scholarly journals Glucodensities: A new representation of glucose profiles using distributional data analysis

2021 ◽  
pp. 096228022199806
Author(s):  
Marcos Matabuena ◽  
Alexander Petersen ◽  
Juan C Vidal ◽  
Francisco Gude
Keyword(s):  
Data Analysis ◽  
Glucose Monitoring ◽  
Natural Generalization ◽  
Clinical Sensitivity ◽  
Standard Clinical Practice ◽  
Functional Representation ◽  
Glucose Profiles ◽  
Time In Range ◽  
Source Of Information ◽  
Free Living Conditions

Biosensor data have the potential to improve disease control and detection. However, the analysis of these data under free-living conditions is not feasible with current statistical techniques. To address this challenge, we introduce a new functional representation of biosensor data, termed the glucodensity, together with a data analysis framework based on distances between them. The new data analysis procedure is illustrated through an application in diabetes with continuous-time glucose monitoring (CGM) data. In this domain, we show marked improvement with respect to state-of-the-art analysis methods. In particular, our findings demonstrate that (i) the glucodensity possesses an extraordinary clinical sensitivity to capture the typical biomarkers used in the standard clinical practice in diabetes; (ii) previous biomarkers cannot accurately predict glucodensity, so that the latter is a richer source of information and; (iii) the glucodensity is a natural generalization of the time in range metric, this being the gold standard in the handling of CGM data. Furthermore, the new method overcomes many of the drawbacks of time in range metrics and provides more in-depth insight into assessing glucose metabolism.

Individual categorisation of glucose profiles using compositional data analysis

2018 ◽  
Vol 28 (12) ◽  
pp. 3550-3567 ◽  
Author(s):  
Lyvia Biagi ◽  
Arthur Bertachi ◽  
Marga Giménez ◽  
Ignacio Conget ◽  
Jorge Bondia ◽  
...  
Keyword(s):  
Data Analysis ◽  
Compositional Data ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Compositional Data Analysis ◽  
Relative Information ◽  
Glucose Profiles ◽  
Patient Groups ◽  
The Times

The aim of this study was to apply a methodology based on compositional data analysis (CoDA) to categorise glucose profiles obtained from continuous glucose monitoring systems. The methodology proposed considers complete daily glucose profiles obtained from six patients with type 1 diabetes (T1D) who had their glucose monitored for eight weeks. The glucose profiles were distributed into the time spent in six different ranges. The time in one day is finite and limited to 24 h, and the times spent in each of these different ranges are co-dependent and carry only relative information; therefore, CoDA is applied to these profiles. A K-means algorithm was applied to the coordinates obtained from the CoDA to obtain different patterns of days for each patient. Groups of days with relatively high time in the hypo and/or hyperglycaemic ranges and with different glucose variability were observed. Using CoDA of time in different ranges, individual glucose profiles were categorised into groups of days, which can be used by physicians to detect the different conditions of patients and personalise patient's insulin therapy according to each group. This approach can be useful to assist physicians and patients in managing the day-to-day variability that hinders glycaemic control.

scholarly journals Utilizing CGM Ambulatory Glucose Profiles to Optimize Diabetes Management

2021 ◽  
Vol 70 (6 Supplement) ◽  
Author(s):  
Miller
Keyword(s):  
Patient Outcomes ◽  
Diabetes Management ◽  
Treatment Plan ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
International Consensus ◽  
Glucose Profiles ◽  
Time In Range ◽  
Types Of Information ◽  
Improve Patient

LEARNING OBJECTIVES At the end of the activity, participant will be able to: • Identify patients who could benefit from continuous glucose monitoring (CGM) vs fingerstick blood glucose monitoring. • List the types of information provided by CGM systems. • Interpret CGM data using the ambulatory glucose profile (AGP) to assess if the patient is achieving targets established by the International Consensus on Time in Range. • Modify the treatment plan based on CGM data to improve patient outcomes.

scholarly journals Critical Reappraisal of the Time-in-Range: Alternative or Useful Addition to Glycated Hemoglobin?

2019 ◽  
Vol 14 (5) ◽  
pp. 922-927
Author(s):  
Lutz Heinemann ◽  
Guido Freckmann ◽  
Dirk Müller-Wieland ◽  
Monika Kellerer
Keyword(s):  
Glucose Control ◽  
Glycated Hemoglobin ◽  
Glucose Monitoring ◽  
Current Therapy ◽  
Additional Information ◽  
Attractive Option ◽  
Patients With Diabetes ◽  
Glucose Profiles ◽  
Time In Range

The HbA1c value is a well-established parameter used to characterize glucose control. Continuous glucose monitoring (CGM)-derived parameters calculated using daily glucose profiles such as Time-in-Range (TiR) have increasingly been gaining interest for assessing a patient’s current therapy. The question has arisen as to whether TiR could replace HbA1c? Because TiR focuses on the current quality of glucose control during a minimum of 10 to 14 days of CGM use and reflects the variability of glucose concentrations. Time-in-Range could be considered an attractive option for improving diabetes control in patients with diabetes. Due to the lack of established standards for glucose measurements with CGM systems, results from different CGM systems can deviate from each other. Time-in-Range should not be viewed as a replacement for HbA1c, but should be used to deliver valuable additional information.

Increased Time-in-Range with Sotagliflozin as Adjunct Therapy to Insulin in Adults with Type 1 Diabetes as Demonstrated by 24-Week Continuous Glucose Monitoring (inTandem1, inTandem2)

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1179-P ◽  
Author(s):  
THOMAS DANNE ◽  
BERTRAND CARIOU ◽  
JOHN B. BUSE ◽  
SATISH K. GARG ◽  
JULIO ROSENSTOCK ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Adjunct Therapy ◽  
Time In Range

Effect of Professional CGM (pCGM) on Glucose Management in Type 2 Diabetes Patients in Primary Care

2021 ◽  
pp. 193229682199872
Author(s):  
Gregg D. Simonson ◽  
Richard M. Bergenstal ◽  
Mary L. Johnson ◽  
Janet L. Davidson ◽  
Thomas W. Martens
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Glucose Monitoring ◽  
Care Model ◽  
Time In Range ◽  
Glucose Management ◽  
The Impact ◽  
Primary Care Management

Background: Little data exists regarding the impact of continuous glucose monitoring (CGM) in the primary care management of type 2 diabetes (T2D). We initiated a quality improvement (QI) project in a large healthcare system to determine the effect of professional CGM (pCGM) on glucose management. We evaluated both an MD and RN/Certified Diabetes Care and Education Specialist (CDCES) Care Model. Methods: Participants with T2D for >1 yr., A1C ≥7.0% to <11.0%, managed with any T2D regimen and willing to use pCGM were included. Baseline A1C was collected and participants wore a pCGM (Libre Pro) for up to 2 weeks, followed by a visit with an MD or RN/CDCES to review CGM data including Ambulatory Glucose Profile (AGP) Report. Shared-decision making was used to modify lifestyle and medications. Clinic follow-up in 3 to 6 months included an A1C and, in a subset, a repeat pCGM. Results: Sixty-eight participants average age 61.6 years, average duration of T2D 15 years, mean A1C 8.8%, were identified. Pre to post pCGM lowered A1C from 8.8% ± 1.2% to 8.2% ± 1.3% (n=68, P=0.006). The time in range (TIR) and time in hyperglycemia improved along with more hypoglycemia in the subset of 37 participants who wore a second pCGM. Glycemic improvement was due to lifestyle counseling (68% of participants) and intensification of therapy (65% of participants), rather than addition of medications. Conclusions: Using pCGM in primary care, with an MD or RN/CDCES Care Model, is effective at lowering A1C, increasing TIR and reducing time in hyperglycemia without necessarily requiring additional medications.

scholarly journals Enlarged glycemic variability in sulfonylurea-treated well-controlled type 2 diabetics identified using continuous glucose monitoring

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Fumi Uemura ◽  
Yosuke Okada ◽  
Keiichi Torimoto ◽  
Yoshiya Tanaka
Keyword(s):  
Glucose Level ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
High Dose ◽  
Type 2 Diabetics ◽  
Time In Range ◽  
The Difference ◽  
Glycated Hemoglobin Level

AbstractTime in range (TIR) is an index of glycemic control obtained from continuous glucose monitoring (CGM). The aim was to compare the glycemic variability of treatment with sulfonylureas (SUs) in type 2 diabetes mellitus (T2DM) with well-controlled glucose level (TIR > 70%). The study subjects were 123 patients selected T2DM who underwent CGM more than 24 h on admission without changing treatment. The primary endpoint was the difference in glycemic variability, while the secondary endpoint was the difference in time below range < 54 mg/dL; TBR < 54, between the SU (n = 63) and non-SU (n = 60) groups. The standard deviation, percentage coefficient of variation (%CV), and maximum glucose level were higher in the SU group than in the non-SU group, and TBR < 54 was longer in the high-dose SU patients. SU treatment was identified as a significant factor that affected %CV (β: 2.678, p = 0.034). High-dose SU use contributed to prolonged TBR < 54 (β: 0.487, p = 0.028). Our study identified enlarged glycemic variability in sulfonylurea-treated well-controlled T2DM patients and high-dose SU use was associated with TBR < 54. The results highlight the need for careful adjustment of the SU dose, irrespective of glycated hemoglobin level or TIR value.

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