Diabetes technology & therapeutics最新文献

Background: We assessed real-life glycemic outcomes and predictors of composite measures of optimal glycemic control in children and adolescents with type 1 diabetes (T1D) during their initial 12 months of the MiniMed™ 780G use. Methods: This prospective observational multicenter study collected demographic, clinical, and 2-week 780G system data at five time points. Optimal glycemic control was defined as a composite glycemic control (CGC) score requiring the attainment of four recommended continuous glucose monitoring (CGM) targets, as well as the glycemia risk index (GRI) of hypoglycemia and hyperglycemia and composite CGM index (COGI). Outcome measures included longitudinal changes in multiple glycemic parameters and CGC, GRI, and COGI scores, as well as predictors of these optimal measures. Results: The cohort included 93 children, 43% girls, with a median age of 15.1 years (interquartile range [IQR] 12.9,17.0). A longitudinal analysis adjusted for age and socioeconomic index yielded a significant improvement in glycemic control for the entire cohort (p_time < 0.001) after the transition to 780G. The mean hemoglobin A1c (HbA1c) (SE) was 8.65% (0.12) at baseline and dropped by >1% after 1 year to 7.54% (0.14) (p_time < 0.001). Optimal glycemic control measures improved at 12 months post 780G; CGC improved by 5.6-fold (P < 0.001) and was attained by 24% of the participants, the GRI score improved by 10-fold (P = 0.009) and was achieved by 10% of them, and the COGI improved by 7.6-fold (P < 0.001) and was attained by 20% of them. Lower baseline HbA1c levels and increased adherence to Advanced Hybrid Closed-Loop (AHCL) usage were predictors of achieving optimal glycemic control. Conclusions: The AHCL 780G system enhances glycemic control in children and adolescents with T1D, demonstrating improvements in HbA1c and CGM metrics, albeit most participants did not achieve optimal glycemic control. This highlights yet ongoing challenges in diabetes management, emphasizing the need for continued proactive efforts on the part of health care professionals, youth, and caregivers.

Objectives: Background investigated whether Ramadan, a yearly religious fasting lasting for 1 month, could challenge the metabolic control obtained under a hybrid closed-loop (HCL) therapy in patients living with type 1 diabetes (T1D). Material and Method: This real-life prospective study involved 20 patients with T1D and moderate to high-risk score of adverse events at baseline. We compared continuous glucose monitoring (CGM) parameters under HCL therapy 1 month before and during the Ramadan fasting month. The main outcome was the evolution of the percentage of time-in-range (TIR, 70-180 mg/dL) between the two time points, and secondary outcomes were the evolution of other CGM parameters and frequency of acute metabolic events. Results: We observed no statistical difference regarding TIR (mean±SD) (63 ± 11% during fasting vs. 62 ± 12% before) as well as for other parameters including time spent under 70 mg/dL (1.1 ± 1.0% vs. 1.5 ± 1.3%) and percentage of HCL use (93 ± 5% vs. 94 ± 5%). No acute metabolic event was observed during fasting under HCL. Results were homogenous across baseline risk score groups.

Objective: To evaluate the psychometric properties of a patient-reported outcome measure, the Automated Insulin Delivery-Benefits and Burdens Scale (AID-BBS), which was designed to assess benefits and burdens of AID use in adults with type 1 diabetes (T1D). The measure was hypothesized to have validity, reliability, and clinical utility for predicting likelihood of continued use of an AID system. Research Design and Methods: A total of 217 adults with T1D (ages from 18 to 82 years) who were enrolled in an AID system research trial completed AID-BBS items at study midpoint (6 weeks) and at the end of the trial (13 weeks). Data were collected on pre-post glycemic outcomes. Participants completed other patient-reported psychosocial outcome measures (e.g., emotional well-being, diabetes distress, attitudes toward diabetes technology, diabetes treatment satisfaction) at Week 13. Likelihood of continued device use was assessed with three items at 13 weeks. Results: Exploratory factor analysis supported a one-factor structure for each subscale (15-item benefit and 9-item burden subscale) when evaluated separately. Convergent, discriminant, and predictive validity, internal consistency, and test-retest reliability were supported. Benefit and burden subscales at week 6 predicted usage intention above and beyond device impact on glycemic outcomes, also controlling for baseline glycemic outcomes. Conclusion: Findings support the AID-BBS as a psychometrically valid, reliable, and useful instrument for assessing burdens and benefits associated with AID system use in adults with T1D. The measure can be used to help health care providers set realistic expectations and proactively address modifiable burdens. Clinical Trial Registration Number: NCT04200313.

Aims/Hypotheses: To investigate the frequency and characteristics of partial remission in Swedish children with type 1 diabetes and whether the insulin delivery method, that is, continuous subcutaneous insulin infusion (CSII) or multiple daily injections (MDIs), affects incidence and duration of this period, 2007-2011. Factors that increase the proportion of subjects who enter partial remission and extend this period can improve long-term metabolic control and reduce the risk of severe hypoglycemia, improve quality of life, and, in the long run, reduce late complications. Methods: Longitudinal data from 2007 to 2020 were extracted from the Swedish National Quality Register (SWEDIABKIDS) with all reported newly diagnosed children. Data on C-peptide from the participants in the Better Diabetes Diagnosis study from 2007 to 2010 were used. The definition of partial remission was insulin dose-adjusted HbA1c: HbA1c (%) + [4 × total daily insulin dose (U/kg/day)] ≤9. Results: Of the 3887 patients, 56% were boys. More boys than girls were in partial remission throughout the follow-up period until 24 months after diabetes onset. Fewer children 0-6 years old had partial remission at 3 and 12 months but not at 24 months compared with older age-groups. A larger proportion of patients using CSII at 12 and 24 months remained in partial remission compared with those with MDI (37% vs. 33%, P = 0.02 and 31% vs. 27%, P = 0.01, respectively). The level of C-peptide was higher in the group with partial remission and mean HbA1c was lower (both P < 0.001). Partial remission at 12 months after diabetes onset was associated with CSII (odds ratio [OR]: 1.39, confidence interval [CI]:1.13, 1.71), shorter diabetes duration (OR: 0.80, CI: 0.76, 0.84), and male sex (OR: 1.23, CI: 1.04, 1.46). Conclusions/Interpretation: Insulin through MDI, longer duration of diabetes, and female sex were associated with lower frequency of partial remission. Use of CSII seems to contribute to longer partial remission among Swedish children with type 1 diabetes.

Background and Aims: Guidelines now recommend inpatient continuous glucose monitor (CGM) use with confirmatory blood glucose measurements. However, the Food and Drug Administration has not yet officially approved CGM for inpatient use in large part because its accuracy has not been established in this setting. We tested the accuracy of the Dexcom G6 (G6) in 28 adults on an insulin infusion in a medical-surgical intensive care unit with 1064 matched CGM and arterial point-of-care pairs. Methods: The participants were on average 57.29 (SD 2.39) years, of whom 13 had a prior diagnosis of diabetes and 14 were admitted for a surgical diagnosis. The first 19 participants received the G6 without calibration and had a mean absolute relative difference (MARD) of 13.19% (IQR 5.11, 19.03) across 659 matched pairs, which just meets the critical care expert recommendation of MARD <14%. We then aimed to improve accuracy for the subsequent 9 participants using a calibration protocol. Results: The MARD for calibrated participants was 9.65% (3.03, 13.33), significantly lower than for uncalibrated participants (P < 0.001). Calibration also demonstrated excellent safety with 100% of values within the Clarke Error Grid zones A and B compared with 99.07% without calibration. Our protocol achieved the lowest MARD and safest CEG profile in the critical care setting and well exceeds the critical care expert recommendations. Our large sample of heterogenous critically ill patients also reached comparable accuracy to the MARD of 9% for G6 in outpatients. We believe our calibration protocol will allow G6 to be used with sufficient accuracy in inpatients.

Background and Aim: Glucagon-like peptide-1 receptor agonists (GLP-1 RA) therapy provides glycemic benefits to individuals with type 2 diabetes (T2D). However, the effects of GLP-1 RA therapy in combination with FreeStyle Libre systems (FSL) are unknown. This study aimed to compare changes in hemoglobin A1c (HbA1c) between people acquiring GLP-1 with FSL (GLP-1+FSL) versus GLP-1 without FSL (GLP-1). Methods: This real-world study used Optum's de-identified Market Clarity Data, a linked electronic health records (EHR)-claims database, and included adults with T2D and HbA1c ≥8% who acquired their first GLP-1 RA medication between 2018 and 2022. GLP-1+FSL subjects acquired their first FSL within ±30 days of their first GLP-1 acquisition. Cohorts were matched 1:5 on baseline insulin therapy, age, sex, baseline HbA1c, and GLP-1 type. Paired changes in HbA1c were compared between unmatched and matched groups at 6 months. Results: The study included 24,724 adults in the unmatched cohort (GLP-1+FSL, n = 478; GLP-1, n = 24,246). The matched cohort included 478 GLP-1+FSL users and 2,390 GLP-1 users: mean age 53.5 ± 11.8 and 53.5 ± 11.3 years, HbA1c 10.25 ± 1.68% and 10.22 ± 1.69%, respectively. HbA1c reduction was greater in the GLP-1+FSL group compared with the GLP-1 group in the unmatched cohort (-2.43% vs. -1.73%, difference 0.70%, P < 0.001, respectively) and in the matched cohort (-2.43% vs. -2.06%, difference 0.37%, P < 0.001). GLP-1+FSL vs. GLP-1 treatment was associated with greater HbA1c reduction in the intensive insulin (-2.32% vs. -1.50%), nonintensive insulin (-2.50% vs. -1.74%), and noninsulin group (-2.46% vs. -1.78%), as well as in patients using semaglutide (-2.73% vs. -1.92%) and dulaglutide (-2.45% vs. -1.71%) GLP-1 RA, all P < 0.001. Conclusions: Adults with suboptimally controlled T2D, initiating GLP-1 RA with FreeStyle Libre, had greater improvement in HbA1c compared with those treated with GLP-1 RA only. These results suggest an additional glycemic benefit of FSL when used with a GLP-1 RA in T2D treatment.

In the last decade, technology developed by people with diabetes and their loved ones has added to the options for diabetes management. One such example is that of automated insulin delivery (AID) algorithms, which were created and shared as open source by people living with type 1 diabetes (T1D) years before commercial systems were first available. Now, numerous options for commercial systems exist in some countries, yet tens of thousands of people with diabetes are still choosing Open-Source AID (OS-AID), previously called "do-it-yourself" (DIY) systems, which are noncommercial versions of these open-source AID systems. In this article, we provide point and counterpoint perspectives regarding (1) safety and efficacy, (2) regulation and support, (3) user choice and flexibility, (4) access and affordability, and (5) patient and provider education, for open source and commercial AID systems. The perspectives reflected here include that of a person living with T1D who uses and has developed OS-AID systems, a physician-researcher based in the United States who conducts clinical trials to support development of commercial AID systems and supports people with diabetes using all types of AID, and an endocrinologist with T1D who uses both systems and treats people with diabetes using all types of AID.

Objective: To predict hypoglycemia and hyperglycemia risk during and after activity for adolescents with type 1 diabetes (T1D) using real-world data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study. Methods: Adolescents with T1D (n = 225; [mean ± SD] age = 14 ± 2 years; HbA1c = 7.1 ± 1.3%; T1D duration = 5 ± 4 years; 56% using hybrid closed loop), wearing continuous glucose monitors (CGMs), logged 3738 total activities over 10 days. Repeated Measures Random Forest (RMRF) and Repeated Measures Logistic Regression (RMLR) models were used to predict a composite risk of hypoglycemia (<70 mg/dL) and hyperglycemia (>250 mg/dL) within 2 h after starting exercise. Results: RMRF achieved high precision predicting composite risk and was more accurate than RMLR Area under the receiver operating characteristic curve (AUROC 0.737 vs. 0.661; P < 0.001). Activities with minimal composite risk had a starting glucose between 132 and 160 mg/dL and a glucose rate of change at activity start between -0.4 and -1.9 mg/dL/min. Time <70 mg/dL and time >250 mg/dL during the prior 24 h, HbA1c level, and insulin on board at activity start were also predictive. Separate models explored factors at the end of activity; activities with glucose between 128 and 133 mg/dL and glucose rate of change between 0.4 and -0.6 mg/dL/min had minimal composite risk. Conclusions: Physically active adolescents with T1D should aim to start exercise with an interstitial glucose between 130 and 160 mg/dL with a flat or slightly decreasing CGM trend to minimize risk for developing dysglycemia. Incorporating factors such as historical glucose and insulin can improve prediction modeling for the acute glucose responses to exercise.