Eyal Dassau, United States of America

Harvard University SEAS

Moderator Of 1 Session

PARALLEL SESSION Webcast
Session Type
PARALLEL SESSION
Channel
Madrid
Date
22.02.2020, Saturday
Session Time
08:30 - 10:00

Presenter Of 5 Presentations

INVESTIGATING EFFECTS OF INSULIN ESTIMATION ON FUTURE INSULIN SENSORS’ DESIGN AND IMPLICATION FOR DIABETES MANAGEMENT

Abstract

Background and Aims

Incorporation of an insulin sensor may help to improve performance of future AP algorithms by reducing severe hypoglycemic events. Optimal insulin measurement intervals were identified for a feedback-based threshold suspend safety-layer.

Methods

Personalized Kalman filter-estimated plasma insulin concentration (EPIC) measurements were used to supplement a zone model predictive control algorithm. Insulin delivery was suspended when both CGM was <140 mg/dL and EPIC values were greater than a personalized threshold based on fasting basal insulin concentrations. EPIC measurements occurred at 5-, 30-, 60-, 120-, and 180-minute intervals. Using the UVA/Padova Simulator, the controller was evaluated across ten in-silico subjects for three 8-hour, 50-gram carbohydrate scenarios: 1) sixty-minute exercise, induced via increasing glucose uptake rates, one hour after an announced meal, 2) meal size overestimation by 35% with carbohydrate ratio underestimated by 25%, and 3) announced meal (baseline).

Results

Implementing the EPIC safety-layer, the mean percent time below 70 mg/dL decreased: from 8.09±9.08% to 2.47±5.24% for 5-minute, 7.07±7.75% for 30-minute, 7.57±8.28% for 60-minute, and 7.59±8.26% for 120- through 180-minute intervals (scenario 1); from 5.07±5.33% to 0.00±0.00% for 5- through 30-minute, 0.87±2.76% for 60-minute, 2.12±4.65% for 120-minute, and 3.16±5.38% for 180-minute intervals (scenario 2); and from 0.69±2.17% to 0.00±0.00% for 30- through 120-minute, while remaining at 0.69±2.17% for 180-minute intervals (scenario 3). Infrequent measurements of 30- to 120- minutes resulted in slight performance degradation with increasing sample time.

abstractattd_wolkowicz-table_glycemic control without insulin information compared with epic safety-layer measurement intervals_data shown as mean±standard deviation.png

*Indicates p-value<0.05

Conclusions

The EPIC safety-layer in-silico prevented severe hypoglycemia during challenging scenarios without significant rebound hyperglycemia. Future insulin sensors could potentially be designed utilizing 30- to 120-minute measurement intervals.

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Dexcom Real Time CGM In Pregnancy: Updates in Clinical Research and Practical Application

Session Type
INDUSTRY SESSION
Date
20.02.2020, Thursday
Session Time
13:00 - 14:30
Channel
Rome
Lecture Time
13:50 - 14:10

First clinical report of on-body artificial pancreas in pediatric and outpatient extended use of a mobile app

Session Type
PARALLEL SESSION
Date
20.02.2020, Thursday
Session Time
16:40 - 18:00
Channel
Auditorium A
Lecture Time
17:20 - 17:40

Decision support systems and closed loop

Session Type
PLENARY SESSION
Date
21.02.2020, Friday
Session Time
13:00 - 14:30
Channel
Auditorium A
Lecture Time
13:24 - 13:31

Identifying and classifying physical activity for robust automatic insulin delivery (AID) systems

Session Type
PARALLEL SESSION
Date
21.02.2020, Friday
Session Time
16:40 - 18:00
Channel
London
Lecture Time
17:00 - 17:20