Glycemic variability is associated with sural nerve conduction velocity in outpatients with type 2 diabetes: Usefulness of a new point-of-care device for nerve conduction studies.
Although several studies have shown the association between continuous glucose monitoring (CGM)-derived glycemic variability (GV) and diabetic peripheral neuropathy, no studies have focused on outpatients or used NC-stat®/DPNCheck™, a new point-of-care device for nerve conduction study (NCS). We investigated the association between CGM-derived GV and NCS using DPNCheck™ in outpatients with type 2 diabetes, and further analyzed the difference in results between patients with and without well-controlled HbA1c levels.
All outpatients with type 2 diabetes using the CGM device (FreeStyle Libre Pro®) between 2017 and 2022 were investigated. Sural nerve conduction was evaluated by sensory nerve action potential (SNAP) amplitude and sensory conduction velocity (SCV) using DPNCheck™. Associations of CGM-derived GV metrics with SNAP amplitude and SCV were investigated.
In total, 304 outpatients with type 2 diabetes were included. In a linear regression model, most CGM-derived GV metrics except for the mean amplitude of glucose excursion and low blood glucose index were significantly associated with SCV, but not with SNAP amplitude. The significant associations of most CGM-derived GV metrics with SCV remained after adjustment for possible confounding factors, but not after adjustment for glycated hemoglobin (HbA1c). Most CGM-derived GV metrics were significantly associated with SCV after adjustment for HbA1c in patients with a HbA1c ≤ 6.9%, but not in those with a HbA1c ≥ 7.0%.
In outpatients with type 2 diabetes, multiple CGM-derived GV metrics were significantly associated with SCV obtained by DPNCheck™. GV may have independent impacts on peripheral nerve function, particularly in patients with well-controlled HbA1c levels.
Morita M
，Sada K
，Hidaka S
，Ogawa M
，Shibata H
... -
《-》
Study of Glycemic Variability in Well-controlled Type 2 Diabetic Patients Using Continuous Glucose Monitoring System.
The world has changed tremendously for patients suffering from diabetes mellitus with the development of cutting-edge technologies like continuous glucose monitoring and flash glucose monitoring systems. Now, the details of constant fluctuations of glucose in their blood can be monitored not only by medical professionals but also by patients, and this is called glycemic variability (GV). Traditional metrics of glycemic control measurement, such as glycated hemoglobin (HbA1c), fail to reflect various short-term glycemic changes like postprandial hyperglycemia and hypoglycemic episodes, paving the way to the occurrence of various diabetic complications even in asymptomatic, well-controlled diabetic patients. This need for advanced management of diabetes and effective monitoring of these swings in blood glucose can be met by using a continuous glucose monitoring system (CGMS).
To evaluate the extent of GV in well-controlled type 2 diabetes mellitus (T2DM) patients using a flash CGMS and to assess the correlation between GV and HbA1c.
A hospital-based prospective observational study was carried out from May 2020 to Oct 2021 at the Department of Medicine, SMS Hospital, Jaipur, Rajasthan (India), after approval from the Ethics Committee of the institution. A total of 30 patients with well-controlled T2DM (HbA1c was ≥6.5, but ≤7.5) were included in the study using simple random techniques after written informed consent from patients. Patients were studied for glycemic excursions over a period of 7 days by using FreeStyle® Libre Pro™, which is a flash glucose monitoring system. The CGM sensor was attached to the left upper arm of the patient on day 0 and removed on day 7. The data recorded in the sensor was then retrieved using pre-installed computer software and analyzed using standard CGM metrics like standard deviation (SD), percentage coefficient of variation (%CV), time above range (TAR), time below range (TBR), and time in range (TIR), out of which %CV was used to quantify GV. %CV has been used to cluster patients into four cohorts from best to worst, namely: best/low CV ≤ 10%, intermediate CV from 10 to 20%, high CV from 20 to 30%, and very high CV of >30%. Scatterplots are used to establish correlations between various parameters.
Data from a total of 30 patients were analyzed using CGMS and thus used for calculating standard CGM metrics; glucose readings every 15 minutes were recorded consecutively for 7-day periods, making it a total of 672 readings for each patient. Interpreting the CGM data of all 30 patients, the following results were found: the mean blood glucose of all cases is 134.925 ± 22.323 mg/dL, the mean SD of blood glucose of all cases is 35.348 ± 9.388 mg/dL, the mean of %CV of all cases is 26.376 ± 6.193%. CGM parameters of time are used in the form of percentages, and the following results were found: the mean of TAR, TBR, and TIR is 14.425 ± 13.211, 5.771 ± 6.808, and 82.594 ± 12.888%, respectively. Clustering the patients into cohorts, the proportion of patients exhibiting best/low %CV (10%) is 0, intermediate %CV (10-20%) is 16.67% (five out of 30 patients), high %CV (20-30%) is 50% (15 out of 30 patients) and very high %CV (>30%) is 33.33% (10 out of 30 patients). Also, there is no significant correlation found between HbA1c and %CV (ρ = 0.076, p-value = 0.690); a significant negative correlation was found between %CV and TIR (ρ = -0.604, p < 0.001S); a positive correlation of %CV with TAR and TBR is significant (ρ = 0.816, p-value of <0.001).
Using a flash CGMS device and considering %CV as the parameter and primary measure of GV, the study demonstrated the overall instability of a person's glycemic control, making note of unrecognized events of hypoglycemia and hyperglycemia in asymptomatic well-controlled T2DM patients, revealing the overall volatile glycemic control. The most important finding of this study is that even those diabetics who are considered well-controlled experience a great degree of GV as assessed by CGM-derived metrics. This study also demonstrated that there is no significant correlation between HbA1c and GV, suggesting that patients may not have optimal control of their diabetes despite having "normal HbA1c" values; hence, GV can be considered an HbA1c-independent danger factor, having more harmful effects than sustained hyperglycemia in the growth of diabetic complications. So, by using CGM-derived metrics, the measurement of GV has the potential to complement HbA1c data. In this manner, a more comprehensive assessment of glycemic excursions can be provided for better treatment decisions, thereby facilitating optimal glycemic control, which is essential for reducing overall complications and promoting good quality of life.
Swami V
，Yadav SK
，Saxena P
，Sharma A
，Dash CK
，Gupta A
... -
《-》
TIR generated by continuous glucose monitoring is associated with peripheral nerve function in type 2 diabetes.
Continuous glucose monitoring (CGM)-derived time-in-range (TIR) of 3.9-10 mmol/L is associated with diabetic retinopathy in type 2 diabetes (T2DM), but its relationship to peripheral nerve function has not been previously investigated. To explore the association between the TIR and nerve conduction study parameters in patients with T2DM, we performed a cross-sectional analysis.
A total of 740 patients with T2DM were enrolled in this study. All of the participants were divided into tertiles according to the TIR (TIR low: ≤53%; TIR medium: 54-76%; TIR high: ≥77%). Composite Z-scores of nerve conduction velocity (CV), latency, and amplitude were calculated. The linear correlation between the TIR and composite nerve function Z-score was evaluated and risk assessment was analysed using binary logistic regression.
The composite Z-score of the CV and amplitude increased with higher TIR and the composite Z-score of latency significantly decreased as the TIR tertiles increased (all P trend < 0.05). After adjusting for age, diabetes duration, height, weight and other confounding factors, higher TIR was associated with a higher composite Z-score of CV (β = 0.230, P < 0.001), amplitude (β = 0.099, P = 0.010), and lower composite Z-score of latency (β = -0.172, P < 0.001). The risk of TIR tertiles and low composite Z-score of CV remained significant even after adjustment of HbA1c (TIR medium: OR = 0.48, P = 0.001; TIR high: OR = 0.41, P < 0.001).
Higher TIR tertiles were independently associated with better peripheral nerve function. CGM-derived TIR may be a promising approach to screen patients for further assessment of possible diabetic peripheral neuropathy.
Li F
，Zhang Y
，Li H
，Lu J
，Jiang L
，Vigersky RA
，Zhou J
，Wang C
，Bao Y
，Jia W
... -
《-》
ResearchGate
(全网免费下载)
钛学术
(全网免费下载)
