New approach to beta cell function screening by nitric oxide assessment of obese individuals at the population level

Abstract

Background: Approximately 27% of Americans today are obese, and this condition increases the prevalence of metabolic syndrome and diabetes. The UK Prospective Diabetes Study suggests that loss of beta cell function can begin at least 10 years before diagnosis, and mean beta cell function is already less than 50% at diagnosis. The aim of this research was to assess the possibility of detecting loss of beta cell function in obese patients by a novel approach involving nitric oxide assessment using a combination of technologies.

Materials and methods: One hundred and fifteen obese patients (93 women, 22 men) of mean age 39 (range 17-62) years, who were candidates for bariatric surgery were included in the study, and underwent laboratory tests, including fasting blood glucose, fasting insulin plasma, and examination with the Electro Sensor complex. The Electro Sensor complex offers a new way to assess nitric oxide production using five technologies managed by software, ie, the galvanic skin response, photoelectrical plethysmography, heart rate variability analysis, bioimpedance analysis, and blood pressure oscillometric measurements. The homeostasis model assessment 2% beta cell function (HOMA2% β) algorithm was calculated from fasting blood glucose and fasting insulin plasma using free software provided by The University of Oxford Diabetes Trial Unit. The Electro Sensor complex percent beta (ESC% β) algorithm was calculated from the Electro Sensor complex data and statistical neural network. Statistical analysis was performed to correlate ESC% β and HOMA2% β using the coefficient of correlation and Spearman's coefficient of rank correlation. Receiver-operating characteristic curves were also constructed to determine the specificity and sensitivity of ESC% β in detecting a HOMA2% β value < 100.

Results: The coefficient of correlation between ESC% β and HOMA2% β was 0.72 (using log values) and the Spearman's coefficient of rank correlation (rho) was 0.799 (P < 0.0001). ESC% β had a sensitivity of 77.14% and specificity of 78.21% (cutoff ≤ 157, corresponding to 40% after conversion into a 0%-100% scale) to detect a HOMA2% β value < 100 (P < 0.0001).

Conclusion: The ESC% β algorithm has a high predictive correlation with HOMA2% β, and good specificity and sensitivity to detect a HOMA2% β value < 100. Therefore, the Electro Sensor complex enabling nitric oxide assessment represents a novel method of screening for beta cell function in the obese population on a large scale. Such a tool, which is easy to administer, noninvasive, and cost-effective, would be of great benefit for widespread screening of beta cell function in obese patients.

Keywords: ESC% β algorithm; Electro Sensor complex; HOMA2% β algorithm; beta cell function; nitric oxide assessment; obese population; screening.

Figure 1

Scatter diagram and regression line ESC% β and HOMA2% β. Abbreviations: HOMA2% β, homeostasis model assessment 2 percent beta cell function; ESC% β, Electro Sensor complex percent beta.

Figure 2

Receiver operating characteristic curve ESC% β versus HOMA2% β value < 100. Abbreviations: HOMA2% β, homeostasis model assessment 2 percent beta cell function; ESC% β, Electro Sensor complex percent beta.