Glucose Concentration can be Predicted Ahead in Time From Continuous Glucose Monitoring Sensor Time-Series

2007 ◽  
Vol 54 (5) ◽  
pp. 931-937 ◽  
Author(s):  
G. Sparacino ◽  
F. Zanderigo ◽  
S. Corazza ◽  
A. Maran ◽  
A. Facchinetti ◽  
...  
Keyword(s):  
Time Series ◽  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glucose Monitoring

Continuous Glucose Monitoring Time Series and Hypo/Hyperglycemia Prevention: Requirements, Methods, Open Problems

2008 ◽  
Vol 4 (3) ◽  
pp. 181-192 ◽  
Author(s):  
Giovanni Sparacino ◽  
Andrea Facchinetti ◽  
Alberto Maran ◽  
Claudio Cobelli
Keyword(s):  
Time Series ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Open Problems ◽  
Monitoring Time

Time-Series Analysis of Continuous Glucose Monitoring Data to Predict Treatment Efficacy in Patients with T2DM

2021 ◽  
Author(s):  
Li Li ◽  
Jie Sun ◽  
Liemin Ruan ◽  
Qifa Song
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Continuous Glucose Monitoring ◽  
Treatment Efficacy ◽  
Treatment Effects ◽  
Glucose Monitoring ◽  
Therapeutic Effects ◽  
Time Series Clustering ◽  
Glucose Lowering ◽  
Series Analysis

Abstract Context There is a challenge to predict treatment effects in patients with T2DM. Objective To assess and predict treatment effects in patients with T2DM through time-series analysis of continuous glucose monitoring (CGM) measurements. Design We extracted and clustered the trend components of CGM measurements to generate representative time-series profiles, which were used as a predictor of treatment effects in groups of patients. Setting and Participants We recruited 111 outpatients with T2DM at Ningbo City First Hospital. Intervention The patients underwent CGM measurement for 14 days at the beginning of glucose-lowering treatment. Main Outcome Measures HbA1c and FPG were obtained at the beginning and 6-month of treatment. Results 111 patients each had 960 –1344 CGM measurements for 14 days at 96 measurements per day. The patients were classified into three groups according to the profiles of trend components of CGM observed values by time-series clustering method, including decreasing (47 patients), increasing (26 patients), and unchanged (38 patients) profiles. After six-month glucose-lowering treatment, FPG declined from 10.2 to 6.8 mmol/L (a decline of 3.5 mmol/L) in the decreasing group, from 8.9 to 9.2 mmol/L (a rise of 0.3 mmol/L) in the increasing group, and from 8.4 to 7.5 mmol/L (a decline of 0.9 mmol/L). The changes of HbA1c were 2.2%, 0.2%, and 0.9% for the three groups (P<0.01), respectively. Conclusions Clustering of the trend components of CGM data generates representative CGM profiles that are predictive of six-month therapeutic effects for T2DM.

scholarly journals Hemodialysis-Related Glycemic Disarray Proven by Continuous Glucose Monitoring: Glycemic Markers and Hypoglycemia

2021 ◽  
Author(s):  
Akinori Hayashi ◽  
Naoya Shimizu ◽  
Agena Suzuki ◽  
Kenta Matoba ◽  
Akari Momozono ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glycated Albumin ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Sensor Glucose ◽  
Time In Range ◽  
Deviation Coefficient ◽  
Glycemic Markers ◽  
Design And Methods

<b>OBJECTIVE</b> <p>There is a high risk of asymptomatic hypoglycemia associated with hemodialysis (HD) using glucose-free dialysate; therefore, the inclusion of glucose in the dialysate is believed to prevent intradialytic hypoglycemia. However, the exact glycemic fluctuation profiles and frequency of asymptomatic hypoglycemia using dialysates containing >100 mg/dL glucose have not been determined.</p> <p><b>RESEARCH DESIGN AND METHODS</b></p> <p>We evaluated the glycemic profiles of 98 type 2 diabetes patients undergoing HD (68 men, HbA1c 6.4±1.2%, glycated albumin 20.8±6.8%) with a dialysate containing 100, 125, or 150 mg/dL glucose using continuous glucose monitoring.</p> <p><b>RESULTS</b></p> <p>Sensor glucose level (SGL) showed a sustained decrease during HD, irrespective of the dialysate glucose concentration, and reached a nadir that was lower than the dialysate glucose concentration in 49 participants (50%). Twenty-one participants (21%) presented with HD-related hypoglycemia, defined by an SGL <70 mg/dL during HD and/or between the end of HD and their next meal. All these hypoglycemic episodes were asymptomatic. Measures of glycemic variability calculated using the SGL data (standard deviation, coefficient of variation, and range of SGL) were higher and time below range (<70 mg/dL) was lower in participants who experienced HD-related hypoglycemia than in those who did not, whereas time in range between 70 and 180 mg/dL, time above range (>180 mg/dL), HbA1c and GA of the two groups were similar.</p> <p><b>CONCLUSIONS</b></p> <p>Despite the use of dialysate containing 100–150 mg/dL glucose, diabetic HD patients experienced HD-related hypoglycemia unawareness frequently. SGL may fall well below the dialysate glucose concentration toward the end of HD.<br> </p>

scholarly journals The Bihormonal Bionic Pancreas Improves Glycemic Control in Individuals With Hyperinsulinism and Postpancreatectomy Diabetes— A Pilot Study

2021 ◽  
Author(s):  
Arpana Rayannavar ◽  
Lauren M. Mitteer ◽  
Courtney A. Balliro ◽  
Firas H. El-Khatib ◽  
Katherine L. Lord ◽  
...  
Keyword(s):  
Pilot Study ◽  
Glycemic Control ◽  
Usual Care ◽  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glucose Monitoring ◽  
Congenital Hyperinsulinism ◽  
Open Label ◽  
Mean Glucose

<i>Objective:</i> To determine if the bihormonal bionic pancreas (BHBP) improves glycemic control and reduces hypoglycemia in individuals with congenital hyperinsulinism (HI) and post-pancreatectomy diabetes (PPD) compared with usual care (UC). <p><i>Methods</i>: Ten subjects with HI and PPD completed this open-label, crossover pilot study. Co-primary outcomes were mean glucose concentration and time with continuous glucose monitoring (CGM) glucose concentration <3.3 mmol/L.</p> <p><i>Results</i>: Mean (SD) CGM glucose concentration was 8.3 mmol/L (0.7) in the BHBP period vs. 9 mmol/L (1.8) in the UC period (p=0.13). Mean (SD) time with CGM glucose concentration <3.3 mmol/L was 0% (0.002) in the BHBP period vs. 1.3% (0.018) in the UC period (p=0.11). </p> <p><i>Conclusion</i>: Relative to UC, the BHBP resulted in comparable glycemic control in our population. </p>

Prediction of Glucose Concentration in Post-Cardiothoracic Surgery Patients Using Continuous Glucose Monitoring

2011 ◽  
Vol 13 (2) ◽  
pp. 127-134 ◽  
Author(s):  
Lukas Schaupp ◽  
Johannes Plank ◽  
Gerd Köhler ◽  
Roland Schaller ◽  
Christopher Wrighton ◽  
...  
Keyword(s):  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glucose Monitoring ◽  
Cardiothoracic Surgery

scholarly journals The Bihormonal Bionic Pancreas Improves Glycemic Control in Individuals With Hyperinsulinism and Postpancreatectomy Diabetes— A Pilot Study

2021 ◽  
Author(s):  
Arpana Rayannavar ◽  
Lauren M. Mitteer ◽  
Courtney A. Balliro ◽  
Firas H. El-Khatib ◽  
Katherine L. Lord ◽  
...  
Keyword(s):  
Pilot Study ◽  
Glycemic Control ◽  
Usual Care ◽  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Glucose Monitoring ◽  
Congenital Hyperinsulinism ◽  
Open Label ◽  
Mean Glucose

<i>Objective:</i> To determine if the bihormonal bionic pancreas (BHBP) improves glycemic control and reduces hypoglycemia in individuals with congenital hyperinsulinism (HI) and post-pancreatectomy diabetes (PPD) compared with usual care (UC). <p><i>Methods</i>: Ten subjects with HI and PPD completed this open-label, crossover pilot study. Co-primary outcomes were mean glucose concentration and time with continuous glucose monitoring (CGM) glucose concentration <3.3 mmol/L.</p> <p><i>Results</i>: Mean (SD) CGM glucose concentration was 8.3 mmol/L (0.7) in the BHBP period vs. 9 mmol/L (1.8) in the UC period (p=0.13). Mean (SD) time with CGM glucose concentration <3.3 mmol/L was 0% (0.002) in the BHBP period vs. 1.3% (0.018) in the UC period (p=0.11). </p> <p><i>Conclusion</i>: Relative to UC, the BHBP resulted in comparable glycemic control in our population. </p>

scholarly journals Estimation of Blood Glucose Concentration During Endurance Sports

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Physical Activity ◽  
Blood Glucose ◽  
Continuous Glucose Monitoring ◽  
Glucose Concentration ◽  
Blood Glucose Concentration ◽  
Glucose Monitoring ◽  
Interstitial Tissue ◽  
Endurance Sports ◽  
Convolution Integral Equation ◽  
Deconvolution Problem

In this paper, we describe a new statistical approach to estimate blood glucose concentration along time during endurance sports based on measurements of glucose concentration in subcutaneous interstitial tissue. The final goal is the monitoring of glucose concentration in blood to maximize performance in endurance sports. Blood glucose concentration control during and after aerobic physical activity could also be useful to reduce the risk of hypoglycemia in type 1 diabetes mellitus subjects. By means of a low invasive technology known as "continuous glucose monitoring", glucose concentration in subcutaneous interstitial tissue can now be measured every five minutes. However, it can be expressed as function of blood glucose concentration along time by means of a convolution integral equation. In the training phase of the proposed approach, based on measurements of glucose concentration in both artery and subcutaneous interstitial tissue during physical activity, the parameters of the convolution kernel are estimated. Then, given a new subject performing aerobic physical activity, a deconvolution problem is solved to estimate glucose concentration in blood from continuous glucose monitoring measurements

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