Use of Continuous Glucose Monitoring Can Address Patient Fears and Facilitate Improved Glycaemic Management

2010 ◽  
Vol 7 (2) ◽  
pp. 88
Author(s):  
Jeff Unger ◽  
Chris Parkin ◽  
◽  
Keyword(s):  
Glycaemic Control ◽  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Severe Hypoglycaemia ◽  
Glucose Monitoring ◽  
Monitoring Strategies ◽  
Increased Risk ◽  
Patients At Risk ◽  
Intensively Managed ◽  
Chronic Hyperglycaemia

Effective diabetes management can delay or prevent many of the complications of diabetes. Achieving optimal glycaemic control, however, often requires intensive insulin treatment, which is associated with an increased risk of severe hypoglycaemia. Many intensively managed patients are reluctant to follow and/or adjust their insulin regimens as needed because of fear of hypoglycaemia. This lack of adherence can result in exposure to chronic hyperglycaemia, oxidative stress and long-term complications. Severe hypoglycaemia can be prevented through vigilance in identifying patients at risk, using appropriate medications and medication regimens, and effective glucose monitoring strategies and technologies. This article reviews some evidence relevant to hypoglycaemia in intensively managed patients and discusses how tools such as continuous glucose monitoring (CGM) can help patients overcome their fear of hypoglycaemia and safely achieve optimal glycaemic control.

scholarly journals Role of continuous subcutaneous glucose monitoring in intensive care

2013 ◽  
Vol 154 (27) ◽  
pp. 1043-1048 ◽  
Author(s):  
Gábor Marics ◽  
Levente Koncz ◽  
Anna Körner ◽  
Borbála Mikos ◽  
Péter Tóth-Heyn
Keyword(s):  
Intensive Care ◽  
Glycaemic Control ◽  
Intensive Care Units ◽  
Continuous Glucose Monitoring ◽  
Pediatric Population ◽  
Glucose Monitoring ◽  
Tissue Perfusion ◽  
Close Monitoring ◽  
Beneficial Effects ◽  
Increased Risk

Critical care associated with stress hyperglycaemia has gained a new view in the last decade since the demonstration of the beneficial effects of strong glycaemic control on the mortality in intensive care units. Strong glycaemic control may, however, induce hypoglycaemia, resulting in increased mortality, too. Pediatric population has an increased risk of hypoglycaemia because of the developing central nervous system. In this view there is a strong need for close monitoring of glucose levels in intensive care units. The subcutaneous continuous glucose monitoring developed for diabetes care is an alternative for this purpose instead of regular blood glucose measurements. It is important to know the limitations of subcutaneous continuous glucose monitoring in intensive care. Decreased tissue perfusion may disturb the results of subcutaneous continuous glucose monitoring, because the measurement occurs in interstitial fluid. The routine use of subcutaneous continuous glucose monitoring in intensive care units is not recommended yet until sufficient data on the reliability of the system are available. The Medtronic subcutaneous continuous glucose monitoring system is evaluated in the review partly based on the authors own results. Orv. Hetil., 2013, 154, 1043–1048.

EXPRESS: Monitoring Motherhood: monitoring and optimising glycaemia in women with pre-existing diabetes in pregnancy

2021 ◽  
pp. 000456322110358
Author(s):  
Claire L Meek
Keyword(s):  
Glycaemic Control ◽  
Continuous Glucose Monitoring ◽  
Multiple Pregnancy ◽  
Glucose Monitoring ◽  
Insulin Dosage ◽  
Diabetes In Pregnancy ◽  
Short Term ◽  
Increased Risk ◽  
Mother And Child ◽  
In Pregnancy

Despite recent advances in care, women with diabetes in pregnancy are still at increased risk of multiple pregnancy complications. Offspring exposed to hyperglycaemia in utero also experience long-term health sequelae affecting neurocognitive and cardiometabolic status. Many of these adverse consequences can be prevented or ameliorated with good medical care, specifically to optimise glycaemic control. The accurate assessment of glycaemia in pregnancy is therefore vital to safeguard the health of mother and child. However, there is no consensus about the best method of monitoring glycaemic control in pregnancy. Short-term changes in insulin dosage and lifestyle, with altered appetite, insulin sensitivity and red cell turnover create difficulties in interpretation of standard laboratory measures such as HbA1c. The ideal marker would provide short-term feedback on daily or weekly glycaemic control, with additional capability to predict pregnancies at high risk of suboptimal outcomes. Several novel biochemical markers are available which allow assessment of dynamic changes in glycaemia over weeks rather than months. Continuous glucose monitoring devices have advanced in accuracy and provide new opportunities for robust assessment of glycaemia in pregnancy. Recent work from the continuous glucose monitoring in pregnant women with type 1 diabetes trial (CONCEPTT) has provided information about the ability of different markers of glycaemia to predict pregnancy outcomes. The aim of this review is to summarise the care for women with pre-existing diabetes in pregnancy, and to highlight the important role of glycaemic monitoring in pregnancy.

scholarly journals Universal Subsidized Continuous Glucose Monitoring Funding for Young People With Type 1 Diabetes: Uptake and Outcomes Over 2 Years, a Population-Based Study

2021 ◽  
Author(s):  
Stephanie R Johnson ◽  
Deborah J Holmes-Walker ◽  
Melissa Chee ◽  
Arul Earnest ◽  
Timothy W Jones ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycaemic Control ◽  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Population Based ◽  
Insulin Regimen ◽  
Economic Analyses ◽  
Almost All

<b>Objective:</b> Continuous glucose monitoring (CGM) is increasingly used in type 1 diabetes management however funding models vary. This study determined the uptake rate and glycaemic outcomes following a change in national health policy to introduce universal subsidised CGM funding for people with type 1 diabetes aged < 21 years. <p><b>Research Design and Methods:</b> Analysis of longitudinal data from 12 months prior to subsidy until 24 months after. Measures and outcomes included age, diabetes duration, HbA1c, episodes of diabetic ketoacidosis and severe hypoglycaemia, insulin regimen, CGM uptake and percentage CGM use. Two data sources were used: the Australasian Diabetes Database Network (ADDN) registry (a prospective diabetes database) and the National Diabetes Supply Scheme (NDSS) registry that includes almost all individuals with type 1 diabetes nationally.</p> <p><b>Results:</b> CGM uptake increased from 5% pre-subsidy to 79% after two years. After CGM introduction, the odds ratio (OR) of achieving the HbA1c target of <7.0% improved at 12 months (OR 2.5, p<0.001) and was maintained at 24 months (OR 2.3, p<0.001). The OR for suboptimal glycaemic control (HbA1c ≥ 9.0%) decreased to 0.34 (p<0.001) at 24 months. Of CGM users, 65% used CGM >75% of time: these had a lower HbA1c at 24 months compared to those with usage <25% (7.8±1.3% vs 8.6±1.8%, respectively, p<0.001). DKA was also reduced in this group (IRR 0.49, 95% CI 0.33-0.74, p<0.001).</p> <b>Conclusions:</b> <a></a>Following national subsidy, CGM use was high and associated with sustained improvement in glycaemic control. This information will inform economic analyses and future policy and serve as a model of evaluation diabetes technologies.

scholarly journals Universal Subsidized Continuous Glucose Monitoring Funding for Young People With Type 1 Diabetes: Uptake and Outcomes Over 2 Years, a Population-Based Study

2021 ◽  
Author(s):  
Stephanie R Johnson ◽  
Deborah J Holmes-Walker ◽  
Melissa Chee ◽  
Arul Earnest ◽  
Timothy W Jones ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycaemic Control ◽  
Continuous Glucose Monitoring ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Population Based ◽  
Insulin Regimen ◽  
Economic Analyses ◽  
Almost All

<b>Objective:</b> Continuous glucose monitoring (CGM) is increasingly used in type 1 diabetes management however funding models vary. This study determined the uptake rate and glycaemic outcomes following a change in national health policy to introduce universal subsidised CGM funding for people with type 1 diabetes aged < 21 years. <p><b>Research Design and Methods:</b> Analysis of longitudinal data from 12 months prior to subsidy until 24 months after. Measures and outcomes included age, diabetes duration, HbA1c, episodes of diabetic ketoacidosis and severe hypoglycaemia, insulin regimen, CGM uptake and percentage CGM use. Two data sources were used: the Australasian Diabetes Database Network (ADDN) registry (a prospective diabetes database) and the National Diabetes Supply Scheme (NDSS) registry that includes almost all individuals with type 1 diabetes nationally.</p> <p><b>Results:</b> CGM uptake increased from 5% pre-subsidy to 79% after two years. After CGM introduction, the odds ratio (OR) of achieving the HbA1c target of <7.0% improved at 12 months (OR 2.5, p<0.001) and was maintained at 24 months (OR 2.3, p<0.001). The OR for suboptimal glycaemic control (HbA1c ≥ 9.0%) decreased to 0.34 (p<0.001) at 24 months. Of CGM users, 65% used CGM >75% of time: these had a lower HbA1c at 24 months compared to those with usage <25% (7.8±1.3% vs 8.6±1.8%, respectively, p<0.001). DKA was also reduced in this group (IRR 0.49, 95% CI 0.33-0.74, p<0.001).</p> <b>Conclusions:</b> <a></a>Following national subsidy, CGM use was high and associated with sustained improvement in glycaemic control. This information will inform economic analyses and future policy and serve as a model of evaluation diabetes technologies.

scholarly journals An Interactive Web Application for the Statistical Analysis of Continuous Glucose Monitoring Data in Epidemiological Studies

2021 ◽  
pp. 193229682098557
Author(s):  
Alysha M. De Livera ◽  
Jonathan E. Shaw ◽  
Neale Cohen ◽  
Anne Reutens ◽  
Agus Salim
Keyword(s):  
Continuous Glucose Monitoring ◽  
Web Application ◽  
Diabetes Management ◽  
Glucose Monitoring ◽  
Epidemiological Studies ◽  
Interactive Software ◽  
Web Based ◽  
Software Applications ◽  
Visualization Of Data ◽  
User Friendly

Motivation: Continuous glucose monitoring (CGM) systems are an essential part of novel technology in diabetes management and care. CGM studies have become increasingly popular among researchers, healthcare professionals, and people with diabetes due to the large amount of useful information that can be collected using CGM systems. The analysis of the data from these studies for research purposes, however, remains a challenge due to the characteristics and large volume of the data. Results: Currently, there are no publicly available interactive software applications that can perform statistical analyses and visualization of data from CGM studies. With the rapidly increasing popularity of CGM studies, such an application is becoming necessary for anyone who works with these large CGM datasets, in particular for those with little background in programming or statistics. CGMStatsAnalyser is a publicly available, user-friendly, web-based application, which can be used to interactively visualize, summarize, and statistically analyze voluminous and complex CGM datasets together with the subject characteristics with ease.

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.

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