Non-invasive screening of diabetes risk by assessing abnormalities of sudomotor function

Exp Clin Endocrinol Diabetes. 2015 Jan;123(1):34-8. doi: 10.1055/s-0033-1357128. Epub 2014 May 5.


Background: The early detection of diabetes, and subsequent lifestyle intervention, may reduce the burden of diabetes and its complications. Several studies have identified a link between sudomotor dysfunction, insulin resistance, and pre-diabetes. The aim of this study was to evaluate the ability of a new non-invasive device EZSCAN evaluating sudomotor function to detect pre-diabetes in a German population at risk for diabetes.

Methods and findings: 200 German subjects at risk for diabetes (mean age 56±14 years, BMI 28.4±5.4 kg/m2) were measured for anthropometric data on inflammatory parameters, including high sensitivity C reactive protein (hs-CRP). The subjects also underwent an oral glucose tolerance test with measurements of plasma glucose, insulin, proinsulin, C-peptide and free fatty acids during 2 h following glucose challenge. Indexes for sensitivity to insulin were calculated: SI using minimal model, HOMA-IR and Matsuda index. Based on the measurement of electrochemical sweat conductance, subjects were classified as no risk, moderate risk or high risk. According to this risk model classification, a significant difference was observed between OGTT-1 h (p=0.004), AUC glucose (p=0.011), AUC C-peptide (p<0.001), HOMA-IR (p=0.009), Matsuda (p=0.002), SI (p<0.001) and hs-CRP (p=0.025) after adjustment for age. Among the 54 subjects with impaired fasting glucose or impaired glucose tolerance according to WHO classification, 37 had a moderate risk and 15 a high risk according to the EZSCAN risk model classification. Among the 12 subjects with newly diagnosed diabetes, 2 had a moderate risk and 10 a high risk according to the risk model classification. No adverse event was reported during or after the study.

Conclusions: These results, in accordance with a previous study performed in India, show that EZSCAN could be developed as a screening tool for diabetes risk, and could help to improve diabetes screening strategies. Results obtained from an at-risk population would have to be confirmed in a larger population.

Publication types

  • Clinical Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Blood Glucose / metabolism
  • C-Reactive Protein
  • Diabetes Mellitus / blood*
  • Diabetes Mellitus / diagnosis*
  • Fatty Acids, Nonesterified / blood
  • Female
  • Glucose Tolerance Test
  • Humans
  • Male
  • Middle Aged
  • Models, Biological*
  • Proinsulin / blood
  • Risk Factors


  • Blood Glucose
  • Fatty Acids, Nonesterified
  • C-Reactive Protein
  • Proinsulin