered in 23.4% of patients with neuropathy, and a hemoglobin A1c level was ordered in 43.2% (Figure 1). B12 levels were ordered in 32.6% of patients with neuropathy and SPEP was performed in 13.3%. In the nondiabetic population, a hemoglobin A1c level was ordered in only 17.1% of cases, B12 levels in 40.6%, and SPEP in 18.7% (Figure 1). Only 10 patients (1.0%) received a GTT. In contrast, 23.2% of patients received at least 1 MRI of the brain or spinal cord (Figure 2). The most common types of MRI performed were brain (13.7%), lumbar spine (9.6%), cervical spine (5.0%), and thoracic spine (1.9%). An electromyogram was performed in 19.8% of patients with neuropathy. Of those receiving an electrodiagnostic test, the mean (SD) number of nerves evaluated on nerve conduction studies was 8.79 (6.89) (median, 7.0; interquartile range, 5-10; range, 1-48). Patients with 1 to 14 nerves evaluated on nerve conduction studies were 2.8 (95% CI, 2.1-3.9) times more likely to have an MRI than were those who received no test. Those with 15 or more nerves evaluated (>1 SD greater than the mean) were 5.2 (95% CI, 2.6-10.3) times more likely to have an MRI than were those who received no test. A complete blood cell count was ordered in 73.1% of patients, thyrotropin level in 55.2%, comprehensive metabolic panel in 53.2%, erythrocyte sedimentation rate in 28.7%, and the antinuclear antibody test in 11.2% (Figure 3). Test utilization from a matched comparison group is given in eFigures 1, 2, and 3.

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Graphic Jump Location

Figure 1. Utilization of diabetic and American Academy of Neurology–recommended tests in 1031 patients with peripheral neuropathy. GTT indicates glucose tolerance test; HbA1c, hemoglobin A1c; and SPEP, serum protein electrophoresis.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Utilization of electromyography (EMG) and magnetic resonance imaging (MRI) in 1031 patients with peripheral neuropathy.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 3. Utilization of common diagnostic tests in 1031 patients with peripheral neuropathy. ANA indicates antinuclear antibody; CBC, complete blood cell count; CMP, comprehensive metabolic panel; ESR, erythrocyte sedimentation rate; PT, prothrombin time; and PTT, partial thromboplastin time.

MEDICARE EXPENDITURES

In the baseline period, before ICD-9 diagnosis of neuropathy, the mean Medicare expenditures were $8067. During the diagnostic period, the mean expenditures increased significantly to $14 362 (P < .001). This increase was also observed after excluding patients with diabetes (mean: $12 190 vs $6633, P < .001). In the follow-up period, the mean Medicare expenditures remained higher (all patients with neuropathy: $11 748; excluding patients with diabetes: $9794) than in the baseline period but were lower than during the diagnostic period. Expenditures from a matched comparison group are given in eTable 2.

Using a nationally representative sample of older US adults, we found that more than 8.1% of the individuals had a new diagnosis of neuropathy and met the inclusion criteria during this 10-year study. Many tests were ordered during the diagnostic period for peripheral neuropathy, but the evaluation was highly variable. Magnetic resonance images of the brain and spine were frequently ordered, whereas the GTT was rarely ordered. Significant increases in cost occurred during the diagnostic period compared with the baseline period. These findings suggest substantial opportunity to improve efficiency in the evaluation of peripheral neuropathy.

The large variation in testing indicates little consensus on an appropriate testing strategy in this population. With more than 400 total patterns of tests and no pattern accounting for more than 4.8% of the total number, no standard approach to the evaluation of peripheral neuropathy currently exists. Similarly, the number of nerves tested on nerve conduction studies exhibited substantial variation but the mean was close to the recommended number of nerves for patients entering a clinical trial as suggested by a 2009 AAN practice parameter. Substantial utilization of diagnostic tests was observed, exhibited by a median of 4 tests ordered of the 15 tests evaluated. Patients with more nerves evaluated on nerve conduction studies also had a higher chance of undergoing an MRI, another expensive test. More research is needed to determine the optimal approach to this prevalent condition and to disseminate this information to the physicians who care for these patients.

When examining test utilization, 2 significant deviations from expected clinical practice and the tests supported by the best available evidence were discovered. The first was that a large proportion of these patients received MRIs of the brain or spine. In fact, each segment of the neuroaxis (brain, cervical, thoracic, and lumbar spine) underwent MRI at a higher-than-expected frequency. When combining all MRI tests together, utilization was even more dramatic, with nearly 1 in 4 undergoing at least 1 MRI. For a condition that affects the peripheral nervous system, this degree of utilization is substantial and suggests that many physicians have significant uncertainty when localizing neuropathy symptoms to the peripheral nervous system. The use of MRI may also result from the large proportion of patients with idiopathic neuropathy, from the fact that results of electrodiagnostic studies can be nondiagnostic or normal, or from patient preferences. Another possibility is that patients with neuropathy are at higher risk for other conditions or symptoms that warrant MRI.

The second deviation from expected practice is that GTTs are rarely ordered. In fact, only 1.0% of this neuropathy population received GTTs. The prevalence of impaired glucose tolerance in otherwise idiopathic patients with neuropathy is higher compared with that of historical controls, and the type of neuropathy in these patients is different (more sensory and painful neuropathies).9,10 Therefore, emerging data support impaired glucose tolerance as potentially one of the most common etiologies of neuropathy, although controversy still exists.1315 This condition is also one of the few potentially treatable causes of neuropathy, with diet and exercise preventing a large percentage of patients from going on to develop diabetes and its inherent risk of neuropathy progression.16 One potential reason for the extremely low utilization of this test is the fact that many physicians use hemoglobin A1c levels to identify individuals with prediabetes.16 However, the cutoff point used to define prediabetes with this test has low sensitivity, and many patients in the Diabetes Prevention Program would not have been included using this criterion.17 These results indicate that 2 of the first steps in increasing the effectiveness and efficiency of the evaluation of peripheral neuropathy may be investigating why so many MRIs are ordered and determining the barriers to utilization of the GTT.

The other 3 tests supported by the AAN systematic review (fasting glucose level, B12 level, and SPEP) were ordered less frequently than expected. In fact, only 49.8% of patients with neuropathy received 1 or more of these 3 tests, and only 17.3% received 2 or more. Although some patients with peripheral neuropathy may not need these tests if they have a well-established cause, these numbers are still significantly lower than if the 25% to 40% of patients that end up with an idiopathic diagnosis were evaluated.11 B12 levels are ordered much more frequently than is SPEP, emphasizing the fact that many physicians do not recognize the evidence in support of ordering this test. Although these data were collected from a period before release of the AAN review, they highlight that physicians were not ordering the tests with the highest levels of evidence to support their use. Understanding the obstacles to the utilization of these tests will be paramount to improving the efficiency of diagnostic testing in this population.

Medicare expenditures in this population rose substantially during the diagnostic period. The expenditures decreased during 12 months of follow-up but did not return to baseline. This pattern is not surprising given the findings that patients with a new diagnosis of neuropathy undergo an extensive evaluation. These expenditures, however, may also reflect other broad expenditures related to their disabling condition, including orthotic devices, walking assist devices, office visits, and hospitalizations, to name a few. These other expenditures likely explain the persistent increase in expenditures in this population, but the transient increase in the diagnostic period is at least partially explained by costs associated with diagnostic tests. Therefore, understanding the relative impact of these tests is important in allowing physicians to practice efficient care, especially in a patient population in whom the etiology frequently remains unclear and there are few disease-modifying therapies. Future studies examining which diagnostic tests are driving the costs and whether they are effective and useful in this population are essential.

This study has important limitations. The ICD-9 diagnosis codes were used to identify patients with peripheral neuropathy, which may lead to misclassification bias. Peripheral neuropathy is a heterogeneous condition, and certain rare subtypes of neuropathy may require a different evaluation than those with DSP. However, few patients in this study had an ICD-9 diagnosis indicating a rarer subtype of neuropathy, and a sensitivity analysis excluding patients with a diagnosis of mononeuritis multiplex, demyelinating neuropathy, or hereditary neuropathy did not significantly change the results. Many patients were included who have a known cause of neuropathy, and these patients may not require any workup for the cause of their neuropathy. On the other hand, 80.0% of the patients without diabetes were coded as idiopathic neuropathy, and the patterns observed in this group were similar to those in the entire cohort. Another limitation is that there are likely patients with neuropathy who did not receive an ICD-9 diagnosis, and this population may be biased toward those with more severe neuropathy. Yet, the high incidence of neuropathy in the present cohort gives support to the likelihood that we are capturing a large proportion of the population with neuropathy. An additional limitation is that we did not investigate detailed information on why patients are receiving specific tests. For example, some of the patients who underwent MRI may have had another indication for this test, such as spinal arthritis. It is also possible that patients with a neuropathy diagnosis were more likely to see a specialist in neurology, which subsequently led to an increase in neurology-specific tests. However, the magnitude of MRI utilization makes these factors unlikely to account for all these tests. We also do not know whether the increase in Medicare expenditures is specifically related to the evaluation of neuropathy. We investigated total expenditures, which includes other nondiagnostic test–related expenditures. On the other hand, the expenditures increased substantially around the time of diagnosis and then decreased toward but not entirely back to that of the baseline period in the subsequent year. We also studied a Medicare population composed largely of patients older than 67 years. How these results apply to a younger population or one with private or no insurance is unclear.

In conclusion, in routine practice from 1998 to 2007, the evaluation of peripheral neuropathy involved substantial use of diagnostic tests, with wide variation in testing patterns. Magnetic resonance imaging, a costly and low-yield test, is frequently performed during the diagnostic period for neuropathy. On the other hand, the GTT, the optimal test for identifying one of the most common and treatable causes of DSP (impaired glucose tolerance and diabetes), is rarely performed. The evaluation and management of peripheral neuropathy is associated with substantial increases in health expenditures. These findings indicate an important opportunity to improve the effectiveness and efficiency of the diagnostic evaluation of this prevalent disease.

Correspondence: Brian Callaghan, MD, Department of Neurology, University of Michigan, 109 Zina Pitcher Pl, Mail Stop 4021 BSRB, Ann Arbor, MI 48104 (bcallagh@med.umich.edu).

Accepted for Publication: October 8, 2011.

Author Contributions:Study concept and design: Callaghan, Kerber, Xu, Langa, and Feldman. Analysis and interpretation of data: Callaghan, McCammon, Kerber, Langa, and Feldman. Drafting of the manuscript: Callaghan. Critical revision of the manuscript for important intellectual content: McCammon, Kerber, Xu, Langa, and Feldman. Statistical analysis: Callaghan, McCammon, and Kerber. Obtained funding: Langa and Feldman. Study supervision: Callaghan, Langa, and Feldman.

Financial Disclosure: Dr Kerber has received speaker honoraria from the AAN 2010 and 2011 annual meetings and has performed consulting work for the AAN.

Funding/Support: Drs Callaghan and Feldman were supported by a National Institutes of Health T32 grant, the Katherine Rayner Program, and the Taubman Medical Institute. The HRS was supported by grant U01 AG09740 from the National Institute on Aging and was performed at the Institute for Social Research, University of Michigan. Dr Langa was supported by grant R01 AG030155 from the National Institute on Aging. Dr Kerber was supported by grant K23 RR024009 from the National Center for Research Resources, National Institutes of Health, and grant R18 HS017690 from the Agency for Healthcare Research and Quality.

Previous Presentation: This study was presented at the 63rd American Academy of Neurology Annual Meeting; April 12, 2011; Honolulu, Hawaii.

Additional Contributions: James Burke, MD, reviewed and edited the manuscript.

Bharucha NE, Bharucha AE, Bharucha EP. Prevalence of peripheral neuropathy in the Parsi community of Bombay.  Neurology. 1991;41(8):1315-1317
PubMed   |  Link to Article
Savettieri G, Rocca WA, Salemi G,  et al; Sicilian Neuro-Epidemiologic Study (SNES) Group.  Prevalence of diabetic neuropathy with somatic symptoms: a door-to-door survey in two Sicilian municipalities.  Neurology. 1993;43(6):1115-1120
PubMed   |  Link to Article
Gregg EW, Sorlie P, Paulose-Ram R,  et al.  Prevalence of lower-extremity disease in the US adult population ≥40 years of age with and without diabetes: 1999-2000 National Health and Nutrition Examination Survey.  Diabetes Care. 2004;27(7):1591-1597
PubMed   |  Link to Article
England JD, Gronseth GS, Franklin G,  et al; American Academy of Neurology.  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. 2009;72(2):185-192
PubMed   |  Link to Article
Smith AG, Singleton JR. The diagnostic yield of a standardized approach to idiopathic sensory-predominant neuropathy.  Arch Intern Med. 2004;164(9):1021-1025
PubMed   |  Link to Article
Palumbo PJ, Elveback LR, Whisnant JP. Neurologic complications of diabetes mellitus: transient ischemic attack, stroke, and peripheral neuropathy.  Adv Neurol. 1978;19:593-601
PubMed
Saperstein DS, Wolfe GI, Gronseth GS,  et al.  Challenges in the identification of cobalamin-deficiency polyneuropathy.  Arch Neurol. 2003;60(9):1296-1301
PubMed   |  Link to Article
Kelly JJ Jr, Kyle RA, O’Brien PC, Dyck PJ. Prevalence of monoclonal protein in peripheral neuropathy.  Neurology. 1981;31(11):1480-1483
PubMed   |  Link to Article
Novella SP, Inzucchi SE, Goldstein JM. The frequency of undiagnosed diabetes and impaired glucose tolerance in patients with idiopathic sensory neuropathy.  Muscle Nerve. 2001;24(9):1229-1231
PubMed   |  Link to Article
Singleton JR, Smith AG, Bromberg MB. Increased prevalence of impaired glucose tolerance in patients with painful sensory neuropathy.  Diabetes Care. 2001;24(8):1448-1453
PubMed   |  Link to Article
McLeod JG, Tuck RR, Pollard JD, Cameron J, Walsh JC. Chronic polyneuropathy of undetermined cause.  J Neurol Neurosurg Psychiatry. 1984;47(5):530-535
PubMed   |  Link to Article
Rector TS, Wickstrom SL, Shah M,  et al.  Specificity and sensitivity of claims-based algorithms for identifying members of Medicare + Choice health plans that have chronic medical conditions.   Health Serv Res. 2004;39(6, pt 1):1839-1857
PubMed   |  Link to Article
Dyck PJ, Dyck PJ, Klein CJ, Weigand SD. Does impaired glucose metabolism cause polyneuropathy? review of previous studies and design of a prospective controlled population-based study.  Muscle Nerve. 2007;36(4):536-541
PubMed   |  Link to Article
Hughes RA, Umapathi T, Gray IA,  et al.  A controlled investigation of the cause of chronic idiopathic axonal polyneuropathy.  Brain. 2004;127(pt 8):1723-1730
PubMed   |  Link to Article
Kissel JT. Peripheral neuropathy with impaired glucose tolerance: a sweet smell of success?  Arch Neurol. 2006;63(8):1055-1056
PubMed   |  Link to Article
Knowler WC, Barrett-Connor E, Fowler SE,  et al; Diabetes Prevention Program Research Group.  Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.  N Engl J Med. 2002;346(6):393-403
PubMed   |  Link to Article
Santos-Rey K, Fernández-Riejos P, Mateo J, Sánchez-Margalet V, Goberna R. Glycated hemoglobin vs. the oral glucose tolerance test for the exclusion of impaired glucose tolerance in high-risk individuals.  Clin Chem Lab Med. 2010;48(12):1719-1722
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. Utilization of diabetic and American Academy of Neurology–recommended tests in 1031 patients with peripheral neuropathy. GTT indicates glucose tolerance test; HbA1c, hemoglobin A1c; and SPEP, serum protein electrophoresis.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Utilization of electromyography (EMG) and magnetic resonance imaging (MRI) in 1031 patients with peripheral neuropathy.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 3. Utilization of common diagnostic tests in 1031 patients with peripheral neuropathy. ANA indicates antinuclear antibody; CBC, complete blood cell count; CMP, comprehensive metabolic panel; ESR, erythrocyte sedimentation rate; PT, prothrombin time; and PTT, partial thromboplastin time.

Tables

Table Graphic Jump LocationTable. Demographic and Clinical Variables in 1031 Patients With Neuropathy

References

Bharucha NE, Bharucha AE, Bharucha EP. Prevalence of peripheral neuropathy in the Parsi community of Bombay.  Neurology. 1991;41(8):1315-1317
PubMed   |  Link to Article
Savettieri G, Rocca WA, Salemi G,  et al; Sicilian Neuro-Epidemiologic Study (SNES) Group.  Prevalence of diabetic neuropathy with somatic symptoms: a door-to-door survey in two Sicilian municipalities.  Neurology. 1993;43(6):1115-1120
PubMed   |  Link to Article
Gregg EW, Sorlie P, Paulose-Ram R,  et al.  Prevalence of lower-extremity disease in the US adult population ≥40 years of age with and without diabetes: 1999-2000 National Health and Nutrition Examination Survey.  Diabetes Care. 2004;27(7):1591-1597
PubMed   |  Link to Article
England JD, Gronseth GS, Franklin G,  et al; American Academy of Neurology.  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. 2009;72(2):185-192
PubMed   |  Link to Article
Smith AG, Singleton JR. The diagnostic yield of a standardized approach to idiopathic sensory-predominant neuropathy.  Arch Intern Med. 2004;164(9):1021-1025
PubMed   |  Link to Article
Palumbo PJ, Elveback LR, Whisnant JP. Neurologic complications of diabetes mellitus: transient ischemic attack, stroke, and peripheral neuropathy.  Adv Neurol. 1978;19:593-601
PubMed
Saperstein DS, Wolfe GI, Gronseth GS,  et al.  Challenges in the identification of cobalamin-deficiency polyneuropathy.  Arch Neurol. 2003;60(9):1296-1301
PubMed   |  Link to Article
Kelly JJ Jr, Kyle RA, O’Brien PC, Dyck PJ. Prevalence of monoclonal protein in peripheral neuropathy.  Neurology. 1981;31(11):1480-1483
PubMed   |  Link to Article
Novella SP, Inzucchi SE, Goldstein JM. The frequency of undiagnosed diabetes and impaired glucose tolerance in patients with idiopathic sensory neuropathy.  Muscle Nerve. 2001;24(9):1229-1231
PubMed   |  Link to Article
Singleton JR, Smith AG, Bromberg MB. Increased prevalence of impaired glucose tolerance in patients with painful sensory neuropathy.  Diabetes Care. 2001;24(8):1448-1453
PubMed   |  Link to Article
McLeod JG, Tuck RR, Pollard JD, Cameron J, Walsh JC. Chronic polyneuropathy of undetermined cause.  J Neurol Neurosurg Psychiatry. 1984;47(5):530-535
PubMed   |  Link to Article
Rector TS, Wickstrom SL, Shah M,  et al.  Specificity and sensitivity of claims-based algorithms for identifying members of Medicare + Choice health plans that have chronic medical conditions.   Health Serv Res. 2004;39(6, pt 1):1839-1857
PubMed   |  Link to Article
Dyck PJ, Dyck PJ, Klein CJ, Weigand SD. Does impaired glucose metabolism cause polyneuropathy? review of previous studies and design of a prospective controlled population-based study.  Muscle Nerve. 2007;36(4):536-541
PubMed   |  Link to Article
Hughes RA, Umapathi T, Gray IA,  et al.  A controlled investigation of the cause of chronic idiopathic axonal polyneuropathy.  Brain. 2004;127(pt 8):1723-1730
PubMed   |  Link to Article
Kissel JT. Peripheral neuropathy with impaired glucose tolerance: a sweet smell of success?  Arch Neurol. 2006;63(8):1055-1056
PubMed   |  Link to Article
Knowler WC, Barrett-Connor E, Fowler SE,  et al; Diabetes Prevention Program Research Group.  Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.  N Engl J Med. 2002;346(6):393-403
PubMed   |  Link to Article
Santos-Rey K, Fernández-Riejos P, Mateo J, Sánchez-Margalet V, Goberna R. Glycated hemoglobin vs. the oral glucose tolerance test for the exclusion of impaired glucose tolerance in high-risk individuals.  Clin Chem Lab Med. 2010;48(12):1719-1722
PubMed   |  Link to Article

Correspondence

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The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
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For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
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