TIR generated by continuous glucose monitoring is associated with peripheral nerve function in type 2 diabetes

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.

Higher Derived Time in Range With IDegLira Versus Insulin Glargine U100 in People With Type 2 Diabetes

BACKGROUND

Derived time in range (dTIR), calculated from self-monitored blood glucose (SMBG-dTIR) profiles, has demonstrated correlation with risk of cardiovascular and microvascular complications. This post hoc analysis of the DUAL V and DUAL VIII trials aimed to compare dTIR with an insulin degludec/liraglutide fixed-ratio combination (IDegLira) versus insulin glargine 100 units/mL (glargine U100) in people with type 2 diabetes (T2D).

MATERIALS AND METHODS

Nine-point SMBG profiles were taken more than 24 hours at baseline and end of trial (EOT: 26 weeks [DUAL V] and 104 weeks [DUAL VIII]) and used to derive the percentage of readings within target range (70-180 mg/dL). Estimated treatment differences (ETDs, IDegLira-glargine U100) were analyzed using analysis of covariance, with treatment as fixed effects and baseline response as a covariate.

RESULTS

ETDs for change from baseline to EOT in dTIR were significantly greater with IDegLira versus glargine U100 in DUAL V (4.18%, P = .027) and DUAL VIII (5.17%, P = .001). The proportions of people achieving ≥70% dTIR at EOT with IDegLira and glargine U100, respectively, were 62% and 60% in DUAL V (P = .7541), and 50% and 26% in DUAL VIII (P < .0001). The proportion achieving a ≥5% increase in dTIR from baseline to EOT with IDegLira and glargine U100 was 63% in both groups in DUAL V (P = .9043), and 44% and 25%, respectively, in DUAL VIII (P < .0001).

CONCLUSIONS

IDegLira was associated with significantly greater increases in dTIR versus basal insulin alone in people with T2D.

TRIAL ID(S)

ClinicalTrials.gov, NCT01952145 (DUAL V); ClinicalTrials.gov, NCT02501161 (DUAL VIII).

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

AIMS/INTRODUCTION

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.

MATERIALS AND METHODS

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.

RESULTS

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%.

CONCLUSIONS

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.

Diabetic Sensorimotor Polyneuropathy: An Overview on Epidemiology, Risk Factors, Classification, Diagnosis, and Treatment

Diabetic distal symmetric sensorimotor polyneuropathy (DSPN) is a common complication of diabetes with devastating consequences. Hyperglycaemia is the major aetiological factor, while emerging data demonstrate that cardiometabolic risk factors also contribute to its development. Diagnosis of DSPN involves interview of medical and neurological history, foot inspection, and sensory and motor function examination with specific tests such as temperature and pinprick perception for small nerve fibers, and vibration and light touch assessments for large nerve fibers. Management includes optimised glycaemic control, treatment of cardiovascular risk factors, and symptomatic treatment aiming at improving life quality. This article provides an overview on epidemiology, risk factors, classification, diagnosis and current treatment of DSPN.

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.

Increased Derived Time in Range Is Associated with Reduced Risk of Major Adverse Cardiovascular Events, Severe Hypoglycemia, and Microvascular Events in Type 2 Diabetes: A Post Hoc Analysis of DEVOTE

Time spent in glycemic target range (time in range [TIR]; plasma glucose 70-180 mg/dL [3.9-10.0 mmol/L]) as a surrogate endpoint for long-term diabetes-related outcomes requires validation. This post hoc analysis investigated the association between TIR, derived from 8-point glucose profiles (derived TIR [dTIR]) at 12 months, and time to cardiovascular or severe hypoglycemic episodes in people with type 2 diabetes in the DEVOTE trial. At 12 months, dTIR was significantly negatively associated with time to first major adverse cardiovascular event (P = 0.0087), severe hypoglycemic episode (P < 0.0001), or microvascular event (P = 0.024). A nonsignificant trend was seen toward association between 12-month hemoglobin A1c (HbA1c) and these outcomes, but this was no longer seen after addition of dTIR to the model. The results support targeting TIR >70% and suggest dTIR could be used in addition to, or in some instances in place of, HbA1c as a clinical biomarker. Trial registration details: ClinicalTrials.gov, NCT01959529.

Relationship between key continuous glucose monitoring-derived metrics and specific cognitive domains in patients with type 2 diabetes mellitus

BACKGROUND

Continuous glucose monitoring (CGM)-derived time in range (TIR) is closely associated with micro- and macrovascular complications in type 2 diabetes mellitus (T2DM). This study was performed to investigate the relationship between key CGM-derived metrics and specific cognitive domains in patients with T2DM.

METHODS

Outpatients with T2DM who were otherwise healthy were recruited for this study. A battery of neuropsychological tests was performed to evaluate cognitive function, including memory, executive functioning, visuospatial ability, attention, and language. Participants wore a blinded flash continuous glucose monitoring (FGM) system for 72 h. The key FGM-derived metrics were calculated, including TIR, time below range (TBR), time above range (TAR), glucose coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE). Furthermore, the glycemia risk index (GRI) was also calculated by the GRI formula. Binary logistic regression was used to assess risk factors for TBR, and we further analysed the associations between neuropsychological test results and key FGM-derived metrics with multiple linear regressions.

RESULTS

A total of 96 outpatients with T2DM were recruited for this study, with 45.8% experiencing hypoglycemia (TBR^{< 3.9 mmol/L}). Spearman analysis results revealed that a higher TBR^{< 3.9 mmol/L} was correlated with worse performance on the Trail Making Test A (TMTA), Clock Drawing Test (CDT), and cued recall scores (P < 0.05). Logistic regression analysis results indicated that the TMTA (OR = 1.010, P = 0.036) and CDT (OR = 0.429, P = 0.016) scores were significant factors influencing the occurrence of TBR^{< 3.9 mmol/L}. Multiple linear regressions further demonstrated that TBR^{< 3.9 mmol/L} (β = -0.214, P = 0.033), TAR^{> 13.9 mmol/L} (β = -0.216, P = 0.030) and TAR^{10.1-13.9 mmol/L} (β = 0.206, P = 0.042) were significantly correlated with cued recall scores after adjusting for confounding factors. However, TIR, GRI, CV and MAGE showed no significant correlation with the results of neuropsychological tests (P > 0.05).

CONCLUSIONS

A higher TBR^{< 3.9 mmol/L} and TAR^{> 13.9 mmol/L} were associated with worse cognitive functions (memory, visuospatial ability, and executive functioning). Conversely, a higher TAR of 10.1-13.9 mmol/L was associated with better memory performance in memory tasks.

Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations

Type 1 diabetes (T1D) management has been revolutionized with the development and routine utilization of continuous glucose monitoring (CGM). CGM technology has allowed for the ability to track dynamic glycemic fluctuations and trends over time allowing for optimization of medical therapy and the prevention of dangerous hypoglycemic events. This review details currently-available real-time and intermittently-scanned CGM devices, clinical benefits, and challenges of CGM use, and current guidelines supporting its use in the clinical care of patients with T1D. We additionally describe future issues that will need to be addressed as CGM technology continues to evolve.

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.

Clinical application guidelines for blood glucose monitoring in China (2022 edition)

Glucose monitoring is an important component of diabetes management. The Chinese Diabetes Society (CDS) has been producing evidence-based guidelines on the optimal use of glucose monitoring since 2011. In recent years, new technologies in glucose monitoring and more clinical evidence, especially those derived from Chinese populations, have emerged. In this context, the CDS organised experts to revise the Clinical application guidelines for blood glucose monitoring in China in 2021. In this guideline, we focus on four methods of glucose monitoring that are commonly used in clinical practice, including capillary glucose monitoring, glycated haemoglobin A1c, glycated albumin, and continuous glucose monitoring. We describe the definitions and technical characteristics of these methods, the factor that may interfere with the measurement, the advantages and caveats in clinical practice, the interpretation of glucose metrics, and the relevant supporting evidence. The recommendations for the use of these methods are also provided. The various methods of glucose monitoring have their strengths and limitations and cannot be replaced by one another. We hope that these guidelines could aid in the optimal application of common methods of glucose monitoring in clinical practice for better diabetes care.

Complications of Diabetes and Metrics of Glycemic Management Derived From Continuous Glucose Monitoring

CONTEXT

Although glycated hemoglobin A1c is currently the best parameter used clinically to assess risk for the development of diabetes complications, it does not provide insight into short-term fluctuations in glucose levels. This review summarizes the relationship between continuous glucose monitoring (CGM)-derived metrics of glycemic variability and diabetes-related complications.

EVIDENCE ACQUISITION

PubMed and Embase databases were searched from January 1, 2010 to August 22, 2020, using the terms type 1 diabetes, type 2 diabetes, diabetes-related microvascular and macrovascular complications, and measures of glycaemic variability. Exclusion criteria were studies that did not use CGM and studies involving participants who were not diabetic, acutely unwell (post stroke, post surgery), pregnant, or using insulin pumps.

EVIDENCE SYNTHESIS

A total of 1636 records were identified, and 1602 were excluded, leaving 34 publications in the final review. Of the 20 852 total participants, 663 had type 1 diabetes (T1D) and 19 909 had type 2 diabetes (T2D). Glycemic variability and low time in range (TIR) showed associations with all studied microvascular and macrovascular complications of diabetes. Notably, higher TIR was associated with reduced risk of albuminuria, retinopathy, cardiovascular disease mortality, all-cause mortality, and abnormal carotid intima-media thickness. Peripheral neuropathy was predominantly associated with standard deviation of blood glucose levels (SD) and mean amplitude of glycemic excursions (MAGE).

CONCLUSION

The evidence supports the association between diabetes complications and CGM-derived measures of intraday glycemic variability. TIR emerged as the most consistent measure, supporting its emerging role in clinical practice. More longitudinal studies and trials are required to confirm these associations, particularly for T1D, for which there are limited data.

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.

Insulin Titration Guidelines for Patients With Type 1 Diabetes: It Is About Time!

PURPOSE

A proposal that an Insulin Advisory Committee develop insulin titration guidelines 100 years after its discovery.

FINDINGS

Glucose control metrics remain poor despite significant advances in diabetes technology.

SUMMARY

A century after the introduction of insulin, health care providers and patients with type 1 diabetes have worldwide access to a variety of insulin delivery devices (IDDs), glucose monitors, bolus calculators (BCs), continuous glucose monitors (CGMs), and automated insulin delivery (AID) systems. However, these advances have not enabled most patients to achieve today's clear A1c and time-in-range goals. Much of this failure arises from the lack of clear insulin titration guidelines for determining appropriate insulin doses. The lack of dosing clarity results in local physicians, clinics, and individual patients managing insulin titrations as they see fit, creating significant inefficiencies for reaching recommended glycemic goals. This review (1) details the widespread problems generated by nonphysiological dose settings in today's BCs, insulin pumps, and AID systems; (2) presents a method to develop and implement optimized total daily doses of insulin to correct the most common problem of hyperglycemia; (3) discusses using large device databases to provide clear insulin titration guidelines that optimize BC settings from an optimized total daily dose (TDD) of insulin for patients with T1D; and (4) recommends the formation of an Insulin Advisory Committee to clarify the steps to take toward universal insulin titration guidelines, optimized BC settings, and a systematic logic for their use in insulin delivery devices.

Time in range in relation to amputation and all-cause mortality in hospitalised patients with diabetic foot ulcers

AIMS

The aim of this study was to evaluate the association of time in range (TIR) with amputation and all-cause mortality in hospitalised patients with diabetic foot ulcers (DFUs).

MATERIALS AND METHODS

A retrospective analysis was performed on 303 hospitalised patients with DFUs. During hospitalisation, TIR, mean blood glucose (MBG), coefficient of variation (CV), time above range (TAR) and time below range (TBR) of patients were determined from seven-point blood glucose profiles. Participants were grouped based on their clinical outcomes (i.e., amputation and death). Logistic regression was employed to analyse the association of TIR with amputation and all-cause mortality of inpatients with DFUs.

RESULTS

Among the 303 enrolled patients, 50 (16.5%) had undergone amputation whereas seven (2.3%) were deceased. Blood glucose was determined in 41,012 samples obtained from all participants. Patients who underwent amputation had significantly lower TIR and higher MBG, CV, level 2 TAR and level 1 TBR whereas deceased patients had significantly lower TIR and higher MBG and level 2 TAR. Both amputation and all-cause mortality rate declined with an increase in TIR quartiles. Logistic regression showed association of TIR with amputation (p = 0.034) and all-cause mortality (p = 0.013) after controlling for 15 confounders. This association was similarly significant in all-cause mortality after further adjustment for CV (p = 0.022) and level 1 TBR (p = 0.021), respectively.

CONCLUSIONS

TIR is inversely associated with amputation and all-cause mortality of hospitalised patients with DFUs. Further prospective studies are warranted to establish a causal relationship between TIR and clinical outcomes in patients with DFUs.

Plasma 1,5-anhydro-D-glucitol is associated with peripheral nerve function and diabetic peripheral neuropathy in patients with type 2 diabetes and mild-to-moderate hyperglycemia

BACKGROUND

Plasma 1,5-anhydro-D-glucitol (1,5-AG) may be a easily accessible marker for glycemic variability under mild-to-moderate hyperglycemia. The present study was to investigate the association of 1,5-AG with peripheral nerve function and diabetic peripheral neuropathy (DPN) in patients with T2D and mild-to-moderate hyperglycemia.

METHODS

We recruited 574 T2D patients with mild-to-moderate hyperglycemia (HbA1c  < 8.0%) for this cross-sectional study, with plasma 1,5-AG synchronously detected. All patients were questioned for neurologic symptoms, examined for neurologic signs and screened for peripheral nerve function. Nerve function included the latency, amplitude and nerve conduction velocity (NCV) of limbs nerves (median, ulnar nerve, common peroneal, superficial peroneal, tibial and sural nerve). Besides, composite Z-score of latency, amplitude and NCV were calculated. DPN was identified as both at least a neurologic symptom/sign and an abnormality of peripheral nerve function.

RESULTS

Among the recruited patients, 23.9% (n  = 137) were identified to be with DPN, and the prevalence of DPN decreased from 36.6%, 24.5%, 21.2%, 13.3% from first (Q1), second (Q2), and third (Q3) to fourth quartile (Q4) of 1,5-AG. Moreover, multivariable linear regression analysis showed 1,5-AG was associated with composite Z-score of nerve latency (β  = - 0.18, t  = - 3.84, p  < 0.001), amplitude(β  =  0.26, t  = 5.35, p  < 0.001) and NCV (β  = 0.24, t  = 5.61, p  < 0.001), respectively. Furthermore, compared to Q4 of 1,5-AG as reference, the adjusted odds ratios and 95% CIs for DPN of Q3, Q2, and Q1 were 1.29(0.59-2.81), 1.85(0.87-3.97), and 2.72(1.16-6.34), respectively. Additionally, receiver operating characteristic analysis revealed that optimal cutoff value of 1,5-AG to indicate DPN was  ≤ 30.8 μmol/L, with sensitivity of 56.20% and specificity of 66.36%.

CONCLUSIONS

Low plasma 1,5-AG is closely associated with impaired peripheral nerve function and DPN in T2D patients under mild-to-moderate hyperglycemia.

Relationship Between Time in Range, Glycemic Variability, HbA1c, and Complications in Adults With Type 1 Diabetes Mellitus

PURPOSE

Real-time continuous glucose monitoring (RT-CGM) provides information on glycemic variability (GV), time in range (TIR), and guidance to avoid hypoglycemia, thereby complimenting HbA1c for diabetes management. We investigated whether GV and TIR were independently associated with chronic and acute diabetes complications.

METHODS

Between September 2014 and January 2017, 515 subjects with type 1 diabetes using sensor-augmented pump therapy were followed for 24 months. The link between baseline HbA1c and CGM-derived glucometrics (TIR [70-180 mg/dL], coefficient of variation [CV], and SD) obtained from the first 2 weeks of RT-CGM use and the presence of complications was investigated. Complications were defined as: composite microvascular complications (presence of neuropathy, retinopathy, or nephropathy), macrovascular complications, and hospitalization for hypoglycemia and/or ketoacidosis.

RESULTS

Individuals with microvascular complications were older (P < 0.001), had a longer diabetes duration (P < 0.001), a higher HbA1c (7.8 ± 0.9 vs 7.5 ± 0.9%, P < 0.001), and spent less time in range (60.4 ± 12.2 vs 63.9 ± 13.8%, P = 0.022) compared with those without microvascular complication. Diabetes duration (odds ratio [OR] = 1.12 [1.09-1.15], P < 0.001) and TIR (OR = 0.97 [0.95-0.99], P = 0.005) were independent risk factors for composite microvascular complications, whereas SD and CV were not. Age (OR = 1.08 [1.03-1.14], P = 0.003) and HbA1c (OR = 1.80 [1.02-3.14], P = 0.044) were risk factors for macrovascular complications. TIR (OR = 0.97 [0.95-0.99], P = 0.021) was the only independent risk factor for hospitalizations for hypoglycemia or ketoacidosis.

CONCLUSIONS

Lower TIR was associated with the presence of composite microvascular complications and with hospitalization for hypoglycemia or ketoacidosis. TIR, SD, and CV were not associated with macrovascular complications.

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.

Metabolic syndrome associated with higher glycemic variability in type 1 diabetes: A multicenter cross-sectional study in china

AIMS

The comorbidity of metabolic syndrome (MetS) and type 1 diabetes mellitus (T1DM) is an obstacle to glucose control in patients with T1DM. We compared glycemic profiles using continuous glucose monitoring (CGM) systems in patients with T1DM with or without MetS.

METHODS

This was a multicenter cross-sectional study of patients with T1DM (N = 207) with or without MetS. CGM data were collected from study enrollment until discharge during a 1-week study session. We analyzed baseline HbA1c, average glucose, estimated HbA1c, time in range (TIR), time above range (TAR), time below range (TBR), coefficient of variation (CV), postprandial glucose excursions (PPGE) and other glycemic variability (GV) metrics. Logistic regression was developed to investigate the association between MetS and CGM metrics.

RESULTS

The results showed higher average baseline HbA1c levels, and a higher percentage of patients with baseline HbA1c levels ≥7.5%, in the T1DM with MetS group. Furthermore, MetS was associated with GV, which indicated a higher CV in patients with T1DM with MetS. However, our results showed that TAR, TIR, TBR and other GV metrics were comparable between the two groups. The T1DM with MetS group also had a higher proportion of patients with high CV (≥ 36%) than the group without MetS. In multivariable logistic regression analysis, the presence of MetS was a risk factor for high CV (≥ 36%) in our study participants.

CONCLUSIONS

T1DM patients with MetS in our study had better β-cell function. However, MetS was associated with worse glycemic control characterized by higher GV and HbA1c levels. Efforts should be expanded to improve treatment of MetS in patients with T1DM to achieve better glycemic control.

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.

Increased levels of serum adenosine deaminase and increased risk of diabetic peripheral neuropathy in type 2 diabetes

BACKGROUND

Increased serum adenosine deaminase (ADA) levels have been shown to be involved in metabolic abnormalities and immune disequilibrium, which may in turn contribute to inflammatory diseases. This study aimed to determine whether increased serum ADA levels are related to diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes (T2D).

METHODS

This study was part of a series exploring the potential risks for DPN. All patients received DPN assessment based on neuropathic symptoms, neuropathic signs, and nerve conduction studies to calculate the composite Z score of nerve latency, amplitude and conduction velocity (NCV). DPN was confirmed by both at least a presentation of neuropathic symptoms/signs and an abnormal nerve conduction index. Serum ADA levels were also synchronously detected.

RESULTS

A total of 384 eligible patients with T2D were recruited for this study, and 24.5% (n=94) were determined to have DPN. Increases in serum ADA levels were closely associated with increases in composite Z score of latency (β=0.263, t=5.273, p<0.001) and decreases in composite Z score of amplitude (β=-0.126, t=-2.352, p=0.019) and NCV (β=-0.201, t=-3.841, p<0.001) after adjusting for other clinical covariates. Moreover, each 5 U/L increase in serum ADA levels was associated with a 1.781-fold increased adjusted odds ratio of having DPN (95% confidence interval: 1.271-2.495). Furthermore, the optimal cut-off value of serum ADA levels to discriminate DPN was ≥14.2 U/L (sensitivity=59.57%, specificity=75.52% and Youden index=0.351) after analysis by receiver operating characteristic curve.

CONCLUSIONS

Increased serum ADA levels may be a potential risk factor for DPN in patients with T2D.

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 platelet count and plateletcrit with nerve conduction function and peripheral neuropathy in patients with type 2 diabetes mellitus

AIMS/INTRODUCTION

Diabetes has been considered as a 'pro-thrombotic state' with enhanced platelet reactivity. Abnormality in platelet aggregation has been found in patients with its most common chronic complication - diabetic peripheral neuropathy (DPN). The purpose of this study was to investigate the potential association of platelet indices with nerve conduction function and the presence of DPN in Chinese patients with type 2 diabetes mellitus.

MATERIALS AND METHODS

This study involved a total of 211 inpatients with type 2 diabetes mellitus and 55 healthy individuals for whom nerve conduction studies were carried out. DPN was diagnosed according to the American Diabetes Association recommendation. Clinical data were retrospectively collected.

RESULTS

Patients with diabetes in whom neuropathy developed had lower levels of platelet count (PLT) and plateletcrit (PCT) than healthy controls (P < 0.05). Statistically significant associations of low PLT and PCT levels with the reduction of summed amplitude/velocity Z-score, and the prolongation of F-wave minimum latency in nerve conduction studies were found. Furthermore, after multivariate adjustment, logistic regression analysis showed that low levels of PLT (odds ratio 2.268, 95% confidence interval 1.072-4.797; P < 0.05; PLT <226 vs PLT ≥226) and PCT (odds ratio 2.050, 95% confidence interval 1.001-4.201; P < 0.05; PCT <0.222 vs PCT ≥0.222) in type 2 diabetes mellitus patients were risk factors for the presence of DPN.

CONCLUSIONS

Lower PLT and PCT levels are closely associated with poorer peripheral nerve conduction functions and the presence of neuropathy in patients with type 2 diabetes mellitus, which suggests that PLT and PCT might be potential biomarkers for showing DPN.

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.

Daytime Glycemic Variability and Frailty in Older Patients with Diabetes: a Pilot Study Using Continuous Glucose Monitoring

We investigated the relationship between glucose variability and frailty. Forty-eight type 2 diabetic patients aged ≥ 65 years were enrolled. The FRAIL scale was used for frailty assessment, and participants were classified into 'healthy & pre-frail' (n = 24) and 'frail' (n = 24) groups. A continuous glucose monitoring (CGM) system was used for a mean of 6.9 days and standardized CGM metrics were analyzed: mean glucose, glucose management indicator (GMI), coefficient of variation, and time in range, time above range (TAR), and time below range. The demographics did not differ between groups. However, among the CGM metrics, mean glucose, GMI, and TAR in the postprandial periods were higher in the frail group (all P < 0.05). After multivariate adjustments, the post-lunch TAR (OR = 1.12, P = 0.019) affected the prevalence of frailty. Higher glucose variability with marked daytime postprandial hyperglycemia is significantly associated with frailty in older patients with diabetes.

Time-in-range for monitoring glucose control: Is it time for a change?

The HbA1c value has been the gold standard for evaluating glucose control for decades. However, it has limitations such as the lack of information on glycemic variability or the risk of hypoglycemia. The increasing use of continuous glucose monitoring has provided patients and healthcare professionals with a range of useful metrics for the management of diabetes. Among them, Time in Range (TIR) is a simple and intuitive metric that gives information regarding the quality of glucose control. It is defined as the time spent in an individual's target glucose range. TIR is strongly correlated with HbA1c, and it has been linked to the risk of developing microvascular and macrovascular complications. The International Consensus on Time in Range has recently set targets for different diabetes populations. For the majority of people with type 1 or type 2 diabetes, a TIR (70-180 mg/dL or 3.9-10.0 mmol/L) of >70%, a time below range (TBR) <70 mg/dL (<3.9 mmol/L) of <4% and a TBR <54 (<3.0 mmol/L) of <1% are recommended. In this review, we address the latest evidence for the use of TIR as an essential parameter in the management of diabetes.

HbA1c and Glucose Management Indicator Discordance: A Real-World Analysis

Background: There can be marked discordance between laboratory and estimated (using the glucose management indicator [GMI]) glycated hemoglobin (HbA1c) from continuous glucose monitoring (CGM). This may cause errors in diabetes management. This study evaluates discordance between laboratory and CGM-estimated HbA1c (eA1C). Methods: We performed a retrospective review of patients with diabetes who use CGM. The patients were seen at the University of Washington (UW) Diabetes Care Center from 2012 to 2019. We used UW's Institute of Translational Health Sciences to extract eligible encounters from the electronic medical record. We required that patients use CGM and that HbA1c and sensor data be obtained fewer than 4 weeks apart. There were no exclusion criteria. We calculated HbA1c-GMI discordance for each subject and assessed for any impact of comorbidities. We defined HbA1c-GMI discordance as absolute difference between laboratory and eA1C. Results: This study included 641 separate office encounters. Ninety-one percent of patients had type 1 diabetes. Most patients had diabetes for greater than 20 years. The mean duration of CGM wear was 24.5 ± 8 days. Only 11% of patients had HbA1c-GMI discordance <0.1%, but 50% and 22% had differences ≥0.5% and ≥1%. There was increased discordance with advanced chronic kidney disease (estimated glomerular filtration rate <60). Discussion: We found substantial discordance between laboratory and eA1C in a real-world setting. Clinicians need be aware that HbA1c may not as accurately reflect mean glucose as previously appreciated.

Improved Estimation of Glycated Hemoglobin from Continuous Glucose Monitoring and Past Glycated Hemoglobin Data

Background: Accurate estimation of glycated hemoglobin (HbA1c) from continuous glucose monitoring (CGM) remains challenging in clinic. We propose two statistical models and validate them in real-life conditions against the current standard, glucose management indicator (GMI). Materials and Methods: Modeling utilized routinely collected data from patients with type 1 diabetes from central Poland (eligibility criteria: age >1 year, diabetes duration >3 months, and CGM use between 01/01/2015 and 12/31/2019). CGM records were extracted from dedicated Medtronic/Abbott databases and cross-referenced with HbA1c values; 28-day periods preceding HbA1c measurement with >75% of the sensor-active time were analyzed. We developed a mixed linear regression, including glycemic variability indices and patient's ID (glucose variability-based patient specific model, GV-PS) intended for closed-group use and linear regression using patient-specific error of GMI (proportional error-based patient agnostic model, PE-PA) for general use. Models were validated with either new HbA1cs from closed-group patients or separate patient-HbA1c pool. External validation was performed with data from clinical trials. Performance metrics included bias, its 95% confidence interval (95% CI), coefficient of determination (R²), and root mean square error (RMSE). Results: We included 723 HbA1c-CGM pairs from 174 patients (mean age 9.9 ± 4.4 years and diabetes duration 3.7 ± 3.6 years). GMI yielded R² = 0.58, with different bias between Medtronic and Abbott devices [0.120% vs. -0.152%, P < 0.0001], and overall 95% CI = -0.9% to +1%, RMSE = 0.47%. GV-PS successfully captured patient-specific variance (closed-group validation: R² = 0.83, bias = 0.026%, 95% CI = -0.562% to 0.591%, RMSE = 0.31%). PE-PA performed similarly on new patients (R² = 0.76, bias = -0.069%, 95% CI = -0.790% to 0.653%, RMSE = 0.37%). In external validation GMI, GV-PS, and PE-PA produced 73.8%, 87.5%, and 91.0% predictions within 0.5% (5.5 mmol/mol) from the true value. Conclusion: Constructed models performed better than GMI. PE-PA provided an accurate estimate of HbA1c with fast and straightforward implementation.

Association of Body Fat Percentage with Time in Range Generated by Continuous Glucose Monitoring during Continuous Subcutaneous Insulin Infusion Therapy in Type 2 Diabetes

BACKGROUND

Obesity is a crucial risk factor associated with type 2 diabetes mellitus (T2DM). Excessive accumulation of body fat may affect the glycemia control in T2DM. This study investigated the relationship between body fat percentage and time in range (TIR) assessed by continuous glucose monitoring (CGM) during short-term continuous subcutaneous insulin infusion (CSII) therapy in T2DM patients.

METHOD

A total of 85 T2DM patients were recruited in this cross-sectional study. All participants underwent 72 h CGM period during short-term CSII therapy. TIR was defined as the percentage of time spent within the target glucose range of 3.9-10.0 mmol/L. Body composition was measured using bioelectrical impedance analysis (BIA) and overfat was defined as an amount of body fat of at least 25% of total body mass for men or at least 30% for women. Multiple linear regression models were used to evaluate the independent association of body fat percentage with TIR after adjusting for confounding factors.

RESULTS

Compared with normal fat T2DM patients, individual with a higher body fat percentage exhibited lower levels of TIR (P = 0.004) and higher 72 h mean blood glucose (72 h MBG) (P = 0.001) during short-term CSII treatment. The prevalence of overfat assessed by body fat percentage decreased with the ascending TIR tertiles (P < 0.05). Multiple linear regression analysis indicated that body fat percentage was significantly associated with TIR independent of age, gender, diabetes duration, HbA1c, and BMI (P = 0.043).

CONCLUSIONS

Body fat percentage was significantly associated with TIR in T2DM during short-term CSII therapy. Reduction of body fat may be an important therapeutic target to improve glycemic control in high body fat T2DM patients, who may benefit less from intensive insulin treatment.