Diabetes Technology Use Research Articles

629-P: Unique Associations between Health Insurance and HbA1c in Adults with Type 1 Diabetes

Diabetes outcomes are affected by socioeconomic factors including health insurance. While some research has examined the impact of health insurance in people with type 1 diabetes (T1D) (e.g., disruptions in health insurance on health outcomes) , it is less clear whether health insurance type (e.g., private versus government-sponsored) shares a unique association with diabetes outcomes. Thus, we examined relationships between demographics, socioeconomic status, and health insurance type with HbA1c in adults in the T1D Exchange Registry - an online longitudinal study of people living with T1D. Participants (N = 7725) were 42.2 years old (SD = 14.6) on average and 75.4% reported their gender as female. Most participants (92.2%) reported their race as White and 5.1% identified as Hispanic. Many participants used insulin pumps (71.3%) and continuous glucose monitors (CGM, 83.0%) . Self-reported HbA1c was 7.3% (SD = 1.58) on average. Health insurance type was categorized into private (79.0%) , Medicaid (9.6%) , Medicare (9.5%) , or no health insurance (1.9%) . Health insurance type, demographic factors (i.e., age, gender, race, ethnicity) , socioeconomic factors (i.e., income, education level) , and diabetes technology use (i.e., insulin pump, CGM) were entered simultaneously into a linear regression with HbA1c as the outcome variable. Private insurance was used as the reference group. Statistical significance was set at p < .05. We found lower HbA1c was associated with identifying race as White (Β = -0.21) , having higher income (Β = -0.10) , having higher education (Β = -0.17) , using an insulin pump (Β = -0.46) and using CGM (Β = -0.72) . Higher HbA1c was associated with identifying as female (Β = 0.14) and having either Medicaid (Β = 0.23) or no health insurance (Β = 0.30) . These results suggest, above and beyond other socioeconomic and demographic factors, health insurance type may contribute to small but meaningful differences in HbA1c. Disclosure C.Kelly: None. H.Nguyen: None. J.Liu: None. K.S.M.Chapman: None. M.Peter: None. C.Leon: None. K.Laferriere: None. J.Ravelson: None. W.Wolf: None.

7-LB: Gender Differences in Reported Consequences of Level 2 and Level 3 Hypoglycemia among Adults Living with Type 1 Diabetes—A BETTER Registry Analysis

Introduction: Hypoglycemia is a common side effect of type 1 diabetes (T1D) therapy with consequences ranging from physical and cognitive impairment to reduced quality of life. Studies evaluating consequences of level 2 (L2H, glucose level<3.0mmol/L without needing assistance from another person to recover) and level 3 (L3H, needing assistance from another person) hypoglycemia between the genders are sparse. Aim: To highlight the differences in reported consequences related to both L2H and L3H between genders. Methods: Self-reported data from an online Canadian registry of adults with T1D were analyzed using logistic regression models adjusted for age, diabetes technology use, hypoglycemia history in the past month, Hypoglycemia Fear Survey II (HFS II) , and Hypoglycemia Confidence Scale (HCS) scores. Results: Among 877 adults (65% women, mean age 43 ± 15 years, mean duration of T1D 25 ± 15 years, 34% reported a HbA1c ≤ 7.0%, 81% used continuous glucose monitoring, and 43% used an insulin pump) , 15% experienced L3H in the past year and 81% experienced L2H in the past month. Women reported more L2H (84% vs. 75%, p=0.004) and worse HFS-II and HCS scores than men (median 33 [IQR 23, 47] vs. 28 [18, 38], p=0.002 and 3.2 [2.9, 3.6] vs. 3.4 [3.0, 3.8], p<0.001, respectively) . The adjusted regression models showed that women were more likely than men to report experiencing persistent fatigue after L2H (OR 1.76, 95%CI [1.19, 2.61]) and increased anxiety, persistent fatigue, or an additional encounter with a healthcare professional after a L3H episode (1.71 [1.04, 2.82]; 1.75 [1.02, 3.00]; 2.59 [1.17, 5.74], respectively) . Conclusion: Women report significantly more L2H and L3H consequences compared to men, in addition to reporting higher fear and lower confidence. Social constructs on stress management may explain the observed gender differences, and suggest taking a gender-based differential approach when addressing hypoglycemia. Disclosure M. K. Talbo: None. M. Lebbar: None. V. Messier: None. Z. Wu: Other Relationship; Eli Lilly and Company. A. Brazeau: Research Support; Eli Lilly and Company, Novo Nordisk, Sanofi. R. Rabasa-lhoret: Consultant; HLS Therapeutics Inc., Pfizer Inc., Other Relationship; Abbott Diabetes, AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Janssen Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Novo Nordisk Canada Inc., Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Canadian Institutes of Health Research, Cystic Fibrosis Canada, Diabetes Canada, Fondation Francophone pour la Recherche en Diabète (FFRD) , JDRF, National Institutes of Health, Société Francophone du Diabète (SFD) , Speaker’s Bureau; Canadian Medical & Surgical Knowledge Translation Research Group (CMS) , CPD Network, Tandem Diabetes Care, Inc. Funding Canadian Institutes of Health Research (JT1-157204) and Juvenile Diabetes Research Foundation (4-SRA-2018-651-Q-R)

284-OR: Diabetes Technology Access for Youth with T1D and High Social Risk: Comparing Intervention Outcomes

Objective: Health disparities exist in diabetes technology access for those youth with T1D who experience high social risk, despite likely benefits. Novel Interventions in Children’s Healthcare (NICH) , designed to improve health for youth with T1D experiencing such disparities, has previously been associated with improved diabetes technology access. This study compares diabetes technology use prior to and after NICH referral, and is the first such study to include a control group. Methods: Youth with T1D served by NICH (n=65) and referred youth (“controls”: n=73) across 3 sites were included. EHR data included DKAs, hospitalizations, ED visits, and presence of diabetes technology 1 year prior and 2 years after NICH initiation. No significant demographic differences. Results: Compared to the controls, NICH youth were significantly more likely to gain a CGM and experience significantly greater reductions in hospital admits, DKAs, and ED visits. After accounting for prior differences, only DKA event reduction and CGM access continued to be significant. Youth in NICH also averaged more years with tech access. Conclusion: This study demonstrates that while youth referred to NICH experience substantial barriers to accessing diabetes technology, youth in NICH were more likely to gain CGM access and have fewer DKA events than controls - and neither group approached national averages in technology access. Disclosure J.Lely: None. M.A.Harris: None. D.Naranjo: None. C.Jenisch: None. A.F.Manabat: None. C.Cruz: None. R.Bensen: None. A.Bonilla ospina: None. D.V.Wagner: None. Funding The Leona M. and Harry B. Helmsley Charitable Trust

1014-P: Characteristics Associated with Diabetes Device Use Before and During the Pandemic in Youth with T1D

Introduction: The impact of the Covid-pandemic on diabetes device uptake and use in youth with T1D is unclear. We assessed demographic, diabetes, and SES characteristics associated with diabetes technology (pump, CGM) use in youth with T1D, aged ≤18 years, pre- and during the pandemic. Methods: EHR provided ∼18 months of data pre- and during the pandemic. Pump and CGM use were defined as device use at ≥50% of visits. Geocoding provided census tract-specific SES measures from the 20American Community Survey. Logistic regression models analyzed the probability of device use vs. non-use in the pre- and pandemic periods by geocoded SES status, adjusted for age, gender, baseline A1c, and T1D duration. Results: Pre-pandemic sample had 734 youth (male 49%, aged 13.8±3.3 years, T1D duration 7.3±3.4 years) ; pandemic sample had 800 youth (male 51%, aged 13.4±3.7 years, T1D duration 6.6±3.9 years) ; 689 were in both periods. Pre- and during pandemic, respectively, there were 25% and 22% device non-users; 19% and 21% pump only; 13% and 16% CGM only; 43% and 41% both. Pre-pandemic baseline A1c differed by the 4 device use groups: non-users 9.1±1.7%; pump 8.5±1.2%; CGM 8.2±1.2%; both 8.1±1.0%; p<.05.In both periods, the odds of device non-users starting a device were reduced in those from low-income tracts (≤$40,000) (pre: OR 0.60, 95%CI 0.40-0.91; during: OR 0.59, 95%CI 0.39-0.88; respectively, both p=.01) and low education tracts (≥30% high school or less) (pre: OR 0.57, 95%CI 0.39-0.85; during: OR 0.65, 95%CI 0.44-0.97; both p≤.03) . While the odds of CGM uptake were significantly reduced by ∼40% in presence of unfavorable census SES factors (p≤.01) , the odds of pump start were not (p≥.05) . Odds of uptake of both devices were significantly reduced by ∼45% in presence of unfavorable census SES factors (p≤.02) in both periods. Conclusion: During the pandemic, there remained decreased uptake and less continued use of diabetes device in lower SES patients. Further work is needed to decrease the inequality gap. Disclosure C.Chen: None. A.Adam: None. S.Ojukwu: None. T.Kaushal: None. L.J.Tinsley: None. L.K.Volkening: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. Funding National Institutes of Health (P30DK036836,T32DK007260)

Glycaemic outcomes in Australasian children and adults with type 1 diabetes: failure to meet targets across the age spectrum.

The goal of therapy in type 1 diabetes (T1D) is to achieve optimal glycaemic targets and reduce complications. Robust data representing glycaemic outcomes across the lifespan are lacking in Australasia. To examine contemporary glycaemic outcomes and rate of use of diabetes technologies in Australasian people with T1D. Cross-sectional analysis of de-identified data from 18 diabetes centres maintained in the Australasian Diabetes Data Network registry during 2019. Glycaemia was measured using glycated haemoglobin (HbA1c). The proportion of people with T1D achieving the international HbA1c target of <53 mmol/mol (7%) was calculated. Rates of continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) use were determined. A total of 7988 individuals with T1D with 30 575 visits were recorded in the registry. The median (interquartile range) age was 15.3 (10.0) years and diabetes duration was 5.7 (9.4) years with 49% on multiple daily injections (MDI) and 36% on CSII. The mean HbA1c for the whole cohort was 66 mmol/mol (8.2%). HbA1c increased with age, from 60 mmol/mol (7.6%) in children <10 years, increasing during adolescence and peaking at 73 mmol/mol (8.8%) in the 20-25 years age group. The HbA1c target of <53 mmol/mol (7%) was met in 18% of children and 13% of adults. HbA1c was lower on CSII as compared with those on MDI (P < 0.0001). Only a minority of children and adults achieve the recommended glycaemic goals despite access to specialist care in major diabetes centres. There is a need to identify factors that improve glycaemic outcomes.

Diabetes Technology Meeting 2021.

Diabetes Technology Society hosted its annual Diabetes Technology Meeting on November 4 to November 6, 2021. This meeting brought together speakers to discuss various developments within the field of diabetes technology. Meeting topics included blood glucose monitoring, continuous glucose monitoring, novel sensors, direct-to-consumer telehealth, metrics for glycemia, software for diabetes, regulation of diabetes technology, diabetes data science, artificial pancreas, novel insulins, insulin delivery, skin trauma, metabesity, precision diabetes, diversity in diabetes technology, use of diabetes technology in pregnancy, and green diabetes. A live demonstration on a mobile app to monitor diabetic foot wounds was presented.

Analysis of "Glycemic Outcomes During Real-World Hybrid Closed-Loop System Use by Individuals With Type 1 Diabetes in the United States".

In an article in the Journal of Diabetes Science and Technology, Arunachalum et al retrospectively analyzed glycemic outcomes, regarding the use of hybrid closed-loop (HCL) systems in individuals with type-1 diabetes (T1D) in the United States in a real-world evidence (RWE) setting. In clinical trials, diabetes technology has shown to improve time in range (TIR) as well as other glucose metrics. In the light of increasing the use of diabetes technology in the T1D population, why do we not see improvement in clinical outcomes? Is it cost-effective to increase the use diabetes technology? Does access to diabetes technology vary in the United States? There is a need for additional clinical studies evaluating the effectiveness of diabetes technology in T1D including health economic aspects.

Young Children with Type 1 Diabetes: Recent Advances in Behavioral Research.

Purpose of ReviewThis review provides a recent update of behavioral research pertinent to young children with T1D and addresses current priorities and future directions.Recent FindingsRates of type 1 diabetes (T1D) in young children (ages 1–7) are continuing to rise. Since 2014, changes to diabetes care and management have impacted young children and reinforced the need for increased attention and interventions to support diabetes management, especially in caregivers who are primarily responsible for their young child’s diabetes management.SummaryT1D is associated with unique physiologic challenges in young children, with constant management demands elevating parental diabetes-related stress and fear of hypoglycemia. Diabetes technology use has significantly increased in young children, contributing to improvements in glycemic levels and parent and child psychosocial functioning. Yet despite the positive outcomes demonstrated in select clinical behavioral interventions, research with this young child age group remains limited in scope and quantity.

Health-Care Disparities in the Use of Diabetes Technologies in the UK

Health inequalities have been a longstanding challenge for decades with widening disparities in recent years. Much focus is rightly placed on inequalities based on race/ethnicity, but it is clear that racial disparities and socioeconomic deprivation are interlinked. The connection between systematic and personal bias against individuals from the most deprived groups, irrespective of ethnicity, clearly exists. Socioeconomic deprivation appears to be an influential factor driving health disparities, with implicit bias directed against individuals living in poverty. This is reflected in access to diabetes technologies such as insulin pump therapy, continuous glucose monitoring systems, and automated insulin delivery where those from ethnic minority backgrounds and those in areas of highest deprivation are least able to access or benefit from such technological advancements. Inequalities are further reinforced by government cuts in spending. Between 2009 and 2020, net expenditure per person in local authorities in the 10% most deprived areas fell by 31% compared with a 16% decrease in the least deprived areas. These regressive cuts included a failure of health-care spending to rise in accord with historical patterns. Compounding the challenges were cuts to public health funding and reductions in welfare payments to families most in need. These widening health inequalities are unacceptable and unfair within a national health system where all individuals are entitled to the same level of care. Improved access to specialist diabetes care teams and to life-enhancing technologies could improve the health of all people with diabetes and reduce its human and financial cost.

The attitudes, experiences, and self-competencies of pediatric endocrinology fellows and attending physicians regarding diabetes technology: the Turkey experience.

Unlike in Western countries, the use of diabetes technologies has been limited in Turkey, or at least until the last few years. This low adoption frequency may be attributed to the lack of experience of pediatric diabetes teams in working with new technologies. The aim of this study is to evaluate the attitudes, experiences and self-efficacies of pediatric endocrinology fellows and attending physicians in terms of use of continuous subcutaneous insulin infusion (CSII) therapy and continuous glucose monitoring (CGM) systems. The questionnaire used in this study consisted of 63 questions including 10 questions evaluating the demographic characteristics and experience of the participants, 33 Likert-type questions related to self-competency, 17 yes/no questions and 3 open-ended questions which evaluated attitudes towards our study area. This questionnaire was e-mailed to pediatric endocrinology fellows and attending physicians working in Turkey. A total of 24 fellows and 28 attending physicians working in the field of pediatric endocrinology participated in the survey. Of the respondents, 61% reported that there was no formal training curriculum regarding diabetes technology at their institutions. The mean scores obtained from the Likert scale questions measuring self-competency in using CSII and CGM were 3.8 and 3.3 out of 5, respectively. Of the respondents, 55% judged themselves to be under-skilled in interpreting pump reports while 39% of the respondents reported themselves as being under-skilled in interpreting CGM reports. While it is true that training programs for using diabetes technology have been established by the National Pediatric Endocrinology Association in Turkey, the development of a specific curriculum for institutions that provide pediatric endocrinology fellowship training in this framework will increase the self-confidence of pediatric endocrinologists in this matter and this will ultimately contribute to the improvement of the metabolic control of children with diabetes.

Associations Between Socioeconomic Status and Patient Experience With Type 1 Diabetes Management and Complications: Cross-sectional Analysis of a Cohort From Québec, Canada

BackgroundLow socioeconomic status (SES) may add to the challenges of type 1 diabetes (T1D) management and be an independent risk factor for chronic and acute diabetes complications. Our aim in this study was to evaluate the association between SES and TID management and risk of complications in a universal health-care system using data from a registry of people living with T1D (PWT1D) in Québec, Canada (the BETTER registry). MethodsThis study was a cross-sectional analysis describing the association between SES factors (education, income, employment and insurance coverage) and T1D outcomes (glycated hemoglobin [A1C], acute and chronic complications and comorbidities), using chi-square tests and regression analyses (adjusted for diabetes duration, sex, ethnicity and diabetes technology use). ResultsIn a sample of 1,333 PWT1D, lower education level was associated with cardiovascular disease (odds ratio [OR], 2.44; p=0.002), depression (OR, 1.56; p=0.020), nephropathy (OR, 2.10; p=0.001) and higher A1C (OR, 1.79; p<0.001). Low-income groups were more likely to report higher A1C (OR, 2.16; p=0.001), retinopathy (OR, 1.84; p=0.038), neuropathy (OR, 1.89; p=0.043), nephropathy (OR, 2.23; p=0.024), severe hypoglycemia (OR, 1.87; p=0.022) and depression (OR, 1.87; p=0.012). Unemployment was associated with retinopathy (OR, 2.37; p=0.009) and neuropathy (OR, 1.96; p=0.035). Diabetic ketoacidosis (OR, 2.81; p=0.001) and neuropathy (OR, 1.67; p=0.020) were more likely to be reported by participants with public insurance. ConclusionsPWT1D from lower SES, particularly those with low income and low education, were more likely to report T1D-related complications and comorbidities. Further longitudinal investigations are needed to better understand the nature and directionality of these associations.

Solutions to Address Inequity in Diabetes Technology Use in Type 1 Diabetes: Results from Multidisciplinary Stakeholder Co-creation Workshops.

Background:Racial–ethnic inequity in type 1 diabetes technology use is well documented and contributes to disparities in glycemic and long-term outcomes. However, solutions to address technology inequity remain sparse and lack stakeholder input.Methods:We employed user-centered design principles to conduct workshop sessions with multidisciplinary panels of stakeholders, building off of our prior study highlighting patient-identified barriers and proposed solutions. Stakeholders were convened to review our prior findings and co-create interventions to increase technology use among underserved populations with type 1 diabetes. Stakeholders included type 1 diabetes patients who had recently onboarded to technology; endocrinology and primary care physicians; nurses; diabetes educators; psychologists; and community health workers. Sessions were recorded and analyzed iteratively by multiple coders for common themes.Results:We convened 7 virtual 2-h workshops for 32 stakeholders from 11 states in the United States. Patients and providers confirmed prior published studies highlighting patient barriers and generated new ideas by co-creating solutions. Common themes of proposed interventions included (1) prioritizing more equitable systems of offering technology, (2) using visual and hands-on approaches to increase accessibility of technology and education, (3) including peer and family support systems more, and (4) assisting with insurance navigation and social needs.Discussion:Our study furthers the field by providing stakeholder-endorsed intervention ideas that propose feasible changes at the patient, provider, and system levels to reduce inequity in diabetes technology use in type 1 diabetes. Multidisciplinary stakeholder engagement in disparities research offers unique insight that is impactful and acceptable to the target population.

An Opportunity for Improvement: Evaluation of Diabetes Technology Education Among Adult Endocrinology Training Programs.

Despite increases in continuous glucose monitor (CGM) and insulin pump use in adults with diabetes, there is room for expansion. Technology adoption may be influenced by the training environment and fellowship education. However, little is known about adult endocrinology trainee comfort with, understanding of, or methods by which trainees receive education about diabetes technology. Mixed methods, sequential explanatory evaluation using survey and semi-structured interviews of endocrinology trainees and fellowship leadership in Accreditation Council for Graduate Medical Education (ACGME)-accredited adult endocrinology fellowship programs to assess trainee and leadership comfort with, perceived knowledge of, and current methods for diabetes technology education. Seventy-seven respondents completed the survey. The majority of training programs have curricula for training on insulin pumps (74%) and CGM (75.3%); 52% of fellows felt curricula are adequate. First- and second-year fellows were more comfortable with CGM than insulin pump use. Only half of third-year fellows felt comfortable with starting insulin pump therapy or recommending insulin dose adjustments based on CGM rate of change arrows. Qualitative interviews identified the importance of both direct instruction and experiential learning in diabetes technology education. Almost half of trainees feel that curricula for learning to use and manage insulin pumps and CGM are inadequate and feel uncomfortable with critical aspects of technology use, demonstrating the need for increased attention to trainee education in the use of diabetes technology. Based on a better understanding of current and preferred methods for instruction, this study provides direction for future development of initiatives to improve fellow education in this field.

Beliefs Around Hypoglycemia and Their Impacts on Hypoglycemia Outcomes in Individuals with Type 1 Diabetes and High Risks for Hypoglycemia Despite Using Advanced Diabetes Technologies.

OBJECTIVEThis study aimed to 1) identify the frequency of severe and level 2 hypoglycemia presenting in individuals with type 1 diabetes using continuous glucose monitoring systems (CGMs), including those with concomitant closed-loop insulin pumps, in a clinical practice setting and 2) evaluate the impact of beliefs around hypoglycemia in the development of severe and level 2 hypoglycemia in this population.RESEARCH DESIGN AND METHODSA cross-sectional survey study in adults with type 1 diabetes using CGMs >6 months was conducted at a large tertiary academic center. Participant demographics, 6-month severe hypoglycemia history, hypoglycemia beliefs (with the Attitude to Awareness of Hypoglycemia questionnaire), and 4-week CGM glucose data were collected. Statistical analysis was performed to assess the presentation of severe and level 2 hypoglycemia and identify associated risk factors.RESULTSA total of 289 participants were recruited (including 257 participants with CGM data within the last 3 months). Of these, 25.6% experienced at least one severe hypoglycemic episode in the last 6 months, and 13.6% presented with ≥1% of time in level 2 hypoglycemia on CGMs. Reporting beliefs about prioritizing hyperglycemia avoidance was associated with severe hypoglycemia development (P < 0.001), while having beliefs of minimal concerns for hypoglycemia was associated with spending ≥1% of time in level 2 hypoglycemia (P = 0.038).CONCLUSIONSDespite the use of advanced diabetes technologies, severe and level 2 hypoglycemia continues to occur in individuals with type 1 diabetes and high hypoglycemia risks. Human factors, including beliefs around hypoglycemia, may continue to impact the effectiveness of glucose self-management.

Development and validation of the self-management Barriers and Supports Evaluation for working-aged adults with type 1 diabetes mellitus

IntroductionTo optimize type 1 diabetes mellitus self-management, experts recommend a person-centered approach, in which care is tailored to meet people’s needs and preferences. Existing tools for tailoring type 1 diabetes...

Hemoglobin A1c trajectories in the first 18 months after diabetes diagnosis in the SWEET diabetes registry.

A majority of youth with type 1 diabetes do not meet recommended hemoglobin A1c (HbA1c) targets. The SWEET diabetes registry is a multi-national registry of youth with diabetes. We used data from this registry to identify characteristics associated with glycemic control. Patients in the SWEET diabetes registry with at least one HbA1c value within 10 days of diagnosis and three follow up measurements in the first 18months of diagnosis were included (~10% of the SWEET diabetes registry). Locally weighted scatterplot smoothing was used to generate curves of HbA1c. Wilcoxon, Kruskal-Wallis, or χ2-tests were used to calculate differences between groups. The mean HbA1c of youth in the SWEET diabetes registry is highest at diagnosis and lowest between months 4 and 5 post-diabetes diagnosis. HbA1c continues to increase steadily through the first 18months of diagnosis. There are no differences in HbA1c trajectories based on sex or use of diabetes technology. Youth in North America/Australia/New Zealand had the highest HbA1c throughout the first 18months of diagnosis. The trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. Youth from countries with the highest gross domestic product (GDP) had the highest HbA1c throughout the first 18months of diagnosis. In this subset of patients, the trajectory of youth from countries with nationalized health insurance was lower than those countries without nationalized health insurance. High GDP and high use of technology did not seem to protect from a higher trajectory.

Practical aspects of diabetes technology use: Continuous glucose monitors, insulin pumps, and automated insulin delivery systems

There have been tremendous advances in diabetes technology in the last decade. Continuous glucose monitors (CGM), insulin pumps, and automated insulin delivery (AID) systems aim to improve glycemic control while simultaneously decreasing the burden of diabetes management. Although diabetes technologies have been shown to decrease both hypoglycemia and hyperglycemia and to improve health-related quality of life in individuals with type 1 diabetes, the impact of these devices in individuals with cystic fibrosis-related diabetes (CFRD) is less clear. There are unique aspects of CFRD, including the different underlying pathophysiology and unique lived health care experience and comorbidities, that likely affect the use, efficacy, and uptake of diabetes technology in this population. Small studies suggest that CGM is accurate and may be helpful in guiding insulin therapy for individuals with CFRD. Insulin pump use has been linked to improvements in lean body mass and hemoglobin A1c among adults with CFRD. A recent pilot study highlighted the promise of AID systems in this population. This article provides an overview of practical aspects of diabetes technology use and device limitations that clinicians must be aware of in caring for individuals with CF and CFRD. Cost and limited insurance coverage remain significant barriers to wider implementation of diabetes technology use among patients with CFRD. Future studies exploring strategies to improve patient and CF provider education about these devices and studies showing the effectiveness of these technologies on health and patient-reported outcomes may lead to improved insurance coverage and increased rates of uptake and sustained use of these technologies in the CFRD community.

Pediatric Diabetic Retinopathy: Updates in Prevalence, Risk Factors, Screening, and Management.

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus and a major cause of vision loss worldwide. The purpose of this review is to provide an update on the prevalence of diabetic retinopathy in youth, discuss risk factors, and review recent advances in diabetic retinopathy screening. While DR has long been considered a microvascular complication, recent data suggests that retinal neurodegeneration may precede the vascular changes associated with DR. The prevalence of DR has decreased in type 1 diabetes (T1D) patients following the results of the Diabetes Control and Complications Trial and implementation of intensive insulin therapy, with prevalence ranging from 14-20% before the year 2000 to 3.7-6% after 2000. In contrast, the prevalence of diabetic retinopathy in pediatric type 2 diabetes (T2D) is higher, ranging from 9.1-50%. Risk factors for diabetic retinopathy are well established and include glycemic control, diabetes duration, hypertension, and hyperlipidemia, whereas diabetes technology use including insulin pumps and continuous glucose monitors has been shown to have protective effects. Screening for DR is recommended for youth with T1D once they are aged ≥ 11years or puberty has started and diabetes duration of 3-5years. Pediatric T2D patients are advised to undergo screening at or soon after diagnosis, and annually thereafter, due to the insidious nature of T2D. Recent advances in DR screening methods including point of care and artificial intelligence technology have increased access to DR screening, while being cost-saving to patients and cost-effective to healthcare systems. While the prevalence of diabetic retinopathy in youth with T1D has been declining over the last few decades, there has been a significant increase in the prevalence of DR in youth with T2D. Improving access to diabetic retinopathy screening using novel screening methods may help improve detection and early treatment of diabetic retinopathy.

Type 1 Diabetes, Sleep, and Hypoglycemia.

To review the relationship between sleep and hypoglycemia, sleep characteristics, and their associations with glycemic control in persons with type 1 diabetes (T1D). The effects of sleep interventions and diabetes technology on sleep are summarized. Nocturnal hypoglycemia affects objective and subjective sleep quality and is related to behavioral, psychological, and physiological factors. Sleep disturbances are common, including inadequate sleep, impaired sleep efficiency, poor subjective satisfaction, irregular timing, increased daytime sleepiness, and sleep apnea. Some have a bidirectional relationship with glycemic control. Preliminary evidence supports sleep interventions (e.g., sleep extension and sleep coach) in improving sleep and glycemic control, while diabetes technology use could potentially improve sleep. Hypoglycemia and sleep disturbances are common among persons with T1D. There is a need to develop sleep promotion programs and test their effects on sleep, glucose, and related outcomes (e.g., self-care, psychological health).

Association of the use of diabetes technology with HbA1c and BMI-SDS in an international cohort of children and adolescents with type 1 diabetes: The SWEET project experience.

To examine the association between the use of diabetes technology (insulin pump [CSII], glucose sensor [CGM] or both) and metabolic control (HbA1c) as well as body adiposity (BMI-SDS) over-time in a cohort of children and adolescents with type 1 diabetes (T1D), that have never used these technologies before. Four thousand six hundred forty three T1D patients (2-18 years, T1D ≥1 year, without celiac disease, no CSII and/or CGM before 2016) participating in the SWEET prospective multicenter diabetes registry, were enrolled. Data were collected at two points (2016; 2019). Metabolic control was assessed by glycated hemoglobin (HbA1c) and body adiposity by BMI-SDS (WHO). Patients were categorized by treatment modality (multiple daily injections [MDI] or CSII) and the use or not of CGM. Linear regression models, adjusted for age, gender, duration of diabetes and region, were applied to assess differences in HbA1c and BMI-SDS among patient groups. The proportion of patients using MDI with CGM and CSII with CGM significantly increased from 2016 to 2019 (7.2%-25.7%, 7.8%-27.8% respectively; p < 0.001). Linear regression models showed a significantly lower HbA1c in groups that switched from MDI to CSII with or without CGM (p < 0.001), but a higher BMI-SDS (from MDI without CGM to CSII with CGM p < 0.05; from MDI without CGM to CSII without CGM p < 0.01). Switching from MDI to CSII is significantly associated with improvement in glycemic control but increased BMI-SDS over-time. Diabetes technology may improve glucose control in youths with T1D although further strategies to prevent excess fat accumulation are needed.