Metabolic effect of adrenaline infusion in people with type 1 diabetes and healthy individuals.

AIMS/HYPOTHESIS: As a result of early loss of the glucagon response, adrenaline is the primary counter-regulatory hormone in type 1 diabetes. Diminished adrenaline responses to hypoglycaemia due to counter-regulatory failure are common in type 1 diabetes, and are probably induced by exposure to recurrent hypoglycaemia, however, the metabolic effects of adrenaline have received less research attention, and also there is conflicting evidence regarding adrenaline sensitivity in type 1 diabetes. Thus, we aimed to investigate the metabolic response to adrenaline and explore whether it is modified by prior exposure to hypoglycaemia. METHODS: Eighteen participants with type 1 diabetes and nine healthy participants underwent a three-step ascending adrenaline infusion during a hyperinsulinaemic-euglycaemic clamp. Continuous glucose monitoring data obtained during the week before the study day were used to assess the extent of hypoglycaemia exposure. RESULTS: While glucose responses during the clamp were similar between people with type 1 diabetes and healthy participants, plasma concentrations of NEFAs and glycerol only increased in the group with type 1 diabetes (p<0.001). Metabolomics revealed an increase in the most common NEFAs (p<0.01). Other metabolic responses were generally similar between participants with type 1 diabetes and healthy participants. Exposure to hypoglycaemia was negatively associated with the NEFA response; however, this was not statistically significant. CONCLUSIONS/INTERPRETATION: In conclusion, individuals with type 1 diabetes respond with increased lipolysis to adrenaline compared with healthy participants by mobilising the abundant NEFAs in plasma, whereas other metabolic responses were similar. This may suggest that the metabolic sensitivity to adrenaline is altered in a pathway-specific manner in type 1 diabetes. TRIAL REGISTRATION: ClinicalTrials.gov NCT05095259.

Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials.

AIMS/HYPOTHESIS: The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events. METHODS: Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately. Poisson mixed models, adjusted for age, sex, diabetes duration and trial identifier were fitted to assess the association of clinical variables with hypoglycaemia event counts. Tree-based gradient-boosting algorithms (XGBoost) were fitted using training data and their predictive performance in terms of area under the receiver operating characteristic curve (AUC) evaluated on test data. Baseline models including age, sex and diabetes duration were compared with models that further included a score of hypoglycaemia in the first 6 weeks from study entry, and full models that included further clinical variables. The relative predictive importance of each covariate was assessed using XGBoost's importance procedure. Prediction across the entire trial duration for each trial (mean of 34.8 weeks for type 1 diabetes and 25.3 weeks for type 2 diabetes) was assessed. RESULTS: For both type 1 and type 2 diabetes, variables associated with more frequent hypoglycaemia included female sex, white ethnicity, longer diabetes duration, treatment with human as opposed to analogue-only insulin, higher glucose variability, higher score for hypoglycaemia across the 6 week baseline period, lower BP, lower lipid levels and treatment with psychoactive drugs. Prediction of any hypoglycaemia event of any severity was greater than prediction of hypoglycaemia requiring assistance (level 3 hypoglycaemia), for which events were sparser. For prediction of level 1 or worse hypoglycaemia during the whole follow-up period, the AUC was 0.835 (95% CI 0.826, 0.844) in type 1 diabetes and 0.840 (95% CI 0.831, 0.848) in type 2 diabetes. For level 3 hypoglycaemia, the AUC was lower at 0.689 (95% CI 0.667, 0.712) for type 1 diabetes and 0.705 (95% CI 0.662, 0.748) for type 2 diabetes. Compared with the baseline models, almost all the improvement in prediction could be captured by the individual's hypoglycaemia history, glucose variability and blood glucose over a 6 week baseline period. CONCLUSIONS/INTERPRETATION: Although hypoglycaemia rates show large variation according to sociodemographic and clinical characteristics and treatment history, looking at a 6 week period of hypoglycaemia events and glucose measurements predicts future hypoglycaemia risk.

The impact of prior exposure to hypoglycaemia on the inflammatory response to a subsequent hypoglycaemic episode.

BACKGROUND: Hypoglycaemia has been shown to induce a systemic pro-inflammatory response, which may be driven, in part, by the adrenaline response. Prior exposure to hypoglycaemia attenuates counterregulatory hormone responses to subsequent hypoglycaemia, but whether this effect can be extrapolated to the pro-inflammatory response is unclear. Therefore, we investigated the effect of antecedent hypoglycaemia on inflammatory responses to subsequent hypoglycaemia in humans. METHODS: Healthy participants (n = 32) were recruited and randomised to two 2-h episodes of either hypoglycaemia or normoglycaemia on day 1, followed by a hyperinsulinaemic hypoglycaemic (2.8 ± 0.1 mmol/L) glucose clamp on day 2. During normoglycaemia and hypoglycaemia, and after 24 h, 72 h and 1 week, blood was drawn to determine circulating immune cell composition, phenotype and function, and 93 circulating inflammatory proteins including hs-CRP. RESULTS: In the group undergoing antecedent hypoglycaemia, the adrenaline response to next-day hypoglycaemia was lower compared to the control group (1.45 ± 1.24 vs 2.68 ± 1.41 nmol/l). In both groups, day 2 hypoglycaemia increased absolute numbers of circulating immune cells, of which lymphocytes and monocytes remained elevated for the whole week. Also, the proportion of pro-inflammatory CD16+-monocytes increased during hypoglycaemia. After ex vivo stimulation, monocytes released more TNF-α and IL-1ß, and less IL-10 in response to hypoglycaemia, whereas levels of 19 circulating inflammatory proteins, including hs-CRP, increased for up to 1 week after the hypoglycaemic event. Most of the inflammatory responses were similar in the two groups, except the persistent pro-inflammatory protein changes were partly blunted in the group exposed to antecedent hypoglycaemia. We did not find a correlation between the adrenaline response and the inflammatory responses during hypoglycaemia. CONCLUSION: Hypoglycaemia induces an acute and persistent pro-inflammatory response at multiple levels that occurs largely, but not completely, independent of prior exposure to hypoglycaemia. Clinical Trial information Clinicaltrials.gov no. NCT03976271 (registered 5 June 2019).

Frequency of hypoglycaemia with basal insulin treatments in adults with type 1 diabetes treated with basal-bolus insulin regimens in treat-to-target trials: A narrative review.

AIM: To summarise, in a narrative review, published data on hypoglycaemia occurrence with basal insulin therapy in adults with type 1 diabetes treated with basal-bolus insulin regimens in treat-to-target randomised controlled trials. METHODS: Data were included from 21 eligible trials, which mainly used self-measured blood glucose or plasma glucose to detect hypoglycaemia. RESULTS: All-day self-measured blood glucose or plasma glucose level 2 (glucose threshold of 3.1 or 3.0 mmol/L) and level 3 (severe, requiring assistance) hypoglycaemic events were reported, respectively, by a range of 69.0%-97.5% and 0%-13.4% adults when receiving basal-bolus insulin therapy, with rates of 10.6-68.1 and 0.0-0.4 events per patient-year of exposure, respectively. Hypoglycaemia rates measured using continuous glucose monitoring (three studies) were numerically, yet consistently, higher than with either other method, except when limiting to symptomatic events. Nocturnal hypoglycaemia rates were generally less than 30% of the equivalent all-day rates. CONCLUSIONS: Differences across the studies in design (e.g., titration targets) and participant characteristics hindered comparison of hypoglycaemia rates by insulin formulation. Consequently, few trends were identified by insulin formulation, study methodology or individuals' characteristics, suggesting that further research is required to identify treatment strategies that facilitate development of individualised recommendations to lower hypoglycaemia risk. These findings are useful to understand hypoglycaemia risk with available basal insulin therapies when used in a multiple daily injection regimen, as well as to provide context for the results of ongoing and future clinical trials, including those for two once-weekly basal insulins, insulin icodec and basal insulin Fc.

Healthcare professionals' competencies and confidence in managing hospitalized patients with type 2 diabetes.

AIMS: In hospitals, 15%-20% of patients have diabetes. Therefore, all healthcare professionals (HCPs) must have a basic knowledge of in-hospital diabetes management. This survey assessed the knowledge of diabetes among HCPs in Denmark. METHODS: A 27-item questionnaire was developed and reviewed independently before the survey was distributed. The questionnaire contained seven baseline questions on the HCPs' current workplace, educational level, usual shift routines and years of experience, 18 multiple-choice questions and 2 cases. RESULTS: A total of 252 completed questionnaires were returned by 133 (52.8%) physicians, 101 (40.1%) nurses and 18 (7.1%) healthcare assistants. HCPs answered 50% of the questions correctly. Having experience from endocrinological departments increased the correct response score (0%-100%) by 6.2% points (95% CI 0.3-12.1) (p = 0.039) and 3.1% points (95% CI 1.5-4.7) for every increase in confidence level on a scale from 1 to 10 (p < 0.001). HCPs scored 8 out of 10 on a confidence level scale on average. In a fictive case, 50% of HCPs administered the correct bolus insulin dose. Hyperglycaemia (>10.0 mmol/L) and hypoglycaemia (<3.9 mmol/L) were correctly identified by around 40% of HCPs. Hypoglycaemia was rated more important than hyperglycaemia by most HCPs. CONCLUSION: Significant gaps in identifying hypo- and hyperglycaemia and correct administration of bolus insulin have been identified, which could be targeted in future education for HCPs. HCPs answered 50% of questions related to in-hospital diabetes management correctly. Experience from endocrinological departments and self-rated confidence levels are associated with HCPs' in-hospital diabetes competencies.

Associations of clinical, psychological, and sociodemographic characteristics and ecological momentary assessment completion in the 10-week Hypo-METRICS study: Hypoglycaemia MEasurements ThResholds and ImpaCtS.

INTRODUCTION: Reporting of hypoglycaemia and its impact in clinical studies is often retrospective and subject to recall bias. We developed the Hypo-METRICS app to measure the daily physical, psychological, and social impact of hypoglycaemia in adults with type 1 and insulin-treated type 2 diabetes in real-time using ecological momentary assessment (EMA). To help assess its utility, we aimed to determine Hypo-METRICS app completion rates and factors associated with completion. METHODS: Adults with diabetes recruited into the Hypo-METRICS study were given validated patient-reported outcome measures (PROMs) at baseline. Over 10 weeks, they wore a blinded continuous glucose monitor (CGM), and were asked to complete three daily EMAs about hypoglycaemia and aspects of daily functioning, and two weekly sleep and productivity PROMs on the bespoke Hypo-METRICS app. We conducted linear regression to determine factors associated with app engagement, assessed by EMA and PROM completion rates and CGM metrics. RESULTS: In 602 participants (55% men; 54% type 2 diabetes; median(IQR) age 56 (45-66) years; diabetes duration 19 (11-27) years; HbA1c 57 (51-65) mmol/mol), median(IQR) overall app completion rate was 91 (84-96)%, ranging from 90 (81-96)%, 89 (80-94)% and 94(87-97)% for morning, afternoon and evening check-ins, respectively. Older age, routine CGM use, greater time below 3.0 mmol/L, and active sensor time were positively associated with app completion. DISCUSSION: High app completion across all app domains and participant characteristics indicates the Hypo-METRICS app is an acceptable research tool for collecting detailed data on hypoglycaemia frequency and impact in real-time.

Real-life hypoglycaemia partially blunts the inflammatory response to experimental hypoglycaemia in people with type 1 diabetes.

AIM: To determine whether recent repeated exposure to real-life hypoglycaemia affects the pro-inflammatory response during a hypoglycemia episode. MATERIALS AND METHODS: This was a post hoc analysis of a hyperinsulinaemic normoglycaemic-hypoglycaemic clamp study, involving 40 participants with type 1 diabetes. Glucose levels 1 week before the clamp were monitored using a Freestyle Libre 1. Blood was drawn during normoglycaemia and hypoglycaemia, and 24 hours after resolution of hypoglycaemia for measurements of inflammatory responses and counterregulatory hormone levels. We determined the relationship between the frequency and duration of spontaneous hypoglycaemia, and time below range (TBR) and the inflammatory response to experimental hypoglycaemia. RESULTS: On average, participants experienced 0.79 (0.43, 1.14) hypoglycaemia episodes per day, with a duration of 78 (47, 110) minutes and TBR of 5.5% (2.8%, 8.5%). TBR and hypoglycaemia frequency were inversely associated with the increase in circulating granulocyte and lymphocyte counts during experimental hypoglycaemia (P < .05 for all). A protein network consisting of DNER, IF-R, uPA, Flt3L, FGF-5 and TWEAK was negatively associated with hypoglycaemia frequency (P < .05), but not with the adrenaline response. Neither other counterregulatory hormones, nor hypoglycaemia awareness status, was associated with any of the inflammatory parameters markers. CONCLUSIONS: Repeated exposure to spontaneous hypoglycaemia is associated with blunted effects of subsequent experimental hypoglycaemia on circulating immune cells and the number of inflammatory proteins.

The effect of bolus advisors on glycaemic parameters in adults with diabetes on intensive insulin therapy: A systematic review with meta-analysis.

AIM: To conduct a systematic review with meta-analysis to provide a comprehensive synthesis of randomized controlled trials (RCTs) and prospective cohort studies investigating the effects of currently available bolus advisors on glycaemic parameters in adults with diabetes. MATERIALS AND METHODS: An electronic search of PubMed, Embase, CINAHL, Cochrane Library and ClinicalTrials.gov was conducted in December 2022. The risk of bias was assessed using the revised Cochrane Risk of Bias tool. (Standardized) mean difference (MD) was selected to determine the difference in continuous outcomes between the groups. A random-effects model meta-analysis and meta-regression were performed. This systematic review was registered on PROSPERO (CRD42022374588). RESULTS: A total of 18 RCTs involving 1645 adults (50% females) with a median glycated haemoglobin (HbA1c) concentration of 8.45% (7.95%-9.30%) were included. The majority of participants had type 1 diabetes (N = 1510, 92%) and were on multiple daily injections (N = 1173, 71%). Twelve of the 18 trials had low risk of bias. The meta-analysis of 10 studies with available data on HbA1c showed that the use of a bolus advisor modestly reduced HbA1c compared to standard treatment (MD -011%, 95% confidence interval -0.22 to -0.01; I2 = 0%). This effect was accompanied by small improvements in low blood glucose index and treatment satisfaction, but not with reductions in hypoglycaemic events or changes in other secondary outcomes. CONCLUSION: Use of a bolus advisor is associated with slightly better glucose control and treatment satisfaction in people with diabetes on intensive insulin treatment. Future studies should investigate whether personalizing bolus advisors using artificial intelligence technology can enhance these effects.

Association between recent exposure to continuous glucose monitoring-recorded hypoglycaemia and counterregulatory and symptom responses to subsequent controlled hypoglycaemia in people with type 1 diabetes.

AIM: Experimental hypoglycaemia blunts the counterregulatory hormone and symptom responses to a subsequent episode of hypoglycaemia. In this study, we aimed to assess the associations between antecedent exposure and continuous glucose monitoring (CGM)-recorded hypoglycaemia during a 1-week period and the counterregulatory responses to subsequent experimental hypoglycaemia in people with type 1 diabetes. MATERIALS AND METHODS: Forty-two people with type 1 diabetes (20 females, mean ± SD glycated haemoglobin 7.8% ± 1.0%, diabetes duration median (interquartile range) 22.0 (10.5-34.9) years, 29 CGM users, and 19 with impaired awareness of hypoglycaemia) wore an open intermittently scanned CGM for 1 week to detect hypoglycaemic exposure before a standardized hyperinsulinaemic-hypoglycaemic [2.8 ± 0.1 mmol/L (50.2 ± 2.3 mg/dl)] glucose clamp. Symptom responses and counterregulatory hormones were measured during the clamp. The study is part of the HypoRESOLVE project. RESULTS: CGM-recorded hypoglycaemia in the week before the clamp was negatively associated with adrenaline response [ß -0.09, 95% CI (-0.16, -0.02) nmol/L, p = .014], after adjusting for CGM use, awareness of hypoglycaemia, glycated haemoglobin and total daily insulin dose. This was driven by level 2 hypoglycaemia [<3.0 mmol/L (54 mg/dl)] [ß -0.21, 95% CI (-0.41, -0.01) nmol/L, p = .034]. CGM-recorded hypoglycaemia was negatively associated with total, autonomic, and neuroglycopenic symptom responses, but these associations were lost after adjusting for potential confounders. CONCLUSIONS: Recent exposure to CGM-detected hypoglycaemia was independently associated with an attenuated adrenaline response to experimental hypoglycaemia in people with type 1 diabetes.

Summary of clinical investigation plan for The DIATEC trial: in-hospital diabetes management by a diabetes team and continuous glucose monitoring or point of care glucose testing - a randomised controlled trial.

BACKGROUND: Worldwide, up to 20 % of hospitalised patients have diabetes mellitus. In-hospital dysglycaemia increases patient mortality, morbidity, and length of hospital stay. Improved in-hospital diabetes management strategies are needed. The DIATEC trial investigates the effects of an in-hospital diabetes team and operational insulin titration algorithms based on either continuous glucose monitoring (CGM) data or standard point-of-care (POC) glucose testing. METHODS: This is a two-armed, two-site, prospective randomised open-label blinded endpoint (PROBE) trial. We recruit non-critically ill hospitalised general medical and orthopaedic patients with type 2 diabetes treated with basal, prandial, and correctional insulin (N = 166). In both arms, patients are monitored by POC glucose testing and diabetes management is done by ward nurses guided by in-hospital diabetes teams. In one of the arms, patients are monitored in addition to POC glucose testing by telemetric CGM viewed by the in-hospital diabetes teams only. The in-hospital diabetes teams have operational algorithms to titrate insulin in both arms. Outcomes are in-hospital glycaemic and clinical outcomes. DISCUSSION: The DIATEC trial will show the glycaemic and clinical effects of in-hospital CGM handled by in-hospital diabetes teams with access to operational insulin titration algorithms in non-critically ill patients with type 2 diabetes. The DIATEC trial seeks to identify which hospitalised patients will benefit from CGM and in-hospital diabetes teams compared to POC glucose testing. This is essential information to optimise the use of healthcare resources before broadly implementing in-hospital CGM and diabetes teams. TRIAL REGISTRATION: Prospectively registered at ClinicalTrials.gov with identification number NCT05803473 on March 27th 2023.

Type 2 diabetes mellitus and higher rate of complete atrioventricular block: a Danish Nationwide Registry.

AIMS: The present study aimed to determine the association between Type 2 diabetes mellitus (T2DM) and third-degree (complete) atrioventricular block. METHODS AND RESULTS: This nationwide nested case-control study included patients older than 18 years, diagnosed with third-degree atrioventricular block between 1 July 1995 and 31 December 2018. Data on medication, comorbidity, and outcomes were collected from Danish registries. Five controls, from the risk set of each case of third-degree atrioventricular block, were matched on age and sex to fit a Cox regression model with time-dependent exposure and time-dependent covariates. Subgroup analysis was conducted with Cox regression models for each subgroup. We located 25 995 cases with third-degree atrioventricular block that were matched with 130 004 controls. The mean age was 76 years and 62% were male. Cases had more T2DM (21% vs. 11%), hypertension (69% vs. 50%), atrial fibrillation (25% vs. 10%), heart failure (20% vs. 6.3%), and myocardial infarction (19% vs. 9.2%), compared with the control group. In Cox regression analysis, adjusting for comorbidities and atrioventricular nodal blocking agents, T2DM was significantly associated with third-degree atrioventricular block (hazard ratio: 1.63, 95% confidence interval: 1.57-1.69). The association remained in several subgroup analyses of diseases also suspected to be associated with third-degree atrioventricular block. There was a significant interaction with comorbidities of interest including hypertension, atrial fibrillation, heart failure, and myocardial infarction. CONCLUSION: In this nationwide study, T2DM was associated with a higher rate of third-degree atrioventricular block compared with matched controls. The association remained independent of atrioventricular nodal blocking agents and other comorbidities known to be associated with third-degree atrioventricular block.

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.

Associations between insulin pump self-management and HbA1c in type 1 diabetes.

AIMS: Insulin pump self-management is important for glycaemic outcomes. We aimed to investigate associations between self-management factors and HbA1c. METHODS: Adult insulin pump users with type 1 diabetes (n = 770) completed an online questionnaire. The latest HbA1c and demographics were extracted from national registries. Associations between HbA1c and self-management (use of advanced features, timing of infusion set change, timing of meal bolus, data-upload and pump settings adjustments) were investigated using backward selected linear regression models. RESULTS: Of the 699 responders eligible for this study, 60% were women; the median age and diabetes duration were 49 and 25 years, respectively. Significant associations with HbA1c were found for changing infusion set every 0-4 days relative to 5-10 days (-5 mmol/mol (-0.4%), p = 0.003), and for never/rarely missing a bolus (-6 mmol/mol (-0.5%), p < 0.001) relative to often missing a bolus. Timing insulin 10-15 min before meal relative to after meal start was also associated with lower HbA1c (-3 mmol/mol (-0.3%), p = 0.023). Self-adjusting pump settings showed the strongest association with lower HbA1c (-6 mmol/mol (-0.6%), p < 0.001) relative to health care professionals doing all adjustments. CONCLUSION: Self-adjusting insulin pump settings, optimal timing and few omissions of meal boluses, and timely change of infusion set are associated with lower HbA1c.

Sustained heart rate-corrected QT prolongation during recovery from hypoglycaemia in people with type 1 diabetes, independently of recovery to hyperglycaemia or euglycaemia.

AIM: To investigate changes in cardiac repolarization abnormalities (heart rate-corrected QT [QTc ] [primary endpoint], T-wave abnormalities) and heart-rate variability measures in people with type 1 diabetes during insulin-induced hypoglycaemia followed by recovery hyperglycaemia versus euglycaemia. METHODS: In a randomized crossover study, 24 individuals with type 1 diabetes underwent two experimental clamps with three steady-state phases during electrocardiographic monitoring: (1) a 45-minute euglycaemic phase (5-8 mmol/L), (2) a 60-minute insulin-induced hypoglycaemic phase (2.5 mmol/L), and (3) 60-minute recovery in either hyperglycaemia (20 mmol/L) or euglycaemia (5-8 mmol/L). RESULTS: All measured markers of arrhythmic risk indicated increased risk during hypoglycaemia. These findings were accompanied by a decrease in vagal tone during both hyperglycaemia and euglycaemia clamps. Compared with baseline, the QTc interval increased during hypoglycaemia, and 63% of the participants exhibited a peak QTc of more than 500 ms. The prolonged QTc interval was sustained during both recovery phases with no difference between recovery hyperglycaemia versus euglycaemia. During recovery, no change from baseline was observed in heart-rate variability measures. CONCLUSIONS: In people with type 1 diabetes, insulin-induced hypoglycaemia prolongs cardiac repolarization, which is sustained during a 60-minute recovery period independently of recovery to hyperglycaemia or euglycaemia. Thus, vulnerability to serious cardiac arrhythmias and sudden cardiac death may extend beyond a hypoglycaemic event, regardless of hyperglycaemic or euglycaemic recovery.

Exercise-related hypoglycaemia induces QTc-interval prolongation in individuals with type 1 diabetes.

AIMS: To investigate changes in cardiac repolarisation during exercise-related hypoglycaemia compared to hypoglycaemia induced at rest in people with type 1 diabetes. MATERIAL AND METHODS: In a randomised crossover study, 15 men with type 1 diabetes underwent two separate hyperinsulinaemic euglycaemic-hypoglycaemic clamp experiments during Holter-ECG monitoring. One experiment included a bout of moderate-intensity cycling exercise (60 min) along with declining plasma glucose (PG; Clamp-exercise). In the other experiment, hypoglycaemia was induced with the participants at rest (Clamp-rest). We studied QTc interval, T-peak to T-end (Tpe) interval and hormonal responses during three steady-state phases: (i) baseline (PG 4.0-8.0 mmol/L); (ii) hypoglycaemic phase (PG <3.0 mmol/L); and (iii) recovery phase (PG 4.0-8.0 mmol/L). RESULTS: Both QTc interval and Tpe interval increased significantly from baseline during the hypoglycaemic phase but with no significant difference between test days. These changes were accompanied by an increase in plasma adrenaline and a decrease in plasma potassium on both days. During the recovery phase, ΔQTc interval was longer during Clamp-rest compared to Clamp-exercise, whereas ΔTpe interval remained similar on the two test days. CONCLUSIONS: We found that both exercise-related hypoglycaemia and hypoglycaemia induced at rest can cause QTc-interval prolongation and Tpe-interval prolongation in people with type 1 diabetes. Thus, both scenarios may increase susceptibility to ventricular arrhythmias.

Hypoglycaemia induces a sustained pro-inflammatory response in people with type 1 diabetes and healthy controls.

AIM: To determine the duration and the extension of the pro-inflammatory response to hypoglycaemia both in people with type 1 diabetes and healthy controls. MATERIALS AND METHODS: Adults with type 1 diabetes (n = 47) and matched controls (n = 16) underwent a hyperinsulinaemic-euglycaemic hypoglycaemic (2.8 ± 0.1 mmoL/L [49.9 ± 2.3 mg/dL]) glucose clamp. During euglycaemia, hypoglycaemia, and 1, 3 and 7 days later, blood was drawn to determine immune cell phenotype, monocyte function and circulating inflammatory markers. RESULTS: Hypoglycaemia increased lymphocyte and monocyte counts, which remained elevated for 1 week. The proportion of CD16+ monocytes increased and the proportion of CD14+ monocytes decreased. During hypoglycaemia, monocytes released more tumour necrosis factor-α and interleukin-1ß, and less interleukin-10, after ex vivo stimulation. Hypoglycaemia increased the levels of 19 circulating inflammatory proteins, including high sensitive C-reactive protein, most of which remained elevated for 1 week. The epinephrine peak in response to hypoglycaemia was positively correlated with immune cell number and phenotype, but not with the proteomic response. CONCLUSIONS: Overall, despite differences in prior exposure to hypoglycaemia, the pattern of the inflammatory responses to hypoglycaemia did not differ between people with type 1 diabetes and healthy controls. In conclusion, hypoglycaemia induces a range of pro-inflammatory responses that are sustained for at least 1 week in people with type 1 diabetes and healthy controls.

Glycaemia and cardiac arrhythmias in people with type 1 diabetes: A prospective observational study.

AIM: To investigate the impact of hypoglycaemia, hyperglycaemia and glycaemic variability on arrhythmia susceptibility in people with type 1 diabetes. MATERIALS AND METHODS: Thirty adults with type 1 diabetes were included in a 12-month observational exploratory study. Daytime and night-time incident rate ratios (IRRs) of arrhythmias were determined for hypoglycaemia (interstitial glucose [IG] <3.9 mmol/L), hyperglycaemia (IG >10.0 mmol/L) and glycaemic variability (standard deviation and coefficient of variation). RESULTS: Hypoglycaemia was not associated with an increased risk of arrhythmias compared with euglycaemia and hyperglycaemia combined (IG ≥ 3.9 mmol/L). However, during daytime, a trend of increased risk of arrhythmias was observed when comparing time spent in hypoglycaemia with euglycaemia (IRR 1.08 [95% CI: 0.99-1.18] per 5 minutes). Furthermore, during daytime, both the occurrence and time spent in hyperglycaemia were associated with an increased risk of arrhythmias compared with euglycaemia (IRR 2.03 [95% CI: 1.21-3.40] and IRR 1.07 [95% CI: 1.02-1.13] per 5 minutes, respectively). Night-time hypoglycaemia and hyperglycaemia were not associated with the risk of arrhythmias. Increased glycaemic variability was not associated with an increased risk of arrhythmias during daytime, whereas a reduced risk was observed during night-time. CONCLUSIONS: Acute hypoglycaemia and hyperglycaemia during daytime may increase the risk of arrhythmias in individuals with type 1 diabetes. However, no such associations were found during night-time, indicating diurnal differences in arrhythmia susceptibility.

Effect of insulin degludec versus insulin glargine U100 on nocturnal glycaemia assessed by plasma glucose profiles in people with type 1 diabetes prone to nocturnal severe hypoglycaemia.

AIM: To compare nocturnal glucose profiles according to hourly plasma glucose measurements during treatment with insulin degludec and insulin glargine U100 in a cohort of people with type 1 diabetes prone to nocturnal severe hypoglycaemia. MATERIALS AND METHODS: The HypoDeg trial is a 2-year investigator-initiated, randomized, controlled crossover trial in 149 participants randomized to treatment with insulin degludec and insulin glargine U100 for 12 months each. The 51 participants in this predefined substudy stayed at least one night in hospital during each treatment arm for plasma glucose samples to be taken. Endpoints were glucose profiles, including mean plasma glucose, glycaemic variability and risk of hypoglycaemia. RESULTS: There were no differences between treatments regarding mean plasma glucose. We saw a flatter glucose profile during insulin degludec compared with insulin glargine U100 treatment, which had a nadir at 4:00 AM, with a subsequent rise. During treatment with insulin degludec, the participants had lower glycaemic variability, with an estimated treatment difference of -4.3% (95% confidence interval [CI] -8.1 to -0.5; P < 0.05). Participants treated with insulin degludec were less likely to experience nocturnal hypoglycaemia below 3.0 mmol/L (hazard ratio 0.36 [95% CI 0.17-0.73; P < 0.05]). CONCLUSION: Based on nocturnal plasma glucose measurements, treatment with insulin degludec compared with insulin glargine U100 administered in the evening results in lower glycaemic variability and lower risk of nocturnal hypoglycaemia without differences in mean plasma glucose.

Glycaemic thresholds for counterregulatory hormone and symptom responses to hypoglycaemia in people with and without type 1 diabetes: a systematic review.

AIM/HYPOTHESIS: The physiological counterregulatory response to hypoglycaemia is reported to be organised hierarchically, with hormone responses usually preceding symptomatic awareness and autonomic responses preceding neuroglycopenic responses. To compare thresholds for activation of these responses more accurately between people with or without type 1 diabetes, we performed a systematic review on stepped hyperinsulinaemic-hypoglycaemic glucose clamps. METHODS: A literature search in PubMed and EMBASE was conducted. We included articles published between 1980 and 2018 involving hyperinsulinaemic stepped hypoglycaemic glucose clamps among people with or without type 1 diabetes. Key exclusion criteria were as follows: data were previously published; other patient population; a clamp not the primary intervention; and an inadequate clamp description. Glycaemic thresholds for counterregulatory hormone and/or symptom responses to hypoglycaemia were estimated and compared using generalised logrank test for interval-censored data, where the intervals were either extracted directly or calculated from the data provided by the study. A glycaemic threshold was defined as the glucose level at which the response exceeded the 95% CI of the mean baseline measurement or euglycaemic control clamp. Because of the use of interval-censored data, we described thresholds using median and IQR. RESULTS: A total of 63 articles were included, whereof 37 papers included participants with type 1 diabetes (n=559; 67.4% male sex, aged 32.7±10.2 years, BMI 23.8±1.4 kg/m2) and 51 papers included participants without diabetes (n=733; 72.4% male sex, aged 31.1±9.2 years, BMI 23.6±1.1 kg/m2). Compared with non-diabetic control individuals, in people with type 1 diabetes, the median (IQR) glycaemic thresholds for adrenaline (3.8 [3.2-4.2] vs 3.4 [2.8-3.9 mmol/l]), noradrenaline (3.2 [3.2-3.7] vs 3.0 [2.8-3.1] mmol/l), cortisol (3.5 [3.2-4.2]) vs 2.8 [2.8-3.4] mmol/l) and growth hormone (3.8 [3.3-3.8] vs. 3.2 [3.0-3.3] mmol/l) all occurred at lower glucose levels in people with diabetes than in those without diabetes (all p≤0.01). Similarly, although both autonomic (median [IQR] 3.4 [3.4-3.4] vs 3.0 [2.8-3.4] mmol/l) and neuroglycopenic (median [IQR] 3.4 [2.8-N/A] vs 3.0 [3.0-3.1] mmol/l) symptom responses were elicited at lower glucose levels in people with type 1 diabetes, the thresholds for autonomic and neuroglycopenic symptoms did not differ for each individual subgroup. CONCLUSIONS/INTERPRETATION: People with type 1 diabetes have glycaemic thresholds for counterregulatory hormone and symptom responses at lower glucose levels than people without diabetes. Autonomic and neuroglycopenic symptoms responses are generated at about similar levels of hypoglycaemia. There was a considerable variation in the methodology of the articles and the high insulin doses in most of the clamps may affect the counterregulatory responses. FUNDING: This article has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement no. 777460. REGISTRATION: This systematic review is registered in PROSPERO (CRD42019120083).

Hypo-METRICS: Hypoglycaemia-MEasurement, ThResholds and ImpaCtS-A multi-country clinical study to define the optimal threshold and duration of sensor-detected hypoglycaemia that impact the experience of hypoglycaemia, quality of life and health economic outcomes: The study protocol.

INTRODUCTION: Hypoglycaemia is a significant burden to people living with diabetes and an impediment to achieving optimal glycaemic outcomes. The use of continuous glucose monitoring (CGM) has improved the capacity to assess duration and level of hypoglycaemia. The personal impact of sensor-detected hypoglycaemia (SDH) is unclear. Hypo-METRICS is an observational study designed to define the threshold and duration of sensor glucose that provides the optimal sensitivity and specificity for events that people living with diabetes experience as hypoglycaemia. METHODS: We will recruit 600 participants: 350 with insulin-treated type 2 diabetes, 200 with type 1 diabetes and awareness of hypoglycaemia and 50 with type 1 diabetes and impaired awareness of hypoglycaemia who have recent experience of hypoglycaemia. Participants will wear a blinded CGM device and an actigraphy monitor to differentiate awake and sleep times for 10 weeks. Participants will be asked to complete three short surveys each day using a bespoke mobile phone app, a technique known as ecological momentary assessment. Participants will also record all episodes of self-detected hypoglycaemia on the mobile app. We will use particle Markov chain Monte Carlo optimization to identify the optimal threshold and duration of SDH that have optimum sensitivity and specificity for detecting patient-reported hypoglycaemia. Key secondary objectives include measuring the impact of symptomatic and asymptomatic SDH on daily functioning and health economic outcomes. ETHICS AND DISSEMINATION: The protocol was approved by local ethical boards in all participating centres. Study results will be shared with participants, in peer-reviewed journal publications and conference presentations.