scholarly journals Real-Time Continuous Glucose Monitoring Significantly Reduces Severe Hypoglycemia in Hypoglycemia-Unaware Patients With Type 1 Diabetes

Diabetes Care ◽  
2013 ◽  
Vol 36 (12) ◽  
pp. 4160-4162 ◽  
Author(s):  
P. Choudhary ◽  
S. Ramasamy ◽  
L. Green ◽  
G. Gallen ◽  
S. Pender ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia

scholarly journals Sustained impact of real-time continuous glucose monitoring in adults with type 1 diabetes on insulin pump therapy: Results after 24 months RESCUE study

2020 ◽  
Author(s):  
Sara Charleer ◽  
Christophe De Block ◽  
Frank Nobels ◽  
Régis P. Radermecker ◽  
Ine Lowyck ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Insulin Pump ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Insulin Pump Therapy ◽  
Pump Therapy ◽  
Acute Hypoglycemia

<b>Objective:</b> In recent years, a growing number of people with type 1 diabetes have access to real-time continuous glucose monitoring (rtCGM). Long-term benefits of rtCGM are unclear due to lack of large studies of long duration. We evaluated whether real-world rtCGM-use up to 24 months offered benefits, in particular to those living with impaired awareness of hypoglycemia (IAH). <p><b>Research Design and Methods:</b> This 24-month, prospective, observational, cohort study followed 441<b> </b>adults with insulin pumps receiving full reimbursement for rtCGM. Forty-two percent had IAH. Primary endpoint was evolution of HbA<sub>1c</sub>, with secondary endpoints change in acute hypoglycemia complications, diabetes-related work absenteeism, and quality of life (QOL) scores. Additionally, we evaluated if people could achieve glycemic consensus targets during follow-up.</p> <p><b>Results:</b> After 24 months, HbA<sub>1c</sub> remained significantly lower compared to baseline (7.64% [60 mmol/mol] vs 7.37% [57 mmol/mol], p<0.0001). Sustained benefits were also observed for the score on the hypoglycemia fear survey and hypoglycemia-related acute complications irrespective of hypoglycemia awareness level. People with IAH had the strongest improvement, especially for severe hypoglycemia (862 events year before vs 119 events per 100 patient-years in second year, p<0.0001). Over 24 months, more people were able to meet hypoglycemia consensus targets at the expense of slightly less people achieving hyperglycemia consensus targets. Furthermore, the number of people with HbA<sub>1c</sub> <7% (<53 mmol/mol) without severe hypoglycemia events more than doubled (11.0% vs 25.4%, p<0.0001).</p> <p><b>Conclusion:</b> Use of rtCGM led to sustained improvements in hypoglycemia-related glucose control over 24 months. Lower fear of hypoglycemia, less acute hypoglycemia-related events and diabetes-related days off work were observed, particularly in those with IAH.</p>

scholarly journals Sustained impact of real-time continuous glucose monitoring in adults with type 1 diabetes on insulin pump therapy: Results after 24 months RESCUE study

2020 ◽  
Author(s):  
Sara Charleer ◽  
Christophe De Block ◽  
Frank Nobels ◽  
Régis P. Radermecker ◽  
Ine Lowyck ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Insulin Pump ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Insulin Pump Therapy ◽  
Pump Therapy ◽  
Acute Hypoglycemia

<b>Objective:</b> In recent years, a growing number of people with type 1 diabetes have access to real-time continuous glucose monitoring (rtCGM). Long-term benefits of rtCGM are unclear due to lack of large studies of long duration. We evaluated whether real-world rtCGM-use up to 24 months offered benefits, in particular to those living with impaired awareness of hypoglycemia (IAH). <p><b>Research Design and Methods:</b> This 24-month, prospective, observational, cohort study followed 441<b> </b>adults with insulin pumps receiving full reimbursement for rtCGM. Forty-two percent had IAH. Primary endpoint was evolution of HbA<sub>1c</sub>, with secondary endpoints change in acute hypoglycemia complications, diabetes-related work absenteeism, and quality of life (QOL) scores. Additionally, we evaluated if people could achieve glycemic consensus targets during follow-up.</p> <p><b>Results:</b> After 24 months, HbA<sub>1c</sub> remained significantly lower compared to baseline (7.64% [60 mmol/mol] vs 7.37% [57 mmol/mol], p<0.0001). Sustained benefits were also observed for the score on the hypoglycemia fear survey and hypoglycemia-related acute complications irrespective of hypoglycemia awareness level. People with IAH had the strongest improvement, especially for severe hypoglycemia (862 events year before vs 119 events per 100 patient-years in second year, p<0.0001). Over 24 months, more people were able to meet hypoglycemia consensus targets at the expense of slightly less people achieving hyperglycemia consensus targets. Furthermore, the number of people with HbA<sub>1c</sub> <7% (<53 mmol/mol) without severe hypoglycemia events more than doubled (11.0% vs 25.4%, p<0.0001).</p> <p><b>Conclusion:</b> Use of rtCGM led to sustained improvements in hypoglycemia-related glucose control over 24 months. Lower fear of hypoglycemia, less acute hypoglycemia-related events and diabetes-related days off work were observed, particularly in those with IAH.</p>

The impact of real-time continuous glucose monitoring on metabolic control in children with type 1 diabetes

2020 ◽  
Author(s):  
Ruxandra Calapod Ioana ◽  
Irina Bojoga ◽  
Duta Simona Gabriela ◽  
Ana-Maria Stancu ◽  
Amalia Arhire ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Metabolic Control ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
The Impact

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.

Improvement of metabolic control after 3-month use of real-time continuous glucose monitoring in patients with type 1 diabetes: a multicenter study in Greece

HORMONES ◽  
2019 ◽  
Vol 18 (4) ◽  
pp. 443-450
Author(s):  
Ioanna Eleftheriadou ◽  
Triantafyllos Didangelos ◽  
Angelos C. Pappas ◽  
Eleni Anastasiou ◽  
Charalampos Vasilopoulos ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Metabolic Control ◽  
Continuous Glucose Monitoring ◽  
Multicenter Study ◽  
Glucose Monitoring

scholarly journals Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes

2019 ◽  
Vol 21 (6) ◽  
pp. 313-321 ◽  
Author(s):  
Dessi P. Zaharieva ◽  
Kamuran Turksoy ◽  
Sarah M. McGaugh ◽  
Rubin Pooni ◽  
Todd Vienneau ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Aerobic Exercise ◽  
Real Time ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Lag Time ◽  
Monitoring Technology
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