Electrochemical skin conductances values and clinical factors affecting sudomotor dysfunction in patients with prediabetes, type 1 diabetes, and type 2 diabetes: A single center experience.

BACKGROUND AND AIM: Sudomotor dysfunction is linked to small fibers damage. We investigated sudomotor dysfunction in a large group of participants with diabetes, prediabetes, and nondiabetic healthy subjects. This study aimed to complete knowledge on sudomotor dysfunction in this population, especially regarding the threshold values for the electrochemical skin conductance (ESC) and factors affecting it. MATERIALS AND METHODS: A total of 690 volunteers in four groups were included in the study (type 1 [T1DG]: n = 80, 61.3% women; type 2 diabetes [T2DG]: n = 438, 63.5% women; prediabetes [Pre-DG]: n = 88, 80.7% women; healthy control [HC-G]: n = 84, 67.5% women). All subjects were investigated for clinical diabetic peripheral polyneuropathy and sudomotor dysfunction. The characteristics of participants obtained from outpatient records were evaluated. We used the Sudoscan device to measure ESC which was normalized for BMI, to improve the discriminative capability of the method. RESULTS: Diabetic polyneuropathy was found in 17.5% of T1DG, 27.4% of T1DG, and 10.2% of Pre-DG. The mean ESC/BMI was lower in subgroups with diabetic polyneuropathy than those without. Mean ESC/BMI was lowest in T2DG and highest in HC-G but comparable in T1DG and Pre-DG. We accepted the "mean ESC/BMI-1 SD" in the HC-G as the threshold for sudomotor dysfunction. Accordingly, the prevalence of sudomotor dysfunction was 18.8%, 44.3%, 59.1%, and 15% in T1DG, T2DG, Pre-DG, and HC-G, respectively. In T2DG, sudomotor dysfunction was found in 66.7% of persons with retinopathy, of which 56.3% had clinical diabetic polyneuropathy. The prevalence of sudomotor dysfunction in subjects with peripheral artery disease, chronic kidney disease, cardiovascular disease, and hypertension was 46.7%, 47.4%, 43.4%, and 50%, respectively, and 42.9%, 38.9%, 45.5%, and 37.3% of whom in the same order detected with clinical diabetic polyneuropathy. Considering the entire group, a logistic regression model demonstrated that the variables associated with SMD were: retinopathy (OR: 2.969; 95% CI: 1.723, 5.114), female gender (OR: 1.952; 95% CI: 1.287, 2.962), and e-GFR (OR: 0.989; 95% CI: 0.981, 0.998). Since the rate of complications was very low in T1DG, excluding this group, a new model similarly revealed that retinopathy and female gender were associated with SMD, however, the association with e-GFR was disappeared. CONCLUSION: The prevalence of sudomotor dysfunction is high when established peripheral polyneuropathy was present in diabetes. Even though, sudomotor dysfunction can also occur before clinical polyneuropathy in both types of diabetes (T1DG: 18.8%, T2DG 44.3%), prediabetes (59.1%), and nondiabetic healthy subjects (15%). The variables associated with sudomotor dysfunction were retinopathy and female sex. Normalization of ESC for BMI would be a beneficial approach. However, before this method is included in the routine screening programs for diabetic polyneuropathy, large-scale and prospective studies are required to reach a consensus on the pathological threshold values.

Status of Weight Change, Lifestyle Behaviors, Depression, Anxiety, and Diabetes Mellitus in a Cohort with Obesity during the COVID-19 Lockdown: Turk-Com Study Group.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic led to a lockdown period. Confinement periods have been related to unhealthy lifestyle behaviors. Our study aimed to determine weight change, changes in eating and exercise habits, the presence of depression and anxiety, and diabetes mellitus (DM) status in a cohort of patients with obesity. METHODS: The study was undertaken in nine centers of Collaborative Obesity Management (COM) of the European Association for the Study of Obesity (EASO) in Turkey. An e-survey about weight change, eating habits, physical activity status, DM status, depression, and anxiety was completed by patients. The International Physical Activity Questionnaire (IPAQ) score was used to determine physical activity in terms of metabolic equivalents (METs). A healthy nutrition coefficient was calculated from the different categories of food consumption. The Patient Health Questionnaire (PHQ-9) and General Anxiety Disorder (GAD-7) Questionnaire  were used for determining depression and anxiety, respectively. RESULTS: Four hundred twenty-two patients (age 45 ± 12.7 years, W/M = 350/72) were included. The healthy nutrition coefficient before the pandemic was 38.9 ± 6.2 and decreased to 38.1 ± 6.4 during the pandemic (p < 0.001). Two hundred twenty-nine (54.8%) patients gained weight, 54 (12.9%) were weight neutral, and 135 (32.3%) lost weight. Patients in the weight loss group had higher MET scores and higher healthy nutrition coefficients compared with the weight gain and weight-neutral groups (p < 0.001). The PHQ and GAD scores were not different between the groups. Percent weight loss was related to healthy nutrition coefficient (CI: 0.884 [0.821-0.951], p = 0.001) and MET categories (CI: 0.408 [0.222-0.748], p = 0.004). One hundred seventy patients had DM. Considering glycemic control, only 12 (8.4%) had fasting blood glucose <100 mg/dL and 36 (25.2%) had postprandial BG <160 mg/dL. When patients with and without DM were compared in terms of dietary compliance, MET category, weight loss status, PHQ-9 scores, and GAD-7 scores, only MET categories were different; 29 (11.7%) of patients in the nondiabetic group were in the highly active group compared with 5 (2.9%) in the diabetic group. CONCLUSION: The COVID-19 lockdown resulted in weight gain in about half of our patients, which was related to changes in physical activity and eating habits. Patients with DM who had moderate glycemic control were similar to the general population in terms of weight loss but were less active.