T1D Duration Research Articles

418-P: Adults with T1D, Neuropathy, and Depressive Symptoms Are in Need of Clinical Intervention

Prolonged T1D and suboptimal glycemic control contributes to diabetic peripheral neuropathy, which may occur with impairing psychological symptoms. This study examined the association between neuropathy and depressive symptoms in adults with T1D.Neuropathy was assessed using the Michigan Neuropathy Screening Instrument history and physical assessment (clinical scores >2 indicate neuropathy) in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) Study. Depressive symptoms were assessed by the Beck Depression Inventory (BDI-II; scores >14 indicate clinically elevations).Neuropathy was detected in 22% of participants with T1D (N=364; 55% female; age=51±9 years; T1D duration=38±9 years) and elevated depressive symptoms in 10%. Participants with neuropathy were older and had longer T1D duration and higher BDI-II scores; they were more likely to have elevated depressive symptoms. In logistic regression models adjusted for age, sex, T1D duration, and A1C, neuropathy was associated with a 7-fold increased odds of elevated depressive symptoms (OR [95% CI] = 7.5 [3.1-17.9, p<0.0001). It is well known that significant pain and depression result in functional impairment across various domains of daily life. Interventions to reduce clinically elevated depressive symptoms and promote adaptive coping in adults with T1D with neuropathy are largely absent, and critically needed.View largeDownload slideView largeDownload slide DisclosureS. E. Wetter: None. K. A. Driscoll: None. J. K. Snell-bergeon: Stock/Shareholder; Self; GlaxoSmithKline plc.FundingNational Institutes of Health (R01HL113029)

915-P: Characteristics of Teens with T1D That Predict Family T1D Management over Time

Aim: Adolescence is challenging for T1D management. To identify families that need more support during this time, we assessed individual and family characteristics that predict adverse communication/behaviors related to T1D care. Method: Teens with T1D (N=283) and a parent (83% mothers) completed validated measures of parent involvement in care, diabetes-specific family conflict, negative affect regarding BG monitoring, and T1D self-care at 0, 6, and 12 mo. We used linear mixed models to assess how baseline characteristics (sex, age, T1D duration, A1c, BG monitoring frequency, injection vs. pump therapy, and parent education) predicted T1D behaviors over 12 months. Results: At baseline, teens (51% male, 32% non-white, 60% pump-treated) had M±SD age 15.0±1.3 years, T1D duration 6.6±3.8 years, and A1c 8.5±1.1%. Significant modifiable and non-modifiable predictors of poorer outcomes are shown (Table). Diabetes family conflict was higher in younger teens, those with higher A1c, and teens with parents without a college degree. T1D management (parent involvement, teen self-care) was poorer for older teens and those on injections. Summary: To prevent adverse family behaviors, clinicians can target modifiable factors (e.g., glycemic control, treatment modality). Clinicians can also provide support to families of teens with non-modifiable risk factors (e.g., lower parent education, younger teens with family conflict). Disclosure R. M. Wasserman: None. L. J. Tinsley: None. P. V. Commissariat: None. L. K. Volkening: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. B. Anderson: None. Funding National Institutes of Health (R01DK095273, P30DK036836); JDRF (2-SRA-2014-253-M-B)

910-P: Psychosocial Characteristics Associated with Diabetes Device Use in Teens with T1D

Insulin pumps and CGM devices can help youth with T1D achieve better glycemic control and alleviate self-care burden. However, not all youth want to use such devices. We compared psychosocial characteristics of teens with T1D and their parents/caregivers according to teen pump use vs. non-use as well as teen CGM use vs. non-use. At baseline, teens/parents completed psychosocial surveys assessing teen depressive symptoms [CESD], disordered eating behaviors, diabetes-specific family conflict, parent involvement in diabetes care, teen self-care, diabetes burden (PAID-Ped/PR), quality of life, and major life events. Diabetes treatment data were collected by interview and EHR review every 3 months for 18 months. Teens using/starting pump or CGM at all/most visits were considered pump users or CGM users, respectively. Chi-square and t-tests compared characteristics of device (pump, CGM) users with non-users. The sample comprised 301 teens aged 13-17 with T1D (41% male); mean age was15.0±1.3 years, T1D duration 6.5±3.7 years, and A1c 8.5±1.1%. Neither age, sex, nor T1D duration was related to device use. CGM and pump non-users had less favorable survey scores than device users for many psychosocial characteristics (Table). Identifying teens with less favorable psychosocial factors may help target those at risk for device non-use, allowing timely intervention and support by clinicians when initiating diabetes technologies.View largeDownload slideView largeDownload slide DisclosureC. Chen: None. L. J. Tinsley: None. L. K. Volkening: None. B. Anderson: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc.FundingNational Institutes of Health (R01DK095273, T32DK007260, P30DK036836); JDRF (2-SRA-2014-253-M-B)

309-OR: Mean CGM Values Before and During COVID-19 Pandemic Demonstrate Noninferiority of Telehealth in Pediatric T1D

Aim: The COVID-19 pandemic called for rapid deployment of telehealth. To assess utility of telehealth in pediatric T1D, we compared CGM glucose values in youth with T1D using CGM before and during the pandemic.Methods: The EHR provided visit frequency and CGM metrics. Data during pandemic (3/16/20 to 10/29/20) were compared with data from the same calendar months in 2019. Youth (N=469) using CGM and seen in both periods were included based on pre-pandemic characteristics: age 1-18 yr, T1D duration ≥6 mo (if age <6) or ≥1 yr (if age ≥6 yr). CGM metrics included mean and SD glucose, coefficient of variation (CV), and glucose management index (GMI). Each youth’s CGM data were averaged in each time period and compared in paired analyses.Results: Youth (46% male) had a mean age 12.4±3.5 yr, T1D duration 6.1±3.6 yr, HbA1c 7.8±0.9%; 80% were pump-treated. Pre-pandemic, 0.1% of visits were telehealth, increasing to 99.6% during pandemic. Mean number of visits during each 7-mo period increased from 2.5 in 2019 to 2.7 in 2020 (p=.006). CGM metrics generally improved during the pandemic period (Table). Those whose visit frequency increased with telehealth had the greatest improvement in CGM glucose, from 192±72 to 183±67 (p<.001).Conclusions: Telehealth allowed increased visit frequency and improved CGM glucose metrics, supporting non-inferiority and potential benefit of telehealth for youth with T1D using CGM.View largeDownload slideView largeDownload slide DisclosureT. Kaushal: None. L. J. Tinsley: None. L. K. Volkening: None. C. Turcotte: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. FundingNational Institutes of Health (K12DK094721, P30DK036836)

925-P: Participation in Daily Physical Activity (PA) Improves Glycemic Control in Youth with T1D

Aim: PA is an important part of diabetes management. ADA recommends that youth with T1D participate daily in ≥60 minutes of moderate to vigorous PA. We prospectively assessed daily PA in youth with T1D and compared demographic and diabetes variables according to frequency of PA ≥60 minutes/day. Methods: Youth (N=125, ages 8-17) with T1D completed 3-day PA records every 3 months for 18 months. Diabetes treatment data and A1c were collected at the same time. For each youth, we calculated the % of days with ≥60 minutes PA and compared those with ≥60 minutes PA on &amp;lt;50% vs. ≥50% of days. Youth with at least 6 days of PA data over 18 months were included. In analyses, baseline age, T1D duration, and pump use were used; mean values over the 18-month period for A1c, insulin dose, and BMI percentile were used. Results: Youth (50% male, 90% white, 74% pump-treated) had a mean±SD age 12.8±2.5 years, T1D duration 6.0±3.2 years, and A1c 8.2±0.9%. Youth had a median of 16 (IQR 12-17) PA record days. The % of days with ≥60 minutes PA ranged from 0 to 100% (median 53% [IQR 35-71%]), with 59% of youth reporting ≥60 minutes PA on ≥50% of days. Youth with ≥60 minutes PA on ≥50% of days were younger (12.4 vs. 13.5 years, p=.02), had shorter T1D duration (5.2 vs. 7.0 years, p=.002), lower daily insulin dose (0.86 vs. 1.00 u/kg, p=.002), and lower A1c (8.1 vs. 8.4%, p=.03) than youth with ≥60 minutes PA on &amp;lt;50% of days. There were no significant differences in sex (51 vs. 47% male, p=.64), race/ethnicity (93 vs. 84% white, p=.11), BMI percentile (69 vs. 70%, p=.85), or pump use (74 vs. 73%, p=.82) between those with ≥60 minutes PA on ≥50% vs. &amp;lt;50% of days. There was a notable temporal difference in youth having ≥60 min PA on ≥50% of days in the summer (75%), fall (51%), winter (58%), and spring (65%), respectively (p=.004). Conclusion: A substantial proportion of youth with T1D do not exercise per recommendations. Given associations of PA with lower A1c, additional efforts to support exercise management in T1D are needed along with support for PA throughout the year. Disclosure R. O. La banca: None. L. K. Volkening: None. H. Desrochers: None. E. Dassau: Consultant; Self; Eli Lilly and Company, Employee; Self; Eli Lilly and Company, Research Support; Self; Dexcom, Inc., Tandem Diabetes Care, Speaker’s Bureau; Self; Dexcom, Inc., Roche Diabetes Care, Stock/Shareholder; Self; Eli Lilly and Company. S. N. Mehta: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. Funding National Institutes of Health (K12DK094721, P30DK036836); Iacocca Family Foundation

546-P: Demographic and Diabetes-Specific Factors Associated with Adverse Psychosocial Outcomes in Teens with T1D

Aim: There has been increased emphasis on psychosocial outcomes and mental health support for people with T1D. We assessed demographic and diabetes factors related to poorer psychosocial outcomes over 1 year in teens with T1D. Methods: At 0, 6, and 12 mo, teens (ages 13-17) and parents completed validated measures of diabetes distress, diabetes self-efficacy, and general teen quality of life; teens also reported depressive symptoms. Linear mixed models assessed demographic and diabetes factors predicting teen- and parent-reported psychosocial outcomes over 1 yr. Results: Teens (N=283, 51% male, 78% white) were M±SD age 15.0±1.3 yrs, with T1D duration 6.6±3.8 yrs, BGM frequency 4.3±2.0 times/day, and A1c 8.5±1.1%; 60% used pumps, 84% had 2-parent families, and 69% had a college educated parent. Risk factors for teen- and parent-reported psychosocial outcomes shared little overlap (Table). Teen reports of poorer psychosocial outcomes were mainly associated with demographic factors (sex, parent education) while parent reports were mainly associated with diabetes factors (A1c, T1D duration, BGM, insulin regimen). Conclusions: For teens with T1D and parents, different factors are associated with adverse psychosocial outcomes. Consideration of both demographic and diabetes-specific factors is important to help providers identify psychosocial risks and provide timely support to families. Disclosure P. V. Commissariat: None. L. J. Tinsley: None. L. K. Volkening: None. R. M. Wasserman: None. B. Anderson: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. Funding National Institutes of Health (R01DK095273, K12DK094721, P30DK036836); JDRF (2-SRA-2014-253-M-B)

228-OR: Inconsistent Antecedent Physical Activity (PA) Impacts Nocturnal Glycemia in Youth with T1D

Aim: Overnight insulin dosing relies on glucose level and evening food intake, although PA also impacts glycemic levels. We assessed associations between antecedent energy expenditure (EE) from PA and nocturnal glycemia in youth with T1D. Methods: Youth completed 3-day PA logs (PA type, duration, intensity) and wore 3-day masked CGM (iPro™) quarterly for 18 months. We assigned a MET value to PA and calculated EE (kcal/day), using only complete 24-hour days. CGM metrics were calculated for days (6 AM-11:59 PM) and nights (12 AM-5:59 AM) when ≥50% of CGM data were available. Results: Youth (N=136, 48% male) were ages 8-17 years (M±SD 12.8±2.5), with T1D duration 5.9±3.1 years and daily insulin dose 0.9±0.3 U/kg; 73% used insulin pumps. Median (IQR) PA duration and EE were 60 (10-120) minutes/day and 287 (0-695) kcal/day, respectively. CGM metrics by day/night appear in Table. In partial correlations adjusted for multiple observations/person, higher EE was associated with lower mean glucose (r=-.12, p=.0001), more %time 180 (r=-.09, p=.006) that night. Time in range was unchanged. When youth EE was 180 (p=.03) that night. Conclusion: In youth with T1D, PA can reduce nocturnal hyperglycemia and increase nocturnal hypoglycemia. These findings can help tailor automated insulin delivery algorithms according to PA. Disclosure R. O. La banca: None. L. K. Volkening: None. K. Milaszewski: Consultant; Self; Lilly USA, LLC. E. Dassau: Consultant; Self; Eli Lilly and Company, Employee; Self; Eli Lilly and Company, Research Support; Self; Dexcom, Inc., Tandem Diabetes Care, Speaker’s Bureau; Self; Dexcom, Inc., Roche Diabetes Care, Stock/Shareholder; Self; Eli Lilly and Company. S. N. Mehta: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc. Funding National Institutes of Health (K12DK094721, P30DK036836); Iacocca Family Foundation

935-P: Favorable Shift in CGM Glucose in Youth with T1D during COVID-19 Pandemic

Aim: COVID-19 caused disruption with potential for changes in lifestyle and T1D care behaviors, especially for youth. We compared CGM-derived glucometrics during the COVID-19 pandemic with the previous year in a clinic-based pediatric sample with T1D using CGM.Method: We used EHR-extracted data to compare CGM metrics during the pandemic (3/16/20 -10/29/20) with the same calendar months in 2019. The sample comprised youth using CGM, aged 1-18 years, with T1D duration ≥6 months (age <6 years) or ≥1 year (age ≥6 years).Results: The pre-pandemic sample comprised 578 youth (53% female, age 12.4±3.5, T1D 6.2±3.5 years). The pandemic sample comprised 605 youth (54% female, age 13.4±3.6, T1D 6.8±3.8 years). Over 80% of youth were common to both samples. Mean CGM glucose was 7 mg/dL lower during the pandemic (186±35) vs. pre-pandemic (193±33) (p<.001). The proportion of youth with mean glucose <145 and 145-154 mg/dL increased 80-100% during the pandemic (5 to 9% and 5 to 10%, respectively), while the proportion with mean glucose ≥210 mg/dL decreased by 29% (31 to 22%). The % of youth with glucose management indicator (GMI) <7% increased by >110% (Figure). The 7-12y age group showed the largest shift in GMI: 8.0 pre- vs. 7.7% during pandemic (p=.003).Conclusion: There was a beneficial shift in glucose levels from pre to during the pandemic. Future studies are needed to assess how changes in healthcare during the pandemic may have improved glycemic outcomes.View largeDownload slideView largeDownload slide DisclosureT. Kaushal: None. L. J. Tinsley: None. L. K. Volkening: None. L. Ambler-osborn: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc.FundingNational Institutes of Health (K12DK094721, P30DK036836)

72-OR: HDL Particle Concentration Predicts Incident Coronary Artery Disease (CAD) in Type 1 Diabetes (T1D)

We have shown that elevated HDL cholesterol (HDL-C) levels (≥80 mg/dL) associate with increased CAD risk in women with T1D. Furthermore, HDL-C levels are not necessarily cardioprotective in nondiabetic individuals, suggesting that the cholesterol content of HDL does not accurately assess CAD risk. We thus determined whether two other HDL metrics, HDL particle concentration (HDL-P) and cholesterol efflux capacity (CEC), predicted incident CAD in a large cohort of childhood onset T1D (n=550). At baseline, mean age was 27.8 yrs, T1D duration was 19.6 yrs and 49% were women. HDL-P was assessed by calibrated ion mobility analysis and CEC was quantified with validated assays in cAMP stimulated J774 cells and in ABCA1-expressing BHK cells. CAD was defined as CAD death, myocardial infarction and/or revascularization. During a median follow-up of 26 yrs, we observed 203 incident CAD cases (36.9%). At baseline, incident cases were older, more likely to have smoked, have hypertension, longer duration of T1D, higher non-HDL-C and markers of kidney disease and inflammation. Cases were also more likely to have lower HDL-P concentrations but similar CEC to non-cases. Cox models with backward elimination were constructed for each HDL metric, allowing for potential confounding variables, including HDL-C. In separate multivariable models, higher concentrations of total HDL-P (T-HDL-P, HR=0.88, 95% CI: 0.83-0.92) and 3 major HDL subpopulations - small (S-HDL-P, HR=0.78, 0.67-0.92), medium (M-HDL-P, HR=0.79, 0.71-0.88) and large-sized (L-HDL-P, HR=0.74, 0.61-0.89) particles - associated with a lower CAD incidence whereas HDL-C did not. Higher total CEC in J774 cells also predicted lower CAD risk (HR=0.74, 0.55-0.996) after similar adjustments, but became non-significant after further adjusting for HDL-P. ABCA1-specific CEC did not predict CAD. Our results suggest that increased HDL-P levels are cardioprotective in T1D, in contrast to HDL-C and CEC which did not independently predict CAD. Disclosure T. Costacou: None. T. Vaisar: Consultant; Self; AstraZeneca. K. Bornfeldt: None. T. J. Orchard: None. J. Heinecke: None. Funding National Institutes of Health (HL130153, DK34818)

553-P: The Type 1 Diabetes High-Fidelity Wraparound (T1D HFW) Program: An Option for the Management of High-Risk Youth?

Despite advances in management, many young adolescents with T1D continue to struggle. Psychosocial factors play a major role. The T1D HFW Program is an innovative strategy to improve the adherence to medical regimens, including self-management and self-efficacy in high-risk youth. It is based on HFW, an evidence-based behavioral health concept described as a structured, team-based and individualized process that includes members who have experience either living with or raising a child with T1D. The aim of this pilot study is to test the feasibility and impact of this intervention in youth 11 to 16 years with T1D followed in a large academic diabetes center who are struggling with their management as defined by poor glycemic control and/or repeated emergency room visits and/or hospitalizations. Outcomes include assessment for behavioral, psychosocial and diabetes related measures with validated instruments. Seventeen youth enrolled and participated so far (58% females, 58% Caucasian, 23% African American, mean age 14±1.4 years, T1D duration 7.5±3.5 years, HbA1c at entry 10.3±2.3%, 65% with a deterioration in HbA1c, 45% prior diabetes related hospitalizations). A significant percent (57%) reported at least one traumatic experience including bullying (66%), witnessing violence (50%), physical/emotional abuse (33%). To date, eight families have transitioned out of the program after a mean of 6.5 months with 62.5% showing improvement and 25% no deterioration in HbA1c. Youth scoring positive for moderate depression on the PHQ-9 went from 27% to 9%. 1/3 of youth indicated positive results for generalized anxiety by the Screen for Child Anxiety Disorders (SCARED) with no change upon finishing the program. 60% of caregivers indicated a positive score on the Diabetes Distress Scale at start, which decreased to 20%. The T1D HFW program through personalized plans with identified support systems may be a promising strategy for youth struggling with T1D. Disclosure J. Schreiber: None. A. G. Nevin: None. L. Jones: None. M. W. Payne: None. K. C. Nash: None. R. Muzumdar: None. I. Libman: Advisory Panel; Self; Novo Nordisk. Funding Children’s Hospital of Pittsburgh Foundation

54-OR: Nucleolin Autoantibody Accelerates Atherosclerosis in Type 1 Diabetes

Hyperglycemia has been evaluated extensively as risk factors for cardiovascular disease (CVD) in people with type 1 diabetes (T1DM). However, the effects of the autoantibody on atherosclerosis and immunogenic trigger are not well understood in T1D. Using the generated several mice models of atherosclerosis including NOD, congenic ApoE-/-/NOD (NDM and no- autoimmune), ApoE-/-/NOD (autoimmunity with insulitis, NDM) and ApoE-/-/NOD autoimmune DM mice, we analyzed immune cells composition of aorta and have observed the increasing numbers of CD3+(CD3+/CD25-), Th1 and Th17 subset of T cells and B cells and decreased Treg (CD3+/CD25+/Foxp3+) in the ApoE-/-/NOD and ApoE-/-/NOD-DM mice vs. control. In addition, we postulate that the identification of specific autoantibody(s) which induce dysregulaton of T-cells, resulting in enhancing its infiltration and accumulation at the plaques could aid new immunotherapies for atherosclerosis. Here we performed autoantigen microarrays to profile and identify specific autoantibodies, enhancing the severe atherosclerosis in subgroups of Medalist patients with chronic duration of T1D due to autoimmunity with positive HLA DR3/4 risk alleles and autoantibodies and compared to the people with monogenic diabetes lacking HLA DR3/4 risk alleles for T1D and autoantibodies. Autoantigen microarrays from the plasma of T1D patients with positive DR3/4 risk and CVD identified 8 autoantibodies changed in the context of atherosclerosis, compared to the people with monogenic diabetes. To confirm the autoantibody profiling data from the patients, we analyzed the autoantibody profiles in the T1D mice models of atherosclerosis described above. Autoantigen microarrays analysis of the plasma of T1D patients and mice showed several common findings that reached significance anti-Nucleolin Ab, p=0.005. These findings indicate autoimmunity may contribute to the progression of atherosclerosis in T1D. Further studies are in progress to replicate these findings in other cohorts of T1D. Disclosure K. Park: None. Q. Li: None. H. Park: None. J. Fu: None. S. Kissler: None. E. Maddaloni: Research Support; Self; European Foundation for the Study of Diabetes, Speaker's Bureau; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes, Merck KGaA. I. Wu: None. A. H. Lichtman: None. G. L. King: Consultant; Self; Agios, Inc., Medtronic, Other Relationship; Self; Janssen Pharmaceuticals, Inc. Funding DK036836, DK036836, EY026080

136-OR: Nocturnal Hypoglycemia Prevention Strategies Used by People with Type 1 Diabetes According to Their Insulin Delivery and Blood Glucose Monitoring Technology

People with T1D (PWT1D) use many strategies to avoid nocturnal hypoglycemia (NH), however, the current evidence on these strategies is limited. Technologies such as continuous subcutaneous insulin infusion (CSII) or continuous glucose monitors (CGM) could help reduce NH and possibly alter PWT1D’ management behaviors. Aim: To describe PWT1D’ preferred NH prevention strategies according to their use of technology. Methods: Self-reported data from an online registry of PWT1D were analyzed. To describe which NH prevention strategies are most often used, we ran a χ2 test with a post hoc pairwise comparison of the groups based on their mode of insulin delivery and glucose monitoring (CSII + self-monitoring of blood glucose (SMBG); CSII + CGM; multiple daily injections (MDI) + CGM; MDI + SMBG). Results: Among 767 adults (64% female, mean age 45 ± 15 years, T1D duration 25 ± 14 years) 42% used MDI + CGM, 40% CSII + CGM, 5% CSII + SMBG, and 13% MDI + SMBG. About 67% reported waking up ≥1 time in the past month due to NH symptoms. The most widely used strategies were verifying bedtime glycemia (71%), having an evening/bedtime snack (60%), and/or reducing nocturnal basal insulin (30%). PWT1D using CSII + CGM or CSII + SMBG relied more on basal insulin reduction (36% and 33.3%, respectively) compared to those using MDI + CGM (26%) or MDI + SMBG (19%). Less PWT1D using CSII + CGM reported having a snack to prevent NH (51%), compared to CSII + SBMG (61%), MDI + CGM (66%), and MDI + SBGM (67%) groups (p&amp;lt;0.001). Conclusion: Results suggest that PWT1D using technology choose different strategies to avoid NH than non-users. CSII users relying on basal insulin adjustment was expected as CSII offers more flexibility for insulin delivery. Snacks remain a popular strategy to prevent NH but are less used by PWT1D on CSII + CGM. While our findings provide some real-life insight into the methods PWT1D use to avoid NH, the efficacy of these strategies still needs further investigation. Disclosure M. K. Talbo: None. V. Messier: Other Relationship; Self; Eli Lilly and Company. K. Desjardins: None. R. Rabasa-lhoret: Advisory Panel; Self; Bayer Inc., Covance Inc., Insulet Corporation, Pfizer Inc., Other Relationship; Self; Abbott, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Dexcom, Inc., Eli Lilly and Company, HLS Therapeutics Inc., Janssen Pharmaceuticals, Inc., Medtronic, Merck &amp; Co., Inc., Novo Nordisk, Sanofi-Aventis, Research Support; Self; Canadian Institutes of Health Research, Cystic Fibrosis Canada, Diabetes Canada, JDRF, National Institutes of Health, Prometic, Société Francophone du Diabète, Speaker’s Bureau; Self; CMS Canadian Medical&amp;Surgical Knowledge Translation Research Group, CPD Network. A. Brazeau: None. T. Peters: None. Funding Canadian Institutes of Health Research (JT1-157204); JDRF (4-SRA-2018-651-Q-R)

625-P: Validation of Formulae to Estimate Insulin Sensitivity in Type 1 Diabetes

Introduction: The “gold standard” measure of insulin sensitivity (IS), a euglycemic hyperinsulinemic clamp, is costly, time- and labour-intensive. Several formulae, developed using clamp data estimate insulin sensitivity, expressed as estimated glucose disposal rate (eGDR) or insulin sensitivity index (eM/I or elog10M/I). Due to clamp complexity and cost these formulae often lacks independent validation.Aim: To validate several formulae estimating IS using independent euglycaemic hyperinsulinemic clamp data.Methods: Euglycemic, hyperinsulinemic clamps were performed in 108 T1D adults (age (mean±SD) 34±7 yrs, T1D duration 10±4 yrs, HbA1c 7.7±1.5%; 33 with microvascular complications). Measured GDR (last 30min of the clamp) ranged 0.5 - 9.6 mg/kg/min (median (LQ, UQ) 4.45 (3.04, 6.5 mg/kg/min) were compared with eGDR and eLog10M/I calculated using simple formulae by (1) Williams, (2) Zheng, (3) Dabelea and (4) and (5) (Australia (AU)) authors, all derived from routine clinical chemistry and demographics. eGDR formula (Duca) was not assessed as it includes adiponectin levels.Results: Results are in Table 1.Conclusion: Authors (AU) formulae to estimate IS, including age, sex, HDL-C, BMI, HbA1c, pulse pressure and WHR had highest correlation with measured GDR and better performance (AUROC) in detecting low IS than other formulae.View largeDownload slideView largeDownload slide DisclosureA. S. Januszewski: None. P. Niedzwiecki: None. N. Sachithanandan: None. G. M. Ward: None. C. Karschimkus: None. D. N. O’neal: Advisory Panel; Self; Abbott Diabetes, Medtronic, Sanofi, Research Support; Self; Dexcom, Inc., GlySens Incorporated, Medtronic, Pacific Diabetes Technologies. D. Zozulinska-ziolkiewicz: None. A. Uruska: None. A. Jenkins: Advisory Panel; Self; Abbott Diabetes, Sanofi-Aventis, Other Relationship; Self; Amgen Inc., Research Support; Self; Abbott, International Diabetes Federation, JDRF, Medtronic, Mylan N. V.

Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes.

The purpose of this study was to describe objective sleep-wake characteristics and glycemia over 7-14 days in young adults with type 1 diabetes. In addition, person-level associations among objective sleep-wake characteristics (total sleep time, sleep variability, and sleep fragmentation index), daytime sleepiness, and glycemia (glycemic control and glucose variability) were examined. In this cross-sectional study, objective sleep-wake characteristics were measured via actigraphy and glucose variability via continuous glucose monitoring over 6-14 days. At baseline, participants completed the Psychomotor Vigilance Test, the Trail Making Test, and questionnaires on daytime sleepiness, sleep quality, and sleep disturbance including sleep diaries. Forty-six participants (mean age, 22.3 ± 3.2 years) wore a wrist actigraph and underwent continuous glucose monitoring concurrently for 6-14 days. Greater sleep variability was directly associated with greater glucose variability (mean of daily differences; r = .33, P = .036). Higher daytime sleepiness was directly associated with greater glucose variability (mean of daily differences; r = .50, P = .001). The association between sleep variability and glucose variability (mean of daily differences) was no longer significant when accounting for daytime sleepiness and controlling for type 1 diabetes duration (P > .05). A higher sleep fragmentation index was associated with greater glucose variability (B = 1.27, P = .010, pr2 = 0.40) after controlling for type 1 diabetes duration and accounting for higher daytime sleepiness. Sleep-wake variability, sleep fragmentation, daytime sleepiness, and the associations with glycemia are new dimensions to consider in young adults with type 1 diabetes. Sleep habits in this population may explain higher glucose variability, and optimizing sleep may improve overall diabetes management. Griggs S, Hickman RL Jr, Strohl KP, Redeker NS, Crawford SL, Grey M. Sleep-wake characteristics, daytime sleepiness, and glycemia in young adults with type 1 diabetes. J Clin Sleep Med. 2021;17(9):1865-1874.

Characteristics Associated With Diabetes Device Use Among Youth With Type 1 Diabetes

Type 1 diabetes (T1D) is a common illness of childhood, requiring lifelong, daily complex management to prevent acute and chronic complications. Studies have shown that use of insulin pumps and continuous glucose monitors (CGM) offers benefit for glycemic control. However, such device use is not universal in adolescents. We aimed to compare baseline socio-demographic and diabetes characteristics associated with diabetes technology (pump and CGM) uptake and continued use in 13-17 year old teens with T1D. Data were derived from a multicenter clinical trial aimed at optimizing self-care and glycemic control in teens with T1D. Socio-demographic and diabetes data were collected quarterly by parent-youth interview and electronic medical record review prospectively over 18 months. Chi-square and t-tests compared characteristics of device and non-device users (pump vs no pump; CGM vs no CGM). The study sample comprised 301 teens (41% male) with mean±SD age 15.0±1.3 years, T1D duration 6.5±3.7 years, and A1c 8.5±1.1%. Most (65%) used a pump at entry or initiated pump therapy during the study; 35% used injection therapy at entry or stopped pump therapy. In contrast, 27% used a CGM at entry or started a CGM during the study, while 73% never used or stopped using CGM. Device users at entry and those who began use had similar characteristics, as did those who never used and those who discontinued device use. Pump users were more likely to use CGM than non-pump users (36% vs 10%, p<.0001). Neither age, sex, nor T1D duration was related to pump or CGM use. Pump users (vs non-pump users) were less likely to have another medical condition (44% vs 59%, p=.01) and more likely to be non-Hispanic white (83% vs 61%, p=.0001); have family annual household income ≥$150,000 (34% vs 19%, p=.0003), private health insurance (92% vs 74%, p<.0001), a parent with college education or higher (67% vs 46%, p=.0005), and a 2-parent household (88% vs 78%, p=.03). Pump users also had lower z-BMI (0.73±0.80 vs 0.97±0.79, p=.01), performed more frequent daily BG monitoring (4.8±1.8 vs 3.9±2.0, p<.0001), and were less likely to have HbA1c ≥9% at initial and last visits (25% vs 43%, p=.005; 31% vs 49%, p=.01). CGM users (vs non-CGM users) were more likely to be non-Hispanic white (88% vs 70%, p=.009); have family annual household income ≥$150,000 (44% vs 23%, p=.0001), a parent with college education or higher (78% vs 53%, p=.0004), and private health insurance (95% vs 82%, p=.005). CGM users also performed more frequent daily BG monitoring (5.2±1.9 vs 4.2±1.9, p=.0002) and were less likely to have HbA1c ≥9% after 18 months (27% vs 42%, p=.03). In summary, we found distinct socio-demographic and diabetes-specific factors associated with device use in adolescents with T1D. These findings provide an opportunity to address barriers associated with device non-use in order to expand device implementation, especially in underserved adolescents with T1D.

Associations between Macular OCT Angiography and Nonproliferative Diabetic Retinopathy in Young Patients with Type 1 Diabetes Mellitus.

Methods OCTA of both eyes was performed in a cross-sectional study of 14 to 30-year-old individuals with at least 10-year duration of T1D and controls recruited from the Norwegian Atherosclerosis and Childhood Diabetes (ACD) study. Vessel density (VD) and foveal avascular zone (FAZ) area in the superficial and deep capillary plexus (SCP and DCP), total retinal volume (TRV), and central macular thickness (CMT) were calculated using automated software. Univariate and multivariate ordered logistic regression (OLR) models were used accordingly. Results We included 168 control eyes and 315 T1D eyes. Lower VD in DCP (OR 0.65, 95% CI 0.51–0.83), longer diabetes duration (OR 1.51, 95% CI 1.22–1.87), and higher waist circumference (OR 1.08, 95% CI 1.02–1.14) were significantly associated with progression of NPDR. VD in SCP and DCP were significantly lower in T1D patients without diabetic retinopathy than in controls. Conclusions Sparser VD in DCP is significantly associated with severity of NPDR, supporting that OCTA might detect the earliest signs of NPDR before it is visible by ophthalmoscopy.

Demographic characteristics and acute complications among adults with type 1 diabetes: Comparison of two multicentre databases from Germany and the United States.

Studies on acute complications in adult T1D were previously reported from the United States (U.S.) and from Germany. The aim was to compare demographic characteristics and patterns of severe hypoglycaemia (SH) and diabetic ketoacidosis (DKA) between Germany and the U.S. Descriptive comparison on individuals aged ≥18 years, with T1D duration ≥2 years were made between the German diabetes-patient registry (DPV) and the U.S. electronic-health-record database (T1PCO). Individuals in both databases were divided into patients with haemoglobin A1c (HbA1c) <7% and HbA1c ≥7%. 5190 (DPV) and 31,430 individuals (T1PCO) fulfilled the inclusion criteria. DPV patients were younger, more often male and had lower body-mass index. In both databases, more males than females had HbA1c <7%. Individuals had higher HbA1c in T1PCO compared to DPV. The relationship between HbA1c and DKA was similar in both databases. SH revealed a U-shaped curve in T1PCO, but no clear pattern was present in DPV. SH events increased with higher age in DPV, but not in T1PCO. Patterns of SH differ between Germany and U.S. Differences in capture of SH among the databases cannot be excluded, but differences in health care including patient education and level of care by specialists are likely.

Structural Gray and White Matter Differences in Patients With Type 1 Diabetes and Impaired Awareness of Hypoglycemia.

Type 1 diabetes (T1D) is associated with an increased risk of cognitive decline, where severe hypoglycemia (SH) and impaired awareness of hypoglycemia (IAH) may play a role. While there is evidence of a possible association between IAH and brain damage, the potential brain changes remain poorly characterized by magnetic resonance imaging (MRI). To investigate whether there are structural brain differences in a group of T1D patients with IAH compared with normal awareness of hypoglycemia (NAH). General practice, population-based, cross-sectional study (July 2018 to July 2019). Endocrinology Department, Hospital Santa Creu i Sant Pau. A total of 40 T1D patients (20 each with IAH and NAH) matched for age, sex, T1D duration, and education level. Using different neuroimaging techniques, we compared whole-brain gray matter (GM) and white matter (WM) differences. We used voxel-based morphometry and cortical surface area analysis methods to assess GM differences, and fractional anisotropy (FA) to assess WM differences. Compared with patients with T1D-NAH, patients with T1D-IAH had reduced GM volumes and cortical surface areas, especially in frontal and parietal regions (P < 0.05 corrected), and also showed reduced FA values in major WM tracts. The observed MRI differences correlated with both SH frequency and IAH severity. MRI for patients with T1D show that IAH is associated with brain changes involving both GM and WM. Further research is needed to elucidate whether the observed differences are a consequence of increased SH episode frequency and increased IAH severity.

HbA1c variability and long-term glycemic control are linked to peripheral neuropathy in patients with type 1 diabetes

BackgroundHbA1c variability has been linked to retinopathy, renal disease and autonomic neuropathy in patients with type 1 diabetes mellitus (T1D) and type 2 diabetes mellitus (T2D). Although the same relationship has been demonstrated for diabetic peripheral neuropathy (DPN) in patients with T2D, data for T1D are still lacking.MethodsPatients older than 17 years of age with ≥ 10 years of T1D duration and follow-up were included. All patients underwent nerve conduction studies and neurological examination. Laboratorial data was retrospectively extracted from chart review. Mean HbA1c (mHbA1c) over 10 years was calculated, as well as HbA1c variability estimated by standard deviation (HbA1c-SD) and coefficient of variation (HbA1c-CV).ResultsFifty patients with T1D were included (30 females and 21 non-caucasians), with mean age and T1D duration of 25.6 ± 5.0 and 17.9 ± 6.1 years, respectively. The frequency of DPN was 24%. Higher mHbA1c (10.4 ± % vs 8.1 ± %; p < 0.001), HbA1c-SD (1.8 ± 0.8 vs 0.9 ± 0.4; p < 0.001), and HbA1c-CV (1.7 ± 0.8 vs 1.2 ± 1.1; p = 0.006) were observed in patients with DPN compared to others. SD-HbA1c and HbA1c-CV were associated with DPN, diagnosed by either clinical or NCS criteria, independent of mHbA1c, age and gender.ConclusionsNot only long-term glycemic control, but also its variability is associated with DPN in patients with T1D. Larger studies are required to confirm this finding.

1319-P: Evaluation of Engagement with an Incentivized Text Messaging (TM) Intervention in Teens with T1D and Suboptimal Glycemic Control

Background: Among digital health interventions, TM can be a useful tool in teens with T1D. However, attrition remains a major issue, with engagement decreasing over time. We aimed to describe patterns of engagement in an incentivized TM intervention and to assess impact of engagement on A1C in teens with T1D and suboptimal control randomized to the TM arm. Methods: Of 165 teens (12-18 years old, T1D duration &amp;gt;1 year, A1C ≥8%) recruited into a 6-month RCT, 83 were assigned to TM intervention and received daily educational/motivational TMs using the MyDiaText™ platform. Socio-demographic and clinical data were obtained from medical record review. Participants were rewarded biweekly for the most consecutive TM responses. TM response rate (RR) was defined as number of responses/total messages received. High RR was defined as &amp;gt;50%. Paired t-tests, ANOVA, and Pearson correlation were used in statistical analysis. Results: At entry, teens (57% males, 52% white) had a mean(±SD) age of 16±2 years, T1D duration 7±4 years; 55% were pump-treated, 65% used CGM, and A1C was 10±1.9%. Clinical concerns for depression were seen in 28%. The mean overall RR was 58.6%(±28.9%), and the high RR group included 66% of participants. High and low RR groups did not differ by sex, race, age, T1D duration, use of technology, baseline A1C, or clinical depression. Over the 6 months, A1C improved significantly to 9.2±1.8% (p=0.00), with 35% improving by ≥1%. High responders were twice as likely to improve A1C by ≥1% than low responders (p=0.18). There was a significant decline in RR over time (r2=0.9, p=0.00). Conclusions: In teens with T1D and suboptimal control, socio-demographic factors did not predict engagement with a financially incentivized TM intervention. However, high responders tended to improve their A1C, likely due to increased engagement in self-care. There remains a need to create a digital health intervention that maintains engagement over extended periods for teens with T1D. Disclosure T. Kaushal: None. T. Lipman: None. L.E. Katz: None. L.M. Laffel: Advisory Panel; Self; Roche Diabetes Care. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Insulogic LLC, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk Inc., Sanofi US. Funding National Institutes of Health (P30DK036836, K12DK094721, 2T32DK063688)