HbA1c variability is independently associated with progression of diabetic kidney disease in an urban multi-ethnic cohort of people with type 1 diabetes.

AIMS/HYPOTHESIS: The role of HbA1c variability in the progression of diabetic kidney disease is unclear, with most studies to date performed in White populations and limited data on its role in predicting advanced kidney outcomes. Our aim was to evaluate if long-term intra-individual HbA1c variability is a risk factor for kidney disease progression (defined as an eGFR decline of ≥50% from baseline with a final eGFR of <30 ml/min per 1.73 m2) in an ethnically heterogeneous cohort of people with type 1 diabetes with a preserved eGFR ≥45 ml/min per 1.73 m2 at baseline. METHODS: Electronic health record data from people attending outpatient clinics between 2004 and 2018 in two large university hospitals in London were collected. HbA1c variability was assessed using three distinct methods: (1) SD of HbA1c (SD-HbA1c); (2) visit-adjusted SD (adj-HbA1c): SD-HbA1c/√n/(n-1), where n is the number of HbA1c measurements per participant; and (3) CV (CV-HbA1c): SD-HbA1c/mean-HbA1c. All participants had six or more follow-up HbA1c measurements. The eGFR was measured using the Chronic Kidney Disease Epidemiology Collaboration equation and clinical/biochemical results from routine care were extracted from electronic health records. RESULTS: In total, 3466 participants (50% female, 78% White, 13% African Caribbean, 3% Asian and 6% of mixed heritage or self-reporting as 'other') were followed for a median (IQR) of 8.2 (4.2-11.6) years. Of this cohort, 249 (7%) showed kidney disease progression. Higher HbA1c variability was independently associated with a higher risk of kidney disease progression, with HRs (95% CIs) of 7.76 (4.54, 13.26), 2.62 (1.75, 3.94) and 5.46 (3.40, 8.79) (lowest vs highest HbA1c variability quartile) for methods 1-3, respectively. Increasing age, baseline HbA1c, systolic BP and urinary albumin/creatinine ratio were also associated with kidney disease progression (p<0.05 for all). African Caribbean ethnicity was associated with an increased risk of kidney disease progression (HR [95% CI] 1.47 [1.09, 1.98], 1.76 [1.32, 2.36] and 1.57 [1.17, 2.12] for methods 1-3, respectively) and this effect was independent of glycaemic variability and other traditional risk factors. CONCLUSIONS/INTERPRETATION: We observed an independent association between HbA1c variability, evaluated using three distinct methods, and significant kidney disease progression in a multi-ethnic type 1 diabetes cohort. Further studies are needed to elucidate the mechanisms that may explain our results and evaluate if HbA1c variability is a modifiable risk factor for preventing diabetic kidney disease progression.

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.

Early treatment with dipeptidyl-peptidase 4 inhibitors reduces glycaemic variability and delays insulin initiation in type 2 diabetes: A propensity score-matched cohort study.

AIMS: To examine whether early treatment intensification using dipeptidyl-peptidase 4 inhibitors (DPP4i) delays insulin initiation in Chinese patients diagnosed with type 2 diabetes for less than 5 years. MATERIALS AND METHODS: In a territory-wide prospective cohort study, patients with type 2 diabetes initiating DPP4i at diabetes duration <2 years (early intensification) and 3-5 years (late intensification) were matched using 1:1 propensity-score matching (n = 908 in each arm). We used Cox regression to compare the risk of insulin initiation between the two groups. We explored the interactive and mediation effects of glycated haemoglobin (HbA1c) variability score (HVS), defined as the percentage of HbA1c varying by ≥0.5% compared with preceding values. RESULTS: Of 1816 patients (60.7% men, mean age 54.4 ± 11.9 years), 92.4% and 71.9% were treated with metformin and sulphonylureas respectively at DPP4i initiation. Early DPP4i intensification [hazard ratio (HR) 0.71, (95% CI 0.58-0.68)] and low HVS (<50%) (HR = 0.40, 0.33-0.50) were associated with delayed insulin initiation during a median 4.08 years of follow-up. Early intensification with low HVS had the lowest risk versus late intensification with high HVS (HR = 0.30, 0.22-0.40) (pinteraction  = 0.013). HVS mediated 19.5% of the total effect of early DPP4i intensification on delaying insulin initiation. The late and early intensification groups had similar HbA1c at month 0 (8.4 ± 1.3% vs. 8.4 ± 1.5%) and month 3 (7.6 ± 1.2% vs. 7.6 ± 1.3%) after DPP4i initiation. By month 12, HbA1c in the late intensification group deteriorated (7.9 ± 1.4%) but remained stable in the early intensification group (7.6 ± 1.4%, p = 0.001) with persistent between-group difference over 72 months (8.2 ± 1.7% vs. 7.7 ± 1.6%, p = 0.001). CONCLUSIONS: In type 2 diabetes, early DPP4i intensification delayed insulin initiation, partially explained by reduced glycaemic variability.

Intra-pancreatic fat is associated with continuous glucose monitoring metrics.

AIM: To investigate the relationship of fat in the pancreas with time spent in different glycaemic ranges. METHODS: Abdominal magnetic resonance imaging at 3.0 Tesla was used to quantify fat in the pancreas as both continuous [i.e. intra-pancreatic fat deposition (IPFD)] and binary (i.e. fatty change of the pancreas vs. normal pancreas) variables. Dexcom G6 devices were used to collect continuous glucose monitoring data every 5 min over a continuous 7-day period. Time above range (TAR), time in range (TIR) and time below range were computed. Statistical models were built to adjust for age, sex, body composition, and other covariates in linear regression analysis and analysis of covariance. RESULTS: In total, 38 individuals were studied. IPFD was significantly associated with TAR (p = .036) and TIR (p = .042) after adjustment for covariates. For every 1% increase in IPFD, there was a 0.3 unit increase in TAR and a decrease in TIR. Individuals with fatty change of the pancreas, when compared with those with normal pancreas, had significantly higher TAR (p = .034) and lower TIR (p = .047) after adjustment for covariates. Neither IPFD (p = .805) nor fatty change of the pancreas (p = .555) was associated with time below range after adjustment for covariates. CONCLUSION: Increased fat in the pancreas is associated with excessive glycaemic variability. Fatty change of the pancreas may contribute to heightening the risk of cardiovascular diseases.

Cross-sectional association of continuous glucose monitoring-derived metrics with cerebral small vessel disease in older adults with type 2 diabetes.

AIM: To examine cross-sectional associations between continuous glucose monitoring (CGM)-derived metrics and cerebral small vessel disease (SVD) in older adults with type 2 diabetes. MATERIALS AND METHODS: In total, 80 patients with type 2 diabetes aged ≥70 years were analysed. Participants underwent CGM for 14 days. From the CGM data, we derived mean sensor glucose, percentage glucose coefficient of variation, mean amplitude of glucose excursion, time in range (TIR, 70-180 mg/dl), time above range (TAR) and time below range metrics, glycaemia risk index and high/low blood glucose index. The presence of cerebral SVD, including lacunes, microbleeds, enlarged perivascular spaces and white matter hyperintensities, was assessed, and the total number of these findings comprised the total cerebral SVD score (0-4). Ordinal logistic regression analyses were performed to examine the association of CGM-derived metrics with the total SVD score. RESULTS: The median SVD score was 1 (interquartile range 0-2). Higher hyperglycaemic metrics, including mean sensor glucose, TAR >180 mg/dl, TAR >250 mg/dl, and high blood glucose index and glycaemia risk index, were associated with a higher total SVD score. In contrast, a higher TIR (per 10% increase) was associated with a lower total SVD score (odds ratio 0.73, 95% confidence interval 0.56-0.95). Glycated haemoglobin, percentage glucose coefficient of variation, mean amplitude of glucose excursions, time below range and low blood glucose index were not associated with total cerebral SVD scores. CONCLUSIONS: The hyperglycaemia metrics and TIR, derived from CGM, were associated with cerebral SVD in older adults with type 2 diabetes.

Chronic hyperglycaemia increases the vulnerability of the hippocampus to oxidative damage induced during post-hypoglycaemic hyperglycaemia in a mouse model of chemically induced type 1 diabetes.

AIMS/HYPOTHESIS: Chronic hyperglycaemia and recurrent hypoglycaemia are independently associated with accelerated cognitive decline in type 1 diabetes. Recurrent hypoglycaemia in rodent models of chemically induced (streptozotocin [STZ]) diabetes leads to cognitive impairment in memory-related tasks associated with hippocampal oxidative damage. This study examined the hypothesis that post-hypoglycaemic hyperglycaemia in STZ-diabetes exacerbates hippocampal oxidative stress and explored potential contributory mechanisms. METHODS: The hyperinsulinaemic glucose clamp technique was used to induce equivalent hypoglycaemia and to control post-hypoglycaemic glucose levels in mice with and without STZ-diabetes and Nrf2-/- mice (lacking Nrf2 [also known as Nfe2l2]). Subsequently, quantitative proteomics based on stable isotope labelling by amino acids in cell culture and biochemical approaches were used to assess oxidative damage and explore contributory pathways. RESULTS: Evidence of hippocampal oxidative damage was most marked in mice with STZ-diabetes exposed to post-hypoglycaemic hyperglycaemia; these mice also showed induction of Nrf2 and the Nrf2 transcriptional targets Sod2 and Hmox-1. In this group, hypoglycaemia induced a significant upregulation of proteins involved in alternative fuel provision, reductive biosynthesis and degradation of damaged proteins, and a significant downregulation of proteins mediating the stress response. Key differences emerged between mice with and without STZ-diabetes following recovery from hypoglycaemia in proteins mediating the stress response and reductive biosynthesis. CONCLUSIONS/INTERPRETATION: There is a disruption of the cellular response to a hypoglycaemic challenge in mice with STZ-induced diabetes that is not seen in wild-type non-diabetic animals. The chronic hyperglycaemia of diabetes and post-hypoglycaemic hyperglycaemia act synergistically to induce oxidative stress and damage in the hippocampus, possibly leading to irreversible damage/modification to proteins or synapses between cells. In conclusion, recurrent hypoglycaemia in sub-optimally controlled diabetes may contribute, at least in part, to accelerated cognitive decline through amplifying oxidative damage in key brain regions, such as the hippocampus. DATA AVAILABILITY: The datasets generated during and/or analysed during the current study are available in ProteomeXchange, accession no. 1-20220824-173727 ( www.proteomexchange.org ). Additional datasets generated during and/or analysed during the present study are available from the corresponding author upon reasonable request.

Higher HbA1c variability is associated with increased arterial stiffness in individuals with type 1 diabetes.

BACKGROUND: Both long-term glycaemic variability and arterial stiffness have been recognized as cardiovascular risk factors. This study aims to investigate whether an association between these phenomena exists in individuals with type 1 diabetes. METHODS: This cross-sectional study included 673 adults (305 men, 368 women) with type 1 diabetes and combined available retrospective laboratory data on HbA1c from the preceding 10 years with outcome data on arterial stiffness and clinical variables from a comprehensive study visit. HbA1c variability was calculated as adjusted standard deviation (adj-HbA1c-SD), coefficient of variation (HbA1c-CV) and average real variability (HbA1c-ARV). As measures of arterial stiffness, carotid-femoral pulse wave velocity (cfPWV; n = 335) and augmentation index (AIx; n = 653) were assessed using applanation tonometry. RESULTS: The study population had a mean age of 47.1 (± 12.0) years and a median duration of diabetes of 31.2 (21.2-41.3) years. The median number of HbA1c assessments per individual was 17 (12-26). All three indices of HbA1c variability were significantly correlated with both cfPWV and AIx after adjustment for sex and age (p < 0.001). In separate multivariable linear regression models, adj-HbA1c-SD and HbA1c-CV were significantly associated with cfPWV (p = 0.032 and p = 0.046, respectively) and AIx (p = 0.028 and p = 0.049, respectively), even after adjustment for HbA1c-mean. HbA1c-ARV was not associated with cfPWV or AIx in the fully adjusted models. CONCLUSIONS: An association independent of HbA1c-mean was found between HbA1c variability and arterial stiffness, suggesting a need to consider multiple HbA1c metrics in studies assessing cardiovascular risk in type 1 diabetes. Longitudinal and interventional studies are needed to confirm any causal relationship and to find strategies for reducing long-term glycaemic variability.

Cross-sectional association of metrics derived from continuous glucose monitoring with cognitive performance in older adults with type 2 diabetes.

AIM: To examine the association between continuous glucose monitoring (CGM)-derived metrics and cognitive performance in older adults with type 2 diabetes (T2D). MATERIALS AND METHODS: A total of 100 outpatients with T2D aged 70 years or older were analysed. Participants underwent CGM for 14 days. As CGM-derived metrics, mean sensor glucose (SG), glucose coefficient of variation (CV), time in range (TIR; 70-180 mg/dl), time above range (TAR; > 180 mg/dl) and time below range (TBR; < 70 mg/dl), were calculated. Participants underwent cognitive tests, including the Japanese version of the Montreal Cognitive Assessment (MoCA-J), a delayed word-recall test from the Alzheimer's Disease Assessment Scale-cognitive subscale, a digit symbol substitution test, a letter word fluency test, a trail-making test (TMT) and digit span test (DSP). RESULTS: In multiple regression analyses adjusted for confounders, a higher mean SG was associated with a lower performance in MoCA-J and TMT part B (TMT-B) (P < .05). A higher TAR was associated with a lower performance in TMT-B and DSP-backward (P < .05). By contrast, a higher TIR was associated with better function in TMT-B and DSP-backward (P < .05). Furthermore, CV and TBR were not associated with any cognitive function. CONCLUSION: Hyperglycaemia metrics and TIR derived from CGM are associated with cognitive functions, especially with executive function and working memory, in older adults with T2D.

Role of continuous glucose monitoring in diabetic patients at high cardiovascular risk: an expert-based multidisciplinary Delphi consensus.

BACKGROUND: Continuous glucose monitoring (CGM) shows in more detail the glycaemic pattern of diabetic subjects and provides several new parameters ("glucometrics") to assess patients' glycaemia and consensually guide treatment. A better control of glucose levels might result in improvement of clinical outcome and reduce disease complications. This study aimed to gather an expert consensus on the clinical and prognostic use of CGM in diabetic patients at high cardiovascular risk or with heart disease. METHODS: A list of 22 statements concerning type of patients who can benefit from CGM, prognostic impact of CGM in diabetic patients with heart disease, CGM use during acute cardiovascular events and educational issues of CGM were developed. Using a two-round Delphi methodology, the survey was distributed online to 42 Italian experts (21 diabetologists and 21 cardiologists) who rated their level of agreement with each statement on a 5-point Likert scale. Consensus was predefined as more than 66% of the panel agreeing/disagreeing with any given statement. RESULTS: Forty experts (95%) answered the survey. Every statement achieved a positive consensus. In particular, the panel expressed the feeling that CGM can be prognostically relevant for every diabetic patient (70%) and that is clinically useful also in the management of those with type 2 diabetes not treated with insulin (87.5%). The assessment of time in range (TIR), glycaemic variability (GV) and hypoglycaemic/hyperglycaemic episodes were considered relevant in the management of diabetic patients with heart disease (92.5% for TIR, 95% for GV, 97.5% for time spent in hypoglycaemia) and can improve the prognosis of those with ischaemic heart disease (100% for hypoglycaemia, 90% for hyperglycaemia) or with heart failure (87.5% for hypoglycaemia, 85% for TIR, 87.5% for GV). The experts retained that CGM can be used and can impact the short- and long-term prognosis during an acute cardiovascular event. Lastly, CGM has a recognized educational role for diabetic subjects. CONCLUSIONS: According to this Delphi consensus, the clinical and prognostic use of CGM in diabetic patients at high cardiovascular risk is promising and deserves dedicated studies to confirm the experts' feelings.

The continuous spectrum of glycaemic variability changes with pancreatic islet function: A multicentre cross-sectional study in China.

AIMS: To investigate glycaemic variability (GV) patterns in patients with type 1 diabetes (T1D), type 2 diabetes (T2D), and latent autoimmune diabetes in adults (LADA). MATERIALS AND METHODS: A total of 842 subjects (510 T1D, 105 LADA, 227 T2D) were enrolled and underwent 1 week of continuous glucose monitoring (CGM). Clinical characteristics and CGM parameters were compared among T1D, LADA, and T2D. LADA patients were divided into two subgroups based on glutamic acid decarboxylase autoantibody titres (≥180 U/mL [LADA-1], <180 U/mL [LADA-2]) and compared. The C-peptide cut-offs for predicting a coefficient of variation (CV) of glucose ≥36% and a time in range (TIR) > 70% were determined using receiver operating characteristic analysis. RESULTS: Twenty-seven patients (9 T1D, 18 T2D) were excluded due to insufficient CGM data. Sex, diabetes duration and HbA1c were comparable among the three groups. Fasting and 2-h postprandial C-peptide (FCP, 2hCP) increased sequentially across T1D, LADA, and T2D. T1D and LADA patients had comparable TIR and GV, whereas those with T2D had much higher TIR and lower GV (p < 0.001). The GV of LADA-1 was close to that of T1D, while the GV of LADA-2 was close to that of T2D. CP exhibited the strongest negative correlation with GV. The cut-offs of FCP/2hCP for predicting a CV ≥ 36% and TIR >70% were 121.6/243.1 and 128.9/252.8 pmol/L, respectively. CONCLUSIONS: GV presented a continuous spectrum across T1D, LADA-1, LADA-2, and T2D. More frequent glucose monitoring is suggested for patients with impaired insulin secretion. CLINICAL TRAIL REGISTRATION: Chinese Clinical Trial Registration (ChiCTR) website approved by WHO; http://www.chictr.org.cn/ - ChiCTR2200065036.

Glucose Awareness to Motivate and Enable Solutions (GAMES) in diabetes mellitus using flash glucose monitoring: A clinical programme.

AIMS: This real-world observational clinical programme evaluated short and medium-term effects of intermittent flash glucose monitoring on HbA1c, glycaemic variability and lifestyle behavioural changes. METHODS: Two first-generation Libre flash glucose monitoring sensors were provided 3-4 months apart with a food, activity diary, user evaluation survey and treatment modification after each sensor wear. T-tests were used to compare glucose variables within each sensor (week 1 vs. week 2) and between sensors (1st sensor vs. 2nd sensor). EasyGV software was used to calculate glycaemic variability. RESULTS: From 42 type 1 diabetes and 120 type 2 diabetes participants, there was no statistically significant change in mean HbA1c for participants with type 1 diabetes at 3-4 months after the 1st sensor but there was a statistically significant HbA1c reduction for participants with type 2 diabetes [-4 mmol/mol (-0.4%), p = 0.008], despite no statistically significant differences in carbohydrate intake, exercise frequency and duration. Greater reduction was seen in those with baseline HbA1c> 86 mmol/mol (10%) in both type 1 [-12 mmol/mol (-1.1%), p = 0.009] and type 2 diabetes [-11 mmol/mol (-1.0%), p = 0.001). Both type 1 and type 2 diabetes showed improvements in Glucose Management Indicator and percentage time-above-range when comparing week 1 versus week 2 of the same sensor. Higher scan frequency resulted in improved glycaemic parameters and certain measures of glycaemic variability. The majority of participants (85%) agreed that flash glucose monitoring is a useful device but only 60% were keen to use it for daily monitoring. CONCLUSION: Constant feedback from flash glucose monitoring improves glycaemic parameters within the first week of wear. Intermittent use 3-4 months apart resulted in greater improvements for those with higher baseline HbA1c.

Towards targeted dietary support for shift workers with type 2 diabetes (Shift-Diabetes study): A mixed-methods case study protocol.

BACKGROUND: Blood glucose is higher in people working night shifts compared to day workers. Changes to eating behaviour, activity and sleep patterns in addition to circadian disruption are likely to impact glucose management in night-shift workers with type 2 diabetes. AIM: To investigate current dietary intake and glucose variability during night work, including barriers and facilitators to dietary behaviour in this context. METHODS: A mixed-methods case study will be conducted. Shift workers with type 2 diabetes working in a hospital setting will be recruited to this two-part study. Part 1: 70 participants will complete a 10-day observational study collecting data on continuous glucose, diet (self-report diary), sleep and physical activity during a period covering night work, rest days and non-night workdays. Mean glucose concentration and variability, and the mean healthy diet index score, will be compared between days of night work, non-night work and rest, after adjusting for other individual factors (sleep/physical activity/demographics). Part 2: A sample (n~13) will complete semi-structured interviews based on behavioural science frameworks to explore barriers/enablers to dietary behaviour when working night shifts. This will inform a quantitative survey to explore the generalisability of interview findings. DISCUSSION: Findings from Part 1 and 2 will be triangulated to identify potential intervention strategies to address key barriers and enablers to healthier eating, and in turn improved glucose control, in shift workers with type 2 diabetes. This will be facilitated through stakeholder consultation and application of behavioural science frameworks. Shift-Diabetes study registration: ISRCTN11764942.

Continuous glucose monitoring to assess glucose variability in type 3c diabetes.

AIM: The effectiveness of continuous glucose monitoring (CGM) in maintaining glycaemic control in type 1 diabetes mellitus and type 2 diabetes mellitus has been well demonstrated. However, the degree of glycaemic variability (GV) in people with type 3c diabetes mellitus has not been fully explored using CGM. This study aims to evaluate GV in type 3c diabetes mellitus participants and compare it to type 1 diabetes mellitus and type 2 diabetes mellitus. METHODS: Participants were grouped according to type of diabetes. GV, defined as percentage coefficient of variation (%CV), and other glycaemic indices were obtained using CGM (FreeStyle Libre, Abbott, Australia) from 82 participants across all three cohorts over a 14-day period. Comparison of baseline characteristics and GV were performed across all groups. Correlation of GV with C-peptide values, and whether pancreatic supplementation had an effect on GV were also assessed in the type 3c diabetes mellitus cohort. RESULTS: GV of type 3c diabetes mellitus participants was within the recommended target of less than %CV 36% (p = 0.004). Type 3c diabetes mellitus participants had the lowest GV among the three groups (p = 0.001). There was a trend for lower C-peptide levels to be associated with higher GV in type 3c diabetes mellitus participants (p = 0.22). Pancreatic enzyme supplementation in type 3c diabetes mellitus participants did not have an effect on GV (p = 0.664). CONCLUSIONS: Although type 3c diabetes mellitus participants were the least variable, they had the highest mean glucose levels and estimated HbA1c , which suggests that the concept of 'brittle' diabetes in type 3c diabetes mellitus is not supported by the results of CGM in this study and may be leading to poorer glycaemic control.

Remembrance of things past: The consequences of recurrent hypoglycaemia in diabetes.

AIMS: People with type 1 and type 2 diabetes still frequently experience hypoglycaemia, which can be severe, leading to loss of consciousness. This review will examine the cellular consequences of recurrent hypoglycaemia. METHODS: This review, based on the Dorothy Hodgkin Lecture given at the Diabetes UK 2022 annual symposium by the author, will discuss our current understanding of the mechanisms by which hypoglycaemia is detected and the consequences of recurrent exposure to hypoglycaemia. RESULTS: Glucose-responsive cells found in the periphery as well as multiple areas of the brain are organised in a classical sensori-motor integrative network encompassing peripheral, hindbrain and hypothalamic components. The mechanism used by glucose-responsive neurons to detect hypoglycaemia parallel those of the classical glucose sensor the pancreatic ß-cell, namely in their use of glucokinase, KATP channels and AMP-activated protein kinase. Recurrent exposure to hypoglycaemia results in a series of cellular adaptations that may be designed to increase the resilience of cells to future hypoglycaemia. This review also highlights how hypoglycaemia, as an oxidative stressor, may also exacerbate chronic hyperglycaemia-induced increases in oxidative stress and inflammation, leading to damage to vulnerable brain regions. CONCLUSIONS: Impaired awareness of hypoglycaemia follows the adaptation of central glucose-responsive neurons to repeated hypoglycaemia and may represent a form of memory called habituation. In diabetes, recurrent hypoglycaemia may have tissue consequences as a result of a profound disruption in the cellular response to a hypoglycaemic challenge that increases vulnerability to oxidative damage.

Impact of anxiety, depression and disease-related distress on long-term glycaemic variability among subjects with Type 1 diabetes mellitus.

BACKGROUND: Anxiety, depression, and disease-related distress are linked to worse overall glycaemic control, in terms of HbA1c. This study was aimed to evaluate whether traits of these emotional disorders are associated with long-term glycaemic variability in subjects with Type 1 diabetes. METHODS: Longitudinal retrospective study. Six-year HbA1c data (2014-2019) from 411 subjects with Type 1 diabetes who had participated in a previous study to design a diabetes-specific quality of life questionnaire in the year 2014 were included. Scores for Spanish versions of the Hospital Anxiety and Depression Scale (HADS) and Problem Areas in Diabetes (PAID) scale were obtained at baseline, along with sociodemographic and clinical data. Long-term glycaemic variability was measured as the coefficient of variation of HbA1c (HbA1c-CV). The association between HADS and PAID scores and HbA1c-CV was analysed with Spearman correlations and multiple regression models, both linear and additive, including other covariates (age, sex, diabetes duration time, type of treatment, baseline HbA1c, use of anxiolytic or antidepressant drugs, education level and employment status). RESULTS: Scores of depression, anxiety and distress were positively and significantly correlated to HbA1c-CV in univariate analyses. Multiple regression study demonstrated an independent association only for diabetes distress score (p < 0.001). Age, diabetes duration time, baseline HbA1c, education level and employment status were also significantly associated with HbA1c-CV. However, when subjects were analyzed separately in two age groups, distress scores were associated with HbA1c-CV only among those aged 25 years or older, while anxiety scores, but not distress, were associated with HbA1c-CV among those younger than 25 years. CONCLUSIONS: Psychological factors, particularly disease-related distress and anxiety, are associated with long-term glycaemic variability in subjects with Type 1 diabetes.

Glycaemic Control in Patients Undergoing Percutaneous Coronary Intervention: What Is the Role for the Novel Antidiabetic Agents? A Comprehensive Review of Basic Science and Clinical Data.

Coronary artery disease (CAD) remains one of the most important causes of morbidity and mortality worldwide, and revascularization through percutaneous coronary interventions (PCI) significantly improves survival. In this setting, poor glycaemic control, regardless of diabetes, has been associated with increased incidence of peri-procedural and long-term complications and worse prognosis. Novel antidiabetic agents have represented a paradigm shift in managing patients with diabetes and cardiovascular diseases. However, limited data are reported so far in patients undergoing coronary stenting. This review intends to provide an overview of the biological mechanisms underlying hyperglycaemia-induced vascular damage and the contrasting actions of new antidiabetic drugs. We summarize existing evidence on the effects of these drugs in the setting of PCI, addressing pre-clinical and clinical studies and drug-drug interactions with antiplatelet agents, thus highlighting new opportunities for optimal long-term management of these patients.

Sleep quality and glycaemic variability in a real-life setting in adults with type 1 diabetes.

AIMS/HYPOTHESIS: Suboptimal subjective sleep quality is very common in adults with type 1 diabetes. Reducing glycaemic variability is a key objective in this population. To date, no prior studies have examined the associations between objectively measured sleep quality and overnight glycaemic variability in adults with type 1 diabetes. We aimed to test the hypothesis that poor sleep quality would be associated with greater overnight glycaemic variability. METHODS: Data were collected in the home setting from 20 adults (ten male and ten female participants) with type 1 diabetes who were current insulin pump users. Simultaneous assessments of objective sleep quality (Zmachine Insight+) and continuous glucose monitoring (CGM) were performed over multiple nights (up to 15 nights) in each participant. Due to the real-life nature of this study, the participants kept their usual CGM alerts for out-of-range glucose values. Sleep quality was categorised as 'good' or 'poor' using a composite of objective sleep features (i.e. sleep efficiency, wake after sleep onset and number of awakenings) based on the National Sleep Foundation's consensus criteria. Glycaemic variability was quantified using SD and CV of overnight glucose values based on overnight CGM profiles. RESULTS: A total of 170 nights were analysed. Overall, 86 (51%) nights were categorised as good sleep quality, and 84 (49%) nights were categorised as poor sleep quality. Using linear mixed-effects models, poor sleep quality was significantly associated with greater glycaemic variability as quantified by SD (coefficient: 0.39 [95% CI 0.10, 0.67], p = 0.009) and CV (coefficient: 4.35 [95% CI 0.8, 7.9], p = 0.02) of overnight glucose values, after accounting for age, sex, BMI and overnight insulin dose. There was large inter- and intra-individual variability in sleep and glycaemic characteristics. Both pooled and individual-level data revealed that the nights with poor sleep quality had larger SDs and CVs, and, conversely, the nights with good sleep quality had smaller SDs and CVs. No associations were found between sleep quality and time spent in the target glucose range, or above or below the target glucose range, where CGM alarms are most likely to occur. CONCLUSIONS/INTERPRETATION: Objectively measured sleep quality is associated with overnight glycaemic variability in adults with type 1 diabetes. These findings highlight an important role of sleep quality in overnight glycaemic control in type 1 diabetes. They also provide a strong incentive to both patients and healthcare providers for considering sleep quality in personalised type 1 diabetes glycaemic management plans. Future studies should investigate the mechanisms linking sleep quality to glycaemic variability.

The effects of dapagliflozin, metformin or exercise on glycaemic variability in overweight or obese individuals with prediabetes (the PRE-D Trial): a multi-arm, randomised, controlled trial.

AIMS/HYPOTHESIS: We aimed to investigate the short-term efficacy and safety of three glucose-lowering interventions in overweight or obese individuals with prediabetes defined by HbA1c. METHODS: The PRE-D Trial was a randomised, controlled, parallel, multi-arm, open-label, non-blinded trial performed at Steno Diabetes Center Copenhagen, Gentofte, Denmark. One hundred and twenty participants with BMI ≥25 kg/m2, 30-70 years of age, and prediabetes (HbA1c 39-47 mmol/mol [5.7-6.4%]) were randomised 1:1:1:1 to dapagliflozin (10 mg once daily), metformin (1700 mg daily), interval-based exercise (5 days/week, 30 min/session) or control (habitual lifestyle). Participants were examined at baseline and at 6, 13 and 26 weeks after randomisation. The primary outcome was the 13 week change in glycaemic variability (calculated as mean amplitude of glycaemic excursions [MAGE]) determined using a continuous glucose monitoring system (pre-specified minimal clinically important difference in MAGE ∼30%). RESULTS: One hundred and twelve participants attended the examination at 13 weeks and 111 attended the follow-up visit at 26 weeks. Compared with the control group, there was a small decrease in MAGE in the dapagliflozin group (17.1% [95% CI 0.7, 30.8], p = 0.042) and a small, non-significant, reduction in the exercise group (15.3% [95% CI -1.2, 29.1], p = 0.067), whereas MAGE was unchanged in the metformin group (0.1% [95% CI -16.1, 19.4], p = 0.991)). Compared with the metformin group, MAGE was 17.2% (95% CI 0.8, 30.9; p = 0.041) lower in the dapagliflozin group and 15.4% (95% CI -1.1, 29.1; p = 0.065) lower in the exercise group after 13 weeks, with no difference between exercise and dapagliflozin (2.2% [95% CI -14.8, 22.5], p = 0.815). One serious adverse event occurred in the control group (lung cancer). CONCLUSIONS/INTERPRETATION: Treatment with dapagliflozin and interval-based exercise lead to similar but small improvements in glycaemic variability compared with control and metformin therapy. The clinical importance of these findings in prediabetes is uncertain. TRIAL REGISTRATION: ClinicalTrials.gov NCT02695810 FUNDING: The study was funded by the Novo Nordisk Foundation, AstraZeneca AB, the Danish Innovation Foundation, the University of Copenhagen and Ascensia Diabetes Care Denmark ApS Graphical abstract.

Consequences of recurrent hypoglycaemia on brain function in diabetes.

The discovery of insulin and its subsequent mass manufacture transformed the lives of people with type 1 and 2 diabetes. Insulin, however, was a drug with a 'dark side'. It brought with it the risk of iatrogenic hypoglycaemia. In this short review, the cellular consequences of recurrent hypoglycaemia, with a particular focus on the brain, are discussed. Using the ventromedial hypothalamus as an exemplar, this review highlights how recurrent hypoglycaemia has an impact on the specialised cells in the brain that are critical to the regulation of glucose homeostasis and the counterregulatory response to hypoglycaemia. In these cells, recurrent hypoglycaemia initiates a series of adaptations that ensure that they are more resilient to subsequent hypoglycaemia, but this leads to impaired hypoglycaemia awareness and a paradoxical increased risk of severe hypoglycaemia. This review also highlights how hypoglycaemia, as an oxidative stressor, may also exacerbate chronic hyperglycaemia-induced increases in oxidative stress and inflammation, leading to damage to vulnerable brain regions (and other end organs) and accelerating cognitive decline. Pre-clinical research indicates that glucose recovery following hypoglycaemia is considered a period where reactive oxygen species generation and oxidative stress are pronounced and can exacerbate the longer-term consequence of chronic hypoglycaemia. It is proposed that prior glycaemic control, hypoglycaemia and the degree of rebound hyperglycaemia interact synergistically to accelerate oxidative stress and inflammation, which may explain why increased glycaemic variability is now increasingly considered a risk factor for the complications of diabetes.

The glycaemic compass: Time in range.

This communication describes a contemporary model of diabetes monitoring and therapy assessment, the Time-in-range'(TIR), as the Glycaemic compass. The term 'compass' is apt, as it reflects the dynamic nature of TIR concept. TIR can be used not only as a target, but also as a tool to achieve this target, to explain the importance of good control, and to facilitate changes in therapeutic approach. The theranostic nature of TIR allows it to be termed as a compass for glycaemic control.