Can Innovative Technologies Overcome HbA1c Disparity for African-American Youth with Type 1 Diabetes?

2021 ◽  
pp. 193229682110213
Author(s):  
Stuart Chalew ◽  
Alan M. Delamater ◽  
Sonja Washington ◽  
Jayalakshmi Bhat ◽  
Diane Franz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Racial Disparity ◽  
Diabetes Management ◽  
New Technology ◽  
African American Youth ◽  
Glucose Monitoring ◽  
Supportive Role

Achieving normal or near-normal glycemic control as reflected by HbA1c levels in patients with type 1 diabetes (T1D) is important for preventing the development and progression of chronic complications. Despite delineation and dissemination of HbA1c management targets and advances in insulin pharmacology, insulin delivery systems, and glucose monitoring, the majority of children with T1D do not achieve HbA1c goals. In particular, African Americans are more likely not to reach HbA1c goals and have persistently higher HbA1c than Non-Hispanic Whites. Availability of pumps and other technology has not eliminated the disparity in HbA1c. Multiple factors play a role in the persisting racial disparity in HbA1c outcome. The carefully designed application and deployment of new technology to help the patient/family and facilitate the supportive role of the diabetes management team may be able to overcome racial disparity in glycemic outcome and improve patient quality of life.

scholarly journals The role of glycemic self-control in diabetes management: based on the American Diabetes Association guidelines (2021)

2021 ◽  
pp. 286-292
Author(s):  
G. E. Runova
Keyword(s):  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
American Diabetes Association ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Self Monitoring ◽  
Diabetes Technology

Glycemic control represents an integral part of diabetes mellitus (DM) therapy. It is not surprising that diabetes technology is evolving to not only create new routes of insulin administration, but also to improve the measurement of glycemia. A significant number of new glucose monitoring systems have been launched to the market over the past 10 years. Nevertheless, only 30% of patients with type 1 diabetes and very few patients with type 2 diabetes use continuous or flash glucose monitoring. The reason for this is not only the cost and technical difficulties of continuous glucose monitoring, but also its clinical appropriateness. There is indisputable evidence that patients who receive intensified insulin therapy, especially those with type 1 diabetes, need frequent self-monitoring / continuous glucose monitoring. As for patients with type 2 diabetes receiving basal insulin and / or other antihyperglycemic therapy, the data received seem to be contradictory and uncertain. However, most of the recommendations simmer down to the need for self-monitoring of blood glucose levels in patients with type 2 diabetes. The diabetes technology section of the American Diabetes Association guidelines 2021 goes into details about the role of self-monitoring of blood glucose in diabetes management, including the need for continuous patient education on the principles and rules of self-monitoring, interpretation and practical use of the results of self-monitoring, various standards of glucometers, factors affecting the accuracy of the results. 

scholarly journals Current treatment options and challenges in patients with Type 1 diabetes: Pharmacological, technical advances and future perspectives

2021 ◽  
Author(s):  
Federico Boscari ◽  
Angelo Avogaro
Keyword(s):  
Quality Of Life ◽  
Type 1 Diabetes ◽  
Glucose Control ◽  
Diabetes Management ◽  
Treatment Options ◽  
Artificial Pancreas ◽  
Glucose Monitoring ◽  
Current Treatment

AbstractType 1 diabetes mellitus imposes a significant burden of complications and mortality, despite important advances in treatment: subjects affected by this disease have also a worse quality of life-related to disease management. To overcome these challenges, different new approaches have been proposed, such as new insulin formulations or innovative devices. The introduction of insulin pumps allows a more physiological insulin administration with a reduction of HbA1c level and hypoglycemic risk. New continuous glucose monitoring systems with better accuracy have allowed, not only better glucose control, but also the improvement of the quality of life. Integration of these devices with control algorithms brought to the creation of the first artificial pancreas, able to independently gain metabolic control without the risk of hypo- and hyperglycemic crisis. This approach has revolutionized the management of diabetes both in terms of quality of life and glucose control. However, complete independence from exogenous insulin will be obtained only by biological approaches that foresee the replacement of functional beta cells obtained from stem cells: this will be a major challenge but the biggest hope for the subjects with type 1 diabetes. In this review, we will outline the current scenario of innovative diabetes management both from a technological and biological point of view, and we will also forecast some cutting-edge approaches to reduce the challenges that hamper the definitive cure of diabetes.

scholarly journals Functional data analysis and prediction tools for continuous glucose-monitoring studies

2020 ◽  
pp. 1-10
Author(s):  
Emrah Gecili ◽  
Rui Huang ◽  
Jane C. Khoury ◽  
Eileen King ◽  
Mekibib Altaye ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Functional Data ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Patient Specific ◽  
Prediction Errors ◽  
Medical Monitoring

Abstract Introduction: To identify phenotypes of type 1 diabetes based on glucose curves from continuous glucose-monitoring (CGM) using functional data (FD) analysis to account for longitudinal glucose patterns. We present a reliable prediction model that can accurately predict glycemic levels based on past data collected from the CGM sensor and real-time risk of hypo-/hyperglycemic for individuals with type 1 diabetes. Methods: A longitudinal cohort study of 443 type 1 diabetes patients with CGM data from a completed trial. The FD analysis approach, sparse functional principal components (FPCs) analysis was used to identify phenotypes of type 1 diabetes glycemic variation. We employed a nonstationary stochastic linear mixed-effects model (LME) that accommodates between-patient and within-patient heterogeneity to predict glycemic levels and real-time risk of hypo-/hyperglycemic by creating specific target functions for these excursions. Results: The majority of the variation (73%) in glucose trajectories was explained by the first two FPCs. Higher order variation in the CGM profiles occurred during weeknights, although variation was higher on weekends. The model has low prediction errors and yields accurate predictions for both glucose levels and real-time risk of glycemic excursions. Conclusions: By identifying these distinct longitudinal patterns as phenotypes, interventions can be targeted to optimize type 1 diabetes management for subgroups at the highest risk for compromised long-term outcomes such as cardiac disease or stroke. Further, the estimated change/variability in an individual’s glucose trajectory can be used to establish clinically meaningful and patient-specific thresholds that, when coupled with probabilistic predictive inference, provide a useful medical-monitoring tool.

Impact of Real-Time CGM Data Sharing on Quality of Life in the Caregivers of Adults and Children with Type 1 Diabetes

2020 ◽  
pp. 193229682097842
Author(s):  
William H. Polonsky ◽  
Addie L. Fortmann
Keyword(s):  
Quality Of Life ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Health Outcomes ◽  
Real Time ◽  
Data Sharing ◽  
Diabetes Management ◽  
Health Benefits

Background: To examine caregivers’ experiences with real-time continuous glucose monitoring (RT-CGM) data sharing and its impact on quality of life (QoL) and health outcomes. Methods: Parents of children with type 1 diabetes (T1D) ( N = 303) and spouses/partners of T1D adults ( N = 212) using the Dexcom G5 Mobile or G6 RT-CGM system and who were actively following their T1Ds’ RT-CGM data completed a survey examining their perceived value of data sharing, the impact of sharing on their own QoL and their child/partner’s health, and how they used RT-CGM data to support their T1Ds’ diabetes management. Regression analyses examined whether their actions were linked to reported changes in QoL and health outcomes. Results: Respondents were predominantly non-Hispanic White (91.1% parents; 88.7% partners), female (78.2% parents; 54.7% partners), and college-educated (65.3% parents; 61.8% partners). The majority reported that data sharing had enhanced hypoglycemic confidence (97.7% parents; 98.1% partners), overall well-being (60.4% parents; 63.2% partners), and sleep quality (78.0% parents; 61.3% partners). Of note, three positive caregiver actions were broadly consistent and significant predictors of QoL and health benefits for both parents and partners: celebrating success related to glycemic control, providing encouragement when glycemic control is challenging, and teamwork discussions about how the caregiver should respond to out-of-range values. Conclusions: RT-CGM data sharing was associated with a range of QoL and health benefits for caregivers. Degree of benefits was influenced by the collaborative actions taken by caregivers to support their child’s or partner’s diabetes management. To determine the most effective strategies for collaborative data sharing, longitudinal trials are needed.

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