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Currently available semiautomated insulin-delivery systems require individualized insulin regimens for the initialization of therapy and meal doses based on carbohydrate counting for routine operation. In contrast, the bionic pancreas is initialized only on the basis of body weight, makes all dose decisions and delivers insulin autonomously, and uses meal announcements without carbohydrate counting.In this 13-week, multicenter, randomized trial, we randomly assigned in a 2:1 ratio persons at least 6 years of age with type 1 diabetes either to receive bionic pancreas treatment with insulin aspart or insulin lispro or to receive standard care (defined as any insulin-delivery method with unblinded, real-time continuous glucose monitoring). The primary outcome was the glycated hemoglobin level at 13 weeks. The key secondary outcome was the percentage of time that the glucose level as assessed by continuous glucose monitoring was below 54 mg per deciliter; the prespecified noninferiority limit for this outcome was 1 percentage point. Safety was also assessed.A total of 219 participants 6 to 79 years of age were assigned to the bionic-pancreas group, and 107 to the standard-care group. The glycated hemoglobin level decreased from 7.9% to 7.3% in the bionic-pancreas group and did not change (was at 7.7% at both time points) in the standard-care group (mean adjusted difference at 13 weeks, -0.5 percentage points; 95% confidence interval [CI], -0.6 to -0.3; P0.001). The percentage of time that the glucose level as assessed by continuous glucose monitoring was below 54 mg per deciliter did not differ significantly between the two groups (13-week adjusted difference, 0.0 percentage points; 95% CI, -0.1 to 0.04; P0.001 for noninferiority). The rate of severe hypoglycemia was 17.7 events per 100 participant-years in the bionic-pancreas group and 10.8 events per 100 participant-years in the standard-care group (P = 0.39). No episodes of diabetic ketoacidosis occurred in either group.In this 13-week, randomized trial involving adults and children with type 1 diabetes, use of a bionic pancreas was associated with a greater reduction than standard care in the glycated hemoglobin level. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; ClinicalTrials.gov number, NCT04200313.).

OBJECTIVE To assess whether previously observed brain and cognitive differences between children with type 1 diabetes and control subjects without diabetes persist, worsen, or improve as children grow into puberty and whether differences are associated with hyperglycemia. RESEARCH DESIGN AND METHODS One hundred forty-four children with type 1 diabetes and 72 age-matched control subjects without diabetes (mean ± SD age at baseline 7.0 ± 1.7 years, 46% female) had unsedated MRI and cognitive testing up to four times over 6.4 ± 0.4 (range 5.3–7.8) years; HbA1c and continuous glucose monitoring were done quarterly. FreeSurfer-derived brain volumes and cognitive metrics assessed longitudinally were compared between groups using mixed-effects models at 6, 8, 10, and 12 years. Correlations with glycemia were performed. RESULTS Total brain, gray, and white matter volumes and full-scale and verbal intelligence quotients (IQs) were lower in the diabetes group at 6, 8, 10, and 12 years, with estimated group differences in full-scale IQ of −4.15, −3.81, −3.46, and −3.11, respectively (P < 0.05), and total brain volume differences of −15,410, −21,159, −25,548, and −28,577 mm3 at 6, 8, 10, and 12 years, respectively (P < 0.05). Differences at baseline persisted or increased over time, and brain volumes and cognitive scores negatively correlated with a life-long HbA1c index and higher sensor glucose in diabetes. CONCLUSIONS Detectable changes in brain volumes and cognitive scores persist over time in children with early-onset type 1 diabetes followed longitudinally; these differences are associated with metrics of hyperglycemia. Whether these changes can be reversed with scrupulous diabetes control requires further study. These longitudinal data support the hypothesis that the brain is a target of diabetes complications in young children.

Glucose is a primary fuel source to the brain, yet the influence of dysglycemia on neurodevelopment in children with type 1 diabetes remains unclear. We examined brain activation using functional MRI in 80 children with type 1 diabetes (mean ± SD age 11.5 ± 1.8 years; 46% female) and 47 children without diabetes (control group) (age 11.8 ± 1.5 years; 51% female) as they performed a visuospatial working memory (N-back) task. Results indicated that in both groups, activation scaled positively with increasing working memory load across many areas, including the frontoparietal cortex, caudate, and cerebellum. Between groups, children with diabetes exhibited reduced performance on the N-back task relative to children in the control group, as well as greater modulation of activation (i.e., showed greater increase in activation with higher working memory load). Post hoc analyses indicated that greater modulation was associated in the diabetes group with better working memory function and with an earlier age of diagnosis. These findings suggest that increased modulation may occur as a compensatory mechanism, helping in part to preserve working memory ability, and further, that children with an earlier onset require additional compensation. Future studies that test whether these patterns change as a function of improved glycemic control are warranted.

Objective: To assess whether previously observed brain and cognitive differences between children with type 1 diabetes and non-diabetic controls persist, worsen or improve as children grow into puberty, and whether differences are associated with hyperglycemia. Research Design & Methods: 144 children with type 1 diabetes and 72 non-diabetic age-matched controls, mean±SD age 7.0±1.7 years at baseline, 46% female, had unsedated magnetic resonance imaging and cognitive testing up to 4 times over 6.4±0.4 years (5.3-7.8); HbA1C and continuous glucose monitoring were done quarterly. FreeSurfer-derived brain volumes and cognitive metrics assessed longitudinally were compared between groups using mixed effects models at 6, 8, 10 and 12 years. Correlations with glycemia were performed. Results: Total brain, gray and white matter volumes, full-scale and verbal IQ were lower in the diabetes group [at 6, 8, 10 and 12 years estimate group differences in full-scale IQ respectively: -4.15, -3.81, -3.46, -3.11, p 3x103, -21159, -25548, -28577, p C index and higher sensor glucose in diabetes. Conclusions: Detectable changes in brain volumes and cognitive scores persist over time in children with early-onset type 1 diabetes followed longitudinally; these differences are associated with metrics of hyperglycemia. Whether these changes can be reversed with scrupulous diabetes control requires further study. These longitudinal data support the hypothesis that the brain is a target of diabetes complications in young children.

Glucose is a primary fuel source to the brain, yet the influence of dysglycemia on neurodevelopment in children with type 1 diabetes remains unclear. We examined brain activation using functional MRI in 80 children with type 1 diabetes (mean age ± SD, 11.5±1.8 years; 46% female) and 47 children without diabetes (“control”, mean age 11.8±1.5 years; 51% female) as they performed a visuospatial working memory (N-back) task. Results indicated that in both groups, activation scaled positively with increasing working memory load across many areas, including the frontoparietal cortex, caudate and cerebellum. Between groups, children with diabetes exhibited reduced performance on the N-back task relative to control children, as well as greater modulation of activation (i.e., showed greater a increase in activation with higher working memory load). Post-hoc analyses indicated that greater modulation was associated in the diabetes group with better working memory function and with an earlier age of diagnosis. These findings suggest that increased modulation may occur as a compensatory mechanism, helping in part to preserve working memory ability, and further, that children with an earlier onset require additional compensation. Future studies that test whether these patterns change as a function of improved glycemic control are warranted.

Background: The effect of dysglycemia on brain development and cognition is not well understood. Methods: In a multi-site study, we examined brain activation in 93 children with T1D (mean age 11.5 ± 1.8 years) and 57 nondiabetic children (mean age 11.8 ± 1.5 years) as they performed a classic executive function paradigm, the Go/No-Go task. Participants responded to letters flashed on a screen by a key press (Go) but not to the letter X (No-Go). Results: Despite similar task performance between the groups, children with T1D exhibited greater activation in executive control regions (dorsal anterior cingulate cortex, inferior frontal gyri, cerebellum and supramarginal gyri; p=0.010) and less suppression in the posterior node of the default mode network (DMN) compared to controls (p=0.006). Secondary analyses showed greater activation in executive control regions was associated in T1D with shorter response times and better parent-reported measures of executive function (ps Conclusion: These findings suggest that compensatory recruitment of executive control areas may act to offset T1D-related impairments in the DMN and, at least transiently, allow behavioral performance on Go/No-Go to be equivalent to that of nondiabetic controls. Disclosure L.C. Foland-Ross: None. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Novo Nordisk Inc., Profusa, Inc. Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Beta Bionics, ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care. N. Mauras: Consultant; Self; Novo Nordisk Inc., PicoLife. Research Support; Self; Medtronic MiniMed, Inc. A. Arbelaez: None. N.H. White: None. T. Aye: None. D.M. Wilson: Advisory Panel; Self; Tolerion, Inc. Research Support; Self; Beta Bionics, Dexcom, Inc., Medtronic. W.V. Tamborlane: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic MiniMed, Inc., Novo Nordisk Inc., Sanofi, Takeda Pharmaceutical Company Limited. S.A. Weinzimer: Consultant; Self; Eli Lilly and Company, Sanofi. Consultant; Spouse/Partner; Tandem Diabetes Care. Consultant; Self; Zealand Pharma A/S. Speaker's Bureau; Self; Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Stock/Shareholder; Self; InsuLine Medical Ltd. E. Tsalikian: None. M. Tansey: Advisory Panel; Self; Daiichi Sankyo Company, Limited. A. Cato: None. T. Hershey: Research Support; Spouse/Partner; Sage Pharmaceuticals. L.A. Fox: None. G. Tong: None. K.A. Englert: Consultant; Self; PicoLife Technologies, LLC. P. Mazaika: None. A.L. Reiss: None. Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development (DIRECNET: U01HD-41906, HD-41908, HD-41915, HD-41918, HD-56526, R01HD078463, U54HD087011; National Center for Advancing Translational Sciences (UL1TR000448)

Background: Subtle but significant cognitive differences between youth with and without type 1 diabetes (T1D) have been observed and found to be related to chronic hyperglycemia. We report continued follow-up of prospectively acquired cognitive data obtained over 4.5 years in a large cohort of young children with and without T1D. Methods: 181 children with T1D and 90 age-matched nondiabetic controls underwent age-appropriate neuropsychological testing at three time points: baseline, 18 months, and approximately 2.9 years after the second visit (T1D group: 11.2 ± 1.9 y, HbA1c: 8.1 ± 1.0%, diabetes duration 6.4 y at the time of latest evaluation; control group: mean age 11.6 ± 1.7 years). Effects of T1D on cognition were estimated based on longitudinal mixed effects modeling after controlling for parental full-scale IQ. Results: The T1D group continued to show significantly lower scores on Full Scale IQ (Cohen’s d=-0.31, p=0.024), Verbal IQ (d=-0.33, p=0.009), and Vocabulary (d=-0.42, p=0.002) compared to nondiabetic controls at last follow-up. Processing speed, memory and learning were similar between the T1D and the control groups. Within the T1D group, there was a significant inverse relationship between HbA1c at last follow-up and Vocabulary (r=-0.307, p=0.001) as well as between HbA1c and VIQ (r=-0.200, p=0.037), controlling for parental IQ. Conclusion: In this large cohort of children with relatively well-controlled T1D followed for 4.5 years, differences in full-scale and verbal IQ persist over time compared to nondiabetic controls, and effects on vocabulary and verbal IQ are related to glycemic control. These findings further support the importance of optimizing glycemic control during this critical period of brain maturation. Disclosure S.A. Weinzimer: Consultant; Self; Eli Lilly and Company, Sanofi. Consultant; Spouse/Partner; Tandem Diabetes Care. Consultant; Self; Zealand Pharma A/S. Speaker's Bureau; Self; Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Stock/Shareholder; Self; InsuLine Medical Ltd. J.M. Ambrosino: Consultant; Spouse/Partner; Eli Lilly and Company, Sanofi. Consultant; Self; Tandem Diabetes Care. Consultant; Spouse/Partner; Zealand Pharma A/S. Speaker's Bureau; Spouse/Partner; Insulet Corporation, Medtronic, Tandem Diabetes Care. Stock/Shareholder; Spouse/Partner; InsuLine Medical Ltd. A. Cato: None. B. Jo: None. K.A. Englert: Consultant; Self; PicoLife Technologies, LLC. N.H. White: None. A. Arbelaez: None. T. Hershey: Research Support; Spouse/Partner; Sage Pharmaceuticals. L.A. Fox: None. E. Tsalikian: None. M. Tansey: Advisory Panel; Self; Daiichi Sankyo Company, Limited. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Novo Nordisk Inc., Profusa, Inc. Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Beta Bionics, ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care. T. Aye: None. D.M. Wilson: Advisory Panel; Self; Tolerion, Inc. Research Support; Self; Beta Bionics, Dexcom, Inc., Medtronic. W.V. Tamborlane: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic MiniMed, Inc., Novo Nordisk Inc., Sanofi, Takeda Pharmaceutical Company Limited. A.L. Reiss: None. N. Mauras: Consultant; Self; Novo Nordisk Inc., PicoLife. Research Support; Self; Medtronic MiniMed, Inc. Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development (DIRECNET: U01HD-41906, HD-41908, HD-41915, HD-41918, HD-56526, R01HD-078463, U54HD087011); National Center for Advancing Translational Sciences (UL1TR000448)

Background: The extent to which glycemic exposure adversely impacts the developing brain in young children with early-onset type 1 diabetes (T1D) is controversial. Methods: As part of the multisite DirecNet Study, we performed structural MRI at three time points (baseline, 18 months and approximately 2.9 years after the second visit) in 137 children with T1D (age: 7.0 ± 1.7 years, lifetime average HbA1c: 8.0 ± 0.7%, and diabetes duration: 2.4 years at study entry) and 66 age-matched nondiabetic controls (7.0 1.8 years old). White matter (WM) and gray matter (GM) volumes in various brain regions-of-interest were determined by voxel-based morphometry (VBM). Total cumulative hyperglycemic exposure was determined as HbA1c area under the curve (lifetime A1c) from the time of diagnosis in T1D children. Results: Children with T1D had slower growth of total cortical and subcortical GM and WM than the nondiabetic controls at all timepoints. Gray matter regions (frontal, temporal, subcortical, and occipital cortex) showed less growth in the T1D compared to the control group (p Conclusion: This study demonstrates that children with early-onset T1D and worse glycemic control have slower cortical and subcortical GM and WM growth than nondiabetic controls, suggesting that hyperglycemia is detrimental to the developing brain during this critical period of rapid brain maturation. The long-term consequences of these early alterations in brain growth require further follow-up. Disclosure A. Arbelaez: None. S. O’Donoghue: None. N. Mauras: Consultant; Self; Novo Nordisk Inc., PicoLife. Research Support; Self; Medtronic MiniMed, Inc. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Novo Nordisk Inc., Profusa, Inc. Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Beta Bionics, ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care. N.H. White: None. S.A. Weinzimer: Consultant; Self; Eli Lilly and Company, Sanofi. Consultant; Spouse/Partner; Tandem Diabetes Care. Consultant; Self; Zealand Pharma A/S. Speaker's Bureau; Self; Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Stock/Shareholder; Self; InsuLine Medical Ltd. T. Aye: None. E. Tsalikian: None. D.M. Wilson: Advisory Panel; Self; Tolerion, Inc. Research Support; Self; Beta Bionics, Dexcom, Inc., Medtronic. W.V. Tamborlane: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medtronic MiniMed, Inc., Novo Nordisk Inc., Sanofi, Takeda Pharmaceutical Company Limited. M. Tansey: Advisory Panel; Self; Daiichi Sankyo Company, Limited. A. Cato: None. T. Hershey: Research Support; Spouse/Partner; Sage Pharmaceuticals. L.A. Fox: None. K.A. Englert: Consultant; Self; PicoLife Technologies, LLC. A.L. Reiss: None. Funding Eunice Kennedy Shriver National Institute of Child Health and Human Development (DIRECNET: U01HD-41906, HD-41908, HD-41915, HD-41918, HD-56526, R01HD078463, U54HD087011; National Center for Advancing Translational Sciences (UL1TR000448)

The Gen3 iLet (iLet) is a physically and functionally integrated, bionic pancreas (BP) platform that can operate in bihormonal, insulin-only, or glucagon-only modes. The iLet in insulin-only mode has never been tested in subjects Twenty youth (mean age=12±3 [range 7-17] years) completed a 10-day, randomized crossover study at 3 sites comparing 5 days using the insulin-only iLet to 5 days of usual care (UC) with sensor-augmented pump therapy. During the day, youth were supervised by study staff in a day-camp setting with periods of vigorous physical activity. At night, participants returned home with their guardians, and staff monitored glucose levels remotely. Participants achieved good glycemic control with low levels of hypoglycemia in both the UC and iLet arms (see Table). There were 3 hyperglycemic events associated with iLet malfunction, including one failure of insulin delivery with alarms not heard and two instances of insulin cartridges leaking. These events and others observed by the study teams, guardians, and participants led to changes in the Gen4 iLet under development to improve safety and usability. These results suggest that testing of the improved Gen4 iLet is warranted and offers promise in the pediatric population. Disclosure L. Ekhlaspour: None. G.P. Forlenza: Advisory Panel; Self; Dexcom, Inc. Consultant; Self; Medtronic MiniMed, Inc., Tandem Diabetes Care. Research Support; Self; Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. C. Berget: Consultant; Self; Insulet Corporation, Medtronic. K.R. Bird: None. K.A. Englert: Consultant; Self; PicoLife Technologies, LLC. L. Hsu: None. C.A. Balliro: None. N. Mauras: Consultant; Self; Novo Nordisk Inc., PicoLife. Research Support; Self; Medtronic MiniMed, Inc. R. Wadwa: Advisory Panel; Self; Eli Lilly and Company. Research Support; Self; Beta Bionics, MannKind Corporation, Novo Nordisk Inc., Tandem Diabetes Care, Xeris Pharmaceuticals, Inc. Other Relationship; Self; Dexcom, Inc. B.A. Buckingham: Advisory Panel; Self; ConvaTec Inc., Novo Nordisk Inc., Profusa, Inc. Consultant; Self; Medtronic MiniMed, Inc. Research Support; Self; Beta Bionics, ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Medtronic MiniMed, Inc., Tandem Diabetes Care. Other Relationship; Self; Insulet Corporation, Tandem Diabetes Care. F. El-Khatib: Employee; Self; Beta Bionics. Stock/Shareholder; Self; Beta Bionics. E. Damiano: Advisory Panel; Self; Novo Nordisk A/S. Board Member; Self; Beta Bionics. Employee; Self; Beta Bionics. Stock/Shareholder; Self; Beta Bionics. Stock/Shareholder; Spouse/Partner; Beta Bionics. Other Relationship; Self; Ascensia Diabetes Care, Senseonics. S.J. Russell: Advisory Panel; Self; Companion Medical, Unomedical a/s. Consultant; Self; Flexion Therapeutics. Research Support; Self; Beta Bionics, MITRE Corporation, Novo Nordisk A/S, Zealand Pharma A/S. Other Relationship; Self; ADOCIA, Ascensia Diabetes Care, Ascensia Diabetes Care, Lilly Diabetes, Roche Diabetes Care, Senseonics. Funding National Institute of Diabetes and Digestive and Kidney Diseases (1UC4DK108612)

Background: The purpose of this article is to describe challenges associated with successful use of continuous glucose monitoring (CGM) by young children with type 1 diabetes (T1D) and to detail the techniques and products used to improve the duration of sensor wear. Methods: The DirecNet Study Group conducted 2 studies in 169 children with T1D between the ages of 1 and 9 years who were instructed to wear a CGM device daily. Problems related to skin irritation and sensor adhesiveness in these young children presented challenges to daily use of the CGM. Study coordinators instituted a variety of techniques using commercially available products to attempt to overcome these problems. Results: Three primary factors that contributed to reduced CGM use were identified: the limited body surface area in smaller children, ambient temperature and humidity, as well as the type and duration of physical activity. Using supplemental products to minimize the impact of these factors resulted in improved adherence and reduced skin irritation. Conclusion: Achieving satisfactory adhesion of the CGM sensor and transmitter may involve finding the right supplemental product or combination of products through trial and error. Optimizing adhesion and minimizing skin irritation can significantly improve duration of use and tolerability of CGM devices by young children.

Purpose The purpose of this article is to describe the process of educating families and children with type 1 diabetes on real time continuous glucose monitoring (RT-CGM) and to note the similarities and differences of training patients using continuous subcutaneous insulin infusion (CSII) versus multiple daily injections (MDI). Methods A total of 30 CSII participants and 27 MDI participants were educated using the Navigator RT-CGM in a clinical trial. Time spent with families for visits and calls was tracked and compared between patient groups. The Diabetes Research in Children Network (DirecNet) educators were surveyed to assess the most crucial, time intensive, and difficult educational concepts related to CGM. Results Of the 27 MDI families, an average of 9.6 hours was spent on protocol-prescribed visits and calls (not measured in CSII) and 2 hours on participant-initiated contacts over 3 months. MDI families required an average of 5.4 more phone contacts over 3 months than CSII families. According to the DirecNet educators, lag time and calibrations were the most crucial teaching concepts for successful RT-CGM use. The most time was spent on teaching technical aspects, troubleshooting, and insulin dosing. The most unanticipated difficulties were skin problems including irritation and the sensor not adhering well. Conclusion Educators who teach RT-CGM should emphasize lag time and calibration techniques, technical device training, and sensor insertion. Follow-up focus should include insulin dosing adjustments and skin issues. The time and effort required to introduce RT-CGM provided an opportunity for the diabetes educators to reemphasize good diabetes care practices and promote self-awareness and autonomy to patients and families.

Continuous glucose monitors (CGM), devices that can measure interstitial glucose in “real time,” have become widely available particularly for use in patients with diabetes, and their accuracy and ease of use have greatly improved over the last decade. A number of large and well-controlled clinical trials have firmly established their usefulness in improving metabolic control (as measured by HbA1C) and decreasing time spent in hypoglycemia in adults; however, data have been less robust proving benefit in children and adolescents. Benefits are clearly linked to near-continuous wear. Insulin dosing algorithms based on CGM glucose trends have proven useful in dissecting the large volume of data generated daily by these devices, although these are imperfect tools, particularly in children. The technology is likely to be most useful when integrated with insulin pump delivery systems (sensor augmented). In this review, we concentrate on the analysis of published results of the largest trials in adults and children, including the very young, with diabetes.

The purpose of this article is to describe the process of educating families and children with type 1 diabetes on real time continuous glucose monitoring (RT-CGM) and to note the similarities and differences of training patients using continuous subcutaneous insulin infusion (CSII) versus multiple daily injections (MDI).A total of 30 CSII participants and 27 MDI participants were educated using the Navigator RT-CGM in a clinical trial. Time spent with families for visits and calls was tracked and compared between patient groups. The Diabetes Research in Children Network (DirecNet) educators were surveyed to assess the most crucial, time intensive, and difficult educational concepts related to CGM.Of the 27 MDI families, an average of 9.6 hours was spent on protocol-prescribed visits and calls (not measured in CSII) and 2 hours on participant-initiated contacts over 3 months. MDI families required an average of 5.4 more phone contacts over 3 months than CSII families. According to the DirecNet educators, lag time and calibrations were the most crucial teaching concepts for successful RT-CGM use. The most time was spent on teaching technical aspects, troubleshooting, and insulin dosing. The most unanticipated difficulties were skin problems including irritation and the sensor not adhering well.Educators who teach RT-CGM should emphasize lag time and calibration techniques, technical device training, and sensor insertion. Follow-up focus should include insulin dosing adjustments and skin issues. The time and effort required to introduce RT-CGM provided an opportunity for the diabetes educators to reemphasize good diabetes care practices and promote self-awareness and autonomy to patients and families.