Systematic review of disparities in continuous glucose monitoring and insulin pump utilization in the United States: Key themes and evidentiary gaps.

AIM: This study aims to provide a comprehensive overview of real-world evidence pertaining to disparities in the utilization of continuous glucose monitors (CGMs)/insulin pumps to highlight potential evidentiary gaps and discern emerging themes from the literature. MATERIALS AND METHODS: A systematic review of published manuscripts and abstracts was conducted from: MEDLINE, EMBASE, Nursing and Allied Health, Web of Science and CINHAL. Attributes related to patients, outcomes, interventions (CGMs/pumps/both) and study type were captured. In addition, factors associated with disparities in device utilization were examined. RESULTS: Thirty-six studies were included in the final analysis; the studies predominantly focused on people living with type 1 diabetes. Only two studies included individuals with type 2 diabetes. Almost two-thirds of the studies reported outcomes associated with disparities (e.g. glycated haemoglobin, diabetic ketoacidosis, resource utilization). Most studies highlighted disparities across race, ethnicity and insurance type. Evidentiary gaps were identified, particularly in the evidence for people with type 2 diabetes, the continuation of CGM/pump use and limited studies addressing disparities among Native Americans/American Indians. CONCLUSION: This study reveals critical disparities in diabetes technology use across race, ethnicity and insurance type, particularly among people with type 1 diabetes. Evidentiary gaps assessing disparities in diabetes technology use persist, particularly concerning people with type 2 diabetes, Native American/American Indian and LGBTQ+ populations, and in outcomes related to continuation of use. Social and digital determinants of health, such as income, transportation, residential location and technological literacy, are crucial to achieving equitable access. Future research should focus on the patient journey to identify opportunities for equitable access to diabetes technology as its use grows.

Impact of continuous glucose monitoring on hospitalizations and glucose control in people with type 2 diabetes: real-world analysis.

AIM: The real-world benefits of continuous glucose monitoring (CGM) in the broad type 2 diabetes (T2D) population are not well studied. Our study evaluated the impact of CGM use on health care resource utilization over 12 months in adults with T2D. MATERIALS AND METHODS: This retrospective cohort analysis used Optum's de-identified Market Clarity data of >79 million people to evaluate CGM use in people with T2D who were treated with non-insulin (NIT), basal insulin (BIT) and prandial insulin therapy (PIT). The primary outcomes were changes in all-cause hospitalizations, acute diabetes-related hospitalizations and acute diabetes-related emergency room visits during the 6- and 12-month post-index period following transition from blood glucose monitoring to CGM. A pre-specified subgroup analysis assessed glucose control and medication changes among people with T2D over 1 year. RESULTS: The analysis included 74 679 adults with T2D (NIT; n = 25 269), (BIT; n = 16 264) and (PIT; n = 33 146). Significant reductions in all-cause hospitalizations, acute diabetes-related hospitalizations and acute diabetes-related emergency room visits were observed in the 6-month post-index period that were sustained during the 6-12 month post-index period (NIT, -10.1%, -31.0%, -30.7%; BIT, -13.9%, -47.6%, -28.2%; and PIT, -22.6%, -52.7%, -36.6%, respectively). A subgroup analysis of 6030 people showed mean glycated haemoglobin reductions at approximately 3 months, which were also sustained throughout the post-index period: NIT, -1.1 (0.05)%; BIT, -1.1 (0.06)%; and PIT, -0.9 (0.04)%, p < 0.0001. CONCLUSIONS: CGM use in real-life across different therapeutic regimens in adults with T2D was associated with reductions in health care resource utilization with improved glucose control over 1 year.

Self-care practice and associated factors among patients with diabetes on follow-up at Yirgalem General Hospital, Sidama, Ethiopia: a cross-sectional study.

BACKGROUND: Self-care practice is an integral and efficient part of comprehensive diabetes management, which could be influenced by various socio-demographic, clinical, and lifestyle factors. OBJECTIVE: The study aimed to assess the level of diabetes self-care practice and its associated factors among patients with diabetes on follow-up at Yirgalem General Hospital, Yirgalem, Sidama, Ethiopia. METHODOLOGY: An Institution-based cross-sectional study was conducted from February 15 to May 10, 2022, involving 298 patients with diabetes on follow-up at Yirgalem General Hospital. A pre-tested interviewer-administered questionnaire was utilized to collect data from patients. A descriptive analysis was conducted to determine the level of good self-care practice. Bivariate and multivariable binary logistics regression were performed to determine factors associated with good diabetic self-care practice. Associations with a p-value < 0.05 were considered statistically significant. RESULT: The overall good diabetic self-care practice among patients was 59.4%. Regarding the specific domains of care, 15 (5%) participants had good self-glucose monitoring care, 228 (76.5%) had good exercise self-care, 268 (89.9%) had good dietary self-care, 228 (76.5%) had good foot self-care, and 260 (87.2%) had good diabetic medication adherence. Single marital status (AOR = 5.7, 95% CI: (1.418, 22.915), urban residence (AOR = 2.992, 95% CI: (1.251, 7.153)), and having a glucometer (AOR = 2.273, 95% CI: (1.083, 4.772)) were factors that were significantly associated with good diabetic self-care practice. CONCLUSION: Good diabetic self-care practices among participants was low. Marital status, place of residence, and having a glucometer were statistically significant predictors of good diabetic self-care practices. Targeted intervention addressing those patients from rural areas to increase awareness and practice of self-care, as well as the promotion of having a glucometer at home for self-glucose monitoring is recommended.

Role of Caregivers in Remote Management of Patients With Type 2 Diabetes Mellitus: Systematic Review of Literature.

BACKGROUND: With the growing use of remote monitoring technologies in the management of patients with type 2 diabetes mellitus (T2DM), caregivers are becoming important resources that can be tapped into to improve patient care. OBJECTIVE: This review aims to summarize the role of caregivers in the remote monitoring of patients with T2DM. METHODS: We performed a systematic review in MEDLINE, Embase, Scopus, PsycINFO, and Web of Science up to 2022. Studies that evaluated the role of caregivers in remote management of adult patients with T2DM were included. Outcomes such as diabetes control, adherence to medication, quality of life, frequency of home glucose monitoring, and health care use were evaluated. RESULTS: Of the 1198 identified citations, 11 articles were included. The majority of studies were conducted in North America (7/11, 64%) and South America (2/11, 18%). The main types of caregivers studied were family or friends (10/11, 91%), while the most common remote monitoring modalities evaluated were interactive voice response (5/11, 45%) and phone consultations (4/11, 36%). With regard to diabetes control, 3 of 6 studies showed improvement in diabetes-related laboratory parameters. A total of 2 studies showed improvements in patients' medication adherence rates and frequency of home glucose monitoring. Studies that evaluated patients' quality of life showed mixed evidence. In 1 study, increased hospitalization rates were noted in the intervention group. CONCLUSIONS: Caregivers may play a role in improving clinical outcomes among patients with T2DM under remote monitoring. Studies on mobile health technologies are lacking to understand their impact on Asian populations and long-term patient outcomes.

Evaluation of HbA1c and glucose management indicator discordance in a population of children and adolescents with type 1 diabetes.

BACKGROUND: Glucose management indicator (GMI) is a useful metric for the clinical management of diabetic patients using continuous glucose monitoring (CGM). In adults, a marked discordance between HbA1c and GMI has been reported. To date, no studies have evaluated this discordance in children/adolescents with type 1 diabetes (T1D). METHODS: HbA1c and real-life CGM data of the 12 weeks preceding HbA1c measurement were collected from 805 children/adolescents. The absolute difference between HbA1c and GMI was calculated for both the 12-week and 4-week periods preceding HbA1c measurement and the proportion of discordant patients was defined according to specific thresholds in the entire study population and in subjects stratified by type of CGM, insulin therapy, gender, age and puberty. Regression analyses were performed with HbA1c-GMI discordance as dependent variable and patients' characteristics as independent ones. A new GMI equation for children and adolescent was derived from the linear regression analysis between mean glucose and HbA1c. RESULTS: HbA1c-GMI discordance calculated on the 12-week period was <0.1, ≥0.5 and ≥1.0 in 24.8, 33.9 and 9.2% of the subjects, respectively. No significant differences in the proportion of discordant patients were found comparing patients stratified by type of CGM, insulin therapy, gender, age and puberty. GMI-HbA1c discordance was not significantly explained by age, gender, BMI, type of CGM, insulin therapy, hemoglobin, anemia and autoimmune diseases (R2  = 0.012, p = 0.409). HbA1c-GMI discordance calculated on the 4-week period was comparable. GMI (%) equation derived for this cohort was: 3.74 + 0.022x (mean glucose in mg/dl). CONCLUSIONS: GMI could be meaningfully discordant respect to HbA1c in more than a third of children/adolescents with T1D. This discrepancy should be taken into careful consideration when the two indices are directly compared in daily clinical practice.

Does introduction of continuous glucose monitoring at diagnosis of type 1 diabetes increase uptake in children and adolescents?

OBJECTIVE: To assess whether introduction of continuous glucose monitoring (CGM) at diagnosis of type 1 diabetes (T1D), leads to greater uptake and continuation at 12 and 24 months, in a population-based pediatric diabetes clinic. RESEARCH DESIGN AND METHODS: All T1D children and adolescents diagnosed in the 12 months following full government subsidization of CGM were offered CGM from diagnosis at Women's and Children's Hospital, SA (Cohort 1). Uptake and continuation of CGM was compared to those diagnosed in the preceding year, who were started on CGM after diagnosis, but otherwise had identical diabetes management (Cohort 2). Demographic and clinical data were collected prospectively. The primary outcome variable was CGM wear >75% of the time at 12 and 24 months. RESULTS: In Cohort 1, 84% were started on CGM at diagnosis. 88% had commenced CGM by 12 months and 90% by 24 months. In Cohort 2, CGM was started on average 10 months after diagnosis (range 1-25 months), with 81% started on CGM within 24 months of subsidization. At 24 months, 78% of Cohort 1 and 66% of Cohort 2 were wearing CGM >75% of the time (p = 0.26), higher than the WCH Clinic as a whole (58%). There was no difference in HbA1c between cohorts. CONCLUSION: Starting CGM at diagnosis of T1D is feasible and well received by families, with high uptake across all ages. Although CGM continuation (wearing CGM >75% of the time) was slightly higher in Cohort 1 than Cohort 2, this did not reach statistical significance.

Expect the unexpected: Adolescent and pre-teens' experience of diabetes technology self-management.

OBJECTIVE: Only 17% of adolescents with type 1 diabetes (T1D) are currently meeting their glycemic targets despite advances in diabetes technologies. Self-management behaviors and challenges specific to use of diabetes technologies are insufficiently studied in adolescents. We aimed to describe the experience of diabetes technology self-management, including facilitators and barriers, among preteens/adolescents with low and high A1C. RESEARCH DESIGN AND METHODS: Youth (10-18 years of age) with T1D who use insulin pump therapy were recruited from the larger quantitative cohort of a mixed methods study for participation in semi-structured qualitative interviews. Maximum variability sampling was used to recruit youth with A1C <7.5% (n = 5) and A1C >9% (n = 5). Participants' personal insulin pump and continuous glucose monitoring data were downloaded and served as a visual reference. Interviews were analyzed using a qualitative descriptive approach. RESULTS: Participants were 50% female with a median age of 14.9 years and 80% used CGM. The sample was predominantly white (90.0%). Analysis produced four major themes, Bad Day, Expect the Unexpected, Nighttime Dependence, and Unpredictability, It's Really a Team and interconnecting subthemes. Youth characterized ''Bad Days'' as those requiring increased diabetes focus and self-management effort. The unpredictability (''Expect the Unexpected'') of glucose outcomes despite attention to self-management behaviors was considerable frustration. CONCLUSIONS: Diabetes devices such as insulin pumps are complex machines that rely heavily on individual proficiency, surveillance, and self-management behaviors to achieve clinical benefit. Our findings highlight the dynamic nature of self-management and the multitude of factors that feed youths' self-management behaviors.

Diabetic ketoacidosis at type 1 diabetes diagnosis in children during the COVID-19 pandemic.

OBJECTIVE: The COVID-19 pandemic has led to significant public health measures that have resulted in decreased acute pediatric care utilization. We evaluated whether the rate of severe presentations of new onset type 1 diabetes (DM1), such as, diabetic ketoacidosis (DKA) has changed since the COVID-19 public health measures were enacted. RESEARCH DESIGN AND METHODS: A retrospective chart review of children less than 18 years of age presenting with new onset DM1 during the pandemic period of March 17, 2020 to August 31, 2020 was conducted at two tertiary care pediatric hospitals in Alberta, Canada. Rates of DKA and severe DKA were compared to the same time period in the year 2019 (pre-pandemic control). RESULTS: The number of children presenting with newly diagnosed DM1 was similar during the pandemic year of 2020 compared with 2019 (107 children in 2020 vs. 114 in 2019). The frequency of DKA at DM1 onset was significantly higher in the pandemic period (68.2% vs 45.6%; p < 0.001) and incidence of severe DKA was also higher (27.1% in 2020 vs 13.2% in 2019; p = 0.01). CONCLUSIONS: There was a significant increase in DKA and severe DKA in children presenting with new onset DM1 during the COVID-19 pandemic period. This emphasizes the need for educating health care professionals and families to be aware of the symptoms of hyperglycemia and the importance of early diagnosis and treatment even during public health measures for COVID-19.

Glycemic deviation index: a novel method of integrating glycemic numerical value and variability.

BACKGROUND: There are many continuous blood glucose monitoring (CGM) data-based indicators, and most of these focus on a single characteristic of abnormal blood glucose. An ideal index that integrates and evaluates multiple characteristics of blood glucose has not yet been established. METHODS: In this study, we proposed the glycemic deviation index (GDI) as a novel integrating characteristic, which mainly incorporates the assessment of the glycemic numerical value and variability. To verify its effectiveness, GDI was applied to the simulated 24 h glycemic profiles and the CGM data of type 2 diabetes (T2D) patients (n = 30). RESULTS: Evaluation of the GDI of the 24 h simulated glycemic profiles showed that the occurrence of hypoglycemia was numerically the same as hyperglycemia in increasing GDI. Meanwhile, glycemic variability was added as an independent factor. One-way ANOVA results showed that the application of GDI showed statistically significant differences in clinical glycemic parameters, average glycemic parameters, and glycemic variability parameters among the T2D groups with different glycemic levels. CONCLUSIONS: In conclusion, GDI integrates the characteristics of the numerical value and the variability in blood glucose levels and may be beneficial for the glycemic management of diabetic patients undergoing CGM treatment.

Systematic Review of Self-Monitoring of Blood Glucose in Patients With Type 2 Diabetes.

BACKGROUND: The benefit of self-monitoring of blood glucose in reducing HbA1c in non-insulin-treated participants remains unclear. HbA1c may be improved in this population with said self-monitoring. OBJECTIVE: The aim of this study was to conduct meta-analyses of glycemic control in non-insulin-treated participants with Type 2 diabetes: self-monitoring of blood glucose versus usual care, structured versus unstructured self-monitoring of blood glucose, and use of self-monitoring of blood glucose readings by clinicians to adjust (or modify) therapy versus usual care. METHODS: MEDLINE, Embase, and Cochrane Central were electronically searched to identify articles published from January 1, 2000, to June 30, 2020. Trials investigating changes in HbA1c were selected. Screening was performed independently by two investigators. Two investigators extracted HbA1c at baseline and follow-up for each trial. RESULTS: Nineteen trials involving 4,965 participants were included. Overall, self-monitoring of blood glucose reduced HbA1c. Preplanned subgroup analysis showed that using self-monitoring of blood glucose readings to adjust therapy contributed significantly to the reduction. No significant improvement in HbA1c was shown in self-monitoring of blood glucose without therapy adjustment. The same difference was observed in structured versus unstructured self-monitoring of blood glucose. DISCUSSION: HbA1c is improved with clinician therapy modification based on structured self-monitoring of blood glucose readings. Implications are for clinicians to prescribe structured self-monitoring of blood glucose to modify therapy based on the readings and not prescribe unstructured self-monitoring of blood glucose. Participants with suboptimal glycemic control may benefit most. A self-monitoring of blood glucose regimen that improves clinical and cost-effectiveness is presented. Future studies can investigate this regimen specifically.

A Comprehensive Review of Continuous Glucose Monitoring Accuracy during Exercise Periods.

Continuous Glucose Monitoring (CGM) has been a springboard of new diabetes management technologies such as integrated sensor-pump systems, the artificial pancreas, and more recently, smart pens. It also allows patients to make better informed decisions compared to a few measurements per day from a glucometer. However, CGM accuracy is reportedly affected during exercise periods, which can impact the effectiveness of CGM-based treatments. In this review, several studies that used CGM during exercise periods are scrutinized. An extensive literature review of clinical trials including exercise and CGM in type 1 diabetes was conducted. The gathered data were critically analysed, especially the Mean Absolute Relative Difference (MARD), as the main metric of glucose accuracy. Most papers did not provide accuracy metrics that differentiated between exercise and rest (non-exercise) periods, which hindered comparative data analysis. Nevertheless, the statistic results confirmed that CGM during exercise periods is less accurate.

Association of Real-time Continuous Glucose Monitoring With Glycemic Control and Acute Metabolic Events Among Patients With Insulin-Treated Diabetes.

Importance: Continuous glucose monitoring (CGM) is recommended for patients with type 1 diabetes; observational evidence for CGM in patients with insulin-treated type 2 diabetes is lacking. Objective: To estimate clinical outcomes of real-time CGM initiation. Design, Setting, and Participants: Exploratory retrospective cohort study of changes in outcomes associated with real-time CGM initiation, estimated using a difference-in-differences analysis. A total of 41 753 participants with insulin-treated diabetes (5673 type 1; 36 080 type 2) receiving care from a Northern California integrated health care delivery system (2014-2019), being treated with insulin, self-monitoring their blood glucose levels, and having no prior CGM use were included. Exposures: Initiation vs noninitiation of real-time CGM (reference group). Main Outcomes and Measures: Ten end points measured during the 12 months before and 12 months after baseline: hemoglobin A1c (HbA1c); hypoglycemia (emergency department or hospital utilization); hyperglycemia (emergency department or hospital utilization); HbA1c levels lower than 7%, lower than 8%, and higher than 9%; 1 emergency department encounter or more for any reason; 1 hospitalization or more for any reason; and number of outpatient visits and telephone visits. Results: The real-time CGM initiators included 3806 patients (mean age, 42.4 years [SD, 19.9 years]; 51% female; 91% type 1, 9% type 2); the noninitiators included 37 947 patients (mean age, 63.4 years [SD, 13.4 years]; 49% female; 6% type 1, 94% type 2). The prebaseline mean HbA1c was lower among real-time CGM initiators than among noninitiators, but real-time CGM initiators had higher prebaseline rates of hypoglycemia and hyperglycemia. Mean HbA1c declined among real-time CGM initiators from 8.17% to 7.76% and from 8.28% to 8.19% among noninitiators (adjusted difference-in-differences estimate, -0.40%; 95% CI, -0.48% to -0.32%; P < .001). Hypoglycemia rates declined among real-time CGM initiators from 5.1% to 3.0% and increased among noninitiators from 1.9% to 2.3% (difference-in-differences estimate, -2.7%; 95% CI, -4.4% to -1.1%; P = .001). There were also statistically significant differences in the adjusted net changes in the proportion of patients with HbA1c lower than 7% (adjusted difference-in-differences estimate, 9.6%; 95% CI, 7.1% to 12.2%; P < .001), lower than 8% (adjusted difference-in-differences estimate, 13.1%; 95% CI, 10.2% to 16.1%; P < .001), and higher than 9% (adjusted difference-in-differences estimate, -7.1%; 95% CI, -9.5% to -4.6%; P < .001) and in the number of outpatient visits (adjusted difference-in-differences estimate, -0.4; 95% CI, -0.6 to -0.2; P < .001) and telephone visits (adjusted difference-in-differences estimate, 1.1; 95% CI, 0.8 to 1.4; P < .001). Initiation of real-time CGM was not associated with statistically significant changes in rates of hyperglycemia, emergency department visits for any reason, or hospitalizations for any reason. Conclusions and Relevance: In this retrospective cohort study, insulin-treated patients with diabetes selected by physicians for real-time continuous glucose monitoring compared with noninitiators had significant improvements in hemoglobin A1c and reductions in emergency department visits and hospitalizations for hypoglycemia, but no significant change in emergency department visits or hospitalizations for hyperglycemia or for any reason. Because of the observational study design, findings may have been susceptible to selection bias.

Uninterrupted continuous glucose monitoring access is associated with a decrease in HbA1c in youth with type 1 diabetes and public insurance.

OBJECTIVE: Continuous glucose monitor (CGM) use is associated with improved glucose control. We describe the effect of continued and interrupted CGM use on hemoglobin A1c (HbA1c) in youth with public insurance. METHODS: We reviewed 956 visits from 264 youth with type 1 diabetes (T1D) and public insurance. Demographic data, HbA1c and two-week CGM data were collected. Youth were classified as never user, consistent user, insurance discontinuer, and self-discontinuer. Visits were categorized as never-user visit, visit before CGM start, visit after CGM start, visit with continued CGM use, visit with initial loss of CGM, visit with continued loss of CGM, and visit where CGM is regained after loss. Multivariate regression adjusting for age, sex, race, diabetes duration, initial HbA1c, and body mass index were used to calculate adjusted mean and delta HbA1c. RESULTS: Adjusted mean HbA1c was lowest for the consistent user group (HbA1c 8.6%;[95%CI 7.9,9.3]). Delta HbA1c (calculated from visit before CGM start) was lower for visit after CGM start (-0.39%;[95%CI -0.78,-0.02]) and visit with continued CGM use (-0.29%;[95%CI -0.61,0.02]), whereas it was higher for visit with initial loss of CGM (0.40%;[95%CI -0.06,0.86]), visit with continued loss of CGM (0.46%;[95%CI 0.06,0.85]), and visit where CGM is regained after loss (0.57%;[95%CI 0.06,1.10]). CONCLUSIONS: Youth with public insurance using CGM have improved HbA1c, but only when CGM use is uninterrupted. Interruptions in use, primarily due to gaps in insurance coverage of CGM, were associated with increased HbA1c. These data support both initial and ongoing coverage of CGM for youth with T1D and public insurance.

Comparison of oral glucose tolerance test and ambulatory glycaemic profiles in pregnant women in Uganda with gestational diabetes using the FreeStyle Libre flash glucose monitoring system.

BACKGROUND: The diagnosis of hyperglycaemia in sub-Saharan Africa (SSA) is challenging. Blood glucose levels obtained during oral glucose tolerance test (OGTT) may not reflect home glycaemic profiles. We compare OGTT results with home glycaemic profiles obtained using the FreeStyle Libre continuous glucose monitoring device (FSL-CGM). METHODS: Twenty-eight women (20 with gestational diabetes [GDM], 8 controls) were recruited following OGTT between 24 and 28 weeks of gestation. All women wore the FSL-CGM device for 48-96 h at home in early third trimester, and recorded a meal diary. OGTT was repeated on the final day of FSL-CGM recording. OGTT results were compared with ambulatory glycaemic variables, and repeat OGTT was undertaken whilst wearing FSL-CGM to determine accuracy of the device. RESULTS: FSL-CGM results were available for 27/28 women with mean data capture 92.8%. There were significant differences in the ambulatory fasting, post-prandial peaks, and mean glucose between controls in whom both primary and secondary OGTT was normal (n = 6) and those with two abnormal OGTTs or "true" GDM (n = 7). There was no difference in ambulatory mean glucose between these controls and the 13 women who had an abnormal primary OGTT and normal repeat OGTT. These participants had significantly lower body mass index (BMI) than the true GDM group (29.0 Vs 36.3 kg/m2, p-value 0.014). Paired OGTT/FSL-CGM readings revealed a Mean Absolute difference (MAD) -0.58 mmol/L and Mean Absolute Relative Difference (MARD) -11.9%. Bland-Altman plot suggests FSL-CGM underestimated blood glucose by approximately 0.78 mmol/L. CONCLUSION: Diagnosis of GDM on a single OGTT identifies a proportion of women who do not have a significantly higher home glucose levels than controls. This raises questions about factors which may affect the reproducibility of OGTT in this population, including food insecurity and atypical phenotypes of diabetes. More investigation is needed to understand the suitability of the OGTT as a diagnostic test in sub-Saharan Africa.

Diabetes care: addressing psychosocial well-being in young adults with a newly developed assessment tool.

BACKGROUND: Psychosocial assessment should be part of clinic visits for people with diabetes mellitus (DM). AIMS: To assess the usage and acceptance of a diabetes psychosocial assessment tool (DPAT) and to profile the clinical and psychosocial characteristics of young people with diabetes. METHODS: Over a 12-month period, young adults (18-25 years) attending diabetes clinic were offered DPAT. The tool embeds validated screening tools including the Problem Areas in Diabetes 20 (PAID-20) questionnaire, the Patient Health Questionnaire-4 (PHQ-4) and the World Health Organization Well-Being Index-5 (WHO-5). Baseline clinical data were collected and questions regarding social support, body image, eating concerns, hypoglycaemia and finances were included. RESULTS: Over the 12 month, the form was offered to 155 participants (64.6% of eligible attendees). The majority (96.1%) had type 1 DM with a mean duration of 10.5 (±5.3 SD) years. Average glycated haemoglobin (HbA1c) was 8.7% (±1.5 SD) (or 71.2 mmol/mol ±16.5 SD). Severe diabetes-related distress (PAID-20 ≥ 40) was found in 19.4%. Low WHO-5 scores (28-50 points) were seen in 14.8%. PHQ-4 identified 25.8% with anxiety and 16.1% with depression. Significant weight, shape and eating concerns were identified in 27.1, 26.6 and 28.4%, respectively. Serious hypoglycaemia concerns were raised by 4.5%. CONCLUSION: DPAT revealed a high prevalence of psychosocial stress among young adults with DM. The tool was easy to use and accepted by patients and may aid streamlining referrals to relevant members of a multidisciplinary team.

Diabetes, mortality and glucose monitoring rates in the TREAT Asia HIV Observational Database Low Intensity Transfer (TAHOD-LITE) study.

OBJECTIVES: Diabetes is a growing cause of morbidity and mortality in people living with HIV (PLHIV) receiving antiretroviral therapy (ART). We investigated the association between fasting plasma glucose (FPG) levels and mortality, and factors associated with FPG monitoring rates in Asia. METHODS: Patients from the Therapeutics Research, Education, and AIDS Training in Asia (TREAT Asia) HIV Observational Database Low Intensity Transfer (TAHOD-LITE) cohort were included in the present study if they had initiated ART. Competing risk and Poisson regression were used to analyse the association between FPG and mortality, and assess risk factors for FPG monitoring rates, respectively. FPG was categorized as diabetes (FPG ≥ 7.0 mmol/L), prediabetes (FPG 5.6-6.9 mmol/L) and normal FPG (FPG < 5.6 mmol/L). RESULTS: In total, 33 232 patients were included in the analysis. Throughout follow-up, 59% had no FPG test available. The incidence rate for diabetes was 13.7 per 1000 person-years in the 4649 patients with normal FPG at ART initiation. Prediabetes [sub-hazard ratio (sHR) 1.32; 95% confidence interval (CI) 1.07-1.64] and diabetes (sHR 1.90; 95% CI 1.52-2.38) were associated with mortality compared to those with normal FPG. FPG monitoring increased from 0.34 to 0.78 tests per person-year from 2012 to 2016 (P < 0.001). Male sex [incidence rate ratio (IRR) 1.08; 95% CI 1.03-1.12], age > 50 years (IRR 1.14; 95% CI 1.09-1.19) compared to ≤ 40 years, and CD4 count ≥ 500 cells/µL (IRR 1.04; 95% CI 1.00-1.09) compared to < 200 cells/µL were associated with increased FPG monitoring. CONCLUSIONS: Diabetes and prediabetes were associated with mortality. FPG monitoring increased over time; however, less than half of our cohort had been tested. Greater resources should be allocated to FPG monitoring for early diabetic treatment and intervention and to optimize survival.

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 HbA1c 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 HbA1c 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.

Text-message responsiveness to blood glucose monitoring reminders is associated with HbA1c benefit in teenagers with Type 1 diabetes.

AIMS: To evaluate an 18-month text-messaging intervention in teenagers with Type 1 diabetes and to assess factors associated with text responsiveness and glycaemic benefit. METHODS: Teenagers with diabetes (N = 147), aged 13-17 years, received two-way text reminders at self-selected times to check blood glucose levels and reply with blood glucose results. RESULTS: At baseline, the participants (48% boys, 78% white, 63% pump-treated) had a mean ± sd age of 14.9 ± 1.3 years, diabetes duration of 7.1 ± 3.9 years and HbA1c concentration of 69 ± 12 mmol/mol (8.5 ± 1.1%). The mean proportion of days with ≥1 blood glucose response declined over time (0-6 months, 60 ± 26% of days, 7-12 months, 53 ± 31% of days, 13-18 months, 43 ± 33% of days). Over 18 months, 49% responded with ≥1 blood glucose result on ≥50% of days (high responders). Regression analysis controlling for baseline HbA1c revealed no significant change in HbA1c from baseline to 18 months in high responders (P = 0.54) compared with a significant HbA1c increase in low responders (+0.3%, P = 0.01). In participants with baseline HbA1c ≥64 mmol/mol (≥8%), high responders were 2.5 times more likely than low responders to have a clinically significant [≥5.5 mmol/mol (≥0.5%)] HbA1c decrease over 18 months (P < 0.05). In participants with baseline HbA1c <64 mmol/mol(<8%), high responders were 5.7 times more likely than low responders to have an 18-month HbA1c <58 mmol/mol (<7.5%; P < 0.05). CONCLUSIONS: Teenagers with Type 1 diabetes who responded to text reminders on ≥50% of days over 18 months experienced clinically significant glycaemic benefit. There remains a need to tailor interventions to maintain teenager engagement and optimize improvements.

Asymptomatic hypoglycaemia in Type 1 diabetes: incidence and risk factors.

AIM: The epidemiology of asymptomatic (silent) hypoglycaemia is not well-described. We investigated incidence and risk factors for asymptomatic hypoglycaemia in Type 1 diabetes. METHODS: A cohort of 153 people with Type 1 diabetes participated in 6 days of blinded continuous glucose monitoring (CGM) and recording of hypoglycaemia symptoms. At entry, hypoglycaemia awareness was classified (by three different methods) and HbA1c and C-peptide were measured. Hypoglycaemic episodes were defined as interstitial glucose ≤ 3.9 mmol/l (IG3.9 ) or ≤ 3.0 mmol/l (IG3.0 ) for ≥ 15 min, and were considered asymptomatic if no hypoglycaemic symptoms were reported. RESULTS: At thresholds IG3.9 and IG3.0 , the incidence rates of hypoglycaemic episodes were 5.0 (7.9) [median (IQR)] and 1.3 (3.4) episodes/person-week, respectively. Three-quarters of episodes were asymptomatic. In total, 77% and 52% of participants experienced one or more episode of asymptomatic hypoglycaemia at IG3.9 and IG3.0 [3.0 (6.2) and 1.0 (2.3) asymptomatic episodes/person-week]. At multivariate analysis, reduced awareness was positively associated with asymptomatic hypoglycaemia, particularly nocturnal events, and negatively with symptomatic hypoglycaemia. High insulin dose was associated with increased risk of both asymptomatic and symptomatic hypoglycaemia, whereas low HbA1c and long diabetes duration were risk factors only for symptomatic hypoglycaemia. CONCLUSIONS: Asymptomatic hypoglycaemia constitutes the majority of hypoglycaemic events in Type 1 diabetes. Reduced hypoglycaemia awareness and high insulin dose are risk factors for asymptomatic hypoglycaemia but other conventional risk factors for severe hypoglycaemia do not correlate with risk of asymptomatic episodes.

The impact of using a closed-loop system on food choices and eating practices among people with Type 1 diabetes: a qualitative study involving adults, teenagers and parents.

AIMS: We explored whether, how and why moving onto and using a hybrid day-and-night closed-loop system affected people's food choices and dietary practices to better understand the impact of this technology on everyday life and inform recommendations for training and support given to future users. METHODS: Twenty-four adults, adolescents and parents were interviewed before commencing use of the closed-loop system and following its 3-month use. Data were analysed thematically and longitudinally. RESULTS: While participants described preparing and/or eating similar meals to those consumed prior to using a closed-loop, many described feeling more normal and less burdened by diabetes in dietary situations. Individuals also noted how the use of this technology could lead to deskilling (less precise carbohydrate counting) and less healthy eating (increased snacking and portion sizes and consumption of fatty, energy-dense foods) because of the perceived ability of the system to deal with errors in carbohydrate counting and address small rises in blood glucose without a corrective dose needing to be administered. CONCLUSIONS: While there may be quality-of-life benefits to using a closed-loop, individuals might benefit from additional nutritional and behavioural education to help promote healthy eating. Refresher training in carbohydrate counting may also be necessary to help ensure that users are able to undertake diabetes management in situations where the technology might fail or that they take a break from using it.