Diabetes and EZSCAN 1: The Test ofType 2 Diabetes

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1 diabetes research and clinical practice 88 (2010) Contents lists available at ScienceDirect Diabetes Research and Clinical Practice journal homepage: A new non-invasive technology to screen for dysglycaemia including diabetes Ambady Ramachandran a, *, Anand Moses b, Samith Shetty a, Chandragiri Janakiraman Thirupurasundari a, Abraham Catherin Seeli a, Chamukuttan Snehalatha a, Sunil Singvi c, Jean-Paul Deslypere d a India Diabetes Research Foundation & Dr. A. Ramachandran s Diabetes Hospitals, No. 28, Marshall s Road, Egmore, Chennai , India b Moses Diabetes Centre, Chennai, India c Singhvi Clinic, Chennai, India d Impeto Medical, Paris, France article info Article history: Received 21 August 2009 Received in revised form 16 December 2009 Accepted 21 January 2010 Published on line 25 February 2010 Keywords: EZSCAN 1 Non-invasive technology Diagnosis of dysglycaemia Reverse iontophoresis Impaired glucose tolerance Diabetes mellitus abstract Objective: Assess the ability of a new device based on electrochemical principles using iontophoresis (the EZSCAN 1 ) to detect impaired glucose tolerance (IGT) and type 2 diabetes mellitus (DM). Methods: Eligible Asian Indian subjects, n = 212, had anthropometric and blood pressure measurements, followed by an OGTT, HbA1c, serum lipids tests and EZSCAN 1 measurement. Results: Biochemically, 24 subjects were diagnosed with DM, 30 with IGT, 57 subjects had normal glucose tolerance (NGT) with metabolic syndrome (MS) and 101 had NGT without MS. Fasting plasma glucose (FPG) and HbA1c levels were highest in the DM group ( p < for both). HDL-C levels were different ( p = 0.015). FPG at a cut-off level of 7.0 mmol/l had a low sensitivity to detect DM (29%) EZSCAN 1 had a 75% sensitivity to detect DM, 70% for IGT and 84% for NGT with MS at threshold >50%. Conclusions: FPG had low sensitivity to detect DM in the study group. EZSCAN 1 demonstrated good sensitivity to detect IGT and DM and also identified NGT with MS. The concept of measuring ion fluxes through the skin appears to be a powerful method for early detection of MS, IGT and DM. # 2010 Elsevier Ireland Ltd. All rights reserved. Diabetes mellitus (DM) is one of the most common metabolic disorders. The global burden of DM in adults was estimated to be around 246 million in the year 2007 [1]. It was also estimated that the global prevalence among adults would increase to 7.8% by 2030 [2]. The diabetes epidemic is accelerating in the developing world, with an increasing proportion of affected people in younger age groups [1]. This is likely to increase the burden further due to occurrence of chronic diabetic complications. Since DM is asymptomatic for many years [3], early detection can result in appropriate interventions that can reduce the incidence of complications. Currently, screening tests for type 2 diabetes include risk assessment questionnaires, biochemical tests and combinations of both. The biochemical tests currently available are measurement of blood glucose or HbA1c [1]. Since the main purpose of screening is to detect asymptomatic people with undiagnosed diabetes, questionnaires which are based on the symptoms of diabetes are not adequate [1]. The fasting plasma * Corresponding author. Tel.: ; fax: address: ramachandran@vsnl.com (A. Ramachandran) /$ see front matter # 2010 Elsevier Ireland Ltd. All rights reserved. doi: /j.diabres

2 diabetes research and clinical practice 88 (2010) glucose (FPG) test is recommended for initial screening for non-pregnant adults [3]. However it is an invasive test which has a low sensitivity in many populations [4]. Hence a tool which is easy to administer, non-invasive, with high sensitivity and specificity and cost-effective would be of advantage and of great benefit for diabetes screening. The value of such a tool would increase if it can be used by non-clinical personnel, who assist the doctors. The new EZSCAN 1 device is designed to perform a precise evaluation of sweat gland function through reverse iontophoresis, allowing the measurement of sweat chloride concentrations [5,6]. A preliminary study with the EZSCAN 1 device was done on 90 diabetic subjects and compared with a control population of 142 subjects [5]. It showed a significant reduction of the electrochemical conductance in the diabetic persons compared to control subjects ( vs micro- Siemens (msi), p < 0.001). As the preliminary data showed that this device could be used as a screening tool for detecting DM, a cross-sectional study was initiated at 3 research centres in Chennai, India. The aim of the study was to assess the ability of the EZSCAN 1 to detect metabolic syndrome (MS), impaired glucose tolerance (IGT) and type 2 diabetes mellitus (DM) in subjects not known to have these conditions. 1. Research design and methods 1.1. Study population The study was conducted in June to July 2008 at the India Diabetes Research Foundation and Dr. A. Ramachandran s Diabetes Hospitals, Moses Diabetes Center, and Singhvi Clinic Chennai, India. Approval for the study protocol, subject information sheet and the consent form was obtained from the ethics committee of India Diabetes Research Foundation and A. Ramachandran s Diabetes Hospitals, Chennai prior to commencement of the study Inclusion criteria Inclusion criteria were: age between 21 and 75 years, not known to have IGT or DM according to the ADA criteria [3] Exclusion criteria Exclusion criteria were: persons taking drugs that affect blood glucose levels, e.g. corticosteroids, tricyclic antidepressants, diuretics, epinephrine, estrogens, lithium, phenytoin, salicylates, persons taking drugs that affect the sympathetic nervous system, e.g. beta-blockers, amputation of arm or leg, electrical implantable device (pacemaker, defibrillator), known sensitivity to nickel or any other standard electrodes, or suffering from epilepsy/seizures. Anthropometric and blood pressure measurements were done using standard procedures. Subjects attending the clinics for any non-diabetic condition and who had not been diagnosed with IGT or DM but were at risk for these conditions, were identified and approached for their interest in participating in the study. Written informed consent was obtained from all participants. Two hundred and twelve subjects were recruited. They were instructed to come for all the investigations within a week, with an overnight fasting of 8 10 h. Subjects who tested positive for DM during the OGTT were referred to their physicians for medical care EZSCAN W The EZSCAN 1 (Impeto Medical, Paris, France) is a patented device based on electrophysiological and electrochemistry principles which uses low level DC-induced reverse iontophoresis, together with chronoamperometry, to evaluate the behaviour of tissues in the body [5] Measurement principles Iontophoresis is the physical process that enables electrically charged particles to pass through a membrane after an electrical stimulus and is a common means for introducing substances through the skin for therapy purposes. Reverse iontophoresis, the process carried out by EZSCAN 1, extracts ions from the sweat which is secreted by sympathetic controlled glands. At low active DC current (<4 V), the stratum corneum of the skin constitutes an electrical barrier which prevents any other way of liquid extraction as shown in the Chizmadzhev model [6]. The impact of chloride in sweat conductance is clearly established: the relationship between cystic fibrosis transmembrane regulator of the sweat ducts and sweat ion concentrations has been fully studied in cystic fibrosis [7]. The extracted sweat creates a current when it encounters specific sensors such as nickel electrodes. The current produced is proportional to the chloride concentration that reacts specifically with the nickel electrodes at a low DC stimuli. A time/ampere curve is recorded for each derivation. The conductance, expressed micro-siemens (msi) is the ratio between current generated and the constant DC stimulus. The conductances are characteristic of different parts of the body depending on the topographical distributions of sympathetic ganglions and on the nerve fiber lengths. A specific zone generates the same electrochemical measures in a subject, except when a pathological process modifies the function through a small fiber neuropathy Measurement description The EZSCAN 1 device is presented in Fig. 1. The apparatus consists of two sets of electrodes for the hands and the feet as well as a headband device for the forehead, all of which are connected to a PC for recordings and data management. The test requires only 2 min during which 6 combinations of 15 different low DC voltages are applied. Neither any subject preparation nor supervision by a medical personnel is required. The subject places the hands and feet on the electrodes, puts on the headbandandstandsupquietly duringthestrictly non-invasive, painless test. The data are displayed instantaneously in the form of a geometric figure that allows fast, intuitive interpretation. Detailed results are provided in alphanumerical form. The principle of this method is to induce a continuous current lower than 4 V in between 6 electrodes. These electrodes are placed on areas of the skin rich in sweat

3 304 diabetes research and clinical practice 88 (2010) Fig. 1 A new non-invasive technology to screen a general population for unknown diabetes. EZSCAN W device and screen. glands, namely the forehead, the palmar side of the hands and the plantar side of the feet. Each electrode is used alternatively as an anode or a cathode. The conductances (msi), the ratio of the current measured over the constant power applied and are calculated for the face (left and right part), the hands (left and right), the feet (left and right) as well as for the whole body (global conductance) (mean of all derivations). The measurement of the conductance is done by chronoamperometry (EZSCAN 1 ) and graphically displayed on a standard PC computer. Higher readings in msi indicates lower risk of any abnormality. The EZSCAN 1 scale goes from 0 to 100% and is calculated with an algorithm which takes into account different parameters including the EZSCAN 1 measurements and demographic data. This is shown on the EZSCAN 1 screen and to make interpretation easier, different colour codes are used. The threshold for abnormality is set at >50% on the basis of the available results. A positive response on the EZSCAN 1 is defined as a reading of >50% on the EZSCAN 1 scale. The cut-off for the EZSCAN 1 was evaluated by a receiver operating characteristic curve and maximized three components: area under curve (AUC), specificity and sensitivity Laboratory tests All subjects underwent an OGTT, HbA1c and lipid analyses. OGTT was done as described by the WHO [8], with an overnight fasting of 8 10 h using a glucose load of 75 g anhydrous glucose. Blood samples were drawn in fasting for fasting plasma glucose, HbA1c and lipid panel. 2 h plasma glucose was also measured. Plasma glucose was measured by glucoseoxidase peroxidase method and HbA1c was done by HPLC measurement using BIORAD [3]. Fasting serum lipids (total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol Table 1 Demographic data of the study groups defined by OGTT (mean W SD). NGT without MS NGT and MS IGT DM ANOVA p-value n BMI (kg/m 2 ) ns Age (years) * Male:female ratio Blood pressure (mmhg) Systolic Diastolic Fasting plasma glucose (mmol/l) HbA1c (%) Lipid profile Total cholesterol (mmol/l) ns HDL-C (mmol/l) LDL-C (mmol/l) ns Triglycerides (mmol/l) ns: p > * p < p <

4 diabetes research and clinical practice 88 (2010) Table 2 Panel-1: sensitivity of fasting plasma glucose and of the EZSCAN W to detect DM, IGT and NGT with metabolic syndrome; panel-2: performance of EZSCAN W. Subjects with NGT without MS Subjects with NGT and MS Subjects with IGT Subjects with DM Panel-1 N (as defined by OGTT) FPG > 7.0 mmol/l FPG 7.0 mmol/l Sensitivity (%) FPG > 6.1 mmol/l FPG 6.1 mmol/l Sensitivity (%) EZSCAN 1 > EZSCAN Sensitivity (%) Specificity (%) 54 Subjects with NGT and MS/IGT/DM Subjects with NGT without MS Panel-2 EZSCAN 1 (+) 87 (a) 47 (b) EZSCAN 1 ( ) 24 (c) 54 (d) Sensitivity = a/(a + c) = 78%; specificity = d/(b + d) = 54%; negative predictive value (NPV) = d/(c + d) = 69%; positive predictive value (PPV) = a/ (a + b) = 65%. (LDL-C)) were measured by standard enzymatic procedures. Diabetes is defined as a fasting glucose of >7.0 mmol/l and/or 2 h plasma glucose >11.1 mmol/l while an IGT is defined as a 2 h plasma glucose of 7.8 to <11.1 mmol/l [8]. MS was defined according to the AHA/NCEP criteria [9], modified to suit the Asian population [10]. 2. Statistical analyses Results are shown as mean SD. Means of groups were compared by linear analysis of variance. The post hoc Tukey s multiple comparison test was used in order to compare the difference between each pair of means with appropriate adjustment for the multiple testing. A p-value < 0.05 was regarded as statistically significant. The statistical analysis was done using the Statistical package: R with: package fields version 5.01, package ROCR version [11]. FPG at a cut-off level of 7.0 mmol/l had a low sensitivity to detect DM (29%). Among the IGT subjects only 3% had higher FPG levels. The sensitivity of EZSCAN 1 was 75% to detect DM, 70% for IGT and 84% for NGT with MS (Table 2, panel-1) at a threshold of 50%. The global sensitivity of EZSCAN 1 was 78%, the specificity was 54%, the negative predictive value was 69% and the positive predictive value was 65% (Table 2, panel-2). The ROC graphs of EZSCAN 1, HbA1c and FPG shown in Fig. 2 demonstrates the higher sensitivity of the EZSCAN 1 for detecting overall abnormalities. 3. Results A total of 212 subjects were enrolled in the study. The demographic characteristics are shown in Table 1. Twentyfour subjects were diagnosed with DM, 30 with IGT and 57 with NGT and MS and 101 subjects with NGT without MS. The characteristics of these four groups are also shown in Table 1. Subjects with IGT and DM were older. Systolic and diastolic blood pressure values were higher in the groups with abnormalities. Subjects with IGT and DM had higher HbA1c values. HDL-C values were lower and triglycerides were higher in groups with abnormalities. In the group with NGT and MS, the above parameters were higher due to the selection criteria. Fig. 2 ROC graphs showing the sensitivity of EZSCAN W, HbA1c and fasting plasma glucose to detect abnormalities. ROC graphs vs. OGTT.

5 306 diabetes research and clinical practice 88 (2010) Conclusion references In the study subjects, FPG measurement had a low sensitivity to detect DM, in agreement with previous reports [4]. FPG did not identify people with IGT, as only about one third of the Asian Indian IGT subjects would show impaired fasting glucose values also [12]. TheEZSCAN 1 on the other hand has a good sensitivity to detect both IGT and DM. The study was done in Asian Indian subjects because of the high prevalence of diabetes in this population. The reproducibility of the results in European and Chinese population is being studied. Analysis of the preliminary data indicate that findings are similar in these ethnic groups also (unpublished data). However, the preliminary results of this study have to be confirmed in different ethnic groups and also in larger numbers. An interesting finding in this study was the higher than expected EZSCAN 1 readings in IGT subjects which might indicate that the sweat gland nerves were going through a phase of hypersensitivity during the IGT phase before entering a hypo sensitivity phase in DM [13,14]. Our findings seem to illustrate that the concept of measuring ion fluxes through the skin is a sensitive new method for the early detection of MS, IGT and of DM, independently of other tests. Due to its simplicity and higher sensitivity, the EZSCAN 1 test could potentially replace the measurement of FPG as a screening tool for detection of deranged carbohydrate metabolism in large population samples. The apparent low specificity may be related to the sensitivity of EZSCAN 1 to identify insulin resistance at an early stage. A longitudinal study is now under way to confirm our findings, making use of frequently sampled oral GTT to assess insulin resistance in the study subjects. Disclosure This study was sponsored by Impeto Medical. Conflict of interest Jean-Paul Deslpere is a consultant to Impeto Medical and has been paid for this consultancy work. [1] R. Sicree, J. Shaw, P. Zimmet, Diabetes impaired glucose tolerance prevalence and projections, in: D. Gan (Ed.), Diabetes, 3rd edition, Atlas International Diabetes Federation, Brussels, 2006, pp [2] International Diabetes Federation, Diabetes Atlas, 4th edition, [3] Standards of medical care in diabetes: American Diabetes Association, Diabetes Care 31 (2008) S1. [4] M.M. Engelgau, K.M. Narayan, W.H. Herman, Screening for Type 2 diabetes, Diabetes Care 23 (2000) [5] P. Brunswick, H. Mayaudon, O. Dupuy, L. Bordier, B. Bauduceau, Exploration de l innervation des glandes sudoripares chez le diabétique. Présentation à Congrès Conjoint Alfediam-SFE, Diabète-Endocrinologie, Marseille (2007) 44. [6] Y.A. Chizmadzhev, A.V. Indenborn, P.I. Kuzmin, S.V. Galichenko, J.C. Weaver, R.O. Potts, Electrical properties of skin at moderate voltages: contribution of appendageal macropores, Biophys. J. 74 (1998) [7] P.M. Quinton, Cystic fibrosis: lessons from the sweat gland, Physiology 22 (2007) [8] World Health Organisation, Definition, diagnosis and classification of diabetes mellitus and its complications, in: Report of a WHO Consultation. Part I: Diagnosis and Classification of Diabetes Mellitus, WHO, Geneva, 1999 (WHO/NCD/NCS/99.2). [9] Expert panel on detection, evaluation, and treatment of high blood cholesterol in adults: executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III), J. Am. Med. Assoc. 285 (2001) [10] A. Ramachandran, C. Snehalatha, K. Satyavani, S. Sivasankari, V. Vijay, Metabolic syndrome in urban Asian Indian adults a population study using modified ATP III criteria, Diabetes Res. Clin. Pract. 60 (2003) [11] T. Sing, O. Sander, N. Beerenwinkel, T. Lengauer, ROCR: visualizing classifier performance in R, Bioinformatics 21 (2005) [12] A. Ramachandran, C. Snehalatha, K. Satyavani, V. Vijay, Impaired fasting glucose and impaired glucose tolerance in urban population in India, Diabetes Med. 20 (2003) [13] J. Hilsted, P.A. Low, Diabetic Autonomic Neuropathy in Low PA Clinical Autonomic Disorders: Evaluation and Management, 2nd edition, Philadelphia Lippincott Press, 1997, pp [14] G. Lauria, R. Lombardi, Skin biopsy: a new tool for diagnosing peripheral neuropathy, Br. Med. J. 334 (2007)