Peter G. Jacobs

Feasibility of Continuous Long-Term Glucose Monitoring from a Subcutaneous Glucose Sensor in Humans

The feasibility of continuous long-term glucose monitoring in humans has not yet been demonstrated. Enzyme-based electrochemical glucose sensors with telemetric output were subcutaneously implanted and evaluated in five human subjects with type I diabetes. Subject-worn radio-receiver data-loggers stored sensor outputs. Every 1-4 weeks the subjects glucose levels were manipulated through the full clinical range of interest using standard protocols. Reference blood glucose samples were obtained every 5-10 min and analyzed in our hospital clinical laboratory and/or on glucose meters. The sensor data were evaluated versus the reference data by linear least squares regression and by the Clarke Error Grid method. After surgical explantation and device inspection, the tissue-sensor interface was evaluated histologically. The remaining sensor-membranes were also recalibrated for comparison with preimplant performance. Four of the five glucose sensors tracked glucose in vivo. One sensor responded to manipulated glucose changes for 6.2 months with clinically useful performance (>/=90% of sensor glucose values within the A and B regions of the Clarke Error Grid). For this sensor, recalibration was required every 1-4 weeks. The other three transiently responding sensors had electronic problems associated with packaging failure. The remaining sensor never tracked glucose because of failure to form any sustained connection to adjacent subcutaneous tissue. Thus, stable, clinically useful sensor performance was demonstrated in one of five subjects with diabetes for a sustained interval of greater than 6 months. While this glucose sensor implant technology shows promise in humans, it needs to be made more reliable and robust with respect to device packaging and sensor-tissue connection.

A controlled study of the effectiveness of an adaptive closed-loop algorithm to minimize corticosteroid-induced stress hyperglycemia in type 1 diabetes.

To be effective in type 1 diabetes, algorithms must be able to limit hyperglycemic excursions resulting from medical and emotional stress. We tested an algorithm that estimates insulin sensitivity at regular intervals and continually adjusts gain factors of a fading memory proportional-derivative (FMPD) algorithm. In order to assess whether the algorithm could appropriately adapt and limit the degree of hyperglycemia, we administered oral hydrocortisone repeatedly to create insulin resistance. We compared this indirect adaptive proportional-derivative (APD) algorithm to the FMPD algorithm, which used fixed gain parameters. Each subject with type 1 diabetes (n = 14) was studied on two occasions, each for 33 h. The APD algorithm consistently identified a fall in insulin sensitivity after hydrocortisone. The gain factors and insulin infusion rates were appropriately increased, leading to satisfactory glycemic control after adaptation (premeal glucose on day 2, 148 ± 6 mg/dl). After sufficient time was allowed for adaptation, the late postprandial glucose increment was significantly lower than when measured shortly after the onset of the steroid effect. In addition, during the controlled comparison, glycemia was significantly lower with the APD algorithm than with the FMPD algorithm. No increase in hypoglycemic frequency was found in the APD-only arm. An afferent system of duplicate amperometric sensors demonstrated a high degree of accuracy; the mean absolute relative difference of the sensor used to control the algorithm was 9.6 ± 0.5%. We conclude that an adaptive algorithm that frequently estimates insulin sensitivity and adjusts gain factors is capable of minimizing corticosteroid-induced stress hyperglycemia.

Randomized trial of a dual‐hormone artificial pancreas with dosing adjustment during exercise compared with no adjustment and sensor‐augmented pump therapy

To test whether adjusting insulin and glucagon in response to exercise within a dual‐hormone artificial pancreas (AP) reduces exercise‐related hypoglycaemia.

Nonadjunctive Use of Continuous Glucose Monitoring for Diabetes Treatment Decisions.

While self-monitoring of blood glucose (SMBG) is the current standard used by people with diabetes to manage glucose levels, recent improvements in accuracy of continuous glucose monitoring (CGM) technology are making it very likely that diabetes-related treatment decisions will soon be made based on CGM values alone. Nonadjunctive use of CGM will lead to a paradigm shift in how patients manage their glucose levels and will require substantial changes in how care providers educate their patients, monitor their progress, and provide feedback to help them manage their diabetes. The approval to use CGM nonadjunctively is also a critical step in the pathway toward FDA approval of an artificial pancreas system, which is further expected to transform diabetes care for people with type 1 diabetes. In this article, we discuss how nonadjunctive CGM is expected to soon replace routine SMBG and how this new usage scenario is expected to transform health outcomes and patient care.

Incorporating an exercise detection, grading, and hormone dosing algorithm into the artificial pancreas using accelerometry and heart rate

In this article, we present several important contributions necessary for enabling an artificial endocrine pancreas (AP) system to better respond to exercise events. First, we show how exercise can be automatically detected using body-worn accelerometer and heart rate sensors. During a 22 hour overnight inpatient study, 13 subjects with type 1 diabetes wearing a Zephyr accelerometer and heart rate monitor underwent 45 minutes of mild aerobic treadmill exercise while controlling their glucose levels using sensor-augmented pump therapy. We used the accelerometer and heart rate as inputs into a validated regression model. Using this model, we were able to detect the exercise event with a sensitivity of 97.2% and a specificity of 99.5%. Second, from this same study, we show how patients’ glucose declined during the exercise event and we present results from in silico modeling that demonstrate how including an exercise model in the glucoregulatory model improves the estimation of the drop in glucose during exercise. Last, we present an exercise dosing adjustment algorithm and describe parameter tuning and performance using an in silico glucoregulatory model during an exercise event.

Falls, Functioning, and Disability Among Women With Persistent Symptoms of Chemotherapy-Induced Peripheral Neuropathy

Purpose Chemotherapy-induced peripheral neuropathy (CIPN) may persist after treatment ends and may lead to functional decline and falls. This study compared objective and self-report measures of physical function, gait patterns, and falls between women cancer survivors with and without symptoms of CIPN to identify targets for functional rehabilitation. Methods A secondary data analysis of 512 women cancer survivors (age, 62 ± 6 years; time since diagnosis, 5.8 ± 4.1 years) categorized and compared women self-reporting symptoms of CIPN (CIPN+) with asymptomatic women (CIPN-) on the following: maximal leg strength, timed chair stand, physical function battery, gait characteristics (speed; step number, rate, and length; base of support), self-report physical function and disability, and falls in the past year. Results After an average of 6 years after treatment, 47% of women still reported symptoms of CIPN. CIPN+ had significantly worse self-report and objectively measured function than did CIPN-, with the exception of maximal leg strength and base of support during a usual walk. Gait was slower among CIPN+, with those women taking significantly more, but slower and shorter, steps than did CIPN- (all P < .05). CIPN+ reported significantly more disability and 1.8 times the risk of falls compared with CIPN- ( P < .0001). Increasing symptom severity was linearly associated with worsening function, increasing disability, and higher fall risk (all P < .05). Conclusion This work makes a significant contribution toward understanding the functional impact of CIPN symptoms on cancer survivors. Remarkably, 47% of women in our sample had CIPN symptoms many years after treatment, together with worse function, greater disability, and more falls. CIPN must be assessed earlier in the clinical pathway, and strategies to limit symptom progression and to improve function must be included in clinical and survivorship care plans.

Development of a fully automated closed loop artificial pancreas control system with dual pump delivery of insulin and glucagon

Patients with diabetes have difficulty controlling their blood sugar and suffer from acute effects of hypoglycemia and long-term effects of hyperglycemia, which include disease of the eyes, kidneys and nerves/feet. In this paper, we describe a new system that is used to automatically control blood sugar in people with diabetes through the fully automated measurement of blood glucose levels and the delivery of insulin and glucagon via the subcutaneous route. When a patients blood sugar goes too high, insulin is given to the patient to bring his/her blood sugar back to a normal level. To prevent a patients blood sugar from going too low, the patient is given a hormone called glucagon which raises the patients blood sugar. While other groups have described methods for automatically delivering insulin and glucagon, many of these systems still require human interaction to enter the venous blood sugar levels into the control system. This paper describes the development of a fully automated closed-loop dual sensor bi-hormonal artificial pancreas system that does not require human interaction. The system described in this paper is comprised of two sensors for measuring glucose, two pumps for independent delivery of insulin and glucagon, and a laptop computer running a custom software application that controls the sensor acquisition and insulin and glucagon delivery based on the glucose values recorded. Two control algorithms are designed into the software: (1) an algorithm that delivers insulin and glucagon according to their proportional and derivative errors and proportional and derivative gains and (2) an adaptive algorithm that adjusts the gain factors based on the patients current insulin sensitivity as determined using a mathematical model. Results from this work may ultimately lead to development of a portable, easy to use, artificial pancreas device that can enable far better glycemic control in patients with diabetes.

Effect of Repeated Glucagon Doses on Hepatic Glycogen in Type 1 Diabetes: Implications for a Bihormonal Closed-Loop System.

OBJECTIVE To evaluate subjects with type 1 diabetes for hepatic glycogen depletion after repeated doses of glucagon, simulating delivery in a bihormonal closed-loop system. RESEARCH DESIGN AND METHODS Eleven adult subjects with type 1 diabetes participated. Subjects underwent estimation of hepatic glycogen using 13C MRS. MRS was performed at the following four time points: fasting and after a meal at baseline, and fasting and after a meal after eight doses of subcutaneously administered glucagon at a dose of 2 µg/kg, for a total mean dose of 1,126 µg over 16 h. The primary and secondary end points were, respectively, estimated hepatic glycogen by MRS and incremental area under the glucose curve for a 90-min interval after glucagon administration. RESULTS In the eight subjects with complete data sets, estimated glycogen stores were similar at baseline and after repeated glucagon doses. In the fasting state, glycogen averaged 21 ± 3 g/L before glucagon administration and 25 ± 4 g/L after glucagon administration (mean ± SEM) (P = NS). In the fed state, glycogen averaged 40 ± 2 g/L before glucagon administration and 34 ± 4 g/L after glucagon administration (P = NS). With the use of an insulin action model, the rise in glucose after the last dose of glucagon was comparable to the rise after the first dose, as measured by the 90-min incremental area under the glucose curve. CONCLUSIONS In adult subjects with well-controlled type 1 diabetes (mean A1C 7.2%), glycogen stores and the hyperglycemic response to glucagon administration are maintained even after receiving multiple doses of glucagon. This finding supports the safety of repeated glucagon delivery in the setting of a bihormonal closed-loop system.

MobileRF: a robust device-free tracking system based on a hybrid neural network HMM classifier

We present a device-free indoor tracking system that uses received signal strength (RSS) from radio frequency (RF) transceivers to estimate the location of a person. While many RSS-based tracking systems use a body-worn device or tag, this approach requires no such tag. The approach is based on the key principle that RF signals between wall-mounted transceivers reflect and absorb differently depending on a persons movement within their home. A hierarchical neural network hidden Markov model (NN-HMM) classifier estimates both movement patterns and stand vs. walk conditions to perform tracking accurately. The algorithm and features used are specifically robust to changes in RSS mean shifts in the environment over time allowing for greater than 90% region level classification accuracy over an extended testing period. In addition to tracking, the system also estimates the number of people in different regions. It is currently being developed to support independent living and long-term monitoring of seniors.

Fabrication of a Flexible Amperometric Glucose Sensor Using Additive Processes

This study details the use of printing and other additive processes to fabricate a novel amperometric glucose sensor. The sensor was fabricated using a Au coated 12.7 micron polyimide film as a starting material, where micro-contact printing, electrochemical plating and chloridization, electrohydrodynamic jet (e-jet) printing, and spin coating were used to pattern, deposit, print, and coat functional materials, respectively. We have found that e-jet printing was effective for the deposition and patterning of glucose oxidase inks between ~5 to 1000 micron in width, and we have demonstrated that the enzyme was still active after printing. The thickness of the permselective layer was optimized to obtain a linear response to glucose concentration up to 32 mM. For these sensors no response to acetaminophen, a common interfering compound, was observed.