DECODING Study (Dermal Electrochemical Conductance in Diabetic Neuropathy)

Diabetes Mellitus, Type 2 Clinical Trial

— DECODING  

Official title:

Feasibility and Effectiveness of Electrochemical Dermal Conductance Measurement for the Screening of Diabetic Neuropathy in Primary Care.

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03495089
• Other study ID #: P14/147
• Status: Completed
• Phase: N/A
• Start date: May 2015
• Est. completion date: September 2018

Study information

• Verified date: April 2018
• Source: Jordi Gol i Gurina Foundation
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Diabetes mellitus is the leading cause of polyneuropathy in the Western world. Diabetic neuropathy is a frequent complication of diabetes and may have great clinical transcendence due to pain and possible ulceration of the lower extremities. It is also a relevant cause of morbidity and mortality in patients with diabetes. Although the cause of polyneuropathy in patients with diabetes is only partially known, it has been associated with chronic hyperglycaemia suggesting the possible aetiopathogenic implication of advanced glycosylation end-products. The strategy of choice in the medical management of diabetic neuropathy is early detection since glycaemic control and the use of certain drugs may prevent or slow the development of this disease. Diabetic neuropathy most often presents with a dysfunction of unmyelinated C-fibers, manifested as an alteration of the sweat reflex of the eccrine glands. This dysfunction can now be demonstrated using a newly developed technology which measures dermal electrochemical conductivity. This noninvasive test is easy and cost-effective. The aim of the present study is to evaluate the feasibility and effectiveness of dermal electrochemical conductance measurement (quantitative expression of the sudomotor reflex) as a screening test for the diagnosis of diabetic neuropathy in patients in primary care.

Description:

The prevalence of diabetes mellitus (DM) is very high in Spain, being nearly 14% according to oral glucose tolerance test (OGTT) results . The management of DM requires a significant consumption of healthcare resources, mainly in relation to the care of vascular complications. Among the late microvascular events which may develop in patients with DM, polyneuropathy (PN) is the most common and disabling, and is the leading cause of morbidity and mortality in these patients. Indeed, in Spain, the leading cause of neuropathy is DM, with its prevalence increasing with the presence of DM and other risk factors such as obesity.

PN is defined as the presence of symptoms and/or signs of peripheral nerve dysfunction in people with DM after the exclusion of other possible causes. The Toronto Panel Consensus on PN defined this disorder as "symmetrical, depending on large fibers, sensory-motor attributable to metabolic and micro vessel disorders, as a result of chronic hyperglycemia and other risk factors". In patients with PN, thin fibers (autonomic system - sweating) and thermal and tactile sensitivity are first affected, followed by the involvement of large fibers, presenting an altered vibrating sensation which eventually alters electromyography (EMG) patterns. Therefore, dysfunction of sweat reflex in small distal fibers is one of the earliest changes to be detected in these patients.

The most common clinical presentation of PN is distal symmetric polyneuropathy (DSPN), being predominantly sensory in 80% of cases. Pain is the most important symptom, being described as burning or flashing, lancinating, deep, and with frequent exacerbations during rest (4). Pain often affects the quality of life of these patients, and it is a frequent cause of depression and/or anxiety. Moreover, some patients may develop hypoesthesia, which may lead to severe foot lesions.

The prevalence of DSPN varies greatly according to the population, definition and detection method. The Rochester study, including more than 64,000 patients, reported the prevalence of PN to be between 66% and 59% for type1 DM and type 2 DM, respectively. The 3rd report of the Technical Study Group of Diabetes of the World Health Organization (WHO) described a prevalence of 40% (8), and 50% in patients with more than 25 years of DM evolution. Pirart et al. reported a prevalence ranging from 25 to 48% (7,10-17), while in Spain, Cabezas-Cerrato et al. published a figure of 24.1%. DSPN-related factors are: age, DM duration, metabolic control, male gender, acute myocardial infarction, hyperlipidemia (especially hypertriglyceridemia), smoking, and general cardiovascular risk factors . Puig et al. also included urinary albumin excretion as a risk factor of presenting DSPN.

The diagnosis of DSPN is commonly made based on signs and symptoms and usually includes the use of several questionnaires such as the Neuropathy Disability Score (NDS), the Neuropathy Symptoms Score (NSS) and the Michigan Neuropathy Instrument (MNI). These questionnaires are easy to perform and are reproducible, sensitive and adequate for use in a screening program. Additionally, It was included a short scale (UENS - Utah Early Neuropathy Scale) to screen early neuropathy . This sensitive, fast and practical test, has 5 items and their score ranges from 0 to 42 points.

There are many confirmatory tests, including measurements of nerve conduction velocity (EMG) and bio-thesiometry or skin biopsy. However, those most commonly used are the measurement of altered sensations using a vibrating tuning fork with 128 Hz and/or pressure with Semmes-Weinstein 5:07 monofilament. Monofilament testing (MFT) is widely accepted and recommended by all scientific societies because of its validity, predictive risk, efficiency and simplicity. Feng et al. reported that MFT has a sensitivity of 57-93%, a specificity of 75-100%, a positive predictive value of 36-94% and a negative predictive value of 84-100% compared to the measurement of nerve velocity by EMG. Although electrophysiological measures are more objective and reproducible, they are limited in that they only detect dysfunction based on the presence of thicker and faster (myelinated) fibers and show their involvement later. Consequently, EMG is a specific, albeit very insensitive, test.

Recently developed noninvasive techniques are more reproducible and reliable for the detection of early dysfunction of small fibers. One of these new techniques involves the measurement of dermal electrochemical conductance (DEC) or sudomotor dysfunction index and has been evaluated by well-designed studies (Calvet, Dupin, Winiecki, Black, 2013; Casellini 2013; Devigili 2008; Peltier 2009) which support its use as a screening test .

Ramachandran et al studied the use of DEC to detect diabetes and other disorders of glucose metabolism. In a study on the use of DEC Casellini et al (5) applied a PN test which showed a low sensitivity of 78% and a specificity of 92% in diabetic patients without neuropathy compared to other subjects with neuropathy and a control group. In this latter study, correlation with clinical parameters showed adequate reproducibility of the results, particularly in regard to the measurements of the feet . Several other studies also obtained significantly lower DEC values on comparing diabetic patients and controls. In a study of patients following a 12-month program of intense physical activity, Raisanen et al (23) observed a greater improvement in DEC compared to weight, waist circumference or maximum oxygen volume (VO2 max).

Therefore, taking into account the large number of methods used and the learning curve required to correctly implement these techniques as well as the absence of consensus as to which method is the most adequate to diagnose DSPN, the aim of this study is to validate the usefulness of DEC measurement in the early diagnosis of DSPN compared with traditional techniques in the Primary Care setting.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 147
• Est. completion date: September 2018
• Est. primary completion date: March 2018
• Accepts healthy volunteers: No
• Gender: All
• Age group: 40 Years and older

Eligibility

Inclusion Criteria:

• patients with type 2 DM

• patients with pre-diabetes

• patients without glucose alterations

Three main diagnostic categories (normal, pre-diabetes and diabetes) were defined using the WHO criteria based on 2-h postload glucose [<7.8 (140 mg/dL), 7.8-11.0 mmol/L (140-200 mg/dL) and / or fasting plasma glucose (6.1-6.9 mmol/L; 110-126 mg/dL) and >11.1 mmol/L (>200 mg/dL), respectively.

Exclusion Criteria:

• Type 1 DM

• upper or lower limb amputation (except phalanges),

• diagnosis of neuropathy not related to diabetes

• neuropathy by entrapment

• use of psychoactive substances

• chronic alcoholism

• malnutrition

• treatment with beta-blockers

• presence of terminal disease or life expectancy less than 3 years

Pregnancy will be ruled out in women (negative pregnancy test) and a possible history of gestational diabetes will also be taken into account.

Related Conditions & MeSH terms

• Diabetes Mellitus
• Diabetes Mellitus, Type 2
• Diabetic Neuropathies
• Neuropathy, Diabetic

Intervention

Diagnostic Test:
• dermal electrochemical conductance (DEC)
The patient will undergo DEC quantification using the Sudoscan® device.(Sudoscan®, Impeto Medical, France)
• Monofilament testing
Monofilament testing by Semmes-Weinstein 5:07 MFT (10 g),

Locations

Country	Name	City	State
Spain	Hospital Universitari Sant Joan de Reus	Reus	Tarragona
Spain	Hospital Universitari Mútua Terrassa	Terrassa	Barcelona
Spain	Mútua Terrassa Primary Care	Terrassa	Barcelona

Sponsors (3)

Lead Sponsor	Collaborator
Jordi Gol i Gurina Foundation	Hospital Mutua de Terrassa, Hospital Universitari Sant Joan de Reus

Country where clinical trial is conducted

Spain, 

References & Publications (24)

Cabezas-Cerrato J. The prevalence of clinical diabetic polyneuropathy in Spain: a study in primary care and hospital clinic groups. Neuropathy Spanish Study Group of the Spanish Diabetes Society (SDS). Diabetologia. 1998 Nov;41(11):1263-9. — View Citation

Calle Pascual AL, Runkle Vega I, Díaz Pérez JA, Durán Hervada A, Romero Pérez L. Técnicas de exploración. Av Diabetol. 2006;22(1):42-9. [article in Spanish].

Casellini CM, Parson HK, Richardson MS, Nevoret ML, Vinik AI. Sudoscan, a noninvasive tool for detecting diabetic small fiber neuropathy and autonomic dysfunction. Diabetes Technol Ther. 2013 Nov;15(11):948-53. doi: 10.1089/dia.2013.0129. Epub 2013 Jul 27. — View Citation

Dyck PJ, Kratz KM, Karnes JL, Litchy WJ, Klein R, Pach JM, Wilson DM, O'Brien PC, Melton LJ 3rd, Service FJ. The prevalence by staged severity of various types of diabetic neuropathy, retinopathy, and nephropathy in a population-based cohort: the Rochester Diabetic Neuropathy Study. Neurology. 1993 Apr;43(4):817-24. Erratum in: Neurology 1993 Nov;43(11):2345. — View Citation

Feng Y, Schlösser FJ, Sumpio BE. The Semmes Weinstein monofilament examination as a screening tool for diabetic peripheral neuropathy. J Vasc Surg. 2009 Sep;50(3):675-82, 682.e1. doi: 10.1016/j.jvs.2009.05.017. Epub 2009 Jul 30. Review. — View Citation

Gómez MA GM. Estudio de la conduccion nerviosa en pacientes con diabetes mellitus tipo 2. Rev Peru Endocrinol Metab. 1998;IV:23-33. [article in Spanish].

Gore M, Brandenburg NA, Dukes E, Hoffman DL, Tai KS, Stacey B. Pain severity in diabetic peripheral neuropathy is associated with patient functioning, symptom levels of anxiety and depression, and sleep. J Pain Symptom Manage. 2005 Oct;30(4):374-85. — View Citation

Kanji JN, Anglin RE, Hunt DL, Panju A. Does this patient with diabetes have large-fiber peripheral neuropathy? JAMA. 2010 Apr 21;303(15):1526-32. doi: 10.1001/jama.2010.428. Review. — View Citation

Lu B, Hu J, Wen J, Zhang Z, Zhou L, Li Y, Hu R. Determination of peripheral neuropathy prevalence and associated factors in Chinese subjects with diabetes and pre-diabetes - ShangHai Diabetic neuRopathy Epidemiology and Molecular Genetics Study (SH-DREAMS). PLoS One. 2013 Apr 16;8(4):e61053. doi: 10.1371/journal.pone.0061053. Print 2013. — View Citation

Mayaudon H, Miloche PO, Bauduceau B. A new simple method for assessing sudomotor function: relevance in type 2 diabetes. Diabetes Metab. 2010 Dec;36(6 Pt 1):450-4. doi: 10.1016/j.diabet.2010.05.004. Epub 2010 Aug 23. — View Citation

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Puig ML, Aguirre DR, Rodríguez MC, Alonso ED. Neuropatía periférica de los miembros inferiores en diabéticos tipo 2 de diagnóstico reciente. Av Endocrinol 2006;22(2):149. [article in Spanish].

Raisanen A, Eklund J, Calvet JH, Tuomilehto J. Sudomotor function as a tool for cardiorespiratory fitness level evaluation: comparison with maximal exercise capacity. Int J Environ Res Public Health. 2014 May 30;11(6):5839-48. doi: 10.3390/ijerph110605839. — View Citation

Ramachandran A, Moses A, Shetty S, Thirupurasundari CJ, Seeli AC, Snehalatha C, Singvi S, Deslypere JP. A new non-invasive technology to screen for dysglycaemia including diabetes. Diabetes Res Clin Pract. 2010 Jun;88(3):302-6. doi: 10.1016/j.diabres.2010.01.023. Epub 2010 Feb 25. — View Citation

Said G. Diabetic neuropathy--a review. Nat Clin Pract Neurol. 2007 Jun;3(6):331-40. Review. — View Citation

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Singleton JR, Bixby B, Russell JW, Feldman EL, Peltier A, Goldstein J, Howard J, Smith AG. The Utah Early Neuropathy Scale: a sensitive clinical scale for early sensory predominant neuropathy. J Peripher Nerv Syst. 2008 Sep;13(3):218-27. doi: 10.1111/j.1529-8027.2008.00180.x. — View Citation

Smith AG, Lessard M, Reyna S, Doudova M, Singleton JR. The diagnostic utility of Sudoscan for distal symmetric peripheral neuropathy. J Diabetes Complications. 2014 Jul-Aug;28(4):511-6. doi: 10.1016/j.jdiacomp.2014.02.013. Epub 2014 Mar 6. — View Citation

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Tesfaye S, Stevens LK, Stephenson JM, Fuller JH, Plater M, Ionescu-Tirgoviste C, Nuber A, Pozza G, Ward JD. Prevalence of diabetic peripheral neuropathy and its relation to glycaemic control and potential risk factors: the EURODIAB IDDM Complications Study. Diabetologia. 1996 Nov;39(11):1377-84. — View Citation

Veresiu AI, Bondor CI, Florea B, Vinik EJ, Vinik AI, Gâvan NA. Detection of undisclosed neuropathy and assessment of its impact on quality of life: a survey in 25,000 Romanian patients with diabetes. J Diabetes Complications. 2015 Jul;29(5):644-9. doi: 10.1016/j.jdiacomp.2015.04.001. Epub 2015 Apr 9. — View Citation

Vidal MA, Martínez-Fernández E, Martínez-Vázquez de Castro J, Torres LM. Neuropatía diabética. Eficacia de la amitriptilina y de la gabapentina. Rev Soc Esp Dolor. 2004;11:490-504 [article in Spanish].

Ziegler D, Papanas N, Rathmann W, Heier M, Scheer M, Meisinger C; KORA Study Group. Evaluation of the Neuropad sudomotor function test as a screening tool for polyneuropathy in the elderly population with diabetes and pre-diabetes: the KORA F4 survey. Diabetes Metab Res Rev. 2012 Nov;28(8):692-7. doi: 10.1002/dmrr.2340. — View Citation

* Note: There are 24 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Presence of diabetic neuropathy diagnosed by EMG	Presence of diabetic neuropathy diagnosed by electromyography	Day 1
Secondary	Neuropathy Disability Score	Presence of diabetic neuropathy diagnosed by Neuropathy Disability Score (NDS). - A NDS score greater than or equal to 6 points will be considered as the presence of diabetic neuropathy.	Day 1
Secondary	Utah Early Neuropathy Scale	Presence of diabetic neuropathy diagnosed by Utah Early Neuropathy Scale (UENS). A UENS score greater than or equal to 10 points will be considered as the presence of diabetic neuropathy.	Day 1