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.
Background/Objective
The aim of this study was to systematically assess the association of insulin‐manipulation (intentional under‐ and/or overdosing of insulin), psychiatric comorbidity and diabetes ...complications.
Methods
Two diagnostic interviews (Diabetes‐Self‐Management‐Patient‐Interview and Children's‐Diagnostic‐Interview for Psychiatric Disorders) were conducted with 241 patients (age 10‐22) with type 1 diabetes (T1D) from 21 randomly selected Austrian diabetes care centers. Medical data was derived from medical records.
Results
Psychiatric comorbidity was found in nearly half of the patients with insulin‐manipulation (46.3%) compared to a rate of 17.5% in patients, adherent to the prescribed insulin therapy. Depression (18.3% vs 4.9%), specific phobia (21.1% vs 2.9%), social phobia (7.0% vs 0%), and eating disorders (12.7% vs 1.9%) were elevated in patients with insulin‐manipulation. Females (37.7%) were more often diagnosed (P = 0.001) with psychiatric disorders than males (18.4%). In females, the percentage of psychiatric comorbidity significantly increased with the level of non‐adherence to insulin therapy. Insulin‐manipulation had an effect of +0.89% in HbA1c (P = <0.001) compared to patients adherent to insulin therapy, while there was no association of psychiatric comorbidity with metabolic control (HbA1c 8.16% vs 8.12% 65.68 vs 65.25 mmol/mol). Ketoacidosis, severe hypoglycemia, and frequency of outpatient visits in a diabetes center were highest in patients with insulin‐manipulation.
Conclusions
This is the first study using a systematic approach to assess the prevalence of psychiatric disorders in patients who do or do not manipulate insulin in terms of intentional under‐ and/or overdosing.
Internalizing psychiatric disorders were associated with insulin‐manipulation, especially in female patients and insulin‐manipulation was associated with deteriorated metabolic control and diabetes complications.
Objective
To evaluate the experiences of families with very young children aged 1 to 7 years (inclusive) with type 1 diabetes using day‐and‐night hybrid closed‐loop insulin delivery.
Methods
...Parents/caregivers of 20 children aged 1 to 7 years with type 1 diabetes completed a closed‐loop experience survey following two 3‐week periods of unrestricted day‐and‐night hybrid closed‐loop insulin therapy using Cambridge FlorenceM system at home. Benefits, limitations, and improvements of closed‐loop technology were explored.
Results
Responders reported reduced burden of diabetes management, less time spent managing diabetes, and improved quality of sleep with closed‐loop. Ninety percent of the responders felt less worried about their child's glucose control using closed‐loop. Size of study devices, battery performance and connectivity issues were identified as areas for improvement. Parents/caregivers wished for more options to input information to the system such as temporary glucose targets.
Conclusions
Parents/caregivers of very young children reported important quality of life benefits associated with using closed‐loop, supporting adoption of this technology in this population.
The aim of this study was to assess accuracy of the three most commonly used continuous glucose monitoring (CGM) systems in almost real‐life situation during a diabetes camp in children with type 1 ...diabetes (T1D) aged 9–14 years. Data was gathered during a 2‐week summer camp under physicians' supervision. Out of 38 participating children with T1D (aged: 11.0 9.9; 12.1 years; 57% girls, mean HbA1c 7.2 6.9; 7.7 %,) 37 wore a CGM system (either Abbott FreeStyle Libre (FSL), Dexcom G6 (DEX) or Medtronic Enlite (ENL)) throughout the camp. All concomitantly available data pairs of capillary glucose measurements and sensor values were used for the analysis. Mean absolute relative difference (MARD) was calculated and Parkes Error Grid analyses were done for all three systems used. In total 2079 data pairs were available for analysis. The overall MARDs of CGM systems used at the camp was FSL: 13.3% (6.7;21.6). DEX: 10.3% (5.8; 16.7) and ENL 8.5% (3.6; 15.6). During eu‐, hypo‐ and hyperglycemia MARDs were lowest in ENL. Highest MARDs were seen in hypoglycemia, where all three systems exhibited MARDs above 15%. Overnight MARDs of all systems was higher than during daytime. All sensors performed worst in hypoglycemia. Performance of the adequately calibrated Medtronic system outperformed the factory‐calibrated sensors. For clinical practice, it is important to adequately train children with T1D and families in the correct procedures for sensors that require calibrations.
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’.
Objectives
To identify differences and similarities in HbA1c levels and patterns regarding age and gender in eight high‐income countries.
Subjects
66 071 children and adolescents below18 years of age ...with type 1 diabetes for at least 3 months and at least one HbA1c measurement during the study period.
Methods
Pediatric Diabetes Quality Registry data from Austria, Denmark, England, Germany, Norway, Sweden, the United States, and Wales were collected between 2013 and 2014. HbA1c, gender, age, and duration were used in the analysis.
Results
Distribution of gender and age groups was similar in the eight participating countries. The mean HbA1c varied from 60 to 73 mmol/mol (7.6%‐8.8%) between the countries. The increase in HbA1c between the youngest (0‐9 years) to the oldest (15‐17 years) age group was close to 8 mmol/mol (0.7%) in all countries (P < .001). Females had a 1 mmol/mol (0.1%) higher mean HbA1c than boys (P < .001) in seven out of eight countries.
Conclusions
In spite of large differences in the mean HbA1c between countries, a remarkable similarity in the increase of HbA1c from childhood to adolescence was found.
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.
Objective
To examine glycemic control in youth with type 1 diabetes (T1D) who switched from multiple daily injections (MDI) to a tubeless insulin pump (Omnipod Insulin Management System, Insulet ...Corporation, Billerica, Massachusetts) compared to patients who continued MDI therapy over a 3‐year time period.
Research Design and Methods
This retrospective analysis of the German/Austrian Diabetes Patienten Verlaufsdokumentation registry included data from 263 centers and 2529 patients <20 years (n = 660 tubeless insulin pump; n = 1869 MDI) who initiated treatment on a tubeless insulin pump as of January 1, 2013 and had 1 year of data preswitch from MDI and 3 years of data postswitch to a tubeless pump. Outcomes included the change in glycated hemoglobin (HbA1c), insulin dose, and body mass index (BMI) SD score (SDS).
Results
Youth with T1D who switched from MDI therapy to a tubeless insulin pump showed better glycemic control at 1 year compared to patients who continued MDI treatment, adjusted mean ± SE: 7.5% ± 0.03% (58 mmol/mol) vs 7.7% ± 0.02% (61 mmol/mol); P < .001, with no between‐group difference at 2 and 3 years. Total daily insulin dose was lower (P < .001) in the tubeless insulin pump group, 0.80 ± 0.01, 0.81 ± 0.01, and 0.85 ± 0.01 U/kg, vs the MDI group, 0.89 ± 0.01, 0.94 ± 0.01, and 0.97 ± 0.01 U/kg, at 1, 2, and 3 years, respectively (all P < .001). BMI SDS increased in both groups and was not different over time.
Conclusions
Treatment with a tubeless insulin pump in youth with T1D was associated with improvements in glycemic control compared to MDI after 1 year and appears to be an effective alternative to MDI.
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.
Objective
To investigate the prevalence of asthma in young patients with type 1 diabetes mellitus (T1D) from Austria and Germany and its influence on their metabolic control.
Methods
This ...prospective, multicenter observational cohort study was based on the DPV‐registry (German/Austrian DPV initiative) including 51 926 patients with T1D (<20 years). All clinical data were documented prospectively. To identify patients with additional asthma, the entry of the diagnosis asthma as well as asthma medication was used for classification.
Results
1755 patients (3.4%) of the cohort had the diagnosis asthma or received asthma‐specific drugs. Patients with asthma needed higher insulin doses (0.88 ± 0.3 vs 0.84 ± 0.3 U/kg, P < .01) and had decreased height‐standard deviation score (SDS) (−0.002 ± 1.04 vs 0.085 ± 1.02, P < .01); they were more often males (61% vs 52%, P < .01), had an increased body mass index (BMI)‐SDS (0.31 ± 0.89 vs 0.28 ± 0.89, P = .04) and experienced more severe hypoglycemia (4.5 4.2; 4.8 vs 3.2 3.2; 3.3 events/100 pts. years, P < .01). Glycated hemoglobin A1c (HbA1c) did not differ between patients with and without asthma overall, only sub groups (corticosteroids vs leukotriene antagonist and corticosteroids vs sympatomimetics) revealed differences. No influence of asthma medication on metabolic control or BMI‐SDS could be found.
Conclusion
In our DPV‐database, frequency of asthma and T1D seems similar to the prevalence of asthma in the healthy German background population. The concomitant diagnosis of asthma and T1D had minor influence on metabolic control and diabetes complication rate, although there was no difference in HbA1c overall. Patients with both diseases seem to be slightly growth restricted and require slightly higher insulin doses.
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