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

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.

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Continuous Glucose Monitors and Activity Trackers to Inform Insulin Dosing in Type 1 Diabetes: The University of Virginia Contribution

Sensors ◽

10.3390/s19245386 ◽

2019 ◽

Vol 19 (24) ◽

pp. 5386 ◽

Cited By ~ 2

Author(s):

Chiara Fabris ◽

Basak Ozaslan ◽

Marc D. Breton

Keyword(s):

Physical Activity ◽

Type 1 Diabetes ◽

Glycemic Control ◽

In Silico ◽

University Of Virginia ◽

Percent Time ◽

Activity Trackers ◽

Continuous Glucose Monitors ◽

The University

Objective: Suboptimal insulin dosing in type 1 diabetes (T1D) is frequently associated with time-varying insulin requirements driven by various psycho-behavioral and physiological factors influencing insulin sensitivity (IS). Among these, physical activity has been widely recognized as a trigger of altered IS both during and following the exercise effort, but limited indication is available for the management of structured and (even more) unstructured activity in T1D. In this work, we present two methods to inform insulin dosing with biosignals from wearable sensors to improve glycemic control in individuals with T1D. Research Design and Methods: Continuous glucose monitors (CGM) and activity trackers are leveraged by the methods. The first method uses CGM records to estimate IS in real time and adjust the insulin dose according to a person’s insulin needs; the second method uses step count data to inform the bolus calculation with the residual glucose-lowering effects of recently performed (structured or unstructured) physical activity. The methods were tested in silico within the University of Virginia/Padova T1D Simulator. A standard bolus calculator and the proposed “smart” systems were deployed in the control of one meal in presence of increased/decreased IS (Study 1) and following a 1-hour exercise bout (Study 2). Postprandial glycemic control was assessed in terms of time spent in different glycemic ranges and low/high blood glucose indices (LBGI/HBGI), and compared between the dosing strategies. Results: In Study 1, the CGM-informed system allowed to reduce exposure to hypoglycemia in presence of increased IS (percent time < 70 mg/dL: 6.1% versus 9.9%; LBGI: 1.9 versus 3.2) and exposure to hyperglycemia in presence of decreased IS (percent time > 180 mg/dL: 14.6% versus 18.3%; HBGI: 3.0 versus 3.9), tending toward optimal control. In Study 2, the step count-informed system allowed to reduce hypoglycemia (percent time < 70 mg/dL: 3.9% versus 13.4%; LBGI: 1.7 versus 3.2) at the cost of a minor increase in exposure to hyperglycemia (percent time > 180 mg/dL: 11.9% versus 7.5%; HBGI: 2.4 versus 1.5). Conclusions: We presented and validated in silico two methods for the smart dosing of prandial insulin in T1D. If seen within an ensemble, the two algorithms provide alternatives to individuals with T1D for improving insulin dosing accommodating a large variety of treatment options. Future work will be devoted to test the safety and efficacy of the methods in free-living conditions.

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Time in range for multiple technologies in type 1 diabetes: a systematic review and network meta-analysis

10.2337/figshare.12116691 ◽

2020 ◽

Author(s):

Anthony Pease ◽

Clement Lo ◽

Arul Earnest ◽

Velislava Kiriakova ◽

Danny Liew ◽

...

Keyword(s):

Systematic Review ◽

Type 1 Diabetes ◽

Closed Loop ◽

Meta Analysis ◽

Management Strategies ◽

Glucose Testing ◽

Closed Loop Systems ◽

Percent Time ◽

Time In Range

Background: Time-in-range is a key glycaemic metric, and comparisons of management technologies for this outcome are critical to guide device selection. Purpose: We conducted a systematic review and network meta-analysis to compare and rank technologies for time in glycaemic ranges. Data sources: We searched All Evidenced Based Medicine Reviews, CINAHL, EMBASE, MEDLINE, MEDLINE In-Process and other non-indexed citations, PROSPERO, PsycINFO, PubMed, and Web of Science until 24 April, 2019. Study selection: We included randomised controlled trials >2 weeks duration comparing technologies for management of type 1 diabetes in adults (>18 years of age), excluding pregnant women. Data extraction: Data were extracted using a predefined template. Outcomes were percent time with sensor glucose levels 3.9–10.0mmol/l (70–180mg/dL), >10.0mmol/L (180mg/dL), and <3.9mmol/L (70mg/dL). Data synthesis: We identified 16,772 publications, of which 14 eligible studies compared eight technologies comprising 1,043 participants. Closed loop systems lead to greater percent time-in-range than any other management strategy and was 17.85 (95% predictive interval [PrI] 7.56–28.14) higher than usual care of multiple daily injections with capillary glucose testing. Closed loop systems ranked best for percent time-in-range or above range utilising surface under the cumulative ranking curve (SUCRA–98.5 and 93.5 respectively). Closed loop systems also ranked highly for time below range (SUCRA–62.2). Limitations: Overall risk of bias ratings were moderate for all outcomes. Certainty of evidence was very low. Conclusions: In the first integrated comparison of multiple management strategies considering time-in-range, we found that the efficacy of closed loop systems appeared better than all other approaches.

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Analysis of Glycemic Control in Type 1 Diabetes Patients Using Hybrid Closed Loop Insulin Pump Therapy (Medtronic 670G)

Case Medical Research ◽

10.31525/ct1-nct04051632 ◽

2019 ◽

Author(s):

Keyword(s):

Type 1 Diabetes ◽

Glycemic Control ◽

Closed Loop ◽

Insulin Pump ◽

Insulin Pump Therapy ◽

Pump Therapy ◽

Diabetes Patients

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Glycemic Control in Transition‐Aged Versus Early Adults with Type 1 Diabetes and the Effect of a Government‐Funded Insulin Pump Program

Diabetic Medicine ◽

10.1111/dme.14618 ◽

2021 ◽

Author(s):

Shane P Mooney ◽

Gillian L Booth ◽

Rayzel Shulman ◽

Yingbo Na ◽

Alanna Weisman ◽

...

Keyword(s):

Type 1 Diabetes ◽

Glycemic Control ◽

Insulin Pump

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823-P: Insulin Pump Use and Glycemic Control among Patients with Type 1 Diabetes: Trends from the T1DX-QI Cohort

Diabetes ◽

10.2337/db21-823-p ◽

2021 ◽

Vol 70 (Supplement 1) ◽

pp. 823-P

Author(s):

NUDRAT NOOR ◽

RYAN MCDONOUGH ◽

EMILY CARLSON ◽

ALLISON B. MEKHOUBAD ◽

SUSAN HSIEH ◽

...

Keyword(s):

Type 1 Diabetes ◽

Glycemic Control ◽

Insulin Pump ◽

Diabetes Trends

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Improved Time-in-Range over 1 year is Associated with Reduced Albuminuria in Individuals with Sensor-Augmented Insulin Pump-Treated Type 1 Diabetes

10.2337/figshare.12777122 ◽

2020 ◽

Author(s):

Ajenthen G. Ranjan ◽

Signe V. Rosenlund ◽

Tine W. Hansen ◽

Peter Rossing ◽

Steen Andersen ◽

...

Keyword(s):

Type 1 Diabetes ◽

Insulin Pump ◽

Controlled Trial ◽

Daily Injection ◽

Albumin Creatinine Ratio ◽

Multiple Daily Injection ◽

Blood And Urine Samples ◽

Time In Range ◽

One Year

Aim: To investigate the association between treatment-induced change in continuous glucose monitored (CGM) time-in-range (TIR) and albuminuria in persons with type 1 diabetes (T1D) treated with sensor-augmented-pumps (SAP). Methods: <a></a><a>Twenty-six of fifty-five participants with albuminuria and multiple daily injection-therapy (25% females, 51 (46-63) years, HbA1c 75 (68-88) mmol/mol [9.0 (8.4-10.4)%], UACR 89 (37-250) mg/g) were in a randomized-controlled trial assigned to SAP-therapy for one year</a>. Anthropometrics, CGM-data, blood and urine samples were collected every three months. Results: Mean change (95%-CI) in %TIR was +13.2 (6.2;20.2)%, HbA1C was -14.4 (-17.4;-10.5) mmol/mol [-1.3 (-1.6;-1.0)%] and urinary albumin-creatinine-ratio (UACR) was -15 (-38;17)%, all p<0.05. UACR decreased with 19 (10;28)% per 10% increase in %TIR (p=0.04), 18 (1;30)% per 10 mmol/mol decrease in HbA1C (p=0.07), and 31% per 10 mmHg decrease in mean arterial pressure (p<0.001). Conclusion: In this longitudinal study, treatment-induced increase in %TIR was significantly associated with decrease in albuminuria in T1D.

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30-Year Cardiovascular Disease in Type 1 Diabetes: Risk and Risk Factors Differ by Long-Term Patterns of Glycemic Control

10.2337/figshare.16775965 ◽

2021 ◽

Author(s):

Rachel G. Miller ◽

Trevor J. Orchard ◽

Tina Costacou

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Type 1 Diabetes ◽

Glycemic Control ◽

Latent Class ◽

Diabetes Duration ◽

Cvd Risk ◽

High Hba1c

Objective: We hypothesized that there is heterogeneity in long-term patterns of glycemic control with respect to cardiovascular disease (CVD) development in type 1 diabetes and that risk factors for CVD differ by glycemic control pattern. Thus, we estimated associations between data-derived latent HbA1c trajectories and 30-year CVD risk in the Pittsburgh Epidemiology of Diabetes Complications (EDC) study of childhood-onset (<17 years old) type 1 diabetes. Research Design and Methods: Participants (n=536 with ≥2 HbA1c measurements [median 6] and CVD-free at baseline; mean age 27 and diabetes duration 18 years) were followed from 1986-88 to 2016-18 to ascertain CVD incidence (CVD death, myocardial infarction, stroke, coronary revascularization or blockage ≥50%, ischemic ECG, or angina). Latent HbA1c trajectories and their association with time-to-CVD incidence were simultaneously assessed using Joint Latent Class Mixed Models. Results: Two HbA1c trajectories with respect to differential CVD risk were identified: Low (HbA1c ~8% [64 mmol/mol] and improving over follow-up, 76% of cohort) and High (HbA1c ~10% [86 mmol/mol] and stable, 24%). Overall, 30-year CVD incidence was 47.4% (n=253); MACE incidence 31.0% (n=176). High HbA1c was associated with 3-fold increased CVD risk versus Low HbA1c. Both groups had similar age and diabetes duration. Non-HDLc and estimated glomerular filtration rate were associated with CVD risk only in Low HbA1c; albumin excretion rate was associated with CVD risk only in High HbA1c. Conclusions: These risk factor differences suggest that pathways to CVD may differ by glycemic control, potentially resulting in important implications for prognosis in type 1 diabetes.

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Diabeloop DBLG1 Closed-Loop System Enables Patients With Type 1 Diabetes to Significantly Improve Their Glycemic Control in Real-Life Situations Without Serious Adverse Events: 6-Month Follow-up

10.2337/figshare.13583129 ◽

2021 ◽

Author(s):

Coralie Amadou ◽

Sylvia Franc ◽

Pierre-Yves Benhamou ◽

Sandrine Lablanche ◽

Erik Huneker ◽

...

Keyword(s):

Type 1 Diabetes ◽

Glycemic Control ◽

Adverse Events ◽

Closed Loop ◽

Artificial Pancreas ◽

Real Life ◽

Serious Adverse Events ◽

Life Conditions ◽

Time In Range

OBJECTIVE To analyze safety and efficacy of the DBLG1 hybrid closed-loop artificial pancreas system in patients with Type 1 Diabetes in real life conditions. METHODS Following a one-week run-in period with usual pump, 25 patients were provided with the commercial DBLG1 system. We present the results of Time-in-Range and HbA1c over a 6-month period. RESULTS The mean (SD;range) age of patients was 43 years (13.8; 25-72). At baseline, mean HbA1c and TIR 70-180mg/dL were respectively 7.9% (0.93; 5.6- 8.5) [63mmol/mol (10; 38-69)] and 53% (16.4;21-85). One patient stopped using the system after 2 months. At 6-month, mean HbA1c decreased to 7.1% [54mmol/mol] (p<0.001) and TIR 70-180mg/dL increased to 69.7% (p<0.0001). TIR<70mg/dL decreased from 2.4 to 1.3% (p=0.03). TIR<54mg/dL decreased from 0.32 to 0.24% (p=0.42). No serious adverse event was reported during the study. CONCLUSION The DBLG1 System confirms its ability to significantly improve glycemic control in real life conditions, without serious adverse events.

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