Jose Garcia-Tirado, United States of America

University of Virginia Center for Diabetes Technology (CDT)
Dr. Jose Garcia-Tirado received his PhD in 2014 from the Department of Process and Energy, Universidad Nacional de Colombia. In 2014, he joined the Instituto Tecnológico Metropolitano (ITM) in Medellin, Colombia as Assistant Professor and head of the research group Quality, Metrology, and Production. At the end of 2017, Dr. Garcia- Tirado joined the Center for Diabetes Technology (CDT) as Research Associate. In March 2021, Dr. Garcia-Tirado was appointed as Assistant Professor of the CDT. His research interests include systems identification, estimation theory, receding-horizon control and estimation, and modeling of the glucose homeostasis. In his current work, Dr. Garcia-Tirado is mainly devoted to the refinement of a fully automated insulin delivery system (a.k.a. the artificial pancreas) to tackle automatically meaningful glycemic disturbances caused by meal intake and physical activity. Additional interests encompass but are not limited to the individualization of physiological models and behavioral patterns (eating and exercise patterns) from CGM, insulin pump, meal records, and activity tracker data.

Presenter of 1 Presentation

 Conference Calendar
ORAL PRESENTATION SESSION

FULLY AUTOMATED CLOSED-LOOP IN ADOLESCENTS WITH TYPE 1 DIABETES: A SAFETY AND FEASIBILITY STUDY

Date
Fri, 04.06.2021
Session Name
0340 - Oral Presentation 09 (ID 38)
Lecture Time
17:55 - 18:05
Presenter
Authors

Abstract

Background and Aims

Modern automated insulin delivery system (AID), relying on timely quantification of meals, have reliably improved glycemic control in people with Type 1 Diabetes (T1D) of all ages. Achieving similar control without meal information has so far proven elusive. We present a new generation closed loop control (CLC) algorithm designed for such use.

Methods

Adolescents with T1D were enrolled at the UVA Center for Diabetes Technology (CDT) in a supervised outpatient clinical trial comparing the legacy UVA CLC (USS) with our new algorithm (RCKT) during hybrid (HCL) and fully automated (FCL) use. Four 24h periods were studied with 3 meals repeated from day to day; the second and fourth dinner were unannounced. One algorithm was used for day 1-2 and the other for day 3-4, in random order. Glucose control was evaluated on standard CGM-based metric.

Results

Twenty-one adolescent participants signed consent at CDT. Eighteen completed the study. Time in range (TIR) overall was 79.1±11.4% vs 83.2±10.8 (p=0.22) with dinner bolus and 78.6±11.1% vs 84.5±7.4% (p=0.075) without, for USS and RCKT respectively. Focusing on dinner (6PM-midnight) TIR in HCL was 90.9±12.9% vs 97.8±5.7%, p=0.052, and 58.8±25.7% vs 77.0±22.6%, p=0.02, in FCL. There was no difference in time below 70mg/dL or occurrence of hypofig1.pngglycemia.

Conclusions

Our new AID algorithm was shown to be feasible in adolescents with T1D, equivalent to UVA legacy algorithm in hybrid use, and led to +18% TIR during un-bolused dinners. Additional studies are needed to assess its impact over several days of use and less supervised environments.

Hide