scholarly journals Continuous glucose monitoring reduces pubertal hyperglycemia of type 1 diabetes

2020 ◽  
Vol 33 (7) ◽  
pp. 865-872
Author(s):  
Benjamin Udoka Nwosu ◽  
Shamima Yeasmin ◽  
Sanaa Ayyoub ◽  
Shwetha Rupendu ◽  
Tony R. Villalobos-Ortiz ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Longitudinal Change ◽  
Controlled Study ◽  
Pubertal Status ◽  
Male Age

AbstractBackgroundPhysiologic hyperglycemia of puberty is a major contributor to poor glycemic control in youth with type 1 diabetes (T1D). This study’s aim was to determine the effectiveness of continuous glucose monitoring (CGM) to improve glycemic control in pubertal youth with T1D compared to a non-CGM cohort after controlling for age, sex, BMI, duration, and insulin delivery methodology. The hypothesis is that consistent CGM use in puberty improves compliance with diabetes management, leading to increased percentage (%) time in range (TIR70–180 mg/dL) of glycemia, and lowering of HbA1c.MethodsA longitudinal, retrospective, case-controlled study of 105 subjects consisting of 51 T1D controls (60.8% male) age 11.5 ± 3.8 y; and 54 T1D subjects (48.1% male) age 11.1 ± 5.0 y with confirmed CGM use for 12 months. Pubertal status was determined by Tanner staging. Results were adjusted for baseline HbA1c and diabetes duration.ResultsHbA1c was similar between the controls and the CGM group at baseline: 8.2 ± 1.1% vs 8.3 ± 1.2%, p=0.48 respectively; but was significantly lower in the CGM group 12 months later, 8.2 ± 1.1% vs. 8.7 ± 1.4%, p=0.035. Longitudinal change in HbA1c was similar in the prepubertal cohort between the control- and CGM groups: −0.17 ± 0.98% vs. 0.38 ± 1.5%, p=0.17. In contrast, HbA1c increased with advancing age and pubertal status in the pubertal controls but not in the pubertal CGM group: 0.55 ± 1.4 vs −0.22 ± 1.1%, p=0.020. Percent TIR was inversely related to HbA1c in the CGM group, r=-0.6, p=0.0004, for both prepubertal and pubertal subjects.ConclusionsCGM use significantly improved glycemic control in pubertal youth with T1D compared to non-CGM users.

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.

scholarly journals Cutaneous Reactions to Continuous Glucose Monitoring and Continuous Subcutaneous Insulin Infusion Devices in Type 1 Diabetes Mellitus

2020 ◽  
pp. 193229682091889 ◽  
Author(s):  
Rachel S. Rigo ◽  
Laura E. Levin ◽  
Donald V. Belsito ◽  
Maria C. Garzon ◽  
Rachelle Gandica ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Continuous Subcutaneous Insulin Infusion ◽  
Insulin Infusion ◽  
Diabetes Management ◽  
Demographic Data ◽  
Glucose Monitoring ◽  
Subcutaneous Insulin ◽  
Cutaneous Reactions

Background: Continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) are the standard of care for type 1 diabetes in children. There is little reported on device-related skin complications and treatment options. This study documents cutaneous reactions to CGM and CSII devices in children and young adults with type 1 diabetes. Methods: One hundred and twenty-one subjects (3-25 years) with type 1 diabetes and CGM and/or CSII use were recruited over a three-month period from the Naomi Berrie Diabetes Center at Columbia University Irving Medical Center. A five-question survey was completed for each subject detailing demographic data, diabetes management, and device-related skin complications. Results: Sixty percent of subjects reported skin complications related to CGM and/or CSII use. Terms most frequently used to describe cutaneous reactions were “red,” “itchy,” “painful,” and “rash.” Subjects who used both CGM and CSII were more likely to report skin problems than those who used only CSII (odds ratio 2.9, [95% confidence interval: 1.2-6.7]; P = .015). There were no associations between skin complications and sex or race/ethnicity. Twenty-two percent of subjects with adverse skin event(s) discontinued use of a device due to their skin problem. Seven percent were evaluated by a dermatologist. Eighty-one percent used a range of products to treat their symptoms, with variable perceived clinical outcomes. Conclusions: Skin complications related to CSII or CGM devices are commonly reported in pediatric patients with type 1 diabetes and may lead to interruption or discontinuation of device use. Future studies are needed to elucidate the causes of these reactions and determine the best methods for prevention.

scholarly journals Technology for Augmenting Type 1 Diabetes Mellitus Management

2019 ◽  
Vol 24 (2) ◽  
pp. 99-106
Author(s):  
Michelle Condren ◽  
Samie Sabet ◽  
Laura J. Chalmers ◽  
Taylor Saley ◽  
Jenna Hopwood
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Insulin Pump ◽  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Diabetes Mellitus Management

Type 1 diabetes mellitus has witnessed significant progress in its management over the past several decades. This review highlights technologic advancements in type 1 diabetes management. Continuous glucose monitoring systems are now available at various functionality and cost levels, addressing diverse patient needs, including a recently US Food and Drug Administration (FDA)–approved implantable continuous glucose monitoring system (CGMS). Another dimension to these state-of-the-art technologies is CGMS and insulin pump integration. These integrations have allowed for CGMS-based adjustments to basal insulin delivery rates and suspension of insulin delivery when a low blood glucose event is predicted. This review also includes a brief discussion of upcoming technologies such as patch-based CGMS and insulin-glucagon dual-hormonal delivery.

scholarly journals Improved Glycemic Control in Poorly Controlled Patients with Type 1 Diabetes Using Real-Time Continuous Glucose Monitoring

Diabetes Care ◽  
2006 ◽  
Vol 29 (12) ◽  
pp. 2730-2732 ◽  
Author(s):  
D. Deiss ◽  
J. Bolinder ◽  
J.-P. Riveline ◽  
T. Battelino ◽  
E. Bosi ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring
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