Threshold of hyperglycaemia associated with mortality in critically ill patients: a multicentre, prospective, observational study using continuous glucose monitoring.

AIMS/HYPOTHESIS: Continuous glucose monitoring (CGM) provides comprehensive information on the exposure to dysglycaemia. This study aimed to investigate the threshold of hyperglycaemia related to mortality risk in critically ill patients using CGM technology. METHODS: A total of 293 adult critically ill patients admitted to intensive care units of five medical centres were prospectively included between May 2020 and November 2021. Participants wore intermittently scanned CGM for a median of 12.0 days. The relationships between different predefined time above ranges (TARs), with the thresholds of hyperglycaemia ranging from 7.8 to 13.9 mmol/l (140-250 mg/dl), and in-hospital mortality risk were assessed by multivariate Cox proportional regression analysis. Time in ranges (TIRs) of 3.9 mmol/l (70 mg/dl) to the predefined hyperglycaemic thresholds were also assessed. RESULTS: Overall, 66 (22.5%) in-hospital deaths were identified. Only TARs with a threshold of 10.5 mmol/l (190 mg/dl) or above were significantly associated with the risk of in-hospital mortality, after adjustment for covariates. Furthermore, as the thresholds for TAR increased from 10.5 mmol/l to 13.9 mmol/l (190 mg/dl to 250 mg/dl), the hazards of in-hospital mortality increased incrementally with every 10% increase in TARs. Similar results were observed concerning the associations between TIRs with various upper thresholds and in-hospital mortality risk. For per absolute 10% decrease in TIR 3.9-10.5 mmol/l (70-190 mg/dl), the risk of in-hospital mortality was increased by 12.1% (HR 1.121 [95% CI 1.003, 1.253]). CONCLUSIONS/INTERPRETATION: A glucose level exceeding 10.5 mmol/l (190 mg/dl) was significantly associated with higher risk of in-hospital mortality in critically ill patients.

Accuracy of continuous glucose monitoring in the hospital setting: an observational study.

AIMS/HYPOTHESIS: Continuous glucose monitoring (CGM) improves glycaemic outcomes in the outpatient setting; however, there are limited data regarding CGM accuracy in hospital. METHODS: We conducted a prospective, observational study comparing CGM data from blinded Dexcom G6 Pro sensors with reference point of care and laboratory glucose measurements during participants' hospitalisations. Key accuracy metrics included the proportion of CGM values within ±20% of reference glucose values >5.6 mmol/l or within ±1.1 mmol/l of reference glucose values ≤5.6 mmol/l (%20/20), the mean and median absolute relative difference between CGM and reference value (MARD and median ARD, respectively) and Clarke error grid analysis (CEGA). A retrospective calibration scheme was used to determine whether calibration improved sensor accuracy. Multivariable regression models and subgroup analyses were used to determine the impact of clinical characteristics on accuracy assessments. RESULTS: A total of 326 adults hospitalised on 19 medical or surgical non-intensive care hospital floors were enrolled, providing 6648 matched glucose pairs. The %20/20 was 59.5%, the MARD was 19.2% and the median ARD was 16.8%. CEGA showed that 98.2% of values were in zone A (clinically accurate) and zone B (benign). Subgroups with lower accuracy metrics included those with severe anaemia, renal dysfunction and oedema. Application of a once-daily morning calibration schedule improved accuracy (MARD 11.4%). CONCLUSIONS/INTERPRETATION: The CGM accuracy when used in hospital may be lower than that reported in the outpatient setting, but this may be improved with appropriate patient selection and daily calibration. Further research is needed to understand the role of CGM in inpatient settings.

Consensus guidance for monitoring individuals with islet autoantibody-positive pre-stage 3 type 1 diabetes.

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk of (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb+; (2) when people who are IAb+ are initially identified there is a need for confirmation using a second sample; (3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care.

Cost-utility analysis of Dexcom G6 real-time continuous glucose monitoring versus FreeStyle Libre 1 intermittently scanned continuous glucose monitoring in adults with type 1 diabetes in Belgium.

AIMS/HYPOTHESIS: The aim of this study was to assess the long-term cost-effectiveness of Dexcom G6 real-time continuous glucose monitoring (rtCGM) with alert functionality compared with FreeStyle Libre 1 intermittently scanned continuous glucose monitoring (isCGM) without alerts in adults with type 1 diabetes in Belgium. METHODS: The IQVIA CORE Diabetes Model was used to estimate cost-effectiveness. Input data for the simulated baseline cohort were sourced from the randomised ALERTT1 trial (ClinicalTrials.gov. REGISTRATION NO: NCT03772600). The age of the participants was 42.9 ± 14.1 years (mean ± SD), and the baseline HbA1c was 57.8 ± 9.5 mmol/mol (7.4 ± 0.9%). Participants using rtCGM showed a reduction in HbA1c of 3.6 mmol/mol (0.36 percentage points) based on the 6-month mean between-group difference. In the base case, both rtCGM and isCGM were priced at €3.92/day (excluding value-added tax [VAT]) according to the Belgian reimbursement system. The analysis was performed from a Belgian healthcare payer perspective over a lifetime time horizon. Health outcomes were expressed as quality-adjusted life years. Probabilistic and one-way sensitivity analyses were used to account for parameter uncertainty. RESULTS: In the base case, rtCGM dominated isCGM, resulting in lower diabetes-related complication costs and better health outcomes. The associated main drivers favouring rtCGM were lower HbA1c, fewer severe hypoglycaemic events and reduced fear of hypoglycaemia. The results were robust under a wide range of one-way sensitivity analyses. In models where the price of rtCGM is €5.11/day (a price increase of 30.4%) or €12.34/day (a price increase of 214.8%), rtCGM was cost-neutral or reached an incremental cost-effectiveness ratio of €40,000 per quality-adjusted life year, respectively. CONCLUSIONS/INTERPRETATION: When priced similarly, Dexcom G6 rtCGM with alert functionality has both economic and clinical benefits compared with FreeStyle Libre 1 isCGM without alerts in adults with type 1 diabetes in Belgium, and appears to be a cost-effective glucose monitoring modality. Trial registration ClinicalTrials.gov NCT03772600.

A narrative commentary about interoperability in medical devices and data used in diabetes therapy from an academic EU/UK/US perspective.

People living with diabetes have many medical devices available to assist with disease management. A critical aspect that must be considered is how systems for continuous glucose monitoring and insulin pumps communicate with each other and how the data generated by these devices can be downloaded, integrated, presented and used. Not only is interoperability associated with practical challenges, but also devices must adhere to all aspects of regulatory and legal frameworks. Key issues around interoperability in terms of data ownership, privacy and the limitations of interoperability include where the responsibility/liability for device and data interoperability lies and the need for standard data-sharing protocols to allow the seamless integration of data from different sources. There is a need for standardised protocols for the open and transparent handling of data and secure integration of data into electronic health records. Here, we discuss the current status of interoperability in medical devices and data used in diabetes therapy, as well as regulatory and legal issues surrounding both device and data interoperability, focusing on Europe (including the UK) and the USA. We also discuss a potential future landscape in which a clear and transparent framework for interoperability and data handling also fulfils the needs of people living with diabetes and healthcare professionals.

Glycaemia risk index uncovers distinct glycaemic variability patterns associated with remission status in type 1 diabetes.

AIMS/HYPOTHESIS: The aim of this work was to define a unique remission status using glycaemia risk index (GRI) and other continuous glucose monitoring (CGM) metrics in individuals with type 1 diabetes for improved phenotyping. METHODS: A group of 140 individuals with type 1 diabetes were recruited for a cross-sectional study. The participants were categorised into four groups based on their remission status, which was defined as insulin-dose-adjusted A1c (IDAA1c) <9 or C-peptide ≥300 pmol/l: new-onset (n=24); mid-remission (n=44); post-remission (n=44); and non-remission (individuals who did not experience remission, n=28). Participants in the remission phase were referred to as 'remitters', while those who were not in the remission phase were referred to as 'non-remitters', the latter group including new-onset, post-remission and non-remission participants. Clinical variables such as HbA1c, C-peptide and insulin daily dose, as well as IDAA1C and CGM data, were collected. The patterns of CGM metrics were analysed for each group using generalised estimating equations to investigate the glycaemic variability patterns associated with remission status. Then, unsupervised hierarchical clustering was used to place the participants into subgroups based on GRI and other CGM core metrics. RESULTS: The glycaemic variability patterns associated with remission status were found to be distinct based on the circadian CGM metrics. Remitters showed improved control of blood glucose levels over 14 days within the range of 3.9-10 mmol/l, and lower GRI compared with non-remitters (p<0.001). Moreover, GRI strongly correlated with IDAA1C (r=0.62; p<0.001) and was sufficient to distinguish remitters from non-remitters. Further, four subgroups demonstrating distinct patterns of glycaemic variability associated with different remission status were identified by clustering on CGM metrics: remitters with low risk of dysglycaemia; non-remitters with high risk of hypoglycaemia; non-remitters with high risk of hyperglycaemia; and non-remitters with moderate risk of dysglycaemia. CONCLUSIONS/INTERPRETATION: GRI, an integrative index, together with other traditional CGM metrics, helps to identify different glycaemic variability patterns; this might provide specifically tailored monitoring and management strategies for individuals in the various subclusters.

Continuous glucose monitoring in adults with type 2 diabetes: a systematic review and meta-analysis.

AIMS/HYPOTHESIS: Continuous glucose monitoring (CGM) is increasingly used in the treatment of type 2 diabetes, but the effects on glycaemic control are unclear. The aim of this systematic review and meta-analysis is to provide a comprehensive overview of the effect of CGM on glycaemic control in adults with type 2 diabetes. METHODS: We performed a systematic review using Embase, MEDLINE, Web of Science, Scopus and ClinicalTrials.gov from inception until 2 May 2023. We included RCTs investigating real-time CGM (rtCGM) or intermittently scanned CGM (isCGM) compared with self-monitoring of blood glucose (SMBG) in adults with type 2 diabetes. Studies with an intervention duration <6 weeks or investigating professional CGM, a combination of CGM and additional glucose-lowering treatment strategies or GlucoWatch were not eligible. Change in HbA1c and the CGM metrics time in range (TIR), time below range (TBR), time above range (TAR) and glycaemic variability were extracted. We evaluated the risk of bias using the Cochrane risk-of-bias tool version 2. Data were synthesised by performing a meta-analysis. We also explored the effects of CGM on severe hypoglycaemia and micro- and macrovascular complications. RESULTS: We found 12 RCTs comprising 1248 participants, with eight investigating rtCGM and four isCGM. Compared with SMBG, CGM use (rtCGM or isCGM) led to a mean difference (MD) in HbA1c of -3.43 mmol/mol (-0.31%; 95% CI -4.75, -2.11, p<0.00001, I2=15%; moderate certainty). This effect was comparable in studies that included individuals using insulin with or without oral agents (MD -3.27 mmol/mol [-0.30%]; 95% CI -6.22, -0.31, p=0.03, I2=55%), and individuals using oral agents only (MD -3.22 mmol/mol [-0.29%]; 95% CI -5.39, -1.05, p=0.004, I2=0%). Use of rtCGM showed a trend towards a larger effect (MD -3.95 mmol/mol [-0.36%]; 95% CI -5.46 to -2.44, p<0.00001, I2=0%) than use of isCGM (MD -1.79 mmol/mol [-0.16%]; 95% CI -5.28, 1.69, p=0.31, I2=64%). CGM was also associated with an increase in TIR (+6.36%; 95% CI +2.48, +10.24, p=0.001, I2=9%) and a decrease in TBR (-0.66%; 95% CI -1.21, -0.12, p=0.02, I2=45%), TAR (-5.86%; 95% CI -10.88, -0.84, p=0.02, I2=37%) and glycaemic variability (-1.47%; 95% CI -2.94, -0.01, p=0.05, I2=0%). Three studies reported one or more events of severe hypoglycaemia and macrovascular complications. In comparison with SMBG, CGM use led to a non-statistically significant difference in the incidence of severe hypoglycaemia (RR 0.66, 95% CI 0.15, 3.00, p=0.57, I2=0%) and macrovascular complications (RR 1.54, 95% CI 0.42, 5.72, p=0.52, I2=29%). No trials reported data on microvascular complications. CONCLUSIONS/INTERPRETATION: CGM use compared with SMBG is associated with improvements in glycaemic control in adults with type 2 diabetes. However, all studies were open label. In addition, outcome data on incident severe hypoglycaemia and incident microvascular and macrovascular complications were scarce. REGISTRATION: This systematic review was registered on PROSPERO (ID CRD42023418005).

Continuous glucose monitoring with structured education in adults with type 2 diabetes managed by multiple daily insulin injections: a multicentre randomised controlled trial.

AIMS/HYPOTHESIS: The aim of this study was to compare the effectiveness of stand-alone intermittently scanned continuous glucose monitoring (isCGM) with or without a structured education programme and blood glucose monitoring (BGM) in adults with type 2 diabetes on multiple daily insulin injections (MDI). METHODS: In this 24 week randomised open-label multicentre trial, adults with type 2 diabetes on intensive insulin therapy with HbA1c levels of 58-108 mmol/mol (7.5-12.0%) were randomly assigned in a 1:1:1 ratio to isCGM with a structured education programme on adjusting insulin dose and timing according to graphical patterns in CGM (intervention group), isCGM with conventional education (control group 1) or BGM with conventional education (control group 2). Block randomisation was conducted by an independent statistician. Due to the nature of the intervention, blinding of participants and investigators was not possible. The primary outcome was change in HbA1c from baseline at 24 weeks, assessed using ANCOVA with the baseline value as a covariate. RESULTS: A total of 159 individuals were randomised (n=53 for each group); 148 were included in the full analysis set, with 52 in the intervention group, 49 in control group 1 and 47 in control group 2. The mean (± SD) HbA1c level at baseline was 68.19±10.94 mmol/mol (8.39±1.00%). The least squares mean change (± SEM) from baseline HbA1c at 24 weeks was -10.96±1.35 mmol/mol (-1.00±0.12%) in the intervention group, -6.87±1.39 mmol/mol (-0.63±0.13%) in control group 1 (p=0.0367 vs intervention group) and -6.32±1.42 mmol/mol (-0.58±0.13%) in control group 2 (p=0.0193 vs intervention group). Adverse events occurred in 28.85% (15/52) of individuals in the intervention group, 26.42% (14/53) in control group 1 and 48.08% (25/52) in control group 2. CONCLUSIONS/INTERPRETATION: Stand-alone isCGM offers a greater reduction in HbA1c in adults with type 2 diabetes on MDI when education on the interpretation of graphical patterns in CGM is provided. TRIAL REGISTRATION: ClinicalTrials.gov NCT04926623. FUNDING: This study was supported by Daewoong Pharmaceutical Co., Ltd.

Perceived glucose levels matter more than CGM-based data in predicting diabetes distress in type 1 or type 2 diabetes: a precision mental health approach using n-of-1 analyses.

AIMS/HYPOTHESIS: Diabetes distress is one of the most frequent mental health issues identified in people with type 1 and type 2 diabetes. Little is known about the role of glucose control as a potential contributor to diabetes distress and whether the subjective perception of glucose control or the objective glycaemic parameters are more important for the experience. With the emergence of continuous glucose monitoring (CGM), this is a relevant question as glucose values are now visible in real-time. We employed a precision monitoring approach to analyse the independent associations of perceived and measured glucose control with diabetes distress on a daily basis. By using n-of-1 analyses, we aimed to identify individual contributors to diabetes distress per person and analyse the associations of these individual contributors with mental health at a 3 month follow-up. METHODS: In this prospective, observational study, perceived (hypoglycaemia/hyperglycaemia/glucose variability burden) and measured glucose control (time in hypoglycaemia and hyperglycaemia, CV) were assessed daily for 17 days using an ecological momentary assessment (EMA) approach with a special EMA app and CGM, respectively. Mixed-effect regression analysis was performed, with daily diabetes distress as the dependent variable and daily perceived and CGM-measured metrics of glucose control as random factors. Individual regression coefficients of daily distress with perceived and CGM-measured metrics were correlated with levels of psychosocial well-being at a 3 month follow-up. RESULTS: Data from 379 participants were analysed (50.9% type 1 diabetes; 49.6% female). Perceived glucose variability (t=14.360; p<0.0001) and perceived hyperglycaemia (t=13.637; p<0.0001) were the strongest predictors of daily diabetes distress, while CGM-based glucose variability was not significantly associated (t=1.070; p=0.285). There was great heterogeneity between individuals in the associations of perceived and measured glucose parameters with diabetes distress. Individuals with a stronger association between perceived glucose control and daily distress had more depressive symptoms (ß=0.32), diabetes distress (ß=0.39) and hypoglycaemia fear (ß=0.34) at follow-up (all p<0.001). Individuals with a stronger association between CGM-measured glucose control and daily distress had higher levels of psychosocial well-being at follow-up (depressive symptoms: ß=-0.31; diabetes distress: ß=-0.33; hypoglycaemia fear: ß=-0.27; all p<0.001) but also higher HbA1c (ß=0.12; p<0.05). CONCLUSIONS/INTERPRETATION: Overall, subjective perceptions of glucose seem to be more influential on diabetes distress than objective CGM parameters of glycaemic control. N-of-1 analyses showed that CGM-measured and perceived glucose control had differential associations with diabetes distress and psychosocial well-being 3 months later. The results highlight the need to understand the individual drivers of diabetes distress to develop personalised interventions within a precision mental health approach.

Discordance between mean glucose and time in range in relation to HbA1c in individuals with type 1 diabetes: results from the GOLD and SILVER trials.

AIMS/HYPOTHESIS: Previous studies have shown that individuals with similar mean glucose levels (MG) or percentage of time in range (TIR) may have different HbA1c values. The aim of this study was to further elucidate how MG and TIR are associated with HbA1c. METHODS: Data from the randomised clinical GOLD trial (n=144) and the follow-up SILVER trial (n=98) of adults with type 1 diabetes followed for 2.5 years were analysed. A total of 596 paired HbA1c/continuous glucose monitoring measurements were included. Linear mixed-effects models were used to account for intra-individual correlations in repeated-measures data. RESULTS: In the GOLD trial, the mean age of the participants (± SD) was 44±13 years, 63 (44%) were female, and the mean HbA1c (± SD) was 72±9.8 mmol/mol (8.7±0.9%). When correlating MG with HbA1c, MG explained 63% of the variation in HbA1c (r=0.79, p<0.001). The variation in HbA1c explained by MG increased to 88% (r=0.94, p value for improvement of fit <0.001) when accounting for person-to-person variation in the MG-HbA1c relationship. Time below range (TBR; <3.9 mmol/l), time above range (TAR) level 2 (>13.9 mmol/l) and glycaemic variability had little or no effect on the association. For a given MG and TIR, the HbA1c of 10% of individuals deviated by >8 mmol/mol (0.8%) from their estimated HbA1c based on the overall association between MG and TIR with HbA1c. TBR and TAR level 2 significantly influenced the association between TIR and HbA1c. At a given TIR, each 1% increase in TBR was related to a 0.6 mmol/mol lower HbA1c (95% CI 0.4, 0.9; p<0.001), and each 2% increase in TAR level 2 was related to a 0.4 mmol/mol higher HbA1c (95% CI 0.1, 0.6; p=0.003). However, neither TIR, TBR nor TAR level 2 were significantly associated with HbA1c when accounting for MG. CONCLUSIONS/INTERPRETATION: Inter-individual variations exist between MG and HbA1c, as well as between TIR and HbA1c, with clinically important deviations in relatively large groups of individuals with type 1 diabetes. These results may provide important information to both healthcare providers and individuals with diabetes in terms of prognosis and when making diabetes management decisions.

Use of diabetes technology in children.

Children with type 1 diabetes and their caregivers face numerous challenges navigating the unpredictability of this complex disease. Although the burden of managing diabetes remains significant, new technology has eased some of the load and allowed children with type 1 diabetes to achieve tighter glycaemic management without fear of excess hypoglycaemia. Continuous glucose monitor use alone improves outcomes and is considered standard of care for paediatric type 1 diabetes management. Similarly, automated insulin delivery (AID) systems have proven to be safe and effective for children as young as 2 years of age. AID use improves not only blood glucose levels but also quality of life for children with type 1 diabetes and their caregivers and should be strongly considered for all youth with type 1 diabetes if available and affordable. Here, we review key data on the use of diabetes technology in the paediatric population and discuss management issues unique to children and adolescents.

Glycaemic patterns during breastfeeding with postpartum use of closed-loop insulin delivery in women with type 1 diabetes.

AIMS/HYPOTHESIS: This study aimed to describe the relationship between breastfeeding episodes and maternal glucose levels, and to assess whether this differs with closed-loop vs open-loop (sensor-augmented pump) insulin therapy. METHODS: Infant-feeding diaries were collected at 6 weeks, 12 weeks and 24 weeks postpartum in a trial of postpartum closed-loop use in 18 women with type 1 diabetes. Continuous glucose monitoring (CGM) data were used to identify maternal glucose patterns within the 3 h of breastfeeding episodes. Generalised mixed models adjusted for breastfeeding episodes in the same woman, repeat breastfeeding episodes, carbohydrate intake, infant age at time of feeding and early pregnancy HbA1c. This was a secondary analysis of data collected during a randomised trial (ClinicalTrials.gov registration no. NCT04420728). RESULTS: CGM glucose remained above 3.9 mmol/l in the 3 h post-breastfeeding for 93% (397/427) of breastfeeding episodes. There was an overall decrease in glucose at nighttime within 3 h of breastfeeding (1.1 mmol l-1 h-1 decrease on average; p=0.009). A decrease in nighttime glucose was observed with open-loop therapy (1.2 ± 0.5 mmol/l) but was blunted with closed-loop therapy (0.4 ± 0.3 mmol/l; p<0.01, open-loop vs closed-loop). CONCLUSIONS/INTERPRETATION: There is a small decrease in glucose after nighttime breastfeeding that usually does not result in maternal hypoglycaemia; this appears to be blunted with the use of closed-loop therapy.

Ageing well with diabetes: the role of technology.

Over the past two decades there has been a substantial rise in the adoption of diabetes therapeutic technology among children, adolescents and younger adults with type 1 diabetes, and its use is now also advocated for older individuals. Older people with diabetes are more prone to experience hypoglycaemia because of numerous predisposing factors and are at higher risk of hypoglycaemic events requiring third-party assistance as well as other adverse sequelae. Hypoglycaemia may also have long-term consequences, including cognitive impairment, frailty and disability. Diabetes in older people is often characterised by marked glucose variability related to age-associated changes such as variable appetite and levels of physical activity, comorbidities and polypharmacotherapy. Preventing hypoglycaemia and mitigating glucose excursions may have considerable positive impacts on physical and cognitive function and general well-being and may even prevent or improve frailty. Technology for older people includes continuous glucose monitoring systems, insulin pumps, automated insulin delivery systems and smart insulin pens. Clinical trials and real-world studies have shown that older people with diabetes benefit from technology in terms of glucose management, reductions in hypoglycaemic events, emergency department attendance and hospital admissions, and improvement in quality of life. However, ageing may bring physical impairments and other challenges that hinder the use of technology. Healthcare professionals should identify older adults with diabetes who may benefit from therapeutic technology and then adopt an individualised approach to education and follow-up for individuals and their caregivers. Future research should explore the impact of diabetes technology on outcomes relevant to older people with diabetes.

Advances in diabetes technology to improve the lives of people with cystic fibrosis.

People with cystic fibrosis (CF) are at risk for dysglycaemia caused by progressive beta cell dysfunction and destruction due to pancreatic exocrine disease and fibrosis. CF-related diabetes (CFRD) is a unique form of diabetes that has distinctive features from both type 1 and type 2 diabetes. Recent advances in diabetes technology may be of particular benefit in this population given the complex, multi-system organ involvement and challenging health issues that people with CFRD often face. This review summarises how diabetes technologies, such as continuous glucose monitors (CGMs) and insulin delivery devices: (1) have improved our understanding of CFRD, including how hyperglycaemia affects clinical outcomes in people with CF; (2) may be helpful in the screening and diagnosis of CFRD; and (3) offer promise for improving the management of CFRD and easing the burden that this diagnosis can add to an already medically complicated patient population.

The association of chronic complications with time in tight range and time in range in people with type 1 diabetes: a retrospective cross-sectional real-world study.

AIMS/HYPOTHESIS: The aim of this study was to evaluate the association of chronic complications with time in tight range (TITR: 3.9-7.8 mmol/l) and time in range (TIR: 3.9-10.0 mmol/l) in people with type 1 diabetes. METHODS: The prevalence of microvascular complications (diabetic retinopathy, diabetic nephropathy and diabetic peripheral neuropathy [DPN]) and macrovascular complications according to sensor-measured TITR/TIR was analysed cross-sectionally in 808 adults with type 1 diabetes. Binary logistic regression was used to evaluate the association between TITR/TIR and the presence of complications without adjustment, with adjustment for HbA1c, and with adjustment for HbA1c and other confounding factors (sex, age, diabetes duration, BMI, BP, lipid profile, smoking, and use of statins and renin-angiotensin-aldosterone system inhibitors). RESULTS: The mean TITR and TIR were 33.9 ± 12.8% and 52.5 ± 15.0%, respectively. Overall, 46.0% had any microvascular complication (34.5% diabetic retinopathy, 23.8% diabetic nephropathy, 16.0% DPN) and 16.3% suffered from any macrovascular complication. The prevalence of any microvascular complication, diabetic retinopathy, diabetic nephropathy and a cerebrovascular accident (CVA) decreased with increasing TITR/TIR quartiles (all ptrend<0.05). Each 10% increase in TITR was associated with a lower incidence of any microvascular complication (OR 0.762; 95% CI 0.679, 0.855; p<0.001), diabetic retinopathy (OR 0.757; 95% CI 0.670, 0.856; p<0.001), background diabetic retinopathy (OR 0.760; 95% CI 0.655, 0.882; p<0.001), severe diabetic retinopathy (OR 0.854; 95% CI 0.731, 0.998; p=0.048), diabetic nephropathy (OR 0.799; 95% CI 0.699, 0.915; p<0.001), DPN (OR 0.837; 95% CI 0.717, 0.977; p=0.026) and CVA (OR 0.651; 95% CI 0.470, 0.902; p=0.010). The independent association of TITR with any microvascular complication (OR 0.867; 95% CI 0.762, 0.988; p=0.032), diabetic retinopathy (OR 0.837; 95% CI 0.731, 0.959; p=0.010), background diabetic retinopathy (OR 0.831; 95% CI 0.705, 0.979; p=0.027) and CVA (OR 0.619; 95% CI 0.426, 0.899; p=0.012) persisted after adjustment for HbA1c. Similar results were obtained when controlling for HbA1c and other confounding factors. CONCLUSIONS/INTERPRETATION: TITR and TIR are inversely associated with the presence of microvascular complications and CVA in people with type 1 diabetes. Although this study was not designed to establish a causal relationship, this analysis adds validity to the use of TITR and TIR as key measures in glycaemic management. TRIAL REGISTRATION: ClinicalTrials.gov NCT02601729 and NCT02898714.

The use of technology in type 2 diabetes and prediabetes: a narrative review.

The increasing incidence of type 2 diabetes, which represents 90% of diabetes cases globally, is a major public health concern. Improved glucose management reduces the risk of vascular complications and mortality; however, only a small proportion of the type 2 diabetes population have blood glucose levels within the recommended treatment targets. In recent years, diabetes technologies have revolutionised the care of people with type 1 diabetes, and it is becoming increasingly evident that people with type 2 diabetes can also benefit from these advances. In this review, we describe the current knowledge regarding the role of technologies for people living with type 2 diabetes and the evidence supporting their use in clinical practice. We conclude that continuous glucose monitoring systems deliver glycaemic benefits for individuals with type 2 diabetes, whether treated with insulin or non-insulin therapy; further data are required to evaluate the role of these systems in those with prediabetes (defined as impaired glucose tolerance and/or impaired fasting glucose and/or HbA1c levels between 39 mmol/mol [5.7%] and 47 mmol/mol [6.4%]). The use of insulin pumps seems to be safe and effective in people with type 2 diabetes, especially in those with an HbA1c significantly above target. Initial results from studies exploring the impact of closed-loop systems in type 2 diabetes are promising. We discuss directions for future research to fully understand the potential benefits of integrating evidence-based technology into care for people living with type 2 diabetes and prediabetes.

Technology advances in diabetes pregnancy: right technology, right person, right time.

This review outlines some of the extraordinary recent advances in diabetes technology, which are transforming the management of type 1 diabetes before, during and after pregnancy. It highlights recent improvements associated with use of continuous glucose monitoring (CGM) but acknowledges that neither CGM nor insulin pump therapy are adequate for achieving the pregnancy glucose targets. Furthermore, even hybrid closed-loop (HCL) systems that are clinically effective outside of pregnancy may not confer additional benefits throughout pregnancy. To date, there is only one HCL system, the CamAPS FX, with a strong evidence base for use during pregnancy, suggesting that the pregnancy benefits are HCL system specific. This is in stark contrast to HCL system use outside of pregnancy, where benefits are HCL category specific. The CamAPS FX HCL system has a rapidly adaptive algorithm and lower glucose targets with benefits across all maternal glucose categories, meaning that it is applicable for all women with type 1 diabetes, before and during pregnancy. For women of reproductive years living with type 2 diabetes, the relative merits of using non-insulin pharmacotherapies vs diabetes technology (dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter 2 inhibitors) are unknown. Despite the urgent unmet need and potential benefits, studies of pharmacotherapy and technology use are extremely limited in pregnant women with type 2 diabetes.

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.

Practical considerations for continuous glucose monitoring in elite athletes with type 1 diabetes mellitus: A narrative review.

Type 1 diabetes mellitus (T1DM) refers to a metabolic condition where a lack of insulin impairs the usual homeostatic mechanisms to control blood glucose levels. Historically, participation in competitive sport has posed a challenge for those with T1DM, where the dynamic changes in blood glucose during exercise can result in dangerously high (hyperglycaemia) or low blood glucoses (hypoglycaemia) levels. Over the last decade, research and technological development has enhanced the methods of monitoring and managing blood glucose levels, thus reducing the chances of experiencing hyper- or hypoglycaemia during exercise. The introduction of continuous glucose monitoring (CGM) systems means that glucose can be monitored conveniently, without the need for frequent fingerpick glucose checks. CGM devices include a fine sensor inserted under the skin, measuring levels of glucose in the interstitial fluid. Readings can be synchronized to a reader or mobile phone app as often as every 1-5 min. Use of CGM devices is associated with lower HbA1c and a reduction in hypoglycaemic events, promoting overall health and athletic performance. However, there are limitations to CGM, which must be considered when being used by an athlete with T1DM. These limitations can be addressed by individualized education plans, using protective equipment to prevent sensor dislodgement, as well as further research aiming to: (i) account for disparities between CGM and true blood glucose levels during vigorous exercise; (ii) investigate the effects of temperature and altitude on CGM accuracy, and (iii) explore of the sociological impact of CGM use amongst sportspeople without diabetes on those with T1DM.

Impact of socioeconomic status on chronic control and complications of type 1 diabetes mellitus in users of glucose flash systems: a follow-up study.

BACKGROUND: This study investigates the association between socioeconomic status (SES) and glycemic control in individuals with type 1 diabetes (T1D) using flash glucose monitoring (FGM) devices within a public health system where these technologies are freely available and utilized according to recommended guidelines. METHODS: A follow-up study of 1060 adults (mean age 47.4 ± 15.0 years, 49.0% women) with T1D, receiving care at three Spanish university hospitals that regularly employ the FGM system. SES was assessed using the Spanish Deprivation Index and the average annual net income per person. Glycemic data were collected over a 14-day follow-up period, including baseline glycated hemoglobin (HbA1c) levels prior to sensor placement, the last available HbA1c levels, and FGM-derived glucose metrics. Individuals with sensor usage time < 70% were excluded. Chronic micro and macrovascular complications related to diabetes were documented. Regression models, adjusted for clinical variables, were employed to determine the impact of SES on optimal sensor control (defined as time in range (TIR) ≥ 70% with time below range < 4%) and disease complications. RESULTS: The average follow-up was of 2 years. The mean TIR and the percentage of individuals with optimal control were higher in individuals in the highest SES quartile (64.9% ± 17.8% and 27.9%, respectively) compared to those in the lowest SES quartile (57.8 ± 17.4% and 12.1%) (p < 0.001). Regression models showed a higher risk of suboptimal control (OR 2.27, p < 0.001) and ischemic heart disease and/or stroke (OR 3.59, p = 0.005) in the lowest SES quartile. No association was observed between SES and the risk of diabetic nephropathy and retinopathy. FGM system improved HbA1c levels across all SES quartiles. Although individuals in the highest SES quartile still achieved a significantly lower value at the end of the follow-up 55 mmol/mol (7.2%) compared to those in the lowest SES quartile 60 mmol/mol (7.6%) (p < 0.001), the significant disparities in this parameter between the various SES groups were significantly reduced after FGM technology use. CONCLUSIONS: Socioeconomic status plays a significant role in glycemic control and complications in individuals with T1D, extending beyond access to technology and its proper utilization. The free utilization of FGM technology helps alleviate the impact of social inequalities on glycemic control.