scholarly journals Probabilistic Model of Transition between Categories of Glucose Profiles in Patients with Type 1 Diabetes Using a Compositional Data Analysis Approach

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3593
Author(s):  
Lyvia Biagi ◽  
Arthur Bertachi ◽  
Marga Giménez ◽  
Ignacio Conget ◽  
Jorge Bondia ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Probabilistic Model ◽  
Compositional Data ◽  
Compositional Data Analysis ◽  
Analysis Tool ◽  
Continuous Glucose Monitor ◽  
Discriminant Model ◽  
The Past ◽  
Glucose Profiles

The time spent in glucose ranges is a common metric in type 1 diabetes (T1D). As the time in one day is finite and limited, Compositional Data (CoDa) analysis is appropriate to deal with times spent in different glucose ranges in one day. This work proposes a CoDa approach applied to glucose profiles obtained from six T1D patients using continuous glucose monitor (CGM). Glucose profiles of 24-h and 6-h duration were categorized according to the relative interpretation of time spent in different glucose ranges, with the objective of presenting a probabilistic model of prediction of category of the next 6-h period based on the category of the previous 24-h period. A discriminant model for determining the category of the 24-h periods was obtained, achieving an average above 94% of correct classification. A probabilistic model of transition between the category of the past 24-h of glucose to the category of the future 6-h period was obtained. Results show that the approach based on CoDa is suitable for the categorization of glucose profiles giving rise to a new analysis tool. This tool could be very helpful for patients, to anticipate the occurrence of potential adverse events or undesirable variability and for physicians to assess patients’ outcomes and then tailor their therapies.

scholarly journals Compositional Data Analysis of Glucose Profiles of Type 1 Diabetes Patients

2019 ◽  
Vol 52 (1) ◽  
pp. 1006-1011
Author(s):  
Lyvia Biagi ◽  
Arthur Bertachi ◽  
Josep Antoni Martín-Fernández ◽  
Josep Vehí
Keyword(s):  
Type 1 Diabetes ◽  
Data Analysis ◽  
Compositional Data ◽  
Compositional Data Analysis ◽  
Glucose Profiles ◽  
Diabetes Patients

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 Substantial Intra-Individual Variability in Post-Prandial Time to Peak in Controlled and Free-Living Conditions in Children with Type 1 Diabetes

Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 4154
Author(s):  
Emily Bell ◽  
Sabrina Binkowski ◽  
Elaine Sanderson ◽  
Barbara Keating ◽  
Grant Smith ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Individual Variability ◽  
Living Conditions ◽  
Optimal Time ◽  
Daily Routine ◽  
Free Living ◽  
Continuous Glucose Monitor ◽  
Time To Peak ◽  
Free Living Conditions

The optimal time to bolus insulin for meals is challenging for children and adolescents with type 1 diabetes (T1D). Current guidelines to control glucose excursions do not account for individual differences in glycaemic responses to meals. This study aimed to examine the within- and between-person variability in time to peak (TTP) glycaemic responses after consuming meals under controlled and free-living conditions. Participants aged 8–15 years with T1D ≥ 1 year and using a continuous glucose monitor (CGM) were recruited. Participants consumed a standardised breakfast for six controlled days and maintained their usual daily routine for 14 free-living days. CGM traces were collected after eating. Linear mixed models were used to identify within- and between-person variability in the TTP after each of the controlled breakfasts, free-living breakfasts (FLB), and free-living dinners (FLD) conditions. Thirty participants completed the study (16 females; mean age and standard deviation (SD) 10.5 (1.9)). The TTP variability was greater within a person than the variability between people for all three meal types (between-person vs within-person SD; controlled breakfast 18.5 vs 38.9 minutes; FLB 14.1 vs 49.6 minutes; FLD 5.7 vs 64.5 minutes). For the first time, the study showed that within-person variability in TTP glycaemic responses is even greater than between-person variability.

scholarly journals Alarm Settings of Continuous Glucose Monitoring Systems and Associations to Glucose Outcomes in Type 1 Diabetes

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Yu Kuei Lin ◽  
Danielle Groat ◽  
Owen Chan ◽  
Man Hung ◽  
Anu Sharma ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glucose Monitoring ◽  
Continuous Glucose Monitor ◽  
Cross Sectional ◽  
Therapeutic Goals ◽  
Glucose Levels ◽  
Alarm Threshold ◽  
Negative Impacts ◽  
Average Glucose

Abstract Context Little evidence exists regarding the positive and negative impacts of continuous glucose monitor system (CGM) alarm settings for diabetes control in patients with type 1 diabetes (T1D). Objective Evaluate the associations between CGM alarm settings and glucose outcomes. Design and Setting A cross-sectional observational study in a single academic institution. Patients and Main Outcome Measures CGM alarm settings and 2-week CGM glucose information were collected from 95 T1D patients with > 3 months of CGM use and ≥ 86% active usage time. The associations between CGM alarm settings and glucose outcomes were analyzed. Results Higher glucose thresholds for hypoglycemia alarms (ie, ≥ 73 mg/dL vs < 73 mg/dL) were related to 51% and 65% less time with glucose < 70 and < 54 mg/dL, respectively (P = 0.005; P = 0.016), higher average glucose levels (P = 0.002) and less time-in-range (P = 0.005), but not more hypoglycemia alarms. The optimal alarm threshold for < 1% of time in hypoglycemia was 75 mg/dL. Lower glucose thresholds for hyperglycemia alarms (ie, ≤ 205 mg/dL vs > 205 mg/dL) were related to lower average glucose levels and 42% and 61% less time with glucose > 250 and > 320 mg/dL (P = 0.020, P = 0.016, P = 0.007, respectively), without more hypoglycemia. Lower alarm thresholds were also associated with more alarms (P < 0.0001). The optimal alarm threshold for < 5% of time in hyperglycemia and hemoglobin A1c ≤ 7% was 170 mg/dL. Conclusions Different CGM glucose thresholds for hypo/hyperglycemia alarms are associated with various hypo/hyperglycemic outcomes. Configurations to the hypo/hyperglycemia alarm thresholds could be considered as an intervention to achieve therapeutic goals.

scholarly journals THERAPY OF ENDOCRINE DISEASE: Islet transplantation for type 1 diabetes: so close and yet so far away

2015 ◽  
Vol 173 (5) ◽  
pp. R165-R183 ◽  
Author(s):  
Mohsen Khosravi-Maharlooei ◽  
Ensiyeh Hajizadeh-Saffar ◽  
Yaser Tahamtani ◽  
Mohsen Basiri ◽  
Leila Montazeri ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Islet Transplantation ◽  
Diabetic Patients ◽  
Immune Rejection ◽  
Pancreatic Islet Transplantation ◽  
Insulin Independence ◽  
Endocrine Disease ◽  
The Past ◽  
Source Limitation

Over the past decades, tremendous efforts have been made to establish pancreatic islet transplantation as a standard therapy for type 1 diabetes. Recent advances in islet transplantation have resulted in steady improvements in the 5-year insulin independence rates for diabetic patients. Here we review the key challenges encountered in the islet transplantation field which include islet source limitation, sub-optimal engraftment of islets, lack of oxygen and blood supply for transplanted islets, and immune rejection of islets. Additionally, we discuss possible solutions for these challenges.

scholarly journals Pediatric Medicaid Patients With Type 1 Diabetes Benefit From Continuous Glucose Monitor Technology

2020 ◽  
pp. 193229682090621
Author(s):  
Sonalee J. Ravi ◽  
Alexander Coakley ◽  
Tim Vigers ◽  
Laura Pyle ◽  
Gregory P. Forlenza ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Insulin Pump ◽  
Diabetes Duration ◽  
Continuous Glucose Monitor ◽  
Percent Time ◽  
Time In Range ◽  
Continuous Glucose Monitors ◽  
Hispanic White

Background: We determined the uptake rate of continuous glucose monitors (CGMs) and examined associations of clinical and demographic characteristics with CGM use among patients with type 1 diabetes covered by Colorado Medicaid during the first two years of CGM coverage with no out-of-pocket cost. Method: We retrospectively reviewed data from 892 patients with type 1 diabetes insured by Colorado Medicaid (Colorado Health Program [CHP] and CHP+, Colorado Medicaid expansion). Demographics, insulin pump usage, CGM usage, and hemoglobin A1c (A1c) were extracted from the medical record. Data downloaded into CGM software at clinic appointments were reviewed to determine 30-day use prior to appointments. Subjects with some exposure to CGM were compared to subjects never exposed to CGM, and we examined the effect of CGM use on glycemic control. Results: Twenty percent of subjects had some exposure to CGM with a median of 22 [interquartile range 8, 29] days wear. Sixty one percent of CGM users had >85% sensor wear. Subjects using CGM were more likely to be younger ( P < .001), have shorter diabetes duration ( P < .001), and be non-Hispanic White ( P < .001) than nonusers. After adjusting for age and diabetes duration, combined pump and CGM users had a lower A1c than those using neither technology ( P = .006). Lower A1c was associated with greater CGM use ( P = .002) and increased percent time in range ( P < .001). Conclusion: Pediatric Medicaid patients successfully utilized CGM. Expansion of Medicaid coverage for CGM may help improve glycemic control and lessen disparities in clinical outcomes within this population.

scholarly journals Continuous Glucose Monitor Use With Remote Monitoring Reduces Fear of Hypoglycemia in Pregnant Women With Type 1 Diabetes: A Pilot Study

2019 ◽  
Vol 14 (1) ◽  
pp. 191-192
Author(s):  
Sarit Polsky ◽  
Rachel Garcetti ◽  
Laura Pyle ◽  
Prakriti Joshee ◽  
Jamie K. Demmitt ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Pilot Study ◽  
Pregnant Women ◽  
Remote Monitoring ◽  
Continuous Glucose Monitor ◽  
Fear Of Hypoglycemia

scholarly journals Why is type 1 diabetes increasing?

2013 ◽  
Vol 51 (1) ◽  
pp. R1-R13 ◽  
Author(s):  
Francesco Maria Egro
Keyword(s):  
Type 1 Diabetes ◽  
Epidemiological Studies ◽  
Past Century ◽  
Β Cell ◽  
The Past ◽  
Immunological Mechanisms ◽  
Triggering Factor ◽  
A Cell ◽  
Shift Model

A series of studies have reported a constant global rise in the incidence of type 1 diabetes. Epidemiological and immunological studies have demonstrated that environmental factors may influence the pathogenesis, leading to a cell-mediated pancreatic β-cell destruction associated with humoral immunity. The search for the triggering factor(s) has been going on for the past century, and yet they are still unknown. This review provides an overview of some of the most well-known theories found in the literature: hygiene, viral, vitamin D deficiency, breast milk and cow's milk hypotheses. Although the hygiene hypothesis appears to be the most promising, positive evidence from animal, human and epidemiological studies precludes us from completely discarding any of the other hypotheses. Moreover, due to contrasting evidence in the literature, a single factor is unlikely to cause an increase in the incidence of diabetes all over the world, which suggests that a multifactorial process might be involved. Although the immunological mechanisms are still unclear, there seems to be some overlap between the various hypotheses. It is thought that the emphasis should be shifted from a single to a multifactorial process and that perhaps the ‘balance shift’ model should be considered as a possible explanation for the rise in the incidence of type 1 diabetes.

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