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Publications (21)
Objective
Nocturnal hypoglycemia is a known challenge for people with type 1 diabetes, especially for physically active individuals or those on multiple daily injections. We developed an evidential neural network (ENN) to predict at bedtime the probability and timing of nocturnal hypoglycemia (0-4 vs 4-8 h after bedtime) based on several glucose me...
Exercise can cause dangerous fluctuations in blood glucose in people living with type 1 diabetes (T1D). Aerobic exercise, for example, can cause acute hypoglycemia secondary to increased insulin-mediated and non-insulin-mediated glucose utilization. Less is known about how resistance exercise (RE) impacts glucose dynamics. Twenty-five people with T...
Introduction:
DailyDose is a decision support system designed to provide real time dosing advice and weekly insulin dose adjustments for adults living with type 1 diabetes using multiple daily insulin injections.
Materials and methods:
Twenty-five adults were enrolled in this single-arm study. All participants used Dexcom G6 for continuous gluco...
DailyDose is a smart-phone decision support system developed at Oregon Health & Science University that uses Dexcom G6 CGM and Medtonic’s InPen. The app calculates insulin doses using CGM value and trend, insulin-on-board, carbohydrate amount, and exercise information. Insulin dosing and carbohydrate intake recommendations before and after exercise...
DailyDose is a decision support system developed at Oregon Health & Science University designed for people with T1D on MDI to improve glycemic control. It connects with Dexcom G6 and Medtronic's InPen. DailyDose runs on a smartphone and calculates insulin doses using CGM value and trend, IOB, carbohydrate amount, and exercise information. The syste...
Glucose dynamics during and after resistance exercise in people with T1D is not well understood. We recruited 25 people with T1D to perform 3 separate sessions of in-clinic resistance exercise under low (basal) , medium (1.5x basal) , or high (3.0x basal) insulin infusion levels. Blood glucose was clamped by intravenous dextrose infusion 3 hours pr...
Prevention of hypoglycemia (glucose <70 mg/dL) during aerobic exercise is a major challenge in type 1 diabetes. Providing predictions of glycemic changes during and following exercise can help people with type 1 diabetes avoid hypoglycemia. A unique dataset representing 320 days, and 50,000+ time points of glycemic measurements was collected in adu...
The accuracy of continuous glucose monitoring (CGM) sensors may be significantly impacted by exercise. We evaluated the impact of three different types of exercise on the accuracy of the Dexcom G6 sensor. Twenty-four adults with type 1 diabetes on multiple daily injections wore a G6 sensor. Participants were randomized to aerobic, resistance, or hi...
OBJECTIVE To assess the efficacy and feasibility of a dual-hormone (DH) closed-loop system with insulin and a novel liquid stable glucagon formulation compared with an insulin-only closed-loop system and a predictive low glucose suspend (PLGS) system.
RESEARCH DESIGN AND METHODS In a 76-h, randomized, crossover, outpatient study, 23 participants w...
Type 1 diabetes (T1D) is characterized by pancreatic beta cell dysfunction and insulin depletion. Over 40% of people with T1D manage their glucose through multiple injections of long-acting basal and short-acting bolus insulin, so-called multiple daily injections (MDI)1,2. Errors in dosing can lead to life-threatening hypoglycaemia events (<70 mg d...
Type 1 diabetes (T1D) is a chronic health condition resulting from pancreatic beta cell
dysfunction and insulin depletion. While automated insulin delivery systems are now available, many people choose to manage insulin delivery manually through insulin pumps or through multiple daily injections. Frequent insulin titrations are needed to adequately...
While automated insulin delivery (AID) systems are now commercially available, over 40 percent of people with type 1 diabetes manage their insulin with multiple daily injection therapy (MDI). AID systems can improve time-in-range in adults, however it is not clear if optimal MDI therapy can achieve the same glycemic targets. We have previously show...
Background:
Despite new glucose sensing technologies, nocturnal hypoglycemia is still a problem for people with type 1 diabetes (T1D) as symptoms and sensor alarms may not be detected while sleeping. Accurately predicting nocturnal hypoglycemia before sleep may help minimize nighttime hypoglycemia.
Methods:
A support vector regression (SVR) mode...
Automated insulin delivery systems for people with type 1 diabetes rely on an accurate subcutaneous glucose sensor and an infusion cannula that delivers insulin in response to measured glucose. Integrating the sensor with the infusion cannula would provide substantial benefit by reducing the number of devices inserted into subcutaneous tissue. We d...
Background:
People with type 1 diabetes (T1D) have varying sensitivities to insulin and also varying responses to meals and exercise. We introduce a new adaptive run-to-run model predictive control (MPC) algorithm that can be used to help people with T1D better manage their glucose levels using an artificial pancreas (AP). The algorithm adapts to i...
Background:
Decision support smartphone applications integrated with continuous glucose monitors may improve glycemic control in type 1 diabetes (T1D). We conducted a survey to understand trends and needs of potential users to inform the design of decision support technology.
Methods:
A 70-question survey was distributed October 2017 through May 2...
Purpose
We introduce two validated single (SH) and dual hormone (DH) mathematical models that represent an in-silico virtual patient population (VPP) for type 1 diabetes (T1D). The VPP can be used to evaluate automated insulin and glucagon delivery algorithms, so-called artificial pancreas (AP) algorithms that are currently being used to help peopl...
Most people with type 1 diabetes use multiple daily injections (MDI) therapy, yet there are limited decision support tools for this population. We designed and evaluated a K-nearest-neighbors decision support system (KNN-DSS) that utilizes continuous glucose data and Bluetooth-enabled insulin dose capture devices to detect problematic glycemic patt...
Exercise-related hypoglycemia in T1D is frequent and can be life-threatening. The ability to predict glucose changes at the start of exercise could significantly improve exercise outcomes for people with T1D. We developed multivariate adaptive regression splines (MARS) to predict changes to blood glucose dynamics and to assess whether including pas...
The complexity of T1D results in inadequate glucose control for patients which can lead to acute and chronic complications. We are developing a decision support smartphone application (app) for patients using multiple daily injection (MDI) therapy and continuous glucose monitoring (CGM). This app will use glucose trends, insulin dosing, and physica...
Inflammation is a ubiquitous phenomenon, resulting from such common disease states as obesity, injury, and sepsis, and it is associated with an elevated risk of thrombosis. During inflammation, neutrophils are activated and produce oxidants, such as hydrogen superoxide, which is then converted to hypochlorous acid (HOCl) through the action of the e...
