Metabolic control of type 1 diabetes in youth with autism spectrum disorder: A multicenter Diabetes-Patienten-Verlaufsdokumentation analysis based on 61 749 patients up to 20 years of age

Equity in the Provision of Diabetes Self-Management Education and Support

Diabetes self-management education and support (DSMES) interventions must be accessible to all people with diabetes. To address equity in the delivery of DSMES, interventions should consider the unique needs of various populations. This article outlines the needs of a wide range of populations, including people with diabetes who are racially or ethnically diverse; have limited English proficiency or literacy; are deaf or hard of hearing; are blind or have low vision; are neurodiverse; live with learning disabilities or intellectual or developmental disabilities; have dementia or cognitive impairment; or are of sexual and/or gender minority. The authors discuss how best to tailor DSMES to meet the needs of these diverse groups.

Neurodevelopmental Disorders, Glycemic Control, and Diabetic Complications in Type 1 Diabetes: a Nationwide Cohort Study

CONTEXT

Neurodevelopmental disorders are more prevalent in childhood-onset type 1 diabetes than in the general population, and the symptoms may limit the individual's ability for diabetes management.

OBJECTIVE

This study investigated whether comorbid neurodevelopmental disorders are associated with long-term glycemic control and risk of diabetic complications.

METHODS

This population-based cohort study used longitudinally collected data from Swedish registers. We identified 11 326 individuals born during 1973-2013, diagnosed with type 1 diabetes during 1990-2013 (median onset age: 9.6 years). Among them, 764 had a comorbid neurodevelopmental disorder, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, and intellectual disability. We used multinomial logistic regression to calculate odds ratios (ORs) of having poor glycemic control (assessed by glycated hemoglobin [HbA1c]) and Cox regression to estimate hazard ratios (HRs) of nephropathy and retinopathy.

RESULTS

The median follow-up was 7.5 years (interquartile range [IQR] 3.9, 11.2). Having any neurodevelopmental disorder (ORadjusted 1.51 [95% CI 1.13, 2.03]), or ADHD (ORadjusted 2.31 [95% CI 1.54, 3.45]) was associated with poor glycemic control (mean HbA1c > 8.5%). Increased risk of diabetic complications was observed in patients with comorbid neurodevelopmental disorders (HRadjusted 1.72 [95% CI 1.21, 2.44] for nephropathy, HRadjusted 1.18 [95% CI 1.00, 1.40] for retinopathy) and patients with ADHD (HRadjusted 1.90 [95% CI 1.20, 3.00] for nephropathy, HRadjusted 1.33 [95% CI 1.07, 1.66] for retinopathy). Patients with intellectual disability have a particularly higher risk of nephropathy (HRadjusted 2.64 [95% CI 1.30, 5.37]).

CONCLUSION

Comorbid neurodevelopmental disorders, primarily ADHD and intellectual disability, were associated with poor glycemic control and a higher risk of diabetic complications in childhood-onset type 1 diabetes.

Intermittently Scanned Glucose Values for Continuous Monitoring: Cross-Sectional Analysis of Glycemic Control and Hypoglycemia in 1809 Children and Adolescents with Type 1 Diabetes

Background and Objective: Intermittent scanning continuous glucose monitoring (iscCGM) is increasingly used for glycemic monitoring in diabetes care. In this cross-sectional real-world analysis, iscCGM data were compared to traditional parameters of glycemic control in young people with type 1 diabetes. Methods: Using the DPV registry, most recent data from children and adolescents aged <18 years with uploaded iscCGM sensor profiles with at least 14 days of data and a > 50% completeness were evaluated using recommended parameters of sensor metrics. Analysis was performed stratified by age group, glycemic control, and type of therapy; data were taken from DPV data pool in February 2020. Results: Glucose sensor profiles and clinical data from 1809 individuals (mean age 13.4 years, 53% male, and mean diabetes duration 5.02 years) were evaluated in this study. More than 50% of this population (n = 965) reached the current German treatment target of hemoglobin A1c (HbA1c) <7.5%. In this target, the mean scanning frequency was higher than in groups with HbA1c >7.5 or >8.0% (12.0 vs. 10.2 vs 7.6 times per day). The group of preschool children had the highest frequency of scanning (16.6 vs. 13.3 times per day in school kids and 7.9 in adolescents), the lowest HbA1c level, and the lowest risk for hypoglycemia (low blood glucose index 0.8 vs. 1.0 vs 1.2). Conclusion: Real-world data will help to determine the value of iscCGM to improve clinical and patient-related outcomes in pediatric diabetology. Not only the use of a device but also the intensity of use seems to have a high and direct impact on glycemic control.

The Prevalence of Diabetes in Autistic Persons: A Systematic Review

Background:

It has been proposed that autistic individuals are at an increased risk of type 1 and type 2 diabetes. Improved understanding of diabetes prevalence in autistic persons will help inform resource allocation for diabetes-related public health measures for this patient group.

Objective:

To conduct a systematic review of published literature pertaining to type 1 and type 2 diabetes prevalence in autistic individuals, including comparison with their non-autistic peers.

Methods:

Eligibility criteria included studies investigating the prevalence of diabetes in autistic individuals, as well as having been published in the English language. A systematic search of online databases (MEDLINE, PsycINFO, CINAHL, EMBASE and PubMed) was conducted on 4^th April 2020. Additional approaches included the ancestry method, grey literature searches and expert consultation. Studies were qualitatively analysed with reporting quality appraised.

Results:

19 eligible studies were identified, 7 of which provided type-specific diabetes prevalence data. Of 15 studies that included a non-autistic control group, 9 reported a higher diabetes prevalence among autistic persons, with a statistically significant difference in 4 studies. Studies demonstrating a higher diabetes prevalence in autistic groups had higher average study population sizes and reporting quality ratings.

Conclusion:

It is uncertain whether diabetes is significantly more prevalent in autistic persons relative to their non-autistic peers, though larger studies suggest a trend in this direction. Nevertheless, diabetes is a significant public health issue for the autistic community, which may require a tailored approach for identification and management. Prospero database registration number: CRD42019122176.

Beyond the brain: A multi-system inflammatory subtype of autism spectrum disorder

An immune-mediated subtype of autism spectrum disorder (ASD) has long been hypothesized. This article reviews evidence from family history studies of autoimmunity, immunogenetics, maternal immune activation, neuroinflammation, and systemic inflammation, which suggests immune dysfunction in ASD. Individuals with ASD have higher rates of co-morbid medical illness than the general population. Major medical co-morbidities associated with ASD are discussed by body system. Mechanisms by which FDA-approved and emerging treatments for ASD act upon the immune system are then reviewed. We conclude by proposing the hypothesis of an immune-mediated subtype of ASD which is characterized by systemic, multi-organ inflammation or immune dysregulation with shared mechanisms that drive both the behavioral and physical illnesses associated with ASD. Although gaps in evidence supporting this hypothesis remain, benefits of this conceptualization include framing future research questions that will help define a clinically meaningful subset of patients and focusing clinical interactions on early detection and treatment of high-risk medical illnesses as well as interfering behavioral signs and symptoms across the lifespan.

Autism spectrum disorder in children with Type 1 diabetes

AIM

Links between autism spectrum disorder (ASD) and autoimmune diseases, including Type 1 diabetes have been proposed. This study assessed the frequency of ASD in children with Type 1 diabetes in the T1D Exchange (T1DX) registry and the impact of ASD on characteristics of children with Type 1 diabetes.

METHODS

Analysis included 10 032 participants aged < 18 years (median Type 1 diabetes duration 6.5 years, 48% female, 77% non-Hispanic White). Diagnosis of ASD was defined as autism, Asperger's or pervasive developmental disorder.

RESULTS

A diagnosis of ASD was recorded for 159 (1.58%) participants. Those with ASD were predominantly male (88% vs. 51% of those without ASD, P < 0.001) and slightly older (median 14 vs. 13 years, P = 0.022). Occurrence of diabetic ketoacidosis at Type 1 diabetes diagnosis was similar (35% vs. 41%, P = 0.161). Pump use was lower in those with ASD (51% vs. 63%, P = 0.005) but continuous glucose monitor use was similar (24% vs. 27%, P = 0.351). Median HbA_1c was slightly lower in those with ASD [68 vs. 69 mmol/mol (8.4% vs. 8.5%), P = 0.006]. This difference was more pronounced after adjusting for confounders.

CONCLUSIONS

The frequency of ASD in the T1DX registry was similar to that in the general population. These data show that despite deficits in communication, occurrence of diabetic ketoacidosis was similar in youth with and without ASD. Pump use was less frequent in those with ASD, possibly due to sensory issues, although CGM use did not differ. The lower HbA_1c may be due to a more regimented routine with ASD. Because comorbidities such as ASD complicate care of patients with Type 1 diabetes, further research is needed to support these children.

Prevalence, characteristics, and diabetes management in children with comorbid autism spectrum disorder and type 1 diabetes

OBJECTIVE

To determine autism spectrum disorder (ASD) prevalence within our pediatric type 1 diabetes (T1D) clinic population and determine clinical characteristics and technology used by individuals with both ASD and T1D compared to matched controls with T1D alone and compared to our overall pediatric T1D clinic.

METHODS

Medical chart review showed 30 individuals with both ASD and type 1 diabetes (ASD + T1D). Controls (n = 90) were matched for age, sex, race/ethnicity, and T1D duration. ASD + T1D was compared to both matched controls and the pediatric T1D clinical population.

RESULTS

ASD prevalence in the pediatric T1D population was 1.16% (CI 0.96-1.26). Compared to the T1D clinic, ASD + T1D had more males (93% vs 52%; P < 0.0001), lower hemoglobin A1c (HbA1c) (8.2% vs 8.9%; 66 vs 74 mmol/mol; P = 0.006), and lower insulin pump (CSII) use (37% vs 56%; P < 0.0001). No differences were found between ASD + T1D and matched controls in HbA1c or blood glucose checks per day. The ASD + T1D group was less likely to use CSII than matched controls (37% vs 61%; P = 0.03). HbA1c did not change after CSII initiation in ASD + T1D, but increased for matched controls.

CONCLUSIONS

Prevalence of ASD in the pediatric T1D population is comparable to the general population in Colorado. Individuals with ASD may experience barriers limiting CSII use, but achieve equivalent glycemic control compared to those without ASD. CSII may be more effective in maintaining lower HbA1c over time in those with ASD than in those without ASD.