Association of time in range, as assessed by continuous glucose monitoring, with painful diabetic polyneuropathy

Long-term efficacy of 10 kHz spinal cord stimulation in managing painful diabetic neuropathy: A post-study survey

OBJECTIVE

To evaluate the longer-term efficacy of 10 kHz spinal cord stimulation (SCS) in managing painful diabetic neuropathy (PDN) in a routine clinical setting after the transition from the 24-month SENZA-PDN study.

METHODS

We contacted 142 participants who completed 24 months of postimplantation follow-up in the former randomized controlled trial (SENZA-PDN). Of these, 57 consented and responded to this longer-term post-study survey. Outcomes assessed included pain relief, health-related quality of life (HRQoL) measured using the EuroQol 5-Dimensional 5-Level (EQ-5D-5L) instrument, Patient Global Impression of Change (PGIC), HbA1c, and weight.

RESULTS

Our survey captured patient-reported outcomes at a median of 4.1 years after implantation of a permanent 10 kHz SCS system. Among the surveyed participants, 76.8% (43 of 56) reported clinically meaningful pain relief (≥2 points), and 84.6% (44 of 52) achieved a clinically meaningful improvement in their EQ-5D-5L index score, with a final mean EQ-5D-5L index score of 0.825. Additionally, 74.5% (38 of 51) reported being "Better" or "A great deal better" on the PGIC scale. The surveyed participants reported a mean HbA1c level decrease of 0.4% (p = 0.027), with a more substantial improvement of 1.6% (p < 0.001) among those with type 2 diabetes (T2D) and a higher preimplantation HbA1c (>8%). Significant weight loss was also observed, with a mean reduction of 7.0 kg (p < 0.001) in the overall cohort and 8.7 kg (p < 0.001) in the subgroup with T2D and a higher BMI at preimplantation (≥35 kg/m2).

CONCLUSIONS

High-frequency SCS at 10 kHz provided sustained and clinically meaningful improvements in pain and HRQoL for PDN patients at 4.1 years postimplantation, with no explants in the cohort due to inefficacy. Alongside these benefits, participants experienced metabolic changes that included reductions in body weight and HbA1c beyond that achieved at 24 months, although changes in lifestyle and medication were not accounted for in this analysis. Notably, the cohort's final mean EQ-5D-5L index score was comparable to the US norm. These findings support 10 kHz SCS as a durable and effective treatment option for PDN in routine clinical practice.

Impact of HbA1c variability and time-in-range fluctuations on large and small nerve fiber dysfunction in well-controlled type 2 diabetes: A prospective cohort observational study

AIMS/INTRODUCTION

Glycemic variability (GV) is a critical factor in the development of diabetic sensorimotor polyneuropathy (DSPN). This study aimed to evaluate the association of long-term GV, measured by glycated hemoglobin (HbA1c) average real variability (ARV), and short-term GV, assessed by time-in-range (TIR) ARV, with large and small nerve fiber dysfunction in individuals with well-controlled Type 2 Diabetes (T2D).

MATERIALS AND METHODS

A prospective study conducted at a tertiary hospital in Taiwan included 82 T2D participants. Long-term GV was assessed using HbA1c ARV from visit-to-visit measurements at three-month intervals over 1 year. Short-term GV was evaluated as TIR ARV from seven-day fingerstick data collected quarterly. Large and small nerve functions were assessed using the Toronto Clinical Neuropathy Score (TCNS), nerve conduction studies, quantitative thermal testing, and Sudoscan.

RESULTS

Linear regression analysis adjusted for age, diabetes duration, and renal function revealed strong correlations between HbA1c ARV, TIR ARV, and diabetes duration. At baseline, high HbA1c ARV and TIR ARV groups exhibited higher TCNS and composite nerve conduction amplitude scores but lower cold detection thresholds compared to the low median groups. At one-year follow-up, TCNS significantly increased in the high HbA1c ARV (P = 0.001) and TIR ARV (P = 0.003) groups compared to the low median groups.

CONCLUSIONS

Both long-term and short-term GV significantly contribute to small and large nerve fiber dysfunction in T2D, yielding similar neurological outcomes despite stable mean glucose levels. Combining GV minimization strategies with standard glycemic control may be essential in reducing DSPN risk.

The use of continuous glucose monitoring in people living with obesity, intermediate hyperglycemia or type 2 diabetes

A global trend towards increased obesity, intermediate hyperglycemia (previously termed prediabetes) and type 2 diabetes, has prompted a range of international initiatives to proactively raise awareness and provide action-driven recommendations to prevent and manage these linked disease states. One approach, that has shown success in managing people already diagnosed with type 2 diabetes mellitus, is to use continuous glucose monitoring (CGM) devices to help them manage their chronic condition through understanding and treating their daily glucose fluctuations, in assocation with glucose-lowering medications, including insulin. However, much of the burden of type 2 diabetes mellitus is founded in the delayed detection both of type 2 diabetes mellitus itself, and the intermediate hyperglycemia that precedes it. In this review, we provide evidence that using CGM technology in people at-risk of intermediate hyperglycemia or type 2 diabetes mellitus can significantly improve the rate and timing of detection of dysglycemia. Earlier detection allows intervention, including through continued use of CGM to guide changes to diet and lifestyle, that can delay or prevent harmful progression of early dysglycemia. Although further research is needed to fully understand the cost-effectiveness of this intervention in people at-risk or with early dysglycemia, the proposition for use of CGM technology is clear.

Do continuous glucose monitoring (CGM) metrics predict macrovascular and microvascular complications in diabetes? The FACULTY protocol of a retrospective real-world cohort study

INTRODUCTION

Glycated haemoglobin (HbA1c) is currently the gold standard for assessing glycaemic control in diabetes, given the established relationship with microvascular and macrovascular complications in this condition. However, HbA1c is affected by non-glycaemic factors, while also failing to provide data on hypoglycaemic exposure and glucose variability, which are associated with adverse vascular outcomes. Continuous glucose monitoring (CGM)-derived glucose metrics provide a more comprehensive assessment of glycaemia, but their role in predicting future vascular complications remains unclear. Here, we present the protocol for a real-world cohort study, aiming to establish the relationship between CGM-derived glycaemic metrics and the incidence of macrovascular and/or microvascular complications in people with diabetes.

METHODS AND ANALYSIS

This cohort study will use data from all CGM new users (FreeStyle Libre system) in France who uploaded their glycaemic values onto the LibreView cloud-based system, linked with data from the French nationwide Système National des Données de Santé claims database. The study is expected to include a minimum of 70 000 individuals with diabetes with a first date of glucose data upload to the LibreView platform after 1 January 2018 and with a 6-year follow-up period. The primary outcomes are the first occurrence of new macrovascular or microvascular complications, analysed as a composite outcome and separately. Secondary outcomes will include all-cause mortality and hospital admissions for any cause. This longitudinal study will provide key data on the relationship between CGM-derived glycaemic metrics and micro/macrovascular complications in diabetes. This will have an impact on routine clinical practice by setting targets for the different glycaemic markers, based on robust outcome data, thus helping to optimise glucose management in diabetes.

ETHICS AND DISSEMINATION

The study data-collection protocol is approved by the French National Commission for Informatics and Liberties, including approval from the Comité Ethique et Scientifique pour les Recherches, les Etudes et les Evaluations dans le domaine de la Santé. This study complies with French and European regulations, including those relating to the General Data Protection Regulation. This study uses pseudonymous information, not requiring informed consent. Dissemination plans include full publication of the study outcomes in peer-reviewed journal(s) with open access and presentations at national and international diabetes and cardiovascular conferences.

Diabetic Peripheral Neuropathy and Glycemia Risk Index in Type 2 Diabetes: A Cross-Sectional Study

Purpose

Diabetic peripheral neuropathy (DPN) is a prevalent chronic complication of diabetes which is linked to chronic hyperglycemia and glycemic variability. This study aimed to investigate the association between the glycemia risk index (GRI) and DPN in patients with type 2 diabetes mellitus (T2DM) using continuous glucose monitoring (CGM) data.

Patients and Methods

From 2019 to 2023, 862 adults diagnosed with T2DM were enrolled at a tertiary care diabetes center in Ningbo, China. The medical history and laboratory parameters were recorded. Neurophysiological examinations were performed to evaluate DPN. The CGM data were recorded for 14 days, and the GRI was calculated based on these data. Multivariate logistic regression analyses were conducted to assess the odds ratio (OR) for DPN with an increased GRI.

Results

The prevalence of DPN in the ascending GRI quartiles was 41.6%, 47.9%, 49.1%, and 59.5%, respectively (P for trend < 0.001). In the multivariable logistic analysis, the highest GRI quartile exhibited a 63% greater risk of DPN (OR 1.631, 95% CI: 1.071 to 2.484, P = 0.023) than the lowest quartile after adjusted for age, sex, body mass index, diabetes duration, blood pressure, creatinine, urinary albumin-to-creatinine ratio, lipid profile and glycated hemoglobin.

Conclusion

High GRI levels, as measured by CGM, were associated with a greater likelihood of DPN in T2DM patients.

The application of artificial intelligence in diabetic retinopathy: progress and prospects

In recent years, artificial intelligence (AI), especially deep learning models, has increasingly been integrated into diagnosing and treating diabetic retinopathy (DR). From delving into the singular realm of ocular fundus photography to the gradual development of proteomics and other molecular approaches, from machine learning (ML) to deep learning (DL), the journey has seen a transition from a binary diagnosis of "presence or absence" to the capability of discerning the progression and severity of DR based on images from various stages of the disease course. Since the FDA approval of IDx-DR in 2018, a plethora of AI models has mushroomed, gradually gaining recognition through a myriad of clinical trials and validations. AI has greatly improved early DR detection, and we're nearing the use of AI in telemedicine to tackle medical resource shortages and health inequities in various areas. This comprehensive review meticulously analyzes the literature and clinical trials of recent years, highlighting key AI models for DR diagnosis and treatment, including their theoretical bases, features, applicability, and addressing current challenges like bias, transparency, and ethics. It also presents a prospective outlook on the future development in this domain.

High-Frequency 10-kHz Spinal Cord Stimulation Provides Long-term (24-Month) Improvements in Diabetes-Related Pain and Quality of Life for Patients with Painful Diabetic Neuropathy

BACKGROUND

The SENZA-PDN study evaluated high-frequency 10-kHz spinal cord stimulation (SCS) for the treatment of painful diabetic neuropathy (PDN). Over 24 months, 10-kHz SCS provided sustained pain relief and improved health-related quality of life. This report presents additional outcomes from the SENZA-PDN study, focusing on diabetes-related pain and quality of life outcomes.

METHODS

The SENZA-PDN study randomized 216 participants with refractory PDN to receive either conventional medical management (CMM) or 10-kHz SCS plus CMM (10-kHz SCS + CMM), allowing crossover after six months if pain relief was insufficient. Postimplantation assessments at 24 months were completed by 142 participants with a permanent 10-kHz SCS implant, comprising 84 initial and 58 crossover recipients. Measures included the Brief Pain Inventory for Diabetic Peripheral Neuropathy (BPI-DPN), Diabetes-Related Quality of Life (DQOL), Global Assessment of Functioning (GAF), and treatment satisfaction.

RESULTS

Over 24 months, 10-kHz SCS treatment significantly reduced pain severity by 66.9% (P < .001; BPI-DPN) and pain interference with mood and daily activities by 65.8% (P < .001; BPI-DPN). Significant improvements were also observed in overall DQOL score (P < .001) and GAF score (P < .001), and 91.5% of participants reported satisfaction with treatment.

CONCLUSIONS

High-frequency 10-kHz SCS significantly decreased pain severity and provided additional clinically meaningful improvements in DQOL and overall functioning for patients with PDN. The robust and sustained benefits over 24 months, coupled with high participant satisfaction, highlight that 10-kHz SCS is an efficacious and comprehensive therapy for patients with PDN.

Glycemic variability's impact on painful diabetic peripheral neuropathy in type 2 diabetes patients

Hyperglycemia in type 2 diabetes leads to diabetic peripheral neuropathy (DPN) and neuropathic pain, yet the association between glycemic variability and painful DPN remains insufficiently evidenced. To address this, we conducted a prospective longitudinal cohort study involving adult type 2 diabetes patients at a medical center. DPN was identified using the Michigan Neuropathy Screening Instrument (MNSI), and neuropathic pain was assessed with the Taiwan version of the Douleur Neuropathique 4 (DN4-T) questionnaire. At baseline in 2013, all participants were free of DPN and were re-evaluated in 2019 for the development of painful DPN. We measured visit-to-visit glycemic fluctuations using the coefficient of variation (CV) of fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c). Patients were stratified into tertiles according to their FPG-CV and HbA1c-CV. Among the 622 participants, 267 developed DPN during the six-year follow-up. Following matching of age and sex, 210 patients without DPN and 210 with DPN (including 26 with neuropathic pain) were identified. Our findings revealed a significant association between high FPG-CV and painful DPN, with the highest tertile showing an adjusted odds ratio of 2.82 (95% confidence interval 1.04-7.64) compared to the lowest tertile. On the contrary, HbA1c-CV did not show a significant association with the risk of painful DPN. Our study indicates that higher FPG-CV is associated with an increased risk of painful DPN, supporting the role of glycemic variability in the development of painful DPN.

Treatment of Painful Diabetic Neuropathy with 10 kHz Spinal Cord Stimulation: Long-Term Improvements in Hemoglobin A1c, Weight, and Sleep Accompany Pain Relief for People with Type 2 Diabetes

Purpose

The recent SENZA-PDN study showed that high-frequency (10kHz) spinal cord stimulation (SCS) provided significant, durable pain relief for individuals with painful diabetic neuropathy (PDN), along with secondary benefits, including improved sleep quality and HRQoL. Given that metabolic factors and chronic neuropathic pain are related, we evaluated potential secondary effects of 10kHz SCS on hemoglobin A1c (HbA1c) and weight in SENZA-PDN participants with type 2 diabetes (T2D).

Patients and Methods

This analysis included 144 participants with T2D and lower limb pain due to PDN who received 10kHz SCS during the SENZA-PDN study. Changes in HbA1c, weight, pain intensity, and sleep were evaluated over 24 months, with participants stratified according to preimplantation HbA1c (>7% and >8%) and body mass index (BMI; ≥30 and ≥35 kg/m2).

Results

At 24 months, participants with preimplantation HbA1c >7% and >8% achieved clinically meaningful and statistically significant mean reductions in HbA1c of 0.5% (P = 0.031) and 1.1% (P = 0.004), respectively. Additionally, we observed a significant mean weight loss of 3.1 kg (P = 0.003) across all study participants. In subgroups with BMI ≥30 and ≥35 kg/m2, weight reductions at 24 months were 4.1 kg (P = 0.001) and 5.4 kg (P = 0.005), respectively. These reductions were accompanied by a mean pain reduction of 79.8% and a mean decrease in pain interference with sleep of 65.2% at 24 months across all cohorts.

Conclusion

This is the first study of SCS to demonstrate long-term, significant, and clinically meaningful reductions in HbA1c and weight in study participants with PDN and T2D, particularly among those with elevated preimplantation HbA1c and BMI. Although the mechanism for these improvements has yet to be established, the results suggest possible direct and indirect metabolic benefits with 10kHz SCS in addition to durable pain relief.

Trial Registration

ClincalTrials.gov Identifier, NCT03228420.

Continuous glucose monitoring for the routine care of type 2 diabetes mellitus

Although continuous glucose monitoring (CGM) devices are now considered the standard of care for people with type 1 diabetes mellitus, the uptake among people with type 2 diabetes mellitus (T2DM) has been slower and is focused on those receiving intensive insulin therapy. However, increasing evidence now supports the inclusion of CGM in the routine care of people with T2DM who are on basal insulin-only regimens or are managed with other medications. Expanding CGM to these groups could minimize hypoglycaemia while allowing efficient adaptation and escalation of therapies. Increasing evidence from randomized controlled trials and observational studies indicates that CGM is of clinical value in people with T2DM on non-intensive treatment regimens. If further studies confirm this finding, CGM could soon become a part of routine care for T2DM. In this Perspective we explore the potential benefits of widening the application of CGM in T2DM, along with the challenges that must be overcome for the evidence-based benefits of this technology to be delivered for all people with T2DM.

Increased glycemic variability results in abnormal differentiation of T cell subpopulation in type 2 diabetes patients

AIMS

We aimed to investigate the association between glycemic variability (GV) and the abnormal differentiation of T-cell subpopulations in patients with type 2 diabetes mellitus (T2DM).

METHODS

In total, 108 hospitalized patients with T2DM were enrolled and divided into two subgroups (normal glycemic excursion (NGE) and high glycemic excursion (HGE)) according to their mean amplitude of glycemic excursion (MAGE) level. The MAGE was evaluated via continuous glucose monitoring for 72 h consecutively. Flow cytometry was used to determine the proportions of T cell subpopulations.

RESULTS

The T helper (Th) 1 cell/Th2 cell ratio was significantly higher, and the proportion of regulatory T cells (Tregs) was significantly lower in the NGE group than in the HGE group (all P < 0.05). After fully adjusting for confounders, the MAGE was positively associated with the Th1 cell/Th2 cell ratio (β = 0.370; P = 0.009) and negatively associated with the proportion of Tregs (β = -0.554; P = 0.001).

CONCLUSION

The MAGE was an independent risk factor for abnormally high Th1 cell/Th2 cell ratio and proportion of Tregs. Abnormal differentiation of T cell subpopulations induced by GV may impair β-cell function, aggravate insulin resistance, and contribute to the development of diabetic complications.

Day-to-Day Glycemic Variability Using Continuous Glucose Monitors in Endurance Athletes

OBJECTIVES

The application of continuous glucose monitors (CGMs) to measure interstitial glucose in athletic populations is limited by the lack of accepted athlete-specific reference values. The aim of this study was to develop athlete-specific reference ranges for glycemic variability under standardized diet and exercise conditions.

METHODS

A total of 12 elite racewalkers (n = 7 men, 22.4 ± 3.5 years, VO2max 61.6 ± 7.3 mL kg-1 min-1) completed two 4-d trials separated by 4-d. Athletes were provided a high-energy, high-carbohydrate diet (225 ± 1.6 kJ kg-1 day-1, 8.4 ± 0.3 g kg-1 day-1 carbohydrate) and completed standardized daily exercise. The timing of food consumed and exercise undertaken were matched each day across the 4-d trials. Interstitial glucose data were collected via Freestyle Libre 2 CGMs. Glycemic variability was calculated as the mean amplitude of glycemic excursions (MAGEs), mean of daily differences (MODD), and standard deviation (SD).

RESULTS

Twenty-four hour MODD, MAGE, and SD for interstitial glucose were 12.6 ± 1.8 mg/dL (0.7 ± 0.1 mmol/L), 36.0 ± 5.4 mg/dL (2.0 ± 0.3 mmol/L), and 16.2 ± 1.8 mg/dL (0.9 ± 0.1 mmol/L), respectively. Twenty-four hour mean glucose (MG; 102.6 ± 5.4 mg/dL [5.7 ± 0.3 mmol/L]) was higher than overnight (91.8 ± 5.4 mg/dL [5.1 ± 0.3 mmol/L]; P < .0001) and was lower in women than men (99.0 ± 3.6 mg/dL [5.5 ± 0.2 mmol/L] vs 104.4 ± 3.6 mg/dL [5.8 ± 0.2 mmol/L]; P = .059, d = 1.4).

CONCLUSIONS

This study provides reference indices under standardized diet and exercise conditions for glycemic variability derived from CGMs in endurance athletes which are similar than previously reported for healthy individuals, despite strenuous daily training and a high daily energy and carbohydrate diet.

Future of Time-in-Range Goals in the Era of Advanced Hybrid Closed-Loop Automated Insulin Delivery Systems

The concept of maintaining blood glucose levels within the 70-180 mg/dL range, known as time-in-range, has raised questions regarding its representation of true physiological euglycemia. Some have speculated that focusing on the time spent within the 70-140 mg/dL range, introduced as time in tight range (TITR) through the International Consensus statement, could serve as a more precise metric for assessing normoglycemia in individuals with type 1 diabetes. This article delves into the current status of TITR as an emerging marker and explores how advanced hybrid closed-loop systems may offer a promising avenue for achieving this higher level of glycemic control.

Noninvasive Diabetes Detection through Human Breath Using TinyML-Powered E-Nose

Volatile organic compounds (VOCs) in exhaled human breath serve as pivotal biomarkers for disease identification and medical diagnostics. In the context of diabetes mellitus, the noninvasive detection of acetone, a primary biomarker using electronic noses (e-noses), has gained significant attention. However, employing e-noses requires pre-trained algorithms for precise diabetes detection, often requiring a computer with a programming environment to classify newly acquired data. This study focuses on the development of an embedded system integrating Tiny Machine Learning (TinyML) and an e-nose equipped with Metal Oxide Semiconductor (MOS) sensors for real-time diabetes detection. The study encompassed 44 individuals, comprising 22 healthy individuals and 22 diagnosed with various types of diabetes mellitus. Test results highlight the XGBoost Machine Learning algorithm's achievement of 95% detection accuracy. Additionally, the integration of deep learning algorithms, particularly deep neural networks (DNNs) and one-dimensional convolutional neural network (1D-CNN), yielded a detection efficacy of 94.44%. These outcomes underscore the potency of combining e-noses with TinyML in embedded systems, offering a noninvasive approach for diabetes mellitus detection.

Association of HbA1c Variability with Vibrating Perception Threshold in Middle-Aged and Elderly Patients with Type 2 Diabetes Mellitus: A Retrospective Cohort Study

Purpose

To investigate the relationship between HbA1c variability and vibrating perception threshold (VPT) in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM).

Patients and Methods

A total of 367 middle-aged and elderly patients with T2DM were enrolled. All patients were categorized into the control and vibration sensation deficiency group (VSD) based on VPT. Clinical data were collected. The coefficient of variation of glycated hemoglobin A1c (HbA1c-CV) and the mean glycated hemoglobin A1c(HbA1c-Mean) are considered as indexes of HbA1c variability. Multivariate logistic regression analysis, the generalized linear model and ROC curve correlation analysis were used to analyze the correlation of various factors and VPT.

Results

The multivariate logistic regression analysis revealed that age, systolic blood pressure (SBP), and HbA1c-CV were identified as risk factors for vibration sensation deficiency in middle-aged and elderly patients with T2DM, while estimated glomerular filtration rate (eGFR), triiodothyronine (T3), and alanine aminotransferase (ALT) were considered as protective factors. In the unadjusted generalized linear model, a significant association was observed between HbA1c-CV and VPT values. After adjusting for age, diabetic duration, SBP, homeostatic model assessment for beta-cell function (HOMA-β), ALT, eGFR, T3, 24-hour urinary protein excretion levels, and HbA1c-Mean, HbA1c-CV remained significantly correlated with VPT values on both sides. (left side, B=2.560, 95% CI 1.298~3.823; P<0.001; right side, B=2.608, 95% CI 1.498~3.718, P<0.001). The area under the curve (AUC) for HbA1c-CV and VSD prevalence was 0.723, with a sensitivity of 79.85%, specificity of 56.22%.

Conclusion

The risk of developing VSD increases proportionally with higher HbA1c-CV levels in middle-aged and elderly patients with T2DM. Reaching and maintaining blood glucose stability is essential to the mitigation of diabetes peripheral neuropathy occurrence.

Correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus: a retrospective study

Objective

To investigate the correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM).

Methods

This retrospective analysis includes 222 patients hospitalized at Second Affiliated Hospital of Anhui Medical University from June 2021 to June 2023. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). All patients were categorized into the MCI group and the non-MCI group based on their MoCA score. Long-term blood glucose fluctuations were measured using glycated hemoglobin A1c standard deviation (HbA1c-SD) and fasting plasma glucose standard deviation (FPG-SD). The study compared general clinical data, blood biochemical indicators, and glycemic variability indicators between the two groups. The differences between the groups were compared using t-test, Chi-Square Test, or Mann-Whitney U test. Kendall's correlation analysis, multivariate logistic regression analysis and ROC curve correlation analysis were further used to analyze the correlation and diagnostic power.

Results

The differences in age, MoCA scores, MMSE scores, HOMA-β, HbA1c-M, HbA1c-SD, FPG-M, FPG-SD, eGFR, Smoking, GLP-1RA and SGLT-2i usage were statistically significant between the two groups (P < 0.05). Kendall's correlation analysis showed that age, HbA1c-M, HbA1c-SD, FPG-M, and FPG-SD was negatively correlated with MoCA scores; meanwhile, the HOMA-β, and eGFR was positively correlated with MoCA scores. Multiple logistic regression analysis revealed that HbA1c-SD, FPG-SD and Smoking were risk factors for cognitive dysfunction, while eGFR, GLP-1RA and SGLT-2i usage was a protective effect. The area under the curve (AUC) values for predicting MCI prevalence were 0.830 (95% CI [0.774-0.877], P < 0.001) for HbA1c-SD, 0.791 (95% CI [0.655-0.808], P < 0.001) for FPG-SD, and 0.698 (95% CI [0.633-0.757], P < 0.001) for eGFR. The optimal diagnostic values were 0.91, 1.32, and 74.81 ml/min/1.73 m2 for HbA1c-SD, FPG-SD, and eGFR, respectively.

Conclusions

Cognitive function in middle-aged and elderly T2DM patients is influenced by long-term blood glucose variability, with poorer cognitive function observed in individuals with higher blood glucose variability. The impact of HbA1c-SD on MCI exhibited a greater magnitude compared to that of PFG-SD and smoking. Additionally, renal function, GLP-1RA and SGLT-2i usage exert positive effects on cognitive function.

Relationship Between Time in Range and Dusk Phenomenon in Outpatients with Type 2 Diabetes Mellitus

Purpose

The dusk phenomenon refers to a spontaneous and transient pre-dinner hyperglycemia that affects glucose fluctuation and glycemic control, and the increasing use of continuous glucose monitoring (CGM) has facilitated its diagnosis. We investigated the frequency of the dusk phenomenon and its relationship with the time in range (TIR) in patients with type 2 diabetes mellitus (T2DM).

Patients and Methods

This study involved 102 patients with T2DM who underwent CGM for 14 days. CGM-derived metrics and clinical characteristics were evaluated. A consecutive dusk blood glucose difference (pre-dinner glucose minus 2-hour post-lunch glucose) of ≥ 0 or once-only dusk blood glucose difference of < 0 was diagnosed as the clinical dusk phenomenon (CLDP).

Results

We found that the percentage of CLDP was 11.76% (10.34% in men, 13.64% in women). Compared with the non-CLDP group, the CLDP group tended to be younger and have a lower percentage of TIR (%TIR^3.9-10) and higher percentage of time above range (%TAR^>10 and %TAR^>13.9) (P ≤ 0.05). Adjusted for confounding factors, the binary logistic regression analysis showed a negative association of CLDP with %TIR (odds ratio < 1, P < 0.05). We repeated the correlation analysis based on 70%TIR and found significant differences in hemoglobin A1c, fasting blood glucose, mean blood glucose, standard deviation of the sensor glucose values, glucose coefficient of variation, largest amplitude of glycemic excursions, mean amplitude of glycemic excursions, glucose management indicator, and percentage of CLDP between the two subgroups of TIR ≤ 70% and TIR > 70% (P < 0.05). The negative association between TIR and CLDP still remained after adjustment by the binary logistic regression analysis.

Conclusion

The CLDP was frequently present in patients with T2DM. The TIR was significantly correlated with the CLDP and could serve as an independent negative predictor.

Association between low-carbohydrate diets and continuous glucose monitoring-derived time in ranges

AIMS

Low-carbohydrate diets have become popular in the general community. The mutual relationship between the percentage of total energy intake from carbohydrates (CHO/E), glycemic control indices, and diabetes complications remains unclear.

MATERIALS AND METHODS

This cross-sectional study included 177 patients with type 2 diabetes mellitus who regularly visited outpatient clinics. In this study, dietary questionnaires were used to assess the intake ratio of the three macronutrients, and the low-carbohydrate-diet score was calculated. We investigated the association between the low-carbohydrate-diet score, continuous glucose monitoring (CGM)-derived short-term glycemic control indices, and diabetes complications in patients with type 2 diabetes mellitus.

RESULTS

The results are presented as medians (interquartile ranges) unless otherwise stated. Hemoglobin A1c was 7.1% (6.6-7.7%), CGM-derived time in range (TIR) was 75.3% (62.8-87.0%), body mass index (BMI) was 24.0 (22.1-26.3) kg/m2, and CHO/E was 49.8% (44.8-55.6%). BMI, triglycerides, and CGM-derived time above range decreased significantly with increasing low-carbohydrate-diet scores. However, no significant association was found between the low-carbohydrate-diet score and glycemic control indices, including TIR, mean amplitude of glycemic excursions, and vascular complications of type 2 diabetes mellitus.

CONCLUSION

Moderate-carbohydrate diets positively impact weight control and lipid metabolism but may have a limited effect on short-term glycemic variability in Japanese patients with type 2 diabetes mellitus.

Novel clinical relationships between time in range and microangiopathies in people with type 2 diabetes mellitus on hemodialysis

AIMS/HYPOTHESIS

We investigated associations among glucose time in range (TIR, 70-180 mg/dL), glycemic markers and prevalence of diabetic microangiopathy in people with diabetes undergoing hemodialysis (HD).

METHODS

A total of 107 people with type 2 diabetes undergoing HD (HbA_1c 6.4 %; glycated albumin [GA] 20.6 %) using continuous glucose monitoring were analyzed in this observational and cross-sectional study.

RESULTS

HbA_1c and GA levels significantly negatively correlated with TIR, and positively correlated with time rate of hyperglycemia, but not with time rate of hypoglycemia. TIR of 70 % corresponded to HbA_1c of 6.5 % and GA of 21.2 %. The estimated HbA_1c level corresponding to TIR of 70 % in this study was lower than that previously reported in people with diabetes without HD. The prevalence of diabetic neuropathy was not significantly different between people with TIR ≥ 70 % and those with TIR < 70 % (P = 0.1925), but the prevalence of diabetic retinopathy in people with TIR ≥ 70 % was significantly lower than in those with TIR < 70 % (P = 0.0071).

CONCLUSION/INTERPRETATION

TIR correlated with HbA_1c and GA levels in people with type 2 diabetes on HD. Additionally, a higher TIR resulted in a lower rate of diabetic retinopathy.

RESEARCH IN CONTEXT

What is already known about this subject? What is the key question? What are the new findings? How might this impact on clinical practice in the foreseeable future?

Association between short-term exposure to extreme humidity and painful diabetic neuropathy: a case-crossover analysis

Painful diabetic neuropathy (PDN) is a common complication of diabetes mellitus, which reduces the quality of life. However, the association between PDN and environmental factors, especially ambient humidity, remains unclear. Therefore, this study investigated the impact of extreme humidity events on PDN. Data on PDN-related hospital admissions to two tertiary hospitals in Hefei, China (2014-2019) were obtained. A distributed lag non-linear model with a case-crossover design was used to quantitatively estimate the effects of ambient humidity on PDN, and the results were stratified by sex and age. The 1st, 10th, 90th, and 99th percentiles of relative humidity (RHU) were defined as extreme humidity, and the average relative humidity (74.94%) was set as the reference value. Non-linear exposure-response curves between the RHU and PDN cases were obtained. Extreme humidity (92%) had a significant effect on PDN with a relative risk (RR) of 1.13 (95% confidence interval (CI): 1.01-1.26) on a particular day, which increased with the RHU (RR: 1.21, 95% CI: 1.02-1.45 at 98% extreme humidity). Stratification analysis showed that women (RR: 1.38, 95% CI: 1.07-1.77) and patients aged < 65 years (RR: 1.26, 95% CI: 1.01-1.57) were highly susceptible to this effect on the same day. The results suggest that extreme humidity is a crucial trigger for PDN onset in diabetes patients. Furthermore, the effects vary with sex and age. This study provides detailed evidence of the adverse effects of extreme weather on diabetes patients.

Continuous glucose monitoring and metrics for clinical trials: an international consensus statement

Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.

The association between time in the glucose target range and abnormal ankle-brachial index: a cross-sectional analysis

BACKGROUND

Time in range (TIR), a novel proxy measure of glucose control, is found closely related to diabetic microangiopathy and some other chronic complications, but the correlation between TIR and lower limb angiopathy has not been studied yet. Our purpose is to explore the relationship between TIR and abnormal ankle-brachial index(ABI) in type 2 diabetes.

METHODS

We retrospectively collected patients' information from the database and performed cross-sectional analysis. A total of 405 type 2 diabetes patients were enrolled in this study. ABI was measured and patients were stratified into low, normal, and high groups according to ≤ 0.9, > 0.9 and < 1.3, ≥ 1.3 ABI values. All patients underwent continuous glucose monitoring(CGM), and TIR was defined as the percentage of time in which glucose was in the range of 3.9-10 mmol/L during a 24-h period. Correlations between TIR and abnormal ABI were analyzed using Spearman analysis. And logistic regression was used to explore whether TIR is an independent risk factor for abnormal ABI.

RESULTS

The overall prevalence of abnormal ABI was 20.2% (low 4.9% and high 15.3%). TIR was lower in patients with abnormal ABI values (P = 0.009). The prevalence of abnormal ABI decreased with increasing quartiles of TIR (P = 0.026). Abnormal ABI was negatively correlated with TIR and positively correlated with hypertension, age, diabetes duration, UREA, Scr, ACR, TAR, MBG, and M values (P < 0.05). The logistic regression revealed a significant association between TIR and abnormal ABI, while HbA1C and blood glucose variability measures had no explicit correlation with abnormal ABI. Additionally, there was a significant difference in LDL between the low and high ABI groups (P = 0.009), and in Scr between normal and low groups (P = 0.007). And there were significant differences in TIR (P = 0.003), age (P = 0.023), UREA (P = 0.006), ACR (P = 0.004), TAR (P = 0.015), and MBG (P = 0.014) between normal and high ABI groups, and in diabetes duration between both normal and low (P = 0.023) and normal and high (P = 0.006) groups.

CONCLUSIONS

In type 2 diabetes patients, abnormal ABI is associated with lower TIR, and the correlation is stronger than that with HbA1C. Therefore, the role of TIR should be emphasized in the evaluation of lower limb vascular diseases.

The Emerging Role of Continuous Glucose Monitoring in the Management of Diabetic Peripheral Neuropathy: A Narrative Review

The aim of this narrative review is to present data on the role of continuous glucose monitoring (CGM) in the management of peripheral diabetic neuropathy (DPN) among individuals with type 1 and type 2 diabetes mellitus. Adequate glycaemic control is crucial to prevent the development or progression of DPN. CGM systems are valuable tools for improving glycaemic control and reducing glycaemic variability (GV). Chronic hyperglycaemia is known to be a risk factor for the development of diabetic microvascular complications, including DPN. In addition, there is now evidence that GV, evaluated by mean amplitude of glycaemic excursions, may be a novel factor in the pathogenesis of diabetic complications. Increased GV appears to be an independent risk factor for DPN and correlates with painful neuropathy. Similarly, time-in-range correlates positively with peripheral nerve function and negatively with sudomotor dysfunction. However, relevant studies are rather limited in scope, and the vast majority are cross-sectional and use different methodologies for the assessment of DPN. Therefore, the causal relationship between CGM-derived data and the development of DPN cannot be firmly established at the present time. It also remains to be elucidated whether CGM measures can be considered the new therapeutic targets for DPN management.

A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology

Wider access to continuous glucose monitoring systems, including flash glucose monitoring, has enabled people with diabetes to achieve lower HbA1c levels and reduce the amount of time they spend in hypoglycaemia or hyperglycaemia, and has improved their quality of life. An International Consensus Panel proposed different target glucose ranges and recommendations according to different ages and situations (adults, young people and children with type 1 or type 2 diabetes, as well as elderly people who are at higher risk of hypoglycaemia, and women with diabetes during pregnancy). In this expert opinion, we interpret the international recommendations in the context of established clinical practice for diabetes care, and propose three different step-by-step algorithms to help the healthcare professionals use the most innovative glucose metrics, including time in glucose ranges, glucose management indicator, coefficient of variation, and ambulatory glucose profile. In detail, we focus on glucose metrics as measured by the FreeStyle Libre system and as visualized on the LibreView digital diabetes platform to support appropriate interpretation of flash glucose monitoring data. This is specifically structured for healthcare professionals and general practitioners who may have a low level of confidence with diabetes technology, with the aim of optimizing diabetes management, ensuring effective use of healthcare resources and to maximise outcomes for people with diabetes.

Significance of Glycemic Variability in Diabetes Mellitus

The goal of diabetes treatment is to maintain good glycemic control, prevent the development and progression of diabetic complications, and ensure the same quality of life and life expectancy as healthy people. Hemoglobin A1c (HbA1c) is used as an index of glycemic control, but strict glycemic control using HbA1c as an index may lead to severe hypoglycemia and cardiovascular death. Glycemic variability (GV), such as excessive hyperglycemia and hypoglycemia, is associated with diabetic vascular complications and has been recognized as an important index of glycemic control. Here, we reviewed the definition and evaluated the clinical usefulness of GV, and its relationship with diabetic complications and therapeutic strategies to reduce GV.

Effects of Teneligliptin on HbA1c levels, Continuous Glucose Monitoring-Derived Time in Range and Glycemic Variability in Elderly Patients with T2DM (TEDDY Study)

BACKGROUND

To evaluate the effects of teneligliptin on glycosylated hemoglobin (HbA1c) levels, continuous glucose monitoring (CGM)-derived time in range, and glycemic variability in elderly type 2 diabetes mellitus patients.

METHODS

This randomized, double-blinded, placebo-controlled study was conducted in eight centers in Korea (clinical trial registration number: NCT03508323). Sixty-five participants aged ≥65 years, who were treatment-naïve or had been treated with stable doses of metformin, were randomized at a 1:1 ratio to receive 20 mg of teneligliptin (n=35) or placebo (n=30) for 12 weeks. The main endpoints were the changes in HbA1c levels from baseline to week 12, CGM metrics-derived time in range, and glycemic variability.

RESULTS

After 12 weeks, a significant reduction (by 0.84%) in HbA1c levels was observed in the teneligliptin group compared to that in the placebo group (by 0.08%), with a between-group least squares mean difference of -0.76% (95% confidence interval [CI], -1.08 to -0.44). The coefficient of variation, standard deviation, and mean amplitude of glycemic excursion significantly decreased in participants treated with teneligliptin as compared to those in the placebo group. Teneligliptin treatment significantly decreased the time spent above 180 or 250 mg/dL, respectively, without increasing the time spent below 70 mg/dL. The mean percentage of time for which glucose levels remained in the 70 to 180 mg/dL time in range (TIR70-180) at week 12 was 82.0%±16.0% in the teneligliptin group, and placebo-adjusted change in TIR70-180 from baseline was 13.3% (95% CI, 6.0 to 20.6).

CONCLUSION

Teneligliptin effectively reduced HbA1c levels, time spent above the target range, and glycemic variability, without increasing hypoglycemia in our study population.

Utilizing the New Glucometrics: A Practical Guide to Ambulatory Glucose Profile Interpretation

Traditional continuous glucose monitoring and flash glucose monitoring systems are proven to lower glycated haemoglobin levels, decrease the time and impact of hypoglycaemia or hyperglycaemia and, consequently, improve the quality of life for children and adults with type 1 diabetes mellitus (T1DM) and adults with type 2 diabetes mellitus (T2DM). These glucose-sensing devices can generate large amounts of glucose data that can be used to define a detailed glycaemic profile for each user, which can be compared with targets for glucose control set by an International Consensus Panel of diabetes experts. Targets have been agreed upon for adults, children and adolescents with T1DM and adults with T2DM; separate targets have been agreed upon for older adults with diabetes, who are at higher risk of hypoglycaemia, and women with pregestational T1DM during pregnancy. Along with the objective measures and targets identified by the International Consensus Panel, the dense glucose data delivered by traditional continuous glucose monitoring and flash glucose monitoring systems is used to generate an ambulatory glucose profile, which summarizes the data in a visually impactful format that can be used to identify patterns and trends in daily glucose control, including those that raise clinical concerns. In this article, we provide a practical guide on how to interpret these new glucometrics using a straightforward algorithm, and clear visual examples that demystify the process of reviewing the glycaemic health of people with T1DM or T2DM such that forward-looking goals for diabetes management can be agreed.

Relationship between blood glucose variability in ambulatory glucose profile and standardized continuous glucose monitoring metrics: Subanalysis of a prospective cohort study

AIM

To clarify the relationship between ambulatory glucose profile (AGP) indexes and standardized continuous glucose monitoring (CGM) metrics in patients with type 2 diabetes (T2D).

METHODS

This is an exploratory, cross-sectional analysis of baseline data collected from a prospective, multicentre, 5-year follow-up observational study conducted and published previously by our group. The study participants were 999 outpatients with T2D who used CGM at baseline, and had no apparent history of cardiovascular disease. We investigated the relationship between average interquartile range (IQR) and time in range (TIR). We also calculated, for the first time, the cutoff values to achieve the TIR target values.

RESULTS

In both the TIR more than 70% and TIR more than 90% achievement groups, the average IQR was notably small compared with the non-achievement groups. Particularly in comparison of the TIR quartiles, the average IQR became significantly smaller as the TIR became larger. The average IQR correlated negatively with TIR, and the cutoff values for TIR of more than 70% achievement and TIR of more than 90% achievement were an average IQR (>70%/>90%) of 2.13/1.85 mmol/L.

CONCLUSION

Our results showed a negative correlation between TIR and the range of blood glucose variations visually represented in AGP. The results also showed that the range of blood glucose variations in AGP is associated with indices of intraday and interday blood glucose variations and also with hypoglycaemia. Our results may provide new perspectives in the assessment and application of AGP in the clinical setting.

Time in range, as measured by continuous glucose monitor, as a predictor of microvascular complications in type 2 diabetes: a systematic review

Continuous glucose monitoring (CGM)-derived time in range (TIR) correlates with hemoglobin A1c (A1c) among patients with type 2 diabetes mellitus (T2DM); however, there is a paucity of data evaluating its association with microvascular complications. We conducted this systematic review to examine the association between TIR and microvascular complications of diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic peripheral neuropathy (DPN). We conducted a comprehensive literature search on PubMed, Scopus, and Web of Science online databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Full-text original articles that evaluated the association between CGM-derived TIR and risk of microvascular complications and were published between 2010 and June 2021 were included in our systematic review. The quality of the included studies was evaluated using the National Heart, Lung, and Blood Institute Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Data were analyzed using qualitative synthesis. Eleven studies on a total of 13 987 patients were included in the systematic review. The median sample size, baseline A1c, and diabetes duration were 466 patients (range: 105-5901), 8.2% (SD 0.5%), and 11.3 years (1.0), respectively. Majority of the studies were conducted in Asia (10 out of 11). Four studies evaluated the relationship between CGM-derived TIR and DR and CGM-derived TIR and DN, while seven studies evaluated the relationship between CGM-derived TIR and DPN. A 10% increase in TIR was associated with a reduction in albuminuria, severity of DR, and prevalence of DPN and cardiac autonomic neuropathy. In addition, an association was observed between urinary albumin to creatinine ratio but not with estimated glomerular filtration rate. This review summarizes recent evidence supporting an association between CGM-derived TIR and microvascular complications among patients with T2DM. A larger-scale multicenter investigation that includes more diverse participants is warranted to further validate the utility of TIR as a predictor of diabetic microvascular complications.

Perspectives of glycemic variability in diabetic neuropathy: a comprehensive review

Diabetic neuropathy is one of the most prevalent chronic complications of diabetes, and up to half of diabetic patients will develop diabetic neuropathy during their disease course. Notably, emerging evidence suggests that glycemic variability is associated with the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for diabetic neuropathy. In this review, we describe the commonly used metrics for evaluating glycemic variability in clinical practice and summarize the role and related mechanisms of glycemic variability in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. In addition, we also address the potential pharmacological and non-pharmacological treatment methods for diabetic neuropathy, aiming to provide ideas for the treatment of diabetic neuropathy.

Zhang et al. describe metrics for evaluating glycaemic variability (GV) in clinical practice and summarize the role and related mechanisms of GV in diabetic neuropathy, including cardiovascular autonomic neuropathy, diabetic peripheral neuropathy and cognitive impairment. They aim to stimulate ideas for the treatment of diabetic neuropathy.

Time in range, especially overnight time in range, is associated with sudomotor dysfunction in patients with type 1 diabetes

BACKGROUND

Time in range (TIR) is advocated as key metric of glycemic control and is reported to be associated with microvascular complications of diabetes. Sudomotor dysfunction is among the earliest detectable diabetic peripheral neuropathy (DPN). We set about to research the relationship between TIR including overnight TIR and sudomotor function detected by SUDOSCAN with the intention of exploring the correlation of TIR including overnight TIR and early DPN in type 1 diabetes (T1D).

METHODS

95 patients with T1D were enrolled. TIR including nocturnal TIR of 3.9-10.0 mmol/L was evaluated with CGM. SUDOSCAN measured feet electrochemical skin conductance (FESC) and sudomotor dysfunction was defined as average FESC < 60µS. Logistic regressions were applied to examine the independent association of TIR and overnight TIR with sudomotor function.

RESULTS

The overall prevalence of sudomotor dysfunction was 28.42%. Patients with sudomotor dysfunction had significantly lower TIR for the whole recorded phase and for nighttime. The sudomotor dysfunction prevalence progressively declined with the ascending tertiles of TIR and nocturnal TIR (P for trend < 0.05). Correlation analysis showed that the relationship between nocturnal TIR and FESC was stronger than that between TIR and FESC with correlation coefficients were respectively 0.362 and 0.356 (P < 0.001). Finally, logistic regression analysis indicated the independently negative relation between TIR and nocturnal TIR and sudomotor dysfunction (P < 0.05), and the correlation between nocturnal TIR and sudomotor dysfunction was more statistically significant.

CONCLUSIONS

TIR is negatively correlated with sudomotor dysfunction in T1D independent of HbA1c. Furthermore, decreased nocturnal TIR is more closely related to the impaired function of sudomotor nerves in sweat glands.

Association of sleep quality with glycemic variability assessed by flash glucose monitoring in patients with type 2 diabetes

BACKGROUND

Deterioration of sleep quality has been reported to contribute to the incidence of diabetes and may be responsible for glycemic status in diabetes. The present study explored the relationship between sleep quality and glycemic variability in patients with type 2 diabetes (T2D).

METHODS

We recruited 111 patients with T2D for this cross-sectional study. Each patient underwent flash glucose monitoring for 14 days to obtain glycemic variability parameters, such as standard deviation of glucose (SD), coefficient of variation of glucose (CV), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), and time in glucose range of 3.9-10 mmol/L (TIR_3.9-10). After 14 days of flash glucose monitoring, each patient received a questionnaire on the Pittsburgh Sleep Quality Index (PSQI) to evaluate subjective sleep quality. HbA1c was also collected to assess average glucose.

RESULTS

HbA1c was comparable among the subgroups of PSQI score tertiles. Across ascending tertiles of PSQI scores, SD, CV and MAGE were increased, while TIR_3.9-10 was decreased (p for trend  <  0.05), but not MODD (p for trend  =  0.090). Moreover, PSQI scores were positively correlated with SD, CV, MODD and MAGE (r =  0.322, 0.361, 0.308 and 0.354, respectively, p  <  0.001) and were inversely correlated with TIR_3.9-10 (r  =  - 0.386, p  <  0.001). After adjusting for other relevant data by multivariate linear regression analyses, PSQI scores were independently responsible for SD (β  =  0.251, t  =  2.112, p  =  0.041), CV (β  =  0.286, t  =  2.207, p  =  0.033), MAGE (β  =  0.323, t  =  2.489, p  =  0.018), and TIR_3.9-10 (β  =  - 0.401, t  =  - 3.930, p  <  0.001) but not for MODD (β  =  0.188, t  =  1.374, p  =  0.177).

CONCLUSIONS

Increased glycemic variability assessed by flash glucose monitoring was closely associated with poor subjective sleep quality evaluated by the PSQI in patients with T2D.

Association of serum CTRP9 levels with cardiac autonomic neuropathy in patients with type 2 diabetes mellitus

AIMS

Cardiac autonomic neuropathy (CAN) is a serious complication of diabetes and is associated with adipokines. The C1q tumor necrosis factor-related protein 9 (CTRP9) is a newly discovered adipokine. This study aimed to evaluate the association of serum CTRP9 levels with the prevalence and severity of CAN in patients with type 2 diabetes mellitus.

MATERIALS AND METHODS

We enrolled 262 patients (aged ≥18 years) with type 2 diabetes mellitus into this study. Standard cardiovascular autonomic reflex tests (CARTs) were used to assess CAN and patients were divided into three groups accordingly: a non-CAN group, an early CAN group, and a definite CAN group. Serum CTRP9 levels were measured by enzyme-linked immunosorbent assay, and the tertiles were calculated.

RESULTS

Serum CTRP9 levels decreased significantly in the early CAN and definite CAN groups (P < 0.05). The percentage of definite CAN was the highest at the minimum tertile of serum CTRP9 level (T1; P < 0.05). Additionally, serum CTRP9 levels were negatively correlated with age, DM duration, hemoglobin A1c (HbA1c), and fasting plasma glucose (FPG) while positively correlated with high-density lipoprotein cholesterol (HDL; P < 0.05). The level of CTRP9 was also significantly associated with the four indexes of CARTs (P < 0.05). Furthermore, CTRP9 was a protective factor for definite CAN (P < 0.05). Compared with the maximum tertile (T3) of the serum CTRP9 levels, a decreased level of serum CTRP9 in T1 significantly increased the prevalence ratio of definite CAN in patients with type 2 diabetes mellitus (P < 0.05).

CONCLUSION

Serum CTRP9 levels were independently associated with definite CAN. CTRP9 represents a reliable biomarker for exploring CAN in patients with type 2 diabetes mellitus.

Comprehensive elaboration of glycemic variability in diabetic macrovascular and microvascular complications

Diabetes mellitus is the major risk factor for the development of macrovascular and microvascular complications. It is increasingly recognized that glycemic variability (GV), referring to oscillations in blood glucose levels and representing either short-term or long-term GV, is involved in the pathogenesis of diabetic complications and has emerged as a possible independent risk factor for them. In this review, we summarize the metrics and measurement of GV in clinical practice, as well as comprehensively elaborate the role and related mechanisms of GV in diabetic macrovascular and microvascular complications, aiming to provide the mechanism-based therapeutic strategies for clinicians to manage diabetes mellitus.

Time in Range from Continuous Glucose Monitoring: A Novel Metric for Glycemic Control

Glycosylated hemoglobin (HbA1c) has been the sole surrogate marker for assessing diabetic complications. However, consistently reported limitations of HbA1c are that it lacks detailed information on short-term glycemic control and can be easily interfered with by various clinical conditions such as anemia, pregnancy, or liver disease. Thus, HbA1c alone may not represent the real glycemic status of a patient. The advancement of continuous glucose monitoring (CGM) has enabled both patients and healthcare providers to monitor glucose trends for a whole single day, which is not possible with HbA1c. This has allowed for the development of core metrics such as time spent in time in range (TIR), hyperglycemia, or hypoglycemia, and glycemic variability. Among the 10 core metrics, TIR is reported to represent overall glycemic control better than HbA1c alone. Moreover, various evidence supports TIR as a predictive marker of diabetes complications as well as HbA1c, as the inverse relationship between HbA1c and TIR reveals. However, there are more complex relationships between HbA1c, TIR, and other CGM metrics. This article provides information about 10 core metrics with particular focus on TIR and the relationships between the CGM metrics for comprehensive understanding of glycemic status using CGM.