Published online Nov 15, 2020. doi: 10.4239/wjd.v11.i11.489
Peer-review started: July 27, 2020
First decision: August 9, 2020
Revised: August 21, 2020
Accepted: September 18, 2020
Article in press: September 18, 2020
Published online: November 15, 2020
Previous research showed that up to 50% of diabetic individuals were affected by diabetic peripheral neuropathy (DPN). SUDOSCAN (Impeto Medical, Paris, France) is an emerging technique for the detection of DPN through detecting sudomotor function of the sweat gland. Sudomotor dysfunction, derived by SUDOSCAN, could detect DPN in the inchoate stage. The measurement of SUDOSCAN includes electrochemical skin conductance in hands (HESC, measured in μS) and feet (FESC). The exact pathogenesis of DPN is not fully clarified. The researchers identified glycemic variability as an independent contributor to DPN. Time in range (TIR), as a CGM-derived pivotal metric, has been proved to assess short-lived glycemic control. A lower level of TIR had an adverse effect in patients who were diagnosed with diabetes mellitus with diabetic microvascular complications, including microalbuminuria and retinopathy. But the association between TIR and sudomotor dysfunction has not explored clearly yet.
In this study, we aimed to explore the correlation between TIR calculated by continuous glucose monitoring (CGM) and sudomotor dysfunction detected by SUDOSCAN in Chinese subjects with type 2 diabetes mellitus (T2DM).
Our aim was to provide a novel and objective metric to monitor glycemic control in patients with T2DM, especially those who have combined complications.
This study enrolled 466 inpatients with type 2 diabetes. All subjects underwent 3-d CGM and SUDOSCAN. SUDOSCAN was assessed with electrochemical skin conductance in hands (HESC) and feet (FESC). Average feet ESC < 60 µS was defined as sudomotor dysfunction (+), otherwise it was sudomotor dysfunction (-). TIR refers to the percentage of time when blood glucose is between 3.9-10 mmol/L during a 1-d period. First, we compared clinical variables between the sudomotor dysfunction (-) and sudomotor dysfunction (+) groups. Next, in order to perform more in-depth analyses of the association between TIR and sudomotor dysfunction, we further stratified all participants based on tertiles of TIR. And the prevalence of sudomotor dysfunction in different tertiles of TIR was compared. Next, Spearman’s rank correlation was carried out to evaluate the association of TBR, TIR, or TAR and SUDOSCAN metrics. And binary logistic regression analysis was applied to explore the link between TIR (as a continuous or categorical variable) and sudomotor dysfunction after adjusting for clinical factors including age, diabetes duration, sex, BMI, SBP, DBP, smoking, TG, TC, HbA1c, as well as glycemic variability metrics. A P value < 0.01 was considered statistically significant.
Among 466 T2DM subjects, 135 (28.97%) presented with sudomotor dysfunction. Patients who had combined sudomotor dysfunction had a lower value of TIR (P < 0.001). Compared with the lowest tertile of TIR (T1 group), the middle tertile of TIR (T2 group) and the highest tertile of TIR (T3 group) were associated with an obviously lower prevalence of sudomotor dysfunction (20.51%, 21.94% vs 44.52%, P < 0.001). In addition, TIR was linked with SUDOSCAN indicators like FESC and HESC. With the increase of TIR, HESC and FESC increased (P < 0.001). The regression analysis demonstrated that TIR was inversely and independently linked with the prevalence of sudomotor dysfunction after adjusting for confounding factors (odds ratio = 0.979, 95%CI: 0.971-0.987, P < 0.001).
Patients who have combined sudomotor dysfunction have a lower value of TIR. TIR is linked with SUDOSCAN indicators like FESC, HESC, HASYM, and FASYM robustly. TIR is inversely associated with the prevalence of sudomotor dysfunction independent of HbA1c.
This is the first study to investigate the association between TIR and sudomotor dysfunction assessed by SUDOSCAN. These results will interest researchers in the prevalence and management of DPN. The preliminary data from our study may provide a basis for future large-sample, multi-center research.