Journal of Diabetes Science and Technology最新文献

Background: The number of pregnancies affected by gestational diabetes mellitus (GDM) is growing. With the increased use of smartphones and predictive modeling, a mobile health (mHealth) solution could be developed to improve care and management of GDM while streamlining care through risk stratification.

Methods: A user-centered mHealth tool was designed from ethnographic observations and 11 semi-structured interviews (six health care professionals [HCPs] and five women with GDM), followed by iterative changes and evaluation from three feedback groups with 31 participants (17 HCPs, 14 researchers) and 13 questionnaires with women with GDM.

Results: "MyGDM" includes a clinical dashboard that centralizes the clinic's patients, highlighting off-target blood glucose and predicting the need for pharmacological intervention. It is linked with a patient-facing app that includes structured education, culturally inclusive language options, and meal ideas. Through the feedback sessions, iterative changes were made around visualization and patient safety, and participants were positive toward the potential user experience. In the 13 questionnaires with women with GDM, 100% said it would fit into their lifestyle and help them manage GDM. Educational resources and the "request a call" functions were well received with 61.5% (8/13) and 69.2% (9/13) saying they were very likely or likely to use these, respectively.

Conclusion: A user-centered mHealth tool consisting of a clinical dashboard linked with a patient-facing app for GDM care and management has been designed. Evaluation of the interactive design by end users was positive and showed that it met their needs.

Background: Managing glycemia during Ramadan is challenging for individuals with type 1 diabetes (T1D) due to prolonged fasting and altered eating patterns. While many are exempt from fasting, some choose to fast, necessitating careful monitoring. The glycemia risk index (GRI) is valuable for assessing glycemic quality and interpreting continuous glucose monitoring (CGM) data to identify individuals needing closer clinical attention. This study investigates the effects of Ramadan fasting on glycemic control in T1D, focusing on GRI and its components for hypoglycemia (CHypo) and hyperglycemia (CHyper).

Method: An ambispective study involved 186 individuals with T1D using intermittent scanning CGM (isCGM). Data were retrospectively collected for one month before Ramadan and prospectively during and one month after Ramadan. Clinical, metabolic, and glycemic data were collected, with GRI calculated alongside its components.

Results: During Ramadan, GRI improved by 54.6% (from 56.4 to 25.6), CHypo decreased by 60% (from 6 to 2.4), and CHyper dropped by 40.5% (from 21 to 12.5). However, these benefits were temporary, as glycemic measures increased after Ramadan, reflecting a return to pre-Ramadan patterns once normal routines resumed. No participants were admitted for diabetes emergencies during Ramadan. Adolescents and patients on insulin pumps had more favorable outcomes. GRI and its components significantly correlated with other CGM metrics, with these relationships maintained during and after Ramadan.

Conclusions: Ramadan fasting significantly improved GRI and its components in individuals with T1D. Incorporating GRI as a novel metric alongside classical CGM metrics could enhance glycemic control, highlighting the need for personalized diabetes management strategies.

Introduction: Considerable efforts to standardize continuous glucose monitoring (CGM) have occurred in recent years. The aim was to perform an analysis of clinical studies in clinicaltrials.gov to evaluate trends in CGM endpoint adoption.

Methods: Clinicaltrials.gov was searched for studies of drugs, devices and combination products containing CGM terms posted from 2012 to 2023. 1269 studies were returned and 954 were excluded. 315 studies were divided into two periods (P1 [2012-2017] and P2 [2018-2023]) and differences analyzed using descriptive statistics and two-tailed t tests.

Results: There was a significant 60.3% increase in total clinical studies from P1 (121) to P2 (194). Phase 2 and Phase 3 Studies both saw significant increases of 125.8 and 169.2%, respectively, in P2. Adult-only studies predominated in both periods, with a 40.4% increase in P2. Studies that included pediatric populations, although smaller in number, increased significantly. Most studies were nonindustry-funded, and studies in this category saw a significant 80.0% increase in P2. However, industry-only funded studies also increased significantly by 78.4% in P2 in the same period. Studies of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) increased by 55.8% and 26.9%, respectively, but increases were not statistically significant. Studies of nondiabetes-related indications did increase significantly (233.3%). 27.6% of studies used CGM-derived metrics as primary endpoints (PE). Studies that used time in range (TIR) increased by 222.4% in P2, which was significant. Conversely studies that used mean amplitude of glycemic excursions (MAGE) decreased significantly by 71.3%.

Conclusion: Our data provide evidence of significant increases in the application of CGM endpoints in clinical studies in the last six years, including studies with TIR as the PE. Increases have been driven largely by academia, but our data show that industry is starting to follow suit. The significant increase in studies that included pediatrics is encouraging.

Background: The glycemic characterization of congenital hyperinsulinism (HI), a rare disease causing severe hypoglycemia in childhood, is incomplete. Continuous glucose monitoring (CGM) offers deep glycemic phenotyping to understand disease burden and individualize patient care. Typically, CGM has been restricted to severe HI only, with performance being described in short-term, retrospective studies. We have described CGM-derived phenotyping in a prospective, unselected national cohort providing comprehensive baseline information for future therapeutic trials.

Methods: Glycemic frequency and trends, point accuracy, and patient experiences were drawn from a prospective, nationwide, observational study of unselected patients with persistent HI using the Dexcom G6 CGM device for 12 months as an additional monitoring tool alongside standard of care self- monitoring blood glucose (SMBG).

Findings: Among 45 patients with HI, mean age was six years and 53% carried a genetic diagnosis. Data confirmed higher risk of early morning (03:00-07:00 h) hypoglycemia throughout the study period and demonstrated no longitudinal reduction in hypoglycemia with CGM use. Device accuracy was suboptimal; 17 500 glucose levels paired with SMBG demonstrated mean absolute relative difference (MARD) 25% and hypoglycemia detection of 40%. Patient/parent dissatisfaction with CGM was high; 50% of patients discontinued use, citing inaccuracy and pain. However, qualitative feedback was also positive and families reported improved understanding of glycemic patterns to inform changes in behavior to reduce hypoglycemia.

Interpretation: This comprehensive study provides unbiased insights into glycemic frequency and long-term trends among patients with HI; such data are likely to influence and inform clinical priorities and future therapeutic trials.

Background: While continuous glucose monitoring (CGM) has transformed the care of people with diabetes (PWD) in the ambulatory setting, there continue to be significant barriers to access. With CGM on the horizon in the acute care setting, it is important to consider the potential for this shift to improve ambulatory CGM access to those at the highest risk of morbidity and mortality.

Methods: In this commentary, we review the existing literature on the specific barriers to CGM access for individuals with diabetes in the United States including racial disparities, provider bias, cost and shortage of specialty diabetes care. Key areas explored include the importance of CGM in diabetes management, the consequences of disparities in access to CGM, and leveraging the inpatient setting to promote equitable care and better outcomes for PWD.

Results: We present a vision for a new care model, which leverages the transition of care from the hospital to successfully incorporate CGM into the discharge plan.

Conclusions: Given that CGM utilization is associated with improved outcomes and reduced rates of hospitalization and emergency department visits, a care model that facilitates CGM access upon transition from inpatient to ambulatory care can enhance health equity and quality of life for people with diabetes.

Objectives: Time in range (TIR, 70-180 mg/dL) is an established marker of glycemic control. More recently, time in tight range (TTR, 70-140 mg/dL) has been proposed as well. The aim of this study was to examine the relationship between TIR, TTR, and HbA1c in youth and young adults with type 1 diabetes (T1D) in the German/Austrian/Luxembourgian/Swiss Diabetes Prospective Follow-up (DPV) registry.

Methods: Data of youth and young adults aged ≤25 years with T1D for >3 months, documented in the DPV registry between 2019 and 2022 were analyzed. The most recent available HbA1c and corresponding continuous glucose monitoring (CGM) profiles in the 12 preceding weeks with at least 80% completeness were included. Associations were investigated using correlation and adjusted regression models.

Results: 1901 individuals (median age 14.0 years [IQR 10.4-16.9]) were included in the analysis. TIR and TTR correlated strongly, r = 0.965 (95% CI [0.962, 0.968]), P < .001. TTR estimates predicted from TIR were significantly higher in the group with high coefficient of variation (CV group ≥ 36%), P < .001. Correlations between TIR or TTR and HbA1c were both strong, r = -0.764 (95% CI [-0.782, -0.745]) and r = -0.777 (95% CI [-0.795, -0.759]), both P < .001, with no significant difference (P = .312) However, adjusted regression models indicated a slightly better fit for the prediction of HbA1c from TIR compared with TTR.

Conclusions: Based on large, real-world data from a multinational registry, TIR and TTR correlated strongly, and both showed a good prediction of HbA1c. TTR estimates predicted from TIR were significantly higher in people with high glucose variability (CV).

Metrics derived from continuous glucose monitoring (CGM) systems are often discordant between systems. A major cause is that CGM systems are not standardized; they use various algorithms and calibration methods, leading to discordant CGM readings across systems. This discordance can be addressed by standardizing CGM performance assessments: If manufacturers aim their CGM systems at the same target, then CGM readings will align across systems. This standardization should include the comparator device, sample origin, and study procedures. With better aligned CGM readings, CGM-derived metrics will subsequently also align better between systems.

Rapid technological advancements, such as artificial intelligence, wearable technologies, and telehealth with remote monitoring, are transforming continuous education for health care providers (HCPs) in diabetes management. These technologies improve patient care and necessitate innovative educational approaches to prepare HCPs for clinical integration. Digital education offers real-time, scalable, and cost-effective solutions, especially in areas with health care workforce shortages. However, the effect of digital education on HCPs' knowledge, skills, attitudes, and patient outcomes remains under-researched and necessitates further study. As technologies advance, achieving precision in diabetes continuous education becomes feasible. The 2024 ADA Standards of Care emphasize early adoption of advanced technologies and proficiency among HCPs. This commentary explores transformative trends, discussing limitations and proposing solutions to revolutionize continuous education in diabetes care.