Retrospective Comparison of Commercially Available Automated Insulin Delivery With Open-Source Automated Insulin Delivery Systems in Type 1 Diabetes.

BACKGROUND: Automated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems. MATERIALS AND METHODS: A total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed. RESULTS: The PWT1D using OS-AID systems spent more time in range (TIR)70-180 mg/dL (81.7% vs 73.9%), less time above range (TAR)181-250 mg/dL (11.1% vs 19.6%), less TAR>250 mg/dL (2.5% vs 4.3%), and more time below range (TBR)54-69 mg/dL (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR<54 mg/dL was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%). CONCLUSION: In conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.

Expected Basal Insulin Requirement During Continuous Subcutaneous Insulin Infusion Therapy by Age Group, Sex, and Body Mass Index, Based on 25,718 Young People with Type 1 Diabetes in the DPV Registry.

Background: Since the introduction of insulin pumps into the therapy of pediatric subjects, different approaches have been taken to find optimal basal rates. Previously, the DPV registry provided circadian basal rate patterns for different age groups. As the number of pump users has increased recently and short-acting insulin analogues are now predominant, we performed a new analysis with a larger data pool. Methods: We included all recent basal profiles from type 1 diabetes (T1D) patients between 1 and 25 years from the DPV 2021 data pool. We excluded night-time-only pump users, human regular insulin users, and daily basal rates <0.05 and >1.0 U/(kgBW·d). Results: In the analysis of profiles from 25,718 young persons with T1D, differences in the daily pattern of basal rates were found between age groups. In addition, we saw significant (P < 0.001) differences in total daily basal dose between genders in all age groups except adults. In addition, the shape of the expected basal-rate pattern differed by body mass index, HbA1c, and use of continuous glucose monitoring. Discussion: This analysis demonstrates multiple factors influencing basal patterns and insulin requirement, including age group, gender, overweight, HbA1c, bolus frequency, and sensor use. As circadian basal rates are still mandatory for initiating insulin pump therapy with or without automation, a multimodal approach is necessary to estimate optimal basal rates.

[Antihyperglycemic treatment guidelines for diabetes mellitus type 2 (Update 2023)]. / Antihyperglykämische Therapie bei Diabetes mellitus Typ 2 (Update 2023).

Hyperglycemia significantly contributes to complications in patients with diabetes mellitus. While lifestyle interventions remain cornerstones of disease prevention and treatment, most patients with type 2 diabetes will eventually require pharmacotherapy for glycemic control. The definition of individual targets regarding optimal therapeutic efficacy and safety as well as cardiovascular effects is of great importance. In this guideline we present the most current evidence-based best clinical practice data for healthcare professionals.

[Insulin pump therapy and continuous glucose monitoring]. / Diabetestechnologie (Update 2023).

This Guideline represents the recommendations of the Austrian Diabetes Association (ÖDG) on the use of diabetes technology (insulin pump therapy; continuous glucose monitoring, CGM; hybrid closed-loop systems, HCL; diabetes apps) and access to these technological innovations for people with diabetes mellitus based on current scientific evidence.

[Diabetes mellitus in childhood and adolescence (Update 2023)]. / Diabetes mellitus im Kindes- und Jugendalter (Update 2023).

In contrast to adults, type 1 diabetes mellitus (T1D) is the most frequent form of diabetes in childhood and adolescence (> 90%). After diagnosis the management of children and adolescents with T1D should take place in highly specialized pediatric units experienced in pediatric diabetology. The lifelong substitution of insulin is the cornerstone of treatment whereby modalities need to be individually adapted for patient age and the family routine. In this age group the usage of diabetes technology (glucose sensors, insulinpumps and recently hybrid-closed-loop-systems) is recommended. An optimal metabolic control right from the start of therapy is associated with an improved long-term prognosis. Diabetes education is essential in the management of patients with diabetes and their families and needs to be performed by a multidisciplinary team consisting of a pediatric diabetologists, diabetes educator, dietitian, psychologist and social worker. The Austrian working group for pediatric endocrinology and diabetes (APEDÖ) and the ISPAD (International Society for Pediatric and Adolescent Diabetes) recommend a metabolic goal of HbA1c ≤ 7.0%, ((IFCC) < 53 mmol/mol), and a "Time in range" > 70% for all pediatric age groups without the presence of severe hypoglycemia. Age-related physical, cognitive and psychosocial development, screening for associated diseases, avoidance of acute diabetes-related complications (severe hypoglycemia, diabetic ketoacidosis) and prevention of diabetes-related late complications to ensure high quality of life are the main goals of diabetes treatment in all pediatric age groups.

Frequency and characteristics of diabetes in lipodystrophies and insulin receptoropathies compared with type 1 and type 2: results from the multicenter DPV registry.

Objective: To investigate the frequency, treatment, and outcome of patients with diabetes due to severe insulin resistance syndromes (SIRS). Research Design and Methods: Based on data from the multicenter prospective Diabetes Registry DPV, we analyzed diagnosis, treatment, and outcome of 636,777 patients with diabetes from 1995 to 2022. Results: Diabetes due to SIRS was documented in 67 cases (62.7% females), 25 (37%) had lipodystrophies (LD) and 42 (63%) had congenital defects of insulin signaling. The relative frequency compared to type 1 diabetes (T1D) was about 1:2300. Median age at diabetes diagnosis in patients with SIRS was 14.8 years (interquartile range (IQR) 12.8-33.8). A total of 38 patients with SIRS (57%) received insulin and 34 (51%) other antidiabetics, mostly metformin. As high as 16% of patients with LD were treated with fibrates. Three out of eight patients with generalized LD (37.5%) were treated with metreleptin and one patient with Rabson-Mendenhall syndrome was treated with recombinant insulin-like growth factor 1. The median glycated hemoglobin level at follow-up was 7.1% (54 mmol/mol). Patients with LD had higher triglycerides than patients with T1D and T2D (P < 0.001 and P = 0.022, respectively), and also significantly higher liver enzymes and lower high-density lipoprotein cholesterol than patients with T1D (P < 0.001). Patients with insulin receptor disorders were significantly less likely to be treated with antihypertensive medication than patients with T2D (P = 0.042), despite having similar levels of hypertension. Conclusions: Diabetes due to SIRS is rarely diagnosed and should be suspected in lean children or young adults without classical T1D. Awareness of cardiovascular risk factors in these patients should be raised.

Safety of User-Initiated Intensification of Insulin Delivery Using Cambridge Hybrid Closed-Loop Algorithm.

OBJECTIVE: Many hybrid closed-loop (HCL) systems struggle to manage unusually high glucose levels as experienced with intercurrent illness or pre-menstrually. Manual correction boluses may be needed, increasing hypoglycemia risk with overcorrection. The Cambridge HCL system includes a user-initiated algorithm intensification mode ("Boost"), activation of which increases automated insulin delivery by approximately 35%, while remaining glucose-responsive. In this analysis, we assessed the safety of "Boost" mode. METHODS: We retrospectively analyzed data from closed-loop studies involving young children (1-7 years, n = 24), children and adolescents (10-17 years, n = 19), adults (≥24 years, n = 13), and older adults (≥60 years, n = 20) with type 1 diabetes. Outcomes were calculated per participant for days with ≥30 minutes of "Boost" use versus days with no "Boost" use. Participants with <10 "Boost" days were excluded. The main outcome was time spent in hypoglycemia <70 and <54 mg/dL. RESULTS: Eight weeks of data for 76 participants were analyzed. There was no difference in time spent <70 and <54 mg/dL between "Boost" days and "non-Boost" days; mean difference: -0.10% (95% confidence interval [CI] -0.28 to 0.07; P = .249) time <70 mg/dL, and 0.03 (-0.04 to 0.09; P = .416) time < 54 mg/dL. Time in significant hyperglycemia >300 mg/dL was 1.39 percentage points (1.01 to 1.77; P < .001) higher on "Boost" days, with higher mean glucose and lower time in target range (P < .001). CONCLUSIONS: Use of an algorithm intensification mode in HCL therapy is safe across all age groups with type 1 diabetes. The higher time in hyperglycemia observed on "Boost" days suggests that users are more likely to use algorithm intensification on days with extreme hyperglycemic excursions.

Time in Range in Children with Type 1 Diabetes before and during a Diabetes Camp-A Ceiling Effect?

Background: The aim of this study was to assess and compare the time in range (TIR) of children with type 1 diabetes (T1D) before and during a diabetes summer camp using different therapy modalities. Methods: A retrospective analysis of continuous glucose monitoring (CGM) data collected from 26 children with T1D (mean age: 11.0 ± 1.4 years; 62% female; 62% on insulin pump; Hb1Ac 7.3 ± 0.8% (56.3 ± 8.7 mmol/mol) before and during a 14-day summer camp. CGM methods: 50% intermittently scanned CGM (isCGM) and 50% real-time CGM (rtCGM). No child was using a hybrid closed loop system. Results: Mean TIR during camp was significantly higher than before camp ((67.0 ± 10.7%) vs. 58.2% ± 17.4%, p = 0.004). There was a significant reduction in time above range (TAR) (p = 0.001) and increase in time below range (TBR) (p < 0.001), Children using isCGM showed a more pronounced improvement in TIR during camp compared to rtCGM-users (p = 0.025). The increase in TIR strongly correlated with numbers of scans per day in isCGM-users (r = 0.751, p = 0.003). Compared to isCGM-users, rtCGM-users showed significantly less TBR. The TIR target was met by 30.8% of participants during camp. Conclusion: Glycemic control improved significantly during the camp. However, on average, the therapy goal (TIR > 70%) could not be achieved despite great professional effort.

Evaluating the Impact of Applying Personal Glucose Targets in a Closed-Loop System for People With Type 1 Diabetes.

BACKGROUND: CamAPS FX is a hybrid closed-loop smartphone app used to manage type one diabetes. The closed-loop algorithm has a default target glucose of 5.8 mmol/L (104.5 mg/dL), but users can select personal glucose targets (adjustable between 4.4 mmol/L and 11.0 mmol/L [79 mg/dL and 198 mg/dL, respectively]). METHOD: In this post-hoc analysis, we evaluated the impact of personal glucose targets on glycemic control using data from participants in five randomized controlled trials. RESULTS: Personal glucose targets were widely used, with 20.3% of all days in the data set having a target outside the default target bin (5.5-6.0 mmol/L [99-108 mg/dL]). Personal glucose targets >6.5 mmol/L (117 mg/dL) were associated with significantly less time in target range (3.9-10.0 mmol/L [70-180 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: mean difference = -3.2 percentage points [95% CI: -5.3 to -1.2; P < .001]; 7.0-7.5 mmol/L [126-135 mg/dL]: -10.8 percentage points [95% CI: -14.1 to -7.6; P < .001]). Personal targets >6.5 mmol/L (117 mg/dL) were associated with significantly lower time (<3.9 mmol/L [<70 mg/dL]; 6.5-7.0 mmol/L [117-126 mg/dL]: -1.85 percentage points [95% CI: -2.37 to -1.34; P < .001]; 7.0-7.5 mmol/L [126-135 mg/dL]: -2.68 percentage points [95% CI: -3.49 to -1.86; P < .001]). CONCLUSIONS: Discrete study populations showed differences in glucose control when applying similar personal targets.

Cambridge Hybrid Closed-Loop System in Very Young Children With Type 1 Diabetes Reduces Caregivers' Fear of Hypoglycemia and Improves Their Well-Being.

OBJECTIVE: To evaluate the impact of CamAPS FX hybrid closed-loop (HCL) automated insulin delivery in very young children with type 1 diabetes (T1D) on caregivers' well-being, fear of hypoglycemia, and sleepiness. RESEARCH DESIGN AND METHODS: We conducted a multinational, open-label, randomized crossover study. Children (age 1-7 years) with T1D received treatment for two 4-month periods in random order, comparing HCL with sensor augmented pump (control). At baseline and after each treatment period, caregivers were invited to complete World Health Organization-Five Well-Being Index, Hypoglycemia Fear Survey, and Epworth Sleepiness Scale questionnaires. RESULTS: Caregivers of 74 children (mean ± SD age 5 ± 2 years and baseline HbA1c 7.3 ± 0.7%; 42% female) participated. Results revealed significantly lower scores for hypoglycemia fear (P < 0.001) and higher scores for well-being (P < 0.001) after HCL treatment. A trend toward a reduction in sleepiness score was observed (P = 0.09). CONCLUSIONS: Our results suggest better well-being and less hypoglycemia fear in caregivers of very young children with T1D on CamAPS FX HCL.

Parents' views about healthcare professionals having real-time remote access to their young child's diabetes data: Qualitative study.

OBJECTIVES: We explored parents' views about healthcare professionals having remote access to their young child's insulin and glucose data during a clinical trial to inform use of data sharing in routine pediatric diabetes care. RESEARCH DESIGN AND METHODS: Interviews with 33 parents of 30 children (aged 1-7 years) with type 1 diabetes participating in a randomized trial (KidsAP02) comparing hybrid closed-loop system use with sensor-augmented pump therapy. Data were analyzed using a qualitative descriptive approach. RESULTS: Parents reported multiple benefits to healthcare professionals being able to remotely access their child's glucose and insulin data during the trial, despite some initial concerns regarding the insights offered into everyday family life. Key benefits included: less work uploading/sharing data; improved consultations; and, better clinical input and support from healthcare professionals between consultations. Parents noted how healthcare professionals' real-time data access facilitated remote delivery of consultations during the COVID-19 pandemic, and how these were more suitable for young children than face-to-face appointments. Parents endorsed use of real-time data sharing in routine clinical care, subject to caveats regarding data access, security, and privacy. They also proposed that, if data sharing were used, consultations for closed-loop system users in routine clinical care could be replaced with needs-driven, ad-hoc contact. CONCLUSIONS: Real-time data sharing can offer clinical, logistical, and quality-of-life benefits and enhance opportunities for remote consultations, which may be more appropriate for young children. Wider rollout would require consideration of ethical and cybersecurity issues and, given the heightened intrusion on families' privacy, a non-judgmental, collaborative approach by healthcare professionals.

Parents' experiences of using a hybrid closed-loop system (CamAPS FX) to care for a very young child with type 1 diabetes: Qualitative study.

AIMS: To explore parents' experiences of using a hybrid closed-loop system (CamAPS FX) when caring for a very young child (aged 1-7 years) with type 1 diabetes. METHODS: Interviews with n = 33 parents of 30 children who used the system during a randomised controlled trial. Data analysis used a descriptive thematic approach. RESULTS: While some parents were initially reticent about handing control to the system, all reported clinical benefits to using the technology, having to do less diabetes-related work and needing less clinical input over time. Parents welcomed opportunities to enhance the system's efficacy (using Ease-off and Boost functions) as required. Parents described how the system's automated glucose control facilitated more normality, including sleeping better, worrying less about their child, and feeling more confident and able to outsource care. Parents also described more normality for the child (alongside better sleep, mood and concentration, and lessened distress) and siblings. Parents liked being able to administer insulin using a smartphone, but suggested refinements to device size and functionality. CONCLUSIONS: Using a hybrid closed-loop system in very young children can facilitate greater normality and may result in a lessened demand for health professionals' input. Systems may need to be customised for very young children.

Parents' experiences of using remote monitoring technology to manage type 1 diabetes in very young children during a clinical trial: Qualitative study.

AIMS: To explore parents' experiences of using remote monitoring technology when caring for a very young child with type 1 diabetes during a clinical trial. METHODS: Interviews were conducted with parents of 30 children (aged 1-7 years) participating in a trial (the KidsAP02 study) comparing hybrid closed-loop insulin delivery with sensor-augmented pump therapy. In both arms, parents had access to remote monitoring technology. Data analysis focused on identification of descriptive themes. RESULTS: Remote monitoring technology gave parents improved access to data which helped them pre-empt and manage glucose excursions. Parents observed how, when children were in their own care, they could be more absent while present, as their attention could shift to non-diabetes-related activities. Conversely, when children were others' care, remote monitoring enabled parents to be present while absent, by facilitating oversight and collaboration with caregivers. Parents described how remote monitoring made them feel more confident allowing others to care for their children. Parents' confidence increased when using a hybrid closed-loop system, as less work was required to keep glucose in range. Benefits to children were also highlighted, including being able to play and sleep uninterrupted and attend parties and sleepovers without their parents. While most parents welcomed the increased sense of control remote monitoring offered, some noted downsides, such as lack of respite from caregiving responsibilities. CONCLUSIONS: Remote monitoring can offer manifold benefits to both parents and very young children with type 1 diabetes. Some parents, however, may profit from opportunities to take 'time out'.

Alarming Increase of Ketoacidosis Prevalence at Type 1 Diabetes-Onset in Austria-Results From a Nationwide Registry.

OBJECTIVE: We analyzed the annual prevalence of onset-DKA (diabetic ketoacidosis) from 2012 to 2020 with a sub-analysis for lockdown-periods during the COVID-19 pandemic in 2020. DESIGN: All newly diagnosed children with type 1 diabetes (T1D) aged <15 years are prospectively registered in the population-based Austrian Diabetes Incidence Study in Austria. MAIN OUTCOME MEASURES: The annual DKA prevalence was analyzed using Joinpoint regression. Definition of DKA: pH <7.3, mild DKA: pH 7.3 to ≤ 7.1, severe DKA: pH <7.1. DKA prevalence during the lockdown periods in 2020 and the corresponding periods in 2015-2019 were examined using Fisher's exact test. RESULTS: In the years 2012-2020 the mean prevalence for onset-DKA in Austria was 43.6% [95%CI (confidence interval): 41.6, 45.7] and thus above the mean prevalence of previous decades (1989-2011) of 37,1 % (95%CI: 35.6, 38.6). A particularly high prevalence was found among children <2 years of age (72.0% DKA, 32.8% severe DKA). No significant gender difference was found. Prevalence of severe DKA at T1D-onset increased significantly since 2015 (p = 0.023). During the lockdown in 2020, 59.3% of children were diagnosed with DKA at T1D-onset, compared to 42.1% during the previous 5 years (p = 0.022). Moreover, 20% of children had severe DKA at T1D diagnosis, compared to 14% during the comparison period. CONCLUSIONS: The previously already high prevalence of DKA at T1D-onset has further increased over time. The COVID-19 pandemic has exacerbated the problem of a late or delayed diagnosis of diabetes in children resulting in onset-DKA. The alarmingly increased prevalence of DKA in Austrian children with T1D calls for urgent action.

Increased referrals for congenital hyperinsulinism genetic testing in children with trisomy 21 reflects the high burden of non-genetic risk factors in this group.

BACKGROUND: Hyperinsulinism results from inappropriate insulin secretion during hypoglycaemia. Down syndrome is causally linked to a number of endocrine disorders including Type 1 diabetes and neonatal diabetes. We noted a high number of individuals with Down syndrome referred for hyperinsulinism genetic testing, and therefore aimed to investigate whether the prevalence of Down syndrome was increased in our hyperinsulinism cohort compared to the population. METHODS: We identified individuals with Down syndrome referred for hyperinsulinism genetic testing to the Exeter Genomics Laboratory between 2008 and 2020. We sequenced the known hyperinsulinism genes in all individuals and investigated their clinical features. RESULTS: We identified 11 individuals with Down syndrome in a cohort of 2011 patients referred for genetic testing for hyperinsulinism. This represents an increased prevalence compared to the population (2.5/2011 expected vs. 11/2011 observed, p = 6.8 × 10-5 ). A pathogenic ABCC8 mutation was identified in one of the 11 individuals. Of the remaining 10 individuals, five had non-genetic risk factors for hyperinsulinism resulting from the Down syndrome phenotype: intrauterine growth restriction, prematurity, gastric/oesophageal surgery, and asparaginase treatment for leukaemia. For five individuals no risk factors for hypoglycaemia were reported although two of these individuals had transient hyperinsulinism and one was lost to follow-up. CONCLUSIONS: Down syndrome is more common in patients with hyperinsulinism than in the population. This is likely due to an increased burden of non-genetic risk factors resulting from the Down syndrome phenotype. Down syndrome should not preclude genetic testing as coincidental monogenic hyperinsulinism and Down syndrome is possible.

Randomized Trial of Closed-Loop Control in Very Young Children with Type 1 Diabetes.

BACKGROUND: The possible advantage of hybrid closed-loop therapy (i.e., artificial pancreas) over sensor-augmented pump therapy in very young children with type 1 diabetes is unclear. METHODS: In this multicenter, randomized, crossover trial, we recruited children 1 to 7 years of age with type 1 diabetes who were receiving insulin-pump therapy at seven centers across Austria, Germany, Luxembourg, and the United Kingdom. Participants received treatment in two 16-week periods, in random order, in which the closed-loop system was compared with sensor-augmented pump therapy (control). The primary end point was the between-treatment difference in the percentage of time that the sensor glucose measurement was in the target range (70 to 180 mg per deciliter) during each 16-week period. The analysis was conducted according to the intention-to-treat principle. Key secondary end points included the percentage of time spent in a hyperglycemic state (glucose level, >180 mg per deciliter), the glycated hemoglobin level, the mean sensor glucose level, and the percentage of time spent in a hypoglycemic state (glucose level, <70 mg per deciliter). Safety was assessed. RESULTS: A total of 74 participants underwent randomization. The mean (±SD) age of the participants was 5.6±1.6 years, and the baseline glycated hemoglobin level was 7.3±0.7%. The percentage of time with the glucose level in the target range was 8.7 percentage points (95% confidence interval [CI], 7.4 to 9.9) higher during the closed-loop period than during the control period (P<0.001). The mean adjusted difference (closed-loop minus control) in the percentage of time spent in a hyperglycemic state was -8.5 percentage points (95% CI, -9.9 to -7.1), the difference in the glycated hemoglobin level was -0.4 percentage points (95% CI, -0.5 to -0.3), and the difference in the mean sensor glucose level was -12.3 mg per deciliter (95% CI, -14.8 to -9.8) (P<0.001 for all comparisons). The time spent in a hypoglycemic state was similar with the two treatments (P = 0.74). The median time spent in the closed-loop mode was 95% (interquartile range, 92 to 97) over the 16-week closed-loop period. One serious adverse event of severe hypoglycemia occurred during the closed-loop period. One serious adverse event that was deemed to be unrelated to treatment occurred. CONCLUSIONS: A hybrid closed-loop system significantly improved glycemic control in very young children with type 1 diabetes, without increasing the time spent in hypoglycemia. (Funded by the European Commission and others; ClinicalTrials.gov number, NCT03784027.).

Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin.

Laboratory measured glycated haemoglobin (HbA1c) is the gold standard for assessing glycaemic control in people with diabetes and correlates with their risk of long-term complications. The emergence of continuous glucose monitoring (CGM) has highlighted limitations of HbA1c testing. HbA1c can only be reviewed infrequently and can mask the risk of hypoglycaemia or extreme glucose fluctuations. While CGM provides insights in to the risk of hypoglycaemia as well as daily fluctuations of glucose, it can also be used to calculate an estimated HbA1c that has been used as a substitute for laboratory HbA1c. However, it is evident that estimated HbA1c and HbA1c values can differ widely. The glucose management indicator (GMI), calculated exclusively from CGM data, has been proposed. It uses the same scale (% or mmol/mol) as HbA1c, but is based on short-term average glucose values, rather than long-term glucose exposure. HbA1c and GMI values differ in up to 81% of individuals by more than ±0.1% and by more than ±0.3% in 51% of cases. Here, we review the factors that define these differences, such as the time period being assessed, the variation in glycation rates and factors such as anaemia and haemoglobinopathies. Recognizing and understanding the factors that cause differences between HbA1c and GMI is an important clinical skill. In circumstances when HbA1c is elevated above GMI, further attempts at intensification of therapy based solely on the HbA1c value may increase the risk of hypoglycaemia. The observed difference between GMI and HbA1c also informs the important question about the predictive ability of GMI regarding long-term complications.

International comparison of glycaemic control in people with type 1 diabetes: an update and extension.

AIMS: To update and extend a previous cross-sectional international comparison of glycaemic control in people with type 1 diabetes. METHODS: Data were obtained for 520,392 children and adults with type 1 diabetes from 17 population and five clinic-based data sources in countries or regions between 2016 and 2020. Median HbA1c (IQR) and proportions of individuals with HbA1c < 58 mmol/mol (<7.5%), 58-74 mmol/mol (7.5-8.9%) and ≥75 mmol/mol (≥9.0%) were compared between populations for individuals aged <15, 15-24 and ≥25 years. Logistic regression was used to estimate the odds ratio (OR) of HbA1c < 58 mmol/mol (<7.5%) relative to ≥58 mmol/mol (≥7.5%), stratified and adjusted for sex, age and data source. Where possible, changes in the proportion of individuals in each HbA1c category compared to previous estimates were calculated. RESULTS: Median HbA1c varied from 55 to 79 mmol/mol (7.2 to 9.4%) across data sources and age groups so a pooled estimate was deemed inappropriate. OR (95% CI) for HbA1c < 58 mmol/mol (<7.5%) were 0.91 (0.90-0.92) for women compared to men, 1.68 (1.65-1.71) for people aged <15 years and 0.81 (0.79-0.82) aged15-24 years compared to those aged ≥25 years. Differences between populations persisted after adjusting for sex, age and data source. In general, compared to our previous analysis, the proportion of people with an HbA1c  < 58 mmol/l (<7.5%) increased and proportions of people with HbA1c ≥ 75 mmol/mol (≥9.0%) decreased. CONCLUSIONS: Glycaemic control of type 1 diabetes continues to vary substantially between age groups and data sources. While some improvement over time has been observed, glycaemic control remains sub-optimal for most people with Type 1 diabetes.

Psychological Well-Being of Parents of Very Young Children With Type 1 Diabetes - Baseline Assessment.

Background: Type 1 diabetes in young children is a heavy parental burden. As part of pilot phase of the KIDSAP01 study, we conducted a baseline assessment in parents to study the association between hypoglycemia fear, parental well-being and child behavior. Methods: All parents were invited to fill in baseline questionnaires: hypoglycemia fear survey (HFS), WHO-5, Epworth Sleepiness Scale and Strength and Difficulties Questionnaire (SDQ). Results: 24 children (median age: 5-year, range 1-7 years, 63% male, mean diabetes duration: 3 ± 1.7 years) participated. 23/24 parents filled out the questionnaires. We found a higher score for the hypoglycemia fear behavior 33.9 ± 5.6 compared to hypoglycemia worry 34.6 ± 12.2. Median WHO-5 score was 16 (8 - 22) with poor well-being in two parents. Median daytime sleepiness score was high in five parents (>10). For six children a high total behavioral difficulty score (>16) was reported. Pro social behavior score was lower than normal in six children (<6). Parental well-being was negatively associated with HFS total (r = - 0.50, p <.05) and subscale scores (r = - 0.44, p <.05 for HFS-Worry and HFS-Behavior), child behavior (r = - 0.45, p = .05) and positively with child age and diabetes duration (r = 0.58, p <.01, r = 0.6, p <.01). HFS, parental well-being nor daytime sleepiness are associated with the HbA1c. Conclusion: Regular screening of parental well-being, hypoglycemia fear and child behavior should be part of routine care to target early intervention.