Development of a system to analyze physiological parameters that are influenced by endothelial dysfunction to assess risks of diabetes

Abstract

Vasodilatory Endothelial Dysfunction (VED) is identified as a precursor to cardio- vascular diseases (CVDs) and atherosclerosis. Therefore, early detection of VED is important to prevent the development of severe CVDs and prescribe lifestyle changes or make clinical interventions. Though coronary angiography is the gold standard to detect VED, specialized devices have provided alternative means of detecting VED non-invasively. With these, they have detected VED in patients who are already di- agnosed with CVD or Diabetes Mellitus (DM). Here, we investigated early detection of VED under four subject categories: individuals with pre-diabetes (PDM); healthy individuals with CVD risk factors (HRF); individuals with DM; and individuals with CVD. Non-invasively measured physiological parameters were used to detect VED. We developed a custom-made device to record non-invasive physiological parameters from the distal end of upper limbs namely, Digital Body Temperature, Peripheral Ar- terial Tone, Photo Plethysmography and Peripheral Bio-impedance. Multiple indices which represent unique features of these parameters were calculated considering both long-term and short-term variations. Using these, the performance of this device was validated against the flow-mediated dilation (FMD) procedure in a preliminary study with 10 volunteers (age range: 35 - 60 years): 5 healthy subjects (control) and 5 CVD patients with/without DM. Then the clinical study was conducted with 69 participants (age range: 35-60 years) with all the subject categories: healthy (n=9), HRF (n=15), PDM(n=6),type2DM(n=15),CVDwith/withoutDM(n=24). CVDriskfactorsiden- tified for the HRF category were physical inactivity, unhealthy diet, smoking, alcohol consumption, body mass index, and family history of CVD. Participants with type- 1 DM, liver cirrhosis, renal failure, thyroid disease, spinal cord injuries, and finger deformities were excluded from the study. In the preliminary study, an unpaired t- testperformedbetweenFMDreadingsandindicesderivedfromparameterscalculated from the custom-made device validated device performance. In the clinical study, the ANOVAanalysisshowedpromisingresults(p<0.05)indistinguishinglong-termtrend variations and short-term variations of VED-associated physiological parameters in test subjects diagnosed with CVD or DM along with preclinical stages compared to the healthy conditions. Thereby, we have demonstrated that it may be possible to detect the early development of CVD in preclinical stages through monitoring these VED-associated physiological parameters.