Association of Time in Range, as Assessed by Continuous Glucose Monitoring, With Diabetic Retinopathy in Type 2 Diabetes

Role of Systemic Factors in Improving the Prognosis of Diabetic Retinal Disease and Predicting Response to Diabetic Retinopathy Treatment

Topic

To review clinical evidence on systemic factors that might be relevant to update diabetic retinal disease (DRD) staging systems, including prediction of DRD onset, progression, and response to treatment.

Clinical relevance

Systemic factors may improve new staging systems for DRD to better assess risk of disease worsening and predict response to therapy.

Methods

The Systemic Health Working Group of the Mary Tyler Moore Vision Initiative reviewed systemic factors individually and in multivariate models for prediction of DRD onset or progression (i.e., prognosis) or response to treatments (prediction).

Results

There was consistent evidence for associations of longer diabetes duration, higher glycosylated hemoglobin (HbA1c), and male sex with DRD onset and progression. There is strong trial evidence for the effect of reducing HbA1c and reducing DRD progression. There is strong evidence that higher blood pressure (BP) is a risk factor for DRD incidence and for progression. Pregnancy has been consistently reported to be associated with worsening of DRD but recent studies reflecting modern care standards are lacking. In studies examining multivariate prognostic models of DRD onset, HbA1c and diabetes duration were consistently retained as significant predictors of DRD onset. There was evidence of associations of BP and sex with DRD onset. In multivariate prognostic models examining DRD progression, retinal measures were consistently found to be a significant predictor of DRD with little evidence of any useful marginal increment in prognostic information with the inclusion of systemic risk factor data apart from retinal image data in multivariate models. For predicting the impact of treatment, although there are small studies that quantify prognostic information based on imaging data alone or systemic factors alone, there are currently no large studies that quantify marginal prognostic information within a multivariate model, including both imaging and systemic factors.

Conclusion

With standard imaging techniques and ways of processing images rapidly evolving, an international network of centers is needed to routinely capture systemic health factors simultaneously to retinal images so that gains in prediction increment may be precisely quantified to determine the usefulness of various health factors in the prognosis of DRD and prediction of response to treatment.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

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.

Perspectives and Behaviors of People with Diabetes toward Time in Range and Glucose Control in Diabetes Management: An Online Survey

INTRODUCTION

This study assessed experiences, attitudes, and behaviors of people with diabetes (PwD) regarding diabetes self-management and glucose control, and their level of awareness, knowledge, and attitudes toward time in range (TIR).

METHODS

This quantitative survey was conducted using an online questionnaire across seven countries. Respondents were PwD classified into three subgroups: type 1 (T1), type 2 insulin (T2 insulin), and type 2 not on insulin (T2 N/insulin).

RESULTS

Respondents included 621 people in the T1, 780 people in the T2 insulin, and 735 people in the T2 N/insulin subgroups. Awareness of TIR was low, particularly in the T2 N/insulin subgroup (T1 53%, T2 insulin 29%, T2 N/insulin 9%). Despite a lower current use of continuous glucose monitoring (CGM) among the T2 insulin and T2 N/insulin participants (38% and 9%, respectively), versus T1 participants (64%), most (> 70%) were positive toward utilizing new tools and measures to self-manage blood glucose. Recommendations from their healthcare professionals (HCPs) were cited as a strong motivator to try new measures for analyzing glucose levels. The main barriers cited were limited access to CGM and lack of understanding of TIR benefits. Cost was the main reason given by ≥ 40% of respondents for stopping CGM use.

CONCLUSIONS

There is an unmet need in diabetes management, and TIR and CGM offer a potential solution. PwD are motivated to manage their blood glucose levels and are positive toward utilizing new tools and measures to achieve this goal. HCPs play a pivotal role in informing and guiding PwD on new measures for analyzing glucose.

Associations Between HbA1c and Glucose Time in Range Using Continuous Glucose Monitoring in Type 1 Diabetes: Cross-Sectional Population-Based Study

INTRODUCTION

Continuous glucose monitoring (CGM) introduces novel indicators of glycemic control.

METHODS

This cross-sectional study, based on the Swedish National Diabetes Register, examines 27,980 adults with type 1 diabetes. It explores the relationships between HbA1c (glycated hemoglobin) and various CGM-derived metrics, including TIR (time in range, representing the percentage of time within the range of 4-10 mmol/l for 2 weeks), TAR (time above range), TBR (time below range), mean glucose, standard deviation (SD), and coefficient of variation (CV). Pearson correlation coefficients and linear regression models were utilized for estimation.

RESULTS

The analysis included 46% women, 30% on insulin pump, 7% with previous coronary heart disease and 64% with retinopathy. Mean ± SD values were age 48 ± 18 years, diabetes duration 25 ± 16 years, HbA1c 58.8 ± 12.8 mmol/mol, TIR 58.8 ± 19.0%, TAR 36.3 ± 20.0%, TBR 4.7 ± 5.4%, mean sensor glucose 9.2 ± 2.0 mmol/l, SD 3.3 ± 1.0 mmol/l, and CV 36 ± 7%. The overall association between HbA1c and TIR was - 0.71 (Pearson's r), with R2 0.51 in crude linear regression and 0.57 in an adjusted model. R2 values between HbA1c and CGM mean glucose were 0.605 (unadjusted) 0.619 (adjusted) and TAR (unadjusted 0.554 and fully adjusted 0.568, respectively), while fully adjusted R2 values were 0.458, 0.175 and 0.101 between HbA1c and CGM SD, CGM CV and TBR, respectively.

CONCLUSIONS

This descriptive study demonstrates that the degree of association between HbA1c and new and readily available CGM-derived metrics, i.e., time in range (TIR), time above range (TAR), and CGM mean glucose, is robust in assessing the management of individuals with type 1 diabetes in clinical settings. Metrics from CGM that pertain to variability and hypoglycemia exhibit only weak correlations with HbA1c.

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.

The role of mannose-binding lectin (MBL) in diabetic retinopathy: A scoping review

Diabetes mellitus (DM) is a chronic systemic disease characterized by a multifactorial nature, which may lead to several macro and microvascular complications. Diabetic retinopathy (DR) is one of the most severe microvascular complications of DM, which can result in permanent blindness. The mechanisms involved in the pathogenesis of DR are multiple and still poorly understood. Factors such as dysregulation of vascular regeneration, oxidative and hyperosmolar stress in addition to inflammatory processes have been associated with the pathogenesis of DR. Furthermore, compelling evidence shows that components of the immune system, including the complement system, play a relevant role in the development of the disease. Studies suggest that high concentrations of mannose-binding lectin (MBL), an essential component of the complement lectin pathway, may contribute to the development of DR in patients with DM. This review provides an update on the possible role of the complement system, specifically the lectin pathway, in the pathogenesis of DR and discusses the potential of MBL as a non-invasive biomarker for both, the presence and severity of DR, in addition to its potential as a therapeutic target for intervention strategies.

Quality of life, diabetes-related stress and treatment satisfaction are correlated with glycemia risk index (GRI), time in range and hypoglycemia/hyperglycemia components in type 1 diabetes

INTRODUCTION

To evaluate the relationship between the GRI -component of hypoglycemia (CHypo) and hyperglycemia (CHyper)- with diabetes quality of life (DQoL), diabetes-related stress (DDS), perception of hypoglycemia (Clarke Test), visual analogic scale (VAS) and diabetes-knowledge (DKQ2) in T1D.

METHODS

Cross-sectional study in 92 patients with T1D under intensive insulin treatment (21.7% CSII) and flash glucose monitoring (isCGM). Clinical, metabolic and glycometric parameters and quality of life/satisfaction questionnaires were analyzed.

RESULTS

92 patients (54.3% male, BMI 25.4 ± 4.5 kg/m2, HbA1c 7.5 ± 1.0%, TIR 53.9 ± 15.9%) with mean age 36.1 ± 12.6years and 17.8 ± 11.3 T1D duration. The mean GRI was 60.6 ± 22.2 with a CHypo and CHyper of 5.9 ± 4.8 and 27.3 ± 14.4, respectively. 19.1% presented a pathological Clarke's test. Patients with TIR > 70% and GRI < 40 showed better VAS (8.8 ± 1.3 vs 9.3 ± 0.9, p < 0.05) and DDS (46.4 ± 22.1 vs 36.7 ± 16.6, p < 0.05) scores, showing no differences between groups. CHyper > 15 and Chypo > 3.4 were related to worse levels of DQoL (91.1 ± 23.9 vs 76.6 ± 18.6 and 94.6 ± 24.8 vs 79.8 ± 20.1, p < 0.01), DDS(49.8 ± 22.4 vs 35.7 ± 16.5 and 49.8 ± 22.4 vs 35.7 ± 16.5, p < 0.01),and DKQ2 (24.4 ± 4.3 vs 26.8 ± 5.2 and 24.1 ± 4.8 vs 26.0 ± 4.6, p < 0.05), respectively. Worse metabolic control defined by GRI correlated with worse scores in VAS (r = -0.209, p < 0.05), DQoL (r = 0.205, p < 0.05), and DDS (r = 0.205, p < 0.05). No difference was observed in knowledge´s scale. CHyper correlated with worse scores in VAS (r = -0.231, p < 0.05), DQoL (r = 0.422, p < 0.01), and DDS (r = 0.341, p < 0.01) and lower degree of knowledge DKQ2 (r = -0.231, p < 0.05). When analyzing DQoL as a dependent variable in a multiple lineal regression, only age (β = 0.747; p < 0.001) and CHyper (β = 0.717; p < 0.001) maintained statistical significance.

CONCLUSIONS

Higher GRI was related to worse quality of life, diabetes-related stress and satisfaction with treatment, analogous to the TIR results.CHyper an Chypo were related to a greater decline in quality of life, diabetes-related stress, and lower satisfaction with treatment.However, in a multiple linear regression, only CHyper maintained statistical significance.

Heterogeneity of glycaemic phenotypes in type 1 diabetes

AIMS/HYPOTHESIS

Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes.

METHODS

In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison.

RESULTS

We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes.

CONCLUSIONS/INTERPRETATION

Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.

Correlation Between Blood Urea Nitrogen and Short- and Long-Term Glycemic Variability in Elderly Patients with Type 2 Diabetes Mellitus Who Were hospitalized:A Retrospective Study

Objective

Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by insulin resistance and progressively impaired insulin secretion resulting in dynamic fluctuations in glucose levels.High blood urea nitrogen (BUN) levels have been linked to decreased insulin sensitivity, suppressed insulin synthesis and increased risk of incident diabetes mellitus in humans as well as insulin use in patients with T2DM.This study characterize the association between BUN levels and short-term and long-term glycemic variability(GV) in the elderly patients with T2DM who were hospitalized.

Methods

A total of 927 elderly patients with T2DM were included in the study. The short-term GV was quantified using parameters such as standard deviation (SD), coefficient of variation (CV), time in range (TIR), and mean amplitude of glycemic excursions (MAGE), based on multi-point fingertip blood glucose monitoring. The long-term GV was quantified using parameters such as SD, CV, variation independent of the mean (VIM), and average successive variability (ARV), based on fasting blood glucose(FPG). The relationship between BUN levels and short-term and long-term GV in elderly T2DM who were hospitalized was explored using methods such as Spearman correlation coefficient, linear regression analysis, logistic regression analysis, and interaction tests.

Results

In elderly patients with T2DM were hospitalized, there is a significant correlation between BUN levels and both short-term and long-term GV. BUN is negatively correlated with the GV parameter TIR (r=-0.12, P=0.000), and positively correlated with SD (r=0.12, P=0.000), CV (r=0.07, P=0.026), MAGE (r=0.11, P=0.001), FPG-SD (r=0.08, P=0.013), and FPG-CV (r=0.08, P=0.014).Furthermore, the association remains consistent across different age, gender, BMI, and haemoglobin A1c (HbA1c) subgroups (P interaction > 0.05).

Conclusion

In elderly patients with T2DM were hospitalized, BUN levels were positively associated with GV.Therefore, monitoring BUN levels were beneficial in assessing the degree of GV.

Comparison of efficacy and safety of insulin degludec/liraglutide and insulin glargine U-100/lixisenatide in individuals with type 2 diabetes mellitus using professional continuous glucose monitoring

AIM/INTRODUCTION

Insulin glargine U100/lixisenatide and insulin degludec/liraglutide are fixed-ratio combinations containing basal insulin and a glucagon-like peptide-1 receptor agonist capable of reducing both fasting and postprandial blood glucose levels with a single formulation. This study aimed to compare the time in range (TIR) and the time below range (TBR) level 1 using professional continuous glucose monitoring and to establish criteria for the differential use of the fixed-ratio combinations.

MATERIALS AND METHODS

Thirty-six outpatients with type 2 diabetes mellitus (24 men and 12 women; average age, 62.1 years) were randomly assigned to the groups. At 0 and 18 weeks, a device was worn to compare the TIR and TBR level 1. The correlation between the C-peptide index at baseline and TIR at 18 weeks was assessed.

RESULTS

The TIR and TBR level 1 showed no significant differences between the two groups. Both groups showed significant positive correlations between the C-peptide index and the TIR (P = 0.002, r = 0.679; P = 0.002, r = 0.681, respectively). The changes in glycemic variability, therapeutic indices, and body mass index were not significantly different among the groups (P > 0.05). The receiver operating curve analysis revealed that the cut-off values of the C-peptide index to achieve TIR of >70% at 18 weeks were 1.258 (sensitivity, 77.8%; specificity, 100%) and 1.099 (sensitivity, 57.1%; specificity, 90.9%) in the insulin glargine U100/lixisenatide and insulin degludec/liraglutide groups, respectively.

CONCLUSIONS

A TIR of >70% was achieved for both fixed-ratio combinations without significant differences.

Association between glycemia risk index and arterial stiffness in type 2 diabetes

AIM

This study aims to investigate the association of glycemia risk index (GRI), a novel composite metric derived from continuous glucose monitoring (CGM), with arterial stiffness in patients with type 2 diabetes.

MATERIALS AND METHODS

A total of 342 adults with type 2 diabetes were enrolled between April and June 2023 from 11 communities in Shanghai, China. Medical examinations, including measurements of anthropometric parameters, blood pressure, and venous blood samples were conducted. Brachial-ankle pulse wave velocity (baPWV) was examined to evaluate arterial stiffness. All the participants underwent a 14 day CGM recording and GRI was calculated from the CGM data.

RESULTS

The mean age was 70.3 ± 6.8 years, and 162 (47.4%) were male. Participants with a higher baPWV had significantly higher levels of GRI and hyperglycemia component (both P for trend < 0.05). Linear regression revealed the significant positive linear associations of the GRI with baPWV in unadjusted or adjusted models (All P < 0.05). In the multivariable logistic analysis, each increase in the GRI quartile was associated with a 1.30-fold (95% CI 1.01-1.68, P for trend < 0.05) higher prevalence of increased arterial stiffness after adjustment for age, sex, BMI, diabetes duration, current smoking status, blood pressure, and lipid profile. Subgroup analyses showed that the association between the GRI quartiles and increased arterial stiffness was stronger among participants with a diabetes duration ≥15 years (P for interaction = 0.014).

CONCLUSION

Glycemia risk index assessed by continuous glucose monitoring is associated with increased arterial stiffness in type 2 diabetes.

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).

Association between continuous glucose monitoring-derived glycemic control indices and urinary biomarkers of diabetic kidney disease: Hyogo Diabetes Hypoglycemia Cognition Complications study

AIMS

Glomerular damage and proximal tubular damage play an important role in the pathogenesis of diabetic kidney disease. This study aimed to investigate the relationship between the urinary markers of proximal tubular injury, including urinary liver-type fatty acid-binding protein-to-creatinine ratio (uL-FABP/Cr) and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/Cr), and glycemic control status.

METHODS

This cross-sectional study included 245 and 39 patients with type 2 diabetes mellitus (T2DM) and non-T2DM (NDM), respectively. The participants of this study were fitted with retrospective CGM, and glycemic control indices, such as time in range (TIR) and glycemia risk index (GRI), were calculated.

RESULTS

The results were presented as medians (interquartile ranges). The uL-FABP/Cr was significantly higher in the microalbuminuria than in the normo-albuminuria group [4.2 (2.7-7.1) and 2.2 (1.4-3.4) μg/gCr, respectively, P < 0.001], while the uNAG/Cr in the normo-albuminuria group [6.3 (4.5-10.1) U/gCr] was significantly higher than that in the NDM group [5.3 (3.8-6.3) U/gCr, P = 0.048] but significantly lower than that in the microalbuminuria group [9.2 (6.4-11.1) U/gCr, P = 0.004]. The multivariate logistic regression analysis indicated that CGM-derived TIR was significantly associated with the urinary albumin-to-creatinine ratio [uAlb/Cr, odds ratio (OR) 0.985, 95% confidence interval (CI) 0.971-0.998, P = 0.029] and uNAG/Cr (OR 0.973, 95% CI 0.957-0.989, P = 0.001) independent of renal function. GRI was similarly associated with uAlb/Cr and uNAG/Cr.

CONCLUSION

The findings of this study indicated that uNAG/Cr was elevated before albuminuria development and was associated with CGM-derived TIR and GRI.

Continuous Glucose Monitoring Systems in Noninsulin-Treated People with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Introduction: Continuous glucose monitoring (CGM) has shown favorable outcomes in patients with type 2 diabetes (T2D) who are on insulin therapy. However, the efficacy of CGM in managing glucose levels in noninsulin-treated people with T2D remains controversial. Methods: PubMed, Cochrane, and Embase were searched for randomized controlled trials (RCTs) comparing CGM to self-monitoring of blood glucose (SMBG) in people with T2D not using insulin. We computed weighted mean differences (WMDs) and standard mean differences (SMD) for continuous outcomes, with 95% confidence intervals (CIs). Heterogeneity was assessed using I2 statistics. Statistical analyses were performed using R version 4.2.3. Results: We included six RCTs comprising 407 noninsulin-treated people with T2D of whom 228 were randomized to CGM. Diabetes duration ranged from 5.4 to 13.9 years. The mean age was 57.9 years and the mean body mass index was 30.8 kg/m2. Four trials used real-time CGM (rt-CGM) and two intermittent scanning CGM (is-CGM). Compared with SMBG, CGM significantly reduced the glycated hemoglobin level (WMD -0.31%; 95% CI -0.42 to -0.21; I2 = 0%), glucose level (WMD -11.16 mg/dL; 95% CI -19.94 to -2.39; I2 = 0%), time in hypoglycemia level 2 (WMD -0.28%; 95% CI -0.52 to -0.03; I2 = 91%), glucose time >180 mg/dL (WMD -7.75%; 95% CI -12.04 to -3.45; I2 = 0%), and the standard deviation of glucose variation (WMD -4.00 mg/dL; 95% CI -6.86 to -1.14; I2 = 0%). CGM also increased time in range (WMD 8.63%; 95% CI 4.54-12.71; I2 = 0%) and treatment satisfaction (SMD 0.79; 95% CI 0.54-1.05; I2 = 0%). Conclusion: In this meta-analysis, rt-CGM and is-CGM were associated with improvement in glycemic control in people with T2D not using insulin when compared to SMBG.

Correlation between time in range and serum uric acid in Chinese patients with type-2 diabetes: an observational cross-sectional study

BACKGROUND

At present, the relationship between serum uric acid and blood glucose is controversial, and even opposite conclusions have been reached. We aimed to investigate the relationship between time in range and serum uric acid and estimate the influence of serum uric acid on blood glucose fluctuations in Chinese patients with type-2 diabetes mellitus (T2DM).

METHODS

A total of 458 hospitalized patients with T2DM were selected. According to the SUA level, patients were divided into four groups by quartile: Q1 (≤ 254.5 µmol/L), Q2 (254.5-306.0 µmol/L), Q3 (306.0-385.5 µmol/L) and Q4 (> 385.5 µmol/L). The differences in general data, TIR and other clinical indicators between the four groups were assessed. Multifactor regression was used to analyze the relationship between subgroups of SUA and TIR, TBR, TAR, MAGE, SD, ADRR, MODD and M value. Curve fitting was used to analyze the association between TIR and SUA and to identify the inflection point.

RESULTS

TIR showed an overall increasing trend with increasing SUA, while HbA1c, TAR, MAGE, SD, ADRR, MODD and M value showed an overall decreasing trend with increasing SUA. Multivariate regression analysis showed that, compared with Q1, there was no correlation between SUA and TIR, TAR, ADRR, SD, or MODD in all models of Q2. In the Q3 and Q4 groups, SUA was correlated with SD, MODD, and MAGE in all models. In the Q4 group, SUA was correlated with TIR, TAR, ADRR, and the M value in all models. When SUA > 306 µmol/L (Q3 and Q4), TIR and SUA have a curve-like relationship, and the inflection point of the fitted curve was SUA = 460 mmol/L. Before the inflection point, β was 0.1, indicating that when SUA increases by 10 mmol/L, the corresponding TIR increases by 1%. After the inflection point, there was no significant difference in the correlation between TIR and SUA (P > 0.05).

CONCLUSIONS

There is a close relationship between TIR and SUA in T2DM patients, it is speculated that SUA in a certain range had a positive protective effect on blood glucose control.

Effectiveness of Continuous Glucose Monitoring on Metrics of Glycemic Control in Type 2 Diabetes Mellitus: A Systematic Review and Meta-analysis of Randomized Controlled Trials

PURPOSE

To provide a systematic review and meta-analysis synthesizing the findings of randomized controlled trials (RCTs) of continuous glucose monitors (CGMs) in the management of adults with type 2 diabetes mellitus (T2DM) on glucose control and clinical outcomes.

METHODS

MEDLINE, Embase, and Cochrane were searched for RCTs that assessed the effectiveness of real-time CGM (rt-CGM) or flash CGM (FGM) in adults (≥18 years) with T2DM that reported on at least 1 of the following outcomes: hemoglobin A1c (HbA1c), time in range, time in hyperglycemia, or time in hypoglycemia. The GRADE approach was used to assess certainty of evidence for primary outcomes.

RESULTS

Fourteen RCTs assessing CGM were included, with 825 patients in 9 RCTs using rt-CGM and 822 in 5 RCTs using FGM. Moderate certainty of evidence indicated that use of CGM had a modest but statistically significant reduction in HbA1c levels of about 0.32%. Our analyses of each device type separately showed similar reductions in HbA1c (0.34% and 0.33%, respectively, for rt-CGM and FGM), with trends for improvement in other glucose metrics favoring rt-CGM over self-monitored blood glucose.

CONCLUSION

Both rt-CGM and flash CGM led to modest but statistically significant declines in HbA1c among individuals with T2DM, with little heterogeneity in the results. However, the duration of the included RCTs was relatively short and few studies reported on important clinical outcomes, such as adverse events, emergency department use, or hospitalization. Longer term studies are needed to determine if the short-term improvements in glucose control leads to improvements in clinically important outcomes.

Use of Diabetes Technologies and Retinopathy in Adults With Type 1 Diabetes

Importance

Diabetic retinopathy (DR) is a complication of diabetes that can lead to vision loss. Outcomes of continuous glucose monitoring (CGM) and insulin pump use in DR are not well understood.

Objective

To assess the use of CGM, insulin pump, or both, and DR and proliferative diabetic retinopathy (PDR) in adults with type 1 diabetes (T1D).

Design, Setting, and Participants

A retrospective cohort study of adults with T1D in a tertiary diabetes center and ophthalmology center was conducted from 2013 to 2021, with data analysis performed from June 2022 to April 2023.

Exposure

Use of diabetes technologies, including insulin pump, CGM, and both CGM and insulin pump.

Main Outcomes and Measures

The primary outcome was development of DR or PDR. A secondary outcome was the progression of DR for patients in the longitudinal cohort. Multivariable logistic regression models assessed for development of DR and PDR and association with CGM and insulin pump use.

Results

A total of 550 adults with T1D were included (median age, 40 [IQR, 28-54] years; 54.4% female; 24.5% Black or African American; and 68.4% White), with a median duration of diabetes of 20 (IQR, 10-30) years, and median hemoglobin A1c (HbA1c) of 7.8% (IQR, 7.0%-8.9%). Overall, 62.7% patients used CGM, 58.2% used an insulin pump, and 47.5% used both; 44% (244 of 550) of the participants had DR at any point during the study. On univariate analysis, CGM use was associated with lower odds of DR and PDR, and CGM with pump was associated with lower odds of PDR (all P < .05), compared with no CGM use. Multivariable logistic regression adjusting for age, sex, race and ethnicity, diabetes duration, microvascular and macrovascular complications, insurance type, and mean HbA1c, showed that CGM was associated with lower odds of DR (odds ratio [OR], 0.52; 95% CI, 0.32-0.84; P = .008) and PDR (OR, 0.42; 95% CI, 0.23-0.75; P = .004), compared with no CGM use. In the longitudinal analysis of participants without baseline PDR, 79 of 363 patients (21.8%) had progression of DR during the study.

Conclusions and Relevance

In this cohort study of adults with T1D, CGM use was associated with lower odds of developing DR and PDR, even after adjusting for HbA1c. These findings suggest that CGM may be useful for diabetes management to mitigate risk for DR and PDR.

Determination of Time in Range Associated With HbA1c ≤7% in a Prospective Cohort of Patients With Type 1 Diabetes Using Continuous Glucose Monitoring for Three Months

INTRODUCTION

Finding a goal of time in range (%TIR) that defines good glycemic control is necessary. Previous retrospective studies suggest good concordance between HbA1c ≤7% with a TIR >70%; however, the studies that included the largest number of patients used blood glucose measurement data with a follow-up time of less than 90 days. This study defined the TIR value that best discriminates HbA1c ≤7%.

METHODS

We performed a prospective study of diagnostic tests based on a cohort of patients with type 1 diabetes (T1D) treated with a hybrid closed loop (HCL) followed for three months. The ability of %TIR to distinguish patients with HbA1c ≤7% was evaluated through receiver operating characteristic curve analysis. We determined the %TIR cutoff point with the best operating characteristics.

RESULTS

A total of 118 patients were included (58.1% women, 47% overweight or obese, and 33% with high glycemic variability). A moderate negative correlation (R = -.54, P < .001) was found between %TIR and HbA1c. The discrimination ability was moderate, with an area under the curve of 0.7485 (95% confidence interval = 0.6608-0.8363). The cutoff point that best predicted HbA1c ≤7% was %TIR ≥75.5 (sensitivity 70%, specificity 67%). The findings were similar among those with a coefficient of variation (CV%) ≥36%.

CONCLUSIONS

Our data suggest that the %TIR adequately identifies patients with HbA1c ≤7%. A target of TIR ≥75%, rather than the currently recommended TIR ≥70%, may be a more suitable value for optimal glycemic control.

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.

Risk factors and the CCTA application in patients with vulnerable coronary plaque in type 2 diabetes: a retrospective study

BACKGROUND

Diabetes is an independent risk factor for cardiovascular disease. The purpose of this study was to identify the risk factors for vulnerable coronary plaques (VCPs), which are associated with adverse cardiovascular events, and to determine the value of coronary CT angiography (CCTA) in patients with type 2 diabetes mellitus (T2DM) and VCPs.

METHODS

Ninety-eight T2DM patients who underwent CCTA and intravascular ultrasound (IVUS) were retrospectively included and analyzed. The patients were grouped and analyzed according to the presence or absence of VCPs.

RESULTS

Among the patients with T2DM, time in range [TIR {the percentage of time blood glucose levels were in the target range}] (OR = 0.93, 95% CI = 0.89-0.96; P < 0.001) and the high-density lipoprotein-cholesterol (HDL-C) concentration (OR = 0.24, 95% CI = 0.09-0.63; P = 0.04) were correlated with a lower risk of VCP, but the triglycerides (TG) concentration was correlated with a higher risk of VCP (OR = 1.79, 95% CI = 1.01-3.18; P = 0.045). The area under the receiver operator characteristic curve (AUC) of TIR, and HDL-C and TG concentrations were 0.76, 0.73, and 0.65, respectively. The combined predicted AUC of TIR, and HDL-C and TG concentrations was 0.83 (P < 0.05). The CCTA sensitivity, specificity, false-negative, and false-positive values for the diagnosis of VCP were 95.74%, 94.12%, 4.26%, and 5.88%, respectively. The identification of VCP by CCTA was positively correlated with IVUS (intraclass correlation coefficient [ICC] = 0.90).

CONCLUSIONS

The TIR and HDL-C concentration are related with lower risk of VCP and the TG concentration was related with higher risk of VCP in patients with T2DM. In clinical practice, TIR, HDL-C and TG need special attention in patients with T2DM. The ability of CCTA to identify VCP is highly related to IVUS findings.

Guideline for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition)

With the deepening of aging in China, the prevalence of diabetes in older people has increased noticeably, and standardized diabetes management is critical for improving clinical outcomes of diabetes in older people. In 2021, the National Center of Gerontology, Chinese Society of Geriatrics, and Diabetes Professional Committee of Chinese Aging Well Association organized experts to write the first guideline for diabetes diagnosis and treatment in older people in China, the Guideline for the Management of Diabetes Mellitus in the Elderly in China (2021 Edition). The guideline emphasizes that older patients with diabetes are a highly heterogeneous group requiring comprehensive assessment and stratified and individualized management strategies. The guideline proposes simple treatments and de-intensified treatment strategies for older patients with diabetes. This edition of the guideline provides clinicians with practical and operable clinical guidance, thus greatly contributing to the comprehensive and full-cycle standardized management of older patients with diabetes in China and promoting the extensive development of clinical and basic research on diabetes in older people and related fields. In the past 3 years, evidence-based medicine for older patients with diabetes and related fields has further advanced, and new treatment concepts, drugs, and technologies have been developed. The guideline editorial committee promptly updated the first edition of the guideline and compiled the Guideline for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition). More precise management paths for older patients with diabetes are proposed, for achieving continued standardization of the management of older Chinese patients with diabetes and improving their clinical outcomes.

Exploring the Impact of Glycemic Control on Diabetic Retinopathy: Emerging Models and Prognostic Implications

This review addresses the complexities of type 1 diabetes (T1D) and its associated complications, with a particular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of this review is devoted to technological advances in diabetes management, particularly the use of hybrid closed-loop systems (HCLSs) and to the potential of open-source HCLSs, which could be easily adapted to different patients' needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.

Glycemic Variability As a Prognostic Factor for Mortality in Patients With Critical Illness: A Systematic Review and Meta-Analysis

OBJECTIVES

To perform a systematic review and meta-analysis to evaluate the association of various measures of glycemic variability, including time-domain and complexity-domain, with short-term mortality in patients with critical illness.

DATA SOURCES

We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to November 3, 2023.

STUDY SELECTION

We included English language studies that assessed metrics of glycemic variation or complexity and short-term mortality in patients admitted to the ICU.

DATA EXTRACTION

Two authors performed independent data abstraction and risk-of-bias assessments. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios and mean difference. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty of pooled estimates.

DATA SYNTHESIS

We included 41 studies (n = 162,259). We demonstrate that increased sd, coefficient of variance, glycemic lability index, and decreased time in range are probably associated with increased mortality in critically ill patients (moderate certainty) and that increased mean absolute glucose, mean amplitude of glycemic excursion, and detrended fluctuation analysis may be associated with increased mortality (low certainty).

CONCLUSIONS

We found a consistent association between increased measures of glycemic variability and higher short-term mortality in patient with critical illness. Further research should focus on standardized measurements of glycemic variation and complexity, along with their utility as therapeutic targets and prognostic markers.

Effects of continuous glucose monitoring on glycaemic control in type 2 diabetes: A systematic review and network meta-analysis of randomized controlled trials

AIMS

The aim of this study was to assess the efficacy of continuous glucose monitoring (CGM) versus self-monitoring of blood glucose (SMBG) in maintaining glycaemic control among people with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

The protocol was registered in PROSPERO (CRD42023387583). PubMed, Web of Science, EMBASE and OVID databases were searched from 1 January 2000 until 31 December 2022 for randomized controlled trials comparing CGM with SMBG in glycaemic control among the outpatients with T2DM. The primary endpoint was glycated haemoglobin, while the secondary endpoints included time in range, time below range and time above range. Both traditional and network meta-analyses were conducted to explore the efficacy of CGM on glycaemic control in T2DM.

RESULTS

Eleven high-quality studies, involving 1425 individuals with T2DM, were identified. Traditional meta-analysis revealed that CGM exhibited a significantly decreased [mean difference (MD): -0.31, 95% confidence interval (CI) (-0.45, -0.18)], time above range [MD: -9.06%, 95% CI (-16.00, -2.11)], time below range [MD: -0.30%, 95% CI (-0.49, -0.12)] and a significantly increased time in range [MD: 8.49%, 95% CI (3.96, 13.02)] compared with SMBG. The network meta-analysis showed that real-time CGM can improve the glycaemic control of patients with T2DM to the most extent.

CONCLUSIONS

CGM could provide T2DM with greater benefits in glycaemic management compared with SMBG, particularly in patients using real-time CGM. These findings provide an updated perspective on previous research and offer guidance for CGM use in T2DM.

Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Over the past two decades, there has been continuous advancement in the accuracy and complexity of continuous glucose monitoring devices. Continuous glucose monitoring provides valuable insights into blood glucose dynamics, and can record glucose fluctuations accurately and completely. Glycemic variability (GV) is a straightforward measure of the extent to which a patient's blood glucose levels fluctuate between high peaks and low nadirs. Many studies have investigated the relationship between GV and complications, primarily in the context of type 2 diabetes. Nevertheless, the exact contribution of GV to the development of diabetes complications remains unclear. In this literature review, we aimed to summarize the existing evidence regarding the measurement, target level, pathophysiological mechanisms relating GV and tissue damage, and population-based studies of GV and diabetes complications. Additionally, we introduce novel methods for measuring GV, and discuss several unresolved issues of GV. In the future, more longitudinal studies and trials are required to confirm the exact role of GV in the development of diabetes complications.

Impact of glucose variability on the assessment of the glycemia risk index (GRI) and classic glycemic metrics

OBJECTIVE

To evaluate the impact of glucose variability on the relationship between the GRI and other glycemic metrics in a cohort of pediatric and adult patients with type 1 diabetes (T1D) using intermittent scanning continuous glucose monitoring (isCGM).

METHODS

We performed a cross-sectional study of 202 patients with T1D under intensive insulin treatment (25.2% CSII) using isCGM. Clinical, metabolic, and glycemic metrics were collected, and the GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. The correlation between the GRI and other classical glycometrics in relation to the coefficient of variation (CV) was evaluated.

RESULTS

A total of 202 patients were included (53% male; 67.8% adults) with a mean age of 28.6 ± 15.7 years and 12.5 ± 10.9 years of T1D evolution (TIR 59.0 ± 17.0%; CV 39.8 ± 8.0%; GMI 7.3 ± 1.1%). The mean GRI was 54.0 ± 23.3 with a CHypo and CHyper component of 5.7 ± 4.8 and 23.4 ± 14.3, respectively. A strong negative correlation was observed between the GRI and TIR (R = -0.917; R2 = 0.840; p < 0.001), showing differences when dividing patients with low glycemic variability (CV < 36%) (R = -0.974; R2 = 0.948; p < 0.001) compared to those with greater CV instability (≥36%) (R = -0.885; R2 = 0.784; p < 0.001). The relationship of GRI with its two components was strongly positive with CHyper (R = 0.801; R2 = 0.641; p < 0.001) and moderately positive with CHypo (R = 0.398; R2 = 0.158; p < 0.001). When the GRI was evaluated with the rest of the classic glycemic metrics, a strong positive correlation was observed with HbA1c (R = 0.617; R2 = 0.380; p < 0.001), mean glucose (R = 0.677; R2 = 0.458; p < 0.001), glucose standard deviation (R = 0.778; R2 = 0.605; p < 0.001), TAR > 250 (R = 0.801; R2 = 0.641; p < 0.001), and TBR < 54 (R = 0.481; R2 = 0.231; p < 0.001).

CONCLUSIONS

The GRI correlated significantly with all the glycemic metrics analyzed, especially with the TIR. Glycemic variability (GV) significantly affected the correlation of the GRI with other parameters and should be taken into consideration.

Patient and physician perspectives and experiences of basal insulin titration in type 2 diabetes in the United States: Cross-sectional surveys

AIM

Patient- and physician-associated barriers impact the effectiveness of basal insulin (BI) titration in the management of type 2 diabetes (T2D). We evaluated the experiences of patients with T2D and physicians with BI titration education.

MATERIALS AND METHODS

In this observational, cross-sectional study, patients with T2D and physicians treating patients with T2D were identified by claims in the Optum Research Database and were invited to complete a survey. Eligible patients had 12 months of continuous health-plan enrolment with medical and pharmacy benefits during the baseline period, and recent initiation of BI therapy. Eligible physicians had initiated BI for ≥1 eligible patient with T2D during the past 6 months.

RESULTS

In total, 416 patients and 386 physicians completed the survey. Ninety per cent of physicians reported treating ≥50 patients with T2D; 66% treated ≥25% of patients with BI. Whereas 74% of patients reported that BI titration was explained to them by a physician, 96% of physicians reported doing so. Furthermore, 20% of patients stated they were offered educational materials whereas 56% of physicians reported having provided materials. Physicians had higher expectations of glycaemic target achievement than were seen in the patient survey; their main concern was the patients' ability to titrate accurately (79%).

CONCLUSIONS

There is a marked difference in patients' and physicians' experiences of BI titration education. Novel tools and strategies are required to enable effective BI titration, with more educational resources at the outset, and ongoing access to tools that provide clear, simple direction for self-titration with less reliance on physicians/health care providers.

Time in range and complications of diabetes: a cross-sectional analysis of patients with Type 1 diabetes

BACKGROUND/ OBJECTIVE

To evaluate the association of CGM parameters and HbA1c with diabetes complications in patients with Type 1 Diabetes (T1D).

METHODS

Patients with T1D using the CGM system Freestyle Libre were included in this analysis. The association of CGM-metrics and HbA1c with diabetes complications (any complication, microvascular complications, or macrovascular complications) was assessed using logistic regression unadjusted and adjusted for age, sex, and diabetes duration (model 1), and further adjusted for hypertension and dyslipidemia (model 2).

RESULTS

One hundred and sixty-one patients with T1D were included. The mean (± SD) age was 37.4 ± 13.4 years old and the median T1D duration was 17.7 ± 10.6 years. Time in range (TIR) was associated with any complication and microvascular complications in the unadjusted model and in the adjusted models. TIR was associated with retinopathy in the unadjusted model as well as in model 1, and was associated with macrovascular complications only in the unadjusted model. HbA1c was associated with any complications, microvascular complications, and retinopathy in the unadjusted model but not in the adjusted models. HbA1c was associated with macrovascular complications in the unadjusted model and in the adjusted model 1.

CONCLUSIONS

In this cross-sectional analysis of patients with T1D using intermittent scanned CGM, TIR, and HbA1c were associated with complications of diabetes. TIR may be a better predictor than HbA1c of any complication and microvascular complications, while HbA1c may be a better predictor of macrovascular complications.

Interaction between haptoglobin genotype and glycemic variability on diabetic macroangiopathy: a population-based cross-sectional study

PURPOSE

Haptoglobin (Hp) is a hemoglobin-binding protein that functions as an antioxidant in human plasma. It is reported that glycemic variability (GV) plays a key role in diabetes-related complications associated with impaired glucose metabolism and oxidative stress. Here we aim to investigate whether the effect of GV on diabetic macroangiopathy depends on Hp genotype in type 2 diabetes.

METHODS

A number of 860 Chinese patients with type 2 diabetes was genotyped and assigned to two Hp subgroups (Hp 2-2 and Hp 1 carriers). Glycemic variability (GV) was assessed by using a retrospective continuous glucose monitoring system for three consecutive days, and it was measured using the glucose coefficient of variation (%CV), which is calculated as the ratio of glucose standard deviation to glucose mean. Clinical features, history of cardiac surgery, and vascular imaging tests were utilized to diagnose macroangiopathy. We evaluated the interaction between Hp genotypes and %CV on diabetic macroangiopathy. Furthermore, serum concentration of 8-hydroxy-2'-deoxyguanosine (8-OHdG) was measured using an enzyme-linked immunosorbent assay as a biomarker of oxidative stress.

RESULTS

Serum 8-OHdG levels were positively correlated with %CV in Hp 1 carriers (r = 0.117; p = 0.021). Patients in the highest %CV tertile were associated with a higher prevalence of diabetic macroangiopathy than those in the lowest %CV tertile in Hp 1 carriers (OR = 2.461 [95% CI, 1.183-5.121], p = 0.016), but not in those with Hp 2-2 genotype (OR = 0.540 [95% CI, 0.245-1.191], p = 0.127). A significant interactive effect of Hp genotypes and %CV on diabetic macroangiopathy was found (p interaction = 0.008).

CONCLUSION

Hp genotype modifies the effect of GV on diabetic macroangiopathy among Chinese patients with type 2 diabetes.

What else can we do to prevent diabetic retinopathy?

The classical modifiable factors associated with the onset and progression of diabetic retinopathy are the suboptimal control of blood glucose levels and hypertension, as well as dyslipidaemia. However, there are other less recognised modifiable factors that can play a relevant role, such as the presence of obesity or the abnormal distribution of adipose tissue, and others related to lifestyle such as the type of diet, vitamin intake, exercise, smoking and sunlight exposure. In this article we revisit the prevention of diabetic retinopathy based on modulating the modifiable risk factors, as well as commenting on the potential impact of glucose-lowering drugs on the condition. The emerging concept that neurodegeneration is an early event in the development of diabetic retinopathy points to neuroprotection as a potential therapeutic strategy to prevent the advanced stages of the disease. In this regard, the better phenotyping of very early stages of diabetic retinopathy and the opportunity of arresting its progression using treatments targeting the neurovascular unit (NVU) are discussed.

Comprehensive retinal vascular measurements: time in range is associated with peripheral retinal venular calibers in type 2 diabetes in China

AIM

Retinal vascular parameters are biomarkers of diabetic microangiopathy. We aimed to investigate the relationship between time in range (TIR) assessed by continuous glucose monitoring (CGM) and retinal vascular parameters in patients with type 2 diabetes in China.

METHODS

The TIR assessed by CGM and retinal photographs were obtained at the same time from adults with type 2 diabetes who were recruited. Retinal vascular parameters were extracted from retinal photographs by a validated fully automated computer program, and TIR was defined as between 3.9-7.8 mmol/L over a 24-h period. The association between TIR and caliber of retinal vessels distributed in different zones were analyzed using multivariable linear regression analyses.

RESULTS

For retinal vascular parameters measurements, the peripheral arteriovenous and middle venular calibers widen with decreasing TIR quartiles (P < 0.05). Lower TIR was associated with wider peripheral venule after adjusting for potential confounders. Even after further correction for GV, there was still a significant correlation between TIR and peripheral vascular calibers (CV: β = - 0.015 [- 0.027, - 0.003], P = 0.013; MAGE: β = - 0.013 [- 0.025, - 0.001], P = 0.038) and SD: β = - 0.013 [- 0.026, - 0.001], P = 0.004). Similar findings were not found for the middle and central venular calibers or arterial calibers located in different zones.

CONCLUSIONS

The TIR was associated with adverse changes to peripheral retinal venules but not central and middle vessels in patients with type 2 diabetes, suggesting that peripheral retinal vascular calibers may be affected by glycemic fluctuations earlier.

Spanish Consensus on the Use of Intermittently Scanned Continuous Glucose Monitoring in the Management of Patients With Insulin Therapy: The MONITOR Project

BACKGROUND

Continuous glucose monitoring (CGM) systems are increasingly being adopted as an alternative or adjunct to self-monitoring of blood glucose (SMBG) by patients receiving insulin therapy. However, the available evidence on the role of intermittently scanned CGM or flash CGM (isCGM) remains limited. This consensus aims to evaluate the degree of agreement among Spanish experts on the role of isCGM in the evaluation of glycemic variability, reduction of glycosylated hemoglobin (HbA1c) levels, and selection and adjustment of insulin therapy.

METHODS

Delphi methodology was used to achieve consensus in two survey rounds. A total of 431 Spanish endocrinologists participated in the first round of a 34-item questionnaire survey on isCGM and 427 participated in the second round. Any disagreement was resolved in round 2.

RESULTS

Consensus was reached for 32 statements, and four items were ultimately agreed upon SMBG after round 2. There was a high degree of consensus that isCGM helps to evaluate glycemic variability, improves HbA1c levels, and can guide therapeutic changes in type 1 diabetes patients. However, there was no consensus on the routine use of the interquartile range to evaluate glycemic variability or the selection of HbA1c as the main parameter for monitoring glycemic control.

CONCLUSIONS

Most Spanish experts believe that the isCGM system is appropriate for: (1) identifying glycemic variability and facilitating its management, (2) evaluating hyperglycemia as a complement of HbA1c levels, and (3) guiding therapeutic decisions on insulin selection and dosing. The isCGM system is a useful tool for patients and health care professionals to improve glycemic control in insulin-dependent diabetes.

Expert Recommendations for Using Time-in-Range and Other Continuous Glucose Monitoring Metrics to Achieve Patient-Centered Glycemic Control in People With Diabetes

New metrics for assessing glycemic control beyond HbA1c have recently emerged due to the increasing use of continuous glucose monitoring (CGM) in diabetes clinical practice. Among them, time in range (TIR) has appeared as a simple and intuitive metric that correlates inversely with HbA1c and has also been newly linked to the risk of long-term diabetes complications. The International Consensus on Time in Range established a series of target glucose ranges (TIR, time below range and time above range) and recommendations for time spent within these ranges for different diabetes populations. These parameters should be evaluated together with the ambulatory glucose profile (AGP). Using standardized visual reporting may help people with diabetes and healthcare professionals in the evaluation of glucose control in frequent clinical situations. The objective of the present review is to provide practical insights to quick interpretation of patient-centered metrics based on flash glucose monitoring data, as well as showing some visual examples of common clinical situations and giving practical recommendations for their management.

Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review

Diabetes mellitus is a metabolic disorder with a complex etiology in which glycemic dynamics are disturbed and the body is unable to maintain the process of glucose homeostasis through the pancreas. Persistent symptoms of high blood glucose or low blood glucose may lead to diabetic complications, such as neuropathy, nephropathy, retinopathy, and cardiovascular diseases. Glycemic variability which can represent the presence of excessive glycemic excursions is an indicator for evaluating glucose homoeostasis. Limiting glycemic variability has gradually become an emerging therapeutic target in improve diabetes metabolism and prevent associated complications. This article reviews the progress of research on the various quantifiable parameters of glycemic variability and their relationships with vascular lesions and mechanisms.

Healthcare Professionals' Knowledge of and Attitudes Towards the Use of Time in Range in Diabetes Management: Online Survey Across Seven Countries

INTRODUCTION

Time in range (TIR) is a metric of glycaemic target management derived from continuous glucose monitoring (CGM) data. This study aimed to understand knowledge of and attitudes towards use of TIR among healthcare professionals (HCPs), and gain insights into benefits and barriers to its use in clinical practice.

METHODS

An online survey was disseminated across seven countries. Participants were sampled from online HCP panels and were aware of TIR (defined as amount of time in, below, and above target range). Participants were HCPs classified as specialists (SP), generalists (GP), or allied HCPs (AP; diabetes nurse specialists, diabetes educators, general nurses, nurse practitioners/physician assistants).

RESULTS

Respondents included 741 SP, 671 GP and 307 AP. Most HCPs (approximately 90%) agreed TIR is likely/somewhat likely to become the standard of diabetes management. Perceived benefits of TIR included helping to optimise medication regimen (SP, 71%; GP, 73%; AP, 74%), giving HCPs the knowledge and insights to make informed clinical decisions (SP, 66%; GP, 61%; AP, 72%), and empowering people with diabetes with information to successfully manage their diabetes (SP, 69%; GP, 77%; AP, 78%). Barriers to wider adoption included limited CGM access (SP, 65%; GP, 74%; AP, 69%) and lack of HCP training/education (SP, 45%; GP, 59%; AP, 51%). Most participants considered integration of TIR into clinical guidelines, recognition of TIR by regulators as a primary clinical endpoint, and recognition of TIR by payers as a parameter for diabetes treatment evaluation as key factors for increased use.

CONCLUSIONS

Overall, HCPs agreed on the benefits of using TIR for diabetes management. Besides raising awareness among HCPs and people with diabetes, more training and healthcare system updates are needed to facilitate increased TIR use. In addition, integration into clinical guidelines and recognition by regulators and payers are needed.

Time in Range Estimation in Patients with Type 2 Diabetes is Improved by Incorporating Fasting and Postprandial Glucose Levels

INTRODUCTION

Time in range (TIR) as assessed by continuous glucose monitoring (CGM) measures an individual's glucose fluctuations within set limits in a time period and is increasingly used together with HbA1c in patients with diabetes. HbA1c indicates the average glucose concentration but provides no information on glucose fluctuation. However, before CGM becomes available for patients with type 2 diabetes (T2D) worldwide, especially in developing nations, fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) are still the common biomarkers used for monitoring diabetes conditions. We investigated the importance of FPG and PPG to glucose fluctuation in patients with T2D. We used machine learning to provide a new estimate of TIR based on the HbA1c, together with FPG and PPG.

METHODS

This study included 399 patients with T2D. (1) Univariate and (2) multivariate linear regression models and (3) random forest regression models were developed to predict the TIR. Subgroup analysis was performed in the newly diagnosed T2D population to explore and optimize the prediction model for patients with different disease history.

RESULTS

Regression analysis suggests that FPG was strongly linked to minimum glucose, while PPG was strongly correlated with maximum glucose. After FPG and PPG were incorporated into the multivariate linear regression model, the prediction performance of TIR was improved compared with the univariate correlation between HbA1c and TIR, and the correlation coefficient (95% CI) increased from 0.62 (0.59, 0.65) to 0.73 (0.72, 0.75) (p < 0.001). The random forest model significantly outperformed the linear model (p < 0.001) in predicting TIR through FPG, PPG and HbA1c, with a stronger correlation coefficient 0.79 (0.79, 0.80).

CONCLUSIONS

The results offered a comprehensive understanding of glucose fluctuations through FPG and PPG compared to HbA1c alone. Our novel TIR prediction model based on random forest regression with FPG, PPG, and HbA1c provides a better prediction performance than the univariate model with solely HbA1c. The results indicate a nonlinear relationship between TIR and glycaemic parameters. Our results suggest that machine learning may have the potential to be used in developing better models for understanding patients' disease status and providing necessary interventions for glycaemic control.

Expanding the Role of Continuous Glucose Monitoring in Modern Diabetes Care Beyond Type 1 Disease

Application of continuous glucose monitoring (CGM) has moved diabetes care from a reactive to a proactive process, in which a person with diabetes can prevent episodes of hypoglycemia or hyperglycemia, rather than taking action only once low and high glucose are detected. Consequently, CGM devices are now seen as the standard of care for people with type 1 diabetes mellitus (T1DM). Evidence now supports the use of CGM in people with type 2 diabetes mellitus (T2DM) on any treatment regimen, not just for those on insulin therapy. Expanding the application of CGM to include all people with T1DM or T2DM can support effective intensification of therapies to reduce glucose exposure and lower the risk of complications and hospital admissions, which are associated with high healthcare costs. All of this can be achieved while minimizing the risk of hypoglycemia and improving quality of life for people with diabetes. Wider application of CGM can also bring considerable benefits for women with diabetes during pregnancy and their children, as well as providing support for acute care of hospital inpatients who experience the adverse effects of hyperglycemia following admission and surgical procedures, as a consequence of treatment-related insulin resistance or reduced insulin secretion. By tailoring the application of CGM for daily or intermittent use, depending on the patient profile and their needs, one can ensure the cost-effectiveness of CGM in each setting. In this article we discuss the evidence-based benefits of expanding the use of CGM technology to include all people with diabetes, along with a diverse population of people with non-diabetic glycemic dysregulation.

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.

Current Perspective on the Potential Benefits of Smart Insulin Pens on Glycemic Control in Patients With Diabetes: Spanish Delphi Consensus

INTRODUCTION

Diabetes mellitus (DM) is a chronic disease with high morbidity and mortality, and glycemic control is key to avoiding complications. Technological innovations have led to the development of new tools to help patients with DM manage their condition.

OBJECTIVE

This consensus assesses the current perspective of physicians on the potential benefits of using smart insulin pens in the glycemic control of patients with type 1 diabetes (DM1) in Spain.

METHODS

The Delphi technique was used by 110 physicians who were experts in managing patients with DM1. The questionnaire consisted of 94 questions.

RESULTS

The consensus obtained was 95.74%. The experts recommended using the ambulatory glucose profile report and the different time-in-range (TIR) metrics to assess poor glycemic control. Between 31% and 65% of patients had TIR values less than 70% and were diagnosed based on glycosylated hemoglobin values. They believed that less than 10% of patients needed to remember to administer the basal insulin dose and between 10% and 30% needed to remember the prandial insulin dose.

CONCLUSIONS

The perception of physicians in their usual practice leads them to recommend the use of ambulatory glucose profile and time in range for glycemic control. Forgetting to administer insulin is a very common problem and the actual occurrence rate does not correspond with clinicians' perceptions. Technological improvements and the use of smart insulin pens can increase treatment adherence, strengthen the doctor-patient relationship, and help improve patients' education and quality of life.

The clinical implications of fasting serum insulin levels in patients with insulin-treated type 2 diabetes: a cross-sectional survey

Objective

This study aimed to investigate the clinical implications of fasting serum insulin (FINS) levels in subjects with type 2 diabetes who were receiving insulin therapy.

Methods

A total of 1,553 subjects with type 2 diabetes [774 subjects who had never received insulin treatment (N-INS) and 779 subjects who were receiving insulin therapy (constant insulin treatment, C-INS)] admitted to the Department of Endocrinology and Metabolism of Peking University People's Hospital were enrolled in this study. Their FINS levels were measured and those with hyperinsulinemia were identified. The underlying mechanisms of hyperinsulinemia were revealed by measuring insulin antibodies (IAs) and analyzing changes in FINS levels before and after polyethylene glycol (PEG) precipitation. In addition, the clinical characteristics of patients with different types of hyperinsulinemia were compared.

Results

Higher FINS levels and a higher incidence (43.8%, 341/779) of hyperinsulinemia (FINS > 15μIU/mL) were observed in subjects with C-INS than in subjects with N-INS. Among subjects with C-INS and hyperinsulinemia, 66.9% (228/341) were IAs positive, and the incidence of IAs was found to be positively associated with FINS level. By performing PEG precipitation, we found that all subjects without IAs (i.e., those with real hyperinsulinemia) and 31.1% of subjects (71/228) with IAs (i.e., those with both real and IAs-related hyperinsulinemia) still had hyperinsulinemia after PEG precipitation, whereas FINS levels in the other 68.9% of subjects (157/228) with IAs were normal (IAs-related hyperinsulinemia) after PEG precipitation. Comparisons between the groups showed that subjects with real hyperinsulinemia showed more obvious insulin resistance characteristics, including higher lipid levels, BMIs, and homoeostasis model assessment2-estimated insulin resistance (HOMA2-IR) index, and were more likely to have hypertension, obesity, and metabolic syndromes (p < 0.05). However, the risk of hypoglycemia and glucose variability increased significantly in subjects with IAs compared with those without IAs. A cutoff of FINS to serum C-peptide ratio (≥ 9.3μIU/ng) could be used to screen IAs in clinical practice with 83.3% sensitivity and 70% specificity.

Conclusions

It is necessary to measure FINS in subjects with C-INS to distinguish between types of hyperinsulinemia, which should help to tailor treatment regimens.

Machine Learning-Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study

BACKGROUND

Continuous glucose monitoring (CGM) for diabetes combines noninvasive glucose biosensors, continuous monitoring, cloud computing, and analytics to connect and simulate a hospital setting in a person's home. CGM systems inspired analytics methods to measure glycemic variability (GV), but existing GV analytics methods disregard glucose trends and patterns; hence, they fail to capture entire temporal patterns and do not provide granular insights about glucose fluctuations.

OBJECTIVE

This study aimed to propose a machine learning-based framework for blood glucose fluctuation pattern recognition, which enables a more comprehensive representation of GV profiles that could present detailed fluctuation information, be easily understood by clinicians, and provide insights about patient groups based on time in blood fluctuation patterns.

METHODS

Overall, 1.5 million measurements from 126 patients in the United Kingdom with type 1 diabetes mellitus (T1DM) were collected, and prevalent blood fluctuation patterns were extracted using dynamic time warping. The patterns were further validated in 225 patients in the United States with T1DM. Hierarchical clustering was then applied on time in patterns to form 4 clusters of patients. Patient groups were compared using statistical analysis.

RESULTS

In total, 6 patterns depicting distinctive glucose levels and trends were identified and validated, based on which 4 GV profiles of patients with T1DM were found. They were significantly different in terms of glycemic statuses such as diabetes duration (P=.04), glycated hemoglobin level (P<.001), and time in range (P<.001) and thus had different management needs.

CONCLUSIONS

The proposed method can analytically extract existing blood fluctuation patterns from CGM data. Thus, time in patterns can capture a rich view of patients' GV profile. Its conceptual resemblance with time in range, along with rich blood fluctuation details, makes it more scalable, accessible, and informative to clinicians.

Once-Weekly Insulin Icodec vs. Once-Daily Insulin Glargine U100 for type 2 diabetes: a systematic review and meta-analysis of phase 2 randomized controlled trials

Objective

Insulin Icodec is a novel basal insulin analogue designed for once-weekly administration, therefore might propitiate reduction in the frequency of injections and facilitate treatment adherence. This study aimed to determine the glycemic control and safety profile of Insulin Icodec, compared with Glargine U100 in patients with diabetes mellitus type 2.

Materials and methods

We performed a systematic review and meta-analysis of randomized controlled trials (RCT) data comparing OnceWeekly Insulin Icodec and Once-Daily Insulin Glargine U100 in patients with type 2 diabetes mellitus. PubMed, Embase, and Cochrane databases were searched for trials published up to May 14, 2022. Data were extracted from published reports and quality assessment was performed per Cochrane recommendations.

Results

Three studies were included comprising 453 patients, 230 (50.77%) using Once-Weekly Insulin Icodec and 223 (49.22%) using Once-Daily Insulin Glargine U100. In the pooled data, Glycated Hemoglobin (MD -0.20% CI -0.33 to -0.07%; P=0.002) change from baseline demonstrated a significantly higher reduction in the Icodec group. Time with Glucose in Range (MD 6.60% CI 3.63 to 9.57%; P < 0.0001) and Insulin Dose Difference (MD 0.97UI CI 0.76 to 1.18UI; P < 0.0001) were higher in the Icodec group. There was no significant difference in fasting plasma glucose, body weight change, hypoglycemia or any adverse event evaluated.

Conclusion

OnceWeekly Insulin Icodec was associated with a small reduction in Glycated Hemoglobin, as well as higher Time with Glucose in Range, with similar hypoglycemic adverse events, when compared with Once-Daily Insulin Glargine U100.

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.

Effect of Physical Activity on Metabolic Syndrome Markers in Adults with Type 2 Diabetes: A Systematic Review and Meta-Analysis

People with Type 2 diabetes mellitus (T2DM) are reported to have a high prevalence of metabolic syndrome (MetS), which increases their risk of cardiovascular events. Our aim was to determine the effect of physical activity (PA) on metabolic syndrome markers in people with T2DM. The study design was a systematic review and meta-analysis of randomised controlled trials evaluating the effect of PA on MetS in adults with T2DM. Relevant databases including SPORTdiscus, Cochrane Central Register of Controlled Trials, CINAHL, MEDLINE, PsycINFO, EMBASE, SocINDEX were searched up to August 2022. Primary endpoints were changes in MetS markers (blood pressure, triglyceride, high-density lipoprotein, fasting blood sugar, and waist circumference) after an exercise intervention. Using a random effect model with 95% confidence interval (CI), the mean difference between intervention groups and control groups were calculated. Twenty-six articles were included in the review. Overall, aerobic exercise had a significant effect on waist circumference (Mean Difference: -0.34 cm, 95% CI: -0.84, -0.05; effect size: 2.29, I² = 10.78%). The effect sizes on blood pressure, triglyceride, high-density lipoprotein, fasting blood sugar were not statistically significant. No significant differences were found between exercise and control group following resistance training. Our findings suggest that aerobic exercise can improve waist circumference in people with T2DM and MetS. However, both aerobic and resistance exercise produced no significant difference in the remaining MetS markers. Larger and higher-quality studies are required to determine the full effects of PA on MetS markers in this population.