This proposal continues ten years of research on biobehavioral monitoring methods with proven utility to the assessment of Type 1 diabetes (T1DM), by taking the next logical step - from monitoring to feedback. We plan to test and validate the following general hypothesis: The optimization of glycemic control in T1DM, i.e. the maintenance of near-normal HbA1c without increasing the risk of hypoglycemia, is almost entirely dependent on the quality of two levels of feedback: (1) External behavioral level defined as the availability and utilization by patients of information about symptoms, awareness, risk of hypoglycemia, and HbA1c, and (2) Internal endocrine system level defined as the feedback networks of microvascular recruitment, hormonal counter regulation, and insulin-glucose interaction. Consequently, the proposed research plan includes field investigation of the utility of behavioral feedback (Phase 1) and hospital laboratory investigations of the internal feedback loops of insulin transfer (Phase 2) and counter regulation (Phase 3). Specifically: Phase 1 will create an Integrated Biobehavioral Monitoring and Feedback (IBMF) system and will investigate its clinical utility to improve glycemic control in a field outcomes study of T1 DM patients in their natural environment, assuming that the everyday behavioral control of T1DM depends on the quality of 4 sequential steps: monitoring -> assessment -> feedback to the patient -> behavioral optimization. Phase 2 will investigate, in T1DM subjects at low vs. high risk for hypoglycemia as determined in Phase 1, the time course of insulin transfer from circulation to iterstitium using a stochastic process model of insulin-induced microvascular recruitment and subsequent insulin transport through the capillary endothelium. Phase 3 will use a dynamical network model to investigate the time course of development, and the dynamical characteristics of hypoglycemia-associated autonomic failure (HAAF) in T1DM subjects at low vs. high risk for hypoglycemia as determined in Phase 1. Transferring the results from Phases 2 and 3 into Phase 1 we will clarify: (1) the relative contribution of insulin sensitivity and HAAF to risk for recurrent hypoglycemia in the field, and (2) the ability of IBMF to reverse HAAF and reduce risk of hypoglycemia, thereby contributing to improved glycemic control.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
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Behavioral Medicine, Interventions and Outcomes Study Section (BMIO)
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Garfield, Sanford A
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University of Virginia
Schools of Medicine
United States
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Kovatchev, Boris P (2017) Metrics for glycaemic control - from HbA1c to continuous glucose monitoring. Nat Rev Endocrinol 13:425-436
Kovatchev, Boris; Cobelli, Claudio (2016) Glucose Variability: Timing, Risk Analysis, and Relationship to Hypoglycemia in Diabetes. Diabetes Care 39:502-10
Kovatchev, Boris P; Breton, Marc D (2015) Hemoglobin A1c and Self-Monitored Average Glucose: Validation of the Dynamical Tracking eA1c Algorithm in Type 1 Diabetes. J Diabetes Sci Technol 10:330-5
Kovatchev, Boris P (2015) Measures of Risk and Glucose Variability in Adults Versus Youths. Diabetes Technol Ther 17:766-9
Kovatchev, Boris P; Patek, Stephen D; Ortiz, Edward Andrew et al. (2015) Assessing sensor accuracy for non-adjunct use of continuous glucose monitoring. Diabetes Technol Ther 17:177-86
Fabris, Chiara; Patek, Stephen D; Breton, Marc D (2015) Are Risk Indices Derived From CGM Interchangeable With SMBG-Based Indices? J Diabetes Sci Technol 10:50-9
Lv, Dayu; Kulkarni, Sandip D; Chan, Alice et al. (2015) Pharmacokinetic Model of the Transport of Fast-Acting Insulin From the Subcutaneous and Intradermal Spaces to Blood. J Diabetes Sci Technol 9:831-40
Lv, Dayu; Breton, Marc D; Farhy, Leon S (2013) Pharmacokinetics modeling of exogenous glucagon in type 1 diabetes mellitus patients. Diabetes Technol Ther 15:935-41
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Chan, A; Barrett, E J; Anderson, S M et al. (2012) Muscle microvascular recruitment predicts insulin sensitivity in middle-aged patients with type 1 diabetes mellitus. Diabetologia 55:729-36

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