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ObjectiveThis study evaluated the effects of continuous glucose monitoring (CGM) combined with family behavioral intervention (CGM+FBI) and CGM alone (Standard-CGM) on glycemic outcomes and parental quality of life compared with blood glucose monitoring (BGM) in children ages 2 to

Introduction: Despite the significant impact of type 1 diabetes (T1D) on family, few instruments are available to assess health-related quality of life (HRQOL) among family members of people with T1D. This study aimed to develop and evaluate the psychometric properties of new measures of diabetes-specific HRQOL for parents and partners of people with T1D. We report on the multistep development and validation process for the self-report Type 1 Diabetes and Life (TIDAL) measures, with versions for parents of youth age Public Significance Statement This study developed a set of validated questionnaires to measure health-related quality of life in parents and partners of people with type 1 diabetes. The experiences of family members are important and have implications for the health and well-being of people with diabetes, yet there have been few measures to accurately and reliably assess their quality of life. These new measures can be used in clinical practice and research settings. Keywords: patient-reported outcomes, quality of life, psychosocial, assessment, family Supplemental materials: https://doi.org/10.1037/fsh0000507.supp, Patient-reported outcomes are important to assess and report in clinical trials and patient care (Lohr & Zebrack, 2009), especially for people with chronic conditions including type 1 diabetes (T1D) (Agiostratidou [...]

Author(s): Revital Nimri [sup.1] , Tadej Battelino [sup.2] , Lori M. Laffel [sup.3] , Robert H. Slover [sup.4] , Desmond Schatz [sup.5] , Stuart A. Weinzimer [sup.6] , Klemen Dovc [...], Despite the increasing adoption of insulin pumps and continuous glucose monitoring devices, most people with type 1 diabetes do not achieve their glycemic goals.sup.1. This could be related to a lack of expertise or inadequate time for clinicians to analyze complex sensor-augmented pump data. We tested whether frequent insulin dose adjustments guided by an automated artificial intelligence-based decision support system (AI-DSS) is as effective and safe as those guided by physicians in controlling glucose levels. ADVICE4U was a six-month, multicenter, multinational, parallel, randomized controlled, non-inferiority trial in 108 participants with type 1 diabetes, aged 10-21 years and using insulin pump therapy (ClinicalTrials.gov no. NCT03003806). Participants were randomized 1:1 to receive remote insulin dose adjustment every three weeks guided by either an AI-DSS, (AI-DSS arm, n = 54) or by physicians (physician arm, n = 54). The results for the primary efficacy measure--the percentage of time spent within the target glucose range (70-180 mg dl.sup.-1 (3.9-10.0 mmol l.sup.-1))--in the AI-DSS arm were statistically non-inferior to those in the physician arm (50.2 [plus or minus] 11.1% versus 51.6 [plus or minus] 11.3%, respectively, P < 1 × 10.sup.-7). The percentage of readings below 54 mg dl.sup.-1 ( The randomized-controlled trial ADVICE4U demonstrates non-inferiority of an automated AI-based decision support system compared with advice from expert physicians for optimal insulin dosing in youths with type 1 diabetes.

Background: Meeting glycemic recommendations is challenging for youth with type 1 diabetes. Diabetes technology, including continuous glucose monitoring (CGM) and hybrid closed-loop (HCL) automated insulin delivery systems, significantly increase achievement of glycemic targets; however, many youth struggle to sustain use of early HCL systems. Nocturnal alarm fatigue contributes to disrupted sleep and device discontinuation. Methods: We examined the frequency and causes of nocturnal (10:00 p.m. to 6:00 a.m.) alarms in pediatric patients (N = 76, median age 14.5 years [interquartile range 11.8–17.0 years, range 7–24 years]) starting on a first-generation HCL system in a prospective observational study. Device data were analyzed with linear mixed-effects models to examine change across time at 3-month intervals for 12 months. Results: At baseline (HCL system in nonautomated mode), participants averaged 3.3 ± 0.6 alarms per night. In the 2 weeks after starting HCL (automated) mode, alarm frequency significantly increased to 5.4 ± 0.5 times per night (P <0.001). Alarm frequency decreased through the remainder of the observational period; however, CGM sensor and HCL system use also declined. The types of alarms were evenly distributed among sensor maintenance, sensor threshold, pump, and HCL-specific alarms. Conclusion: These data show that HCL system nocturnal alarms are frequent and may be barriers to sleep quality and device use. Further research is needed to assess the impact of diabetes technology on sleep and to determine method to improve sleep quality with technology use. [ABSTRACT FROM AUTHOR]

Background Rebound hyperglycemia may occur following glucagon treatment for severe hypoglycemia. We assessed rebound hyperglycemia occurrence after nasal glucagon (NG) or injectable glucagon (IG) administration in patients with type 1 diabetes (T1D) and type 2 diabetes (T2D). Methods This was a pooled analysis of 3 multicenter, randomized, open-label studies (NCT03339453, NCT03421379, NCT01994746) in patients ≥18 years with T1D or T2D with induced hypoglycemia. Proportions of patients achieving treatment success [blood glucose (BG) increase to ≥70 mg/dL or increase of ≥20 mg/dL from nadir within 15 and 30 minutes]; BG ≥70 mg/dL within 15 minutes; in-range BG (70-180 mg/dL) 1 to 2 and 1 to 4 hours postdose; and BG >180 mg/dL 1 to 2 and 1 to 4 hours postdose were compared. Incremental area under curve (iAUC) of BG >180 mg/dL and area under curve (AUC) of observed BG values postdose were analyzed. Safety was assessed in all studies. Results Higher proportions of patients had in-range BG with NG vs IG (1-2 hours: P =.0047; 1-4 hours: P =.0034). Lower proportions of patients had at least 1 BG value >180 mg/dL with NG vs IG (1-2 hours: P =.0034; 1-4 hours: P =.0068). iAUC and AUC were lower with NG vs IG (P =.025 and P <.0001). As expected, similar proportions of patients receiving NG or IG achieved treatment success at 15 and 30 minutes (97-100%). Most patients had BG ≥70 mg/dL within 15 minutes (93-96%). The safety profile was consistent with previous studies. Conclusion This study demonstrated lower rebound hyperglycemia risk after NG treatment compared with IG. Clinical Trial Registration NCT03421379, NCT03339453, NCT01994746 [ABSTRACT FROM AUTHOR]

Objective. To further evaluate glycemic outcomes during the observational extension phase of the Continuous Glucose Monitoring (CGM) Intervention for Teens and Young Adults randomized clinical trial (RCT). Subjects and Methods. Following a 26-week RCT comparing CGM with blood glucose monitoring (BGM) in 153 adolescents and young adults aged 14 to <25 years old with suboptimally controlled type 1 diabetes, 70 (89%) participants in the BGM group initiated use of CGM (referred to as BGM–CGM cohort), and 70 (95%) participants in the CGM group continued to use of CGM (CGM–CGM cohort) for an additional 26 weeks. Results. In the CGM–CGM cohort, mean hemoglobin A1c (HbA1c) decreased from 8.9% ± 0.9% (74 ± 9.8 mmol/mol) at randomization to 8.3% ± 1.3% (67 ± 14.2 mmol/mol) at 52 weeks (p < 0.001); however, significant improvement in time in target range (TIR) 70–180 mg/dL was not observed from prerandomization (38% ± 13%) to 52 weeks (41% ± 18%). Median percent time <70 mg/dL decreased from 3.0% before randomization to 1.1% at 52 weeks (p < 0.001). In the BGM–CGM cohort, mean HbA1c decreased from 8.9% ± 1.2% (74 ± 13.1 mmol/mol) before CGM initiation to 8.5% ± 1.3% (69 ± 14.2 mmol/mol) after 26 weeks of CGM use (p < 0.001) and mean TIR increased from 34% ± 12% to 38% ± 15% (p = 0.01). The median percent time <70 mg/dL decreased from 3.3% before CGM initiation to 1.2% after 26 weeks of CGM use (p < 0.001). No participants discontinued CGM use during the extension phase. Conclusions. This further evaluation of CGM supports the findings of the preceding RCT that use of CGM improves glycemic control and reduces hypoglycemia in adolescents and young adults with type 1 diabetes. This trial is registered with NCT03263494. [ABSTRACT FROM AUTHOR]

Successful transition from a pediatric to adult diabetes care provider is associated with reduced ambulatory diabetes care visits and increased acute complications. This study aimed to determine whether the degree of independence in diabetes care and the rate of acute complications after transition to adult diabetes care were associated with individuals' student or employment status. Nonstudents were found to be less likely than students to be independent with diabetes care, and employed nonstudents were at lower risk of diabetic ketoacidosis than unemployed nonstudents. Additional support may be needed for young adults who are not students or are unemployed to improve independence and reduce the risk for acute complications. [ABSTRACT FROM AUTHOR]

Author(s): Petter Bjornstad[sup.1] [sup.2] , Carlos Roncal[sup.3] , Tamara Milagres[sup.3] , Laura Pyle[sup.1] , Miguel Angel Lanaspa[sup.3] , Franziska K. Bishop[sup.2] , Janet K. Snell-Bergeon[sup.1] [sup.2] , Richard J. Johnson[sup.2] [...], Background Urine uric acid (UUA) has been implicated in the pathogenesis of diabetic nephropathy via its effect on tubular cells. We hypothesized that the UUA level would be higher in adolescents with type 1 diabetes (T1D) than in those without T1D. We also hypothesized that UUA and fractional uric acid excretion (FeUA) would be higher in adolescents with T1D and hyperfiltration [estimated glomerular filtration rate (eGFR) [greater than or equal to]141 mL/min/1.73 m.sup.2] than in those without hyperfiltration. Methods The UUA concentration was determined and FeUA calculated in adolescents with (n = 239) and without T1D (n = 75). The eGFR was calculated using the Zappitelli equation based on serum creatinine and cystatin C concentrations. Results Compared to the non-diabetic adolescents enrolled in the study, those with T1D had a higher eGFR (mean ± standard deviation: 120 ± 22 vs. 112 ± 16 mL/min/1.73 m.sup.2; p = 0.0006), lower urine pH (6.2 ± 0.8 vs. 6.5 ± 1.0; p = 0.01), and higher UUA (37.7 ± 18.6 vs. 32.8 ± 18.1 mg/dL; p = 0.049) and FeUA (median [interquartile range]: 6.2 [4.3-8.7] vs. 5.2 [3.6-7.0] %; p = 0.02). Among adolescents with T1D, those with hyperfiltration had higher median FeUA (8.6 [5.2-9.9] vs. 6.0 [4.2-8.3] %; p = 0.02) than those without hyperfiltration. Conclusions The adolescents with T1D enrolled in the study had higher eGFR, higher UUA and more acidic urine than the non-diabetic controls, which may have increased their risk of UUA crystallization. Adolescents with T1D and hyperfiltration had higher FeUA than those without hyperfiltration. These hypothesis-generating observations may suggest a potential pathophysiologic association between uricosuria and hyperfiltration.

Despite evidence of improved diabetes outcomes with diabetes technology such as continuous glucose monitoring (CGM) systems, insulin pumps, and hybrid closed-loop (HCL) insulin delivery systems, these devices are underutilized in clinical practice for the management of insulin-requiring diabetes. This low uptake may be the result of health care providers' (HCPs') lack of confidence or time to prescribe and manage devices for people with diabetes. We administered a survey to HCPs in primary care, pediatric endocrinology, and adult endocrinology practices in the United States. Responding HCPs expressed a need for device-related insurance coverage tools and online data platforms with integration to electronic health record systems to improve diabetes technology uptake in these practice settings across the United States. [ABSTRACT FROM AUTHOR]

OBJECTIVE: We evaluated the performance of the iLet bionic pancreas (BP) in non-Hispanic White individuals (here referred to as "Whites") and in Black, Hispanic, and other individuals (here collectively referred to as "Minorities"). RESEARCH DESIGN AND METHODS: A multicenter, randomized controlled trial evaluated glycemic management with the BP versus standard of care (SC) in 161 adult and 165 pediatric participants with type 1 diabetes over 13 weeks. RESULTS: In Whites (n = 240), the mean baseline-adjusted difference in 13-week HbA1c between the BP and SC groups was −0.45% (95% CI −0.61 to −0.29 [−4.9 mmol/mol; −6.6 to −3.1]; P < 0.001), while this difference among Minorities (n = 84) was −0.53% (−0.83 to −0.24 [−6.0 mmol/mol; −9.2 to −2.8]; P < 0.001). In Whites, the mean baseline-adjusted difference in time in range between the BP and SC groups was 10% (95% CI 7–12; P < 0.001) and in Minorities was 14% (10–18; P < 0.001). CONCLUSIONS: The BP improves glycemic control in both Whites and Minorities and offers promise in decreasing health care disparities. [ABSTRACT FROM AUTHOR]