المؤلفون: Glantz, Namino M., Morales, Jessikah M., Bevier, Wendy C., Larez, Arianna, Hoppe, Charis B., Duncan, Ian, Mackenzie, Andrew, Kerr, David

المصدر: Health Equity ; volume 4, issue 1, page 142-149 ; ISSN 2473-1242

مصطلحات موضوعية: Health Information Management, Public Health, Environmental and Occupational Health, Health Policy, Health (social science)

الإتاحة: https://doi.org/10.1089/heq.2019.0119Test

المؤلفون: Bevier, Wendy C., Pinsker, Jordan E., Church, Mei Mei., Bradley, Paige K., Martinez, Jenny, Chen, Kong Y., Kerr, David

المصدر: The FASEB Journal ; volume 32, issue S1 ; ISSN 0892-6638 1530-6860

الوصف: Introduction For individuals with type 1 diabetes mellitus (T1DM) prolonged vigorous exercise requires careful planning to reduce risk of both hypoglycemia and hyperglycemia. In this case report we describe the experiences of a 59‐year old woman with T1DM who hiked the Camino de Santiago in Spain (805 km, 500 mile). Methods At the time of her trip she weighed 59 kg and height was 165 cm. She averaged 25.8 units/day total daily dose of insulin (56% basal), although this varied depending on her exercise level and less insulin was needed on days with physical activity. She used a continuous glucose monitor (CGM) [Dexcom G4® Platinum CGM (Dexcom Inc, San Diego, CA)] and an OmniPod® insulin pump system (Insulet Corporation, Billerica, MA). She wore a wGT3X‐BT triaxial accelerometry‐based activity monitor (ActiGraph Corporation, Pensacola, FL) on her left hip during the day and took it off at night. Results Thirty‐one of 33 trek days were included for analysis; 2 days excluded due to unreliable data. Her kilocalories of energy expenditure each day [Kcals (mean±SD) 1,481±523; range 248–2,332] and steps per day [33,340±9,828; range 5,239–50,454] mirrored the minutes spent in moderate to vigorous activity [MVPA minutes/day 316±108; range 54–484]. She hiked 21 – 40 km/day (13 – 25 miles) with 2 minimal activity “rest” days. There were 33 days of insulin pump and fingerstick blood glucose (BG) data; due to technical difficulties there were 14 days of CGM data. Her average total daily insulin dose during the trek gradually increased from 28 units/day to over 35 units/day, despite eating similar amounts of carbohydrates each day, reflecting an increased need for correction boluses (Figure). Her average morning fasting BG measurements stayed relatively stable (mid to low 100's mg/dL) until the last few days of the trip when her fasting BG rose to the 200 mg/dL range. Discussion In contrast to mild or moderate exercise, high intensity exercise may cause hyperglycemia that can last for several hours in individuals with T1DM. ...

الإتاحة: https://doi.org/10.1096/fasebj.2018.32.1_supplement.588.8Test

المؤلفون: Dasanayake, Isuru S, Bevier, Wendy C, Castorino, Kristin, Pinsker, Jordan E, Seborg, Dale E, Doyle, Francis J, Dassau, Eyal

المصدر: Journal of Diabetes Science and Technology, vol 9, iss 6

مصطلحات موضوعية: Prevention, Diabetes, Clinical Research, Autoimmune Disease, Cardiovascular, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, 4.1 Discovery and preclinical testing of markers and technologies, Metabolic and endocrine, Actigraphy, Adolescent, Adult, Aged, Algorithms, Automation, Biomarkers, Blood Glucose, Blood Glucose Self-Monitoring, Diabetes Mellitus, Type 1, Early Diagnosis, Exercise, Exercise Test, Female, Heart Rate, Humans, Hypoglycemia, Hypoglycemic Agents, Insulin Infusion Systems

الوقت: 1236 - 1245

الوصف: BackgroundEarly detection of exercise in individuals with type 1 diabetes mellitus (T1DM) may allow changes in therapy to prevent hypoglycemia. Currently there is limited experience with automated methods that detect the onset and end of exercise in this population. We sought to develop a novel method to quickly and reliably detect the onset and end of exercise in these individuals before significant changes in blood glucose (BG) occur.MethodsSixteen adults with T1DM were studied as outpatients using a diary, accelerometer, heart rate monitor, and continuous glucose monitor for 2 days. These data were used to develop a principal component analysis based exercise detection method. Subjects also performed 60 and 30 minute exercise sessions at 30% and 50% predicted heart rate reserve (HRR), respectively. The detection method was applied to the exercise sessions to determine how quickly the detection of start and end of exercise occurred relative to change in BG.ResultsMild 30% HRR and moderate 50% HRR exercise onset was identified in 6 ± 3 and 5 ± 2 (mean ± SD) minutes, while completion was detected in 3 ± 8 and 6 ± 5 minutes, respectively. BG change from start of exercise to detection time was 1 ± 6 and -1 ± 3 mg/dL, and, from the end of exercise to detection time was 6 ± 4 and -17 ± 13 mg/dL, respectively, for the 2 exercise sessions. False positive and negative ratios were 4 ± 2% and 21 ± 22%.ConclusionsThe novel method for exercise detection identified the onset and end of exercise in approximately 5 minutes, with an average BG change of only -6 mg/dL.

وصف الملف: application/pdf

العلاقة: qt25f1p5w7; https://escholarship.org/uc/item/25f1p5w7Test

الإتاحة: https://escholarship.org/uc/item/25f1p5w7Test

المؤلفون: Dasanayake, Isuru S., Bevier, Wendy C., Castorino, Kristin, Pinsker, Jordan E., Seborg, Dale E., Doyle, Francis J., Dassau, Eyal

المصدر: Journal of Diabetes Science and Technology ; volume 9, issue 6, page 1236-1245 ; ISSN 1932-2968 1932-2968

الوصف: Background: Early detection of exercise in individuals with type 1 diabetes mellitus (T1DM) may allow changes in therapy to prevent hypoglycemia. Currently there is limited experience with automated methods that detect the onset and end of exercise in this population. We sought to develop a novel method to quickly and reliably detect the onset and end of exercise in these individuals before significant changes in blood glucose (BG) occur. Methods: Sixteen adults with T1DM were studied as outpatients using a diary, accelerometer, heart rate monitor, and continuous glucose monitor for 2 days. These data were used to develop a principal component analysis based exercise detection method. Subjects also performed 60 and 30 minute exercise sessions at 30% and 50% predicted heart rate reserve (HRR), respectively. The detection method was applied to the exercise sessions to determine how quickly the detection of start and end of exercise occurred relative to change in BG. Results: Mild 30% HRR and moderate 50% HRR exercise onset was identified in 6 ± 3 and 5 ± 2 (mean ± SD) minutes, while completion was detected in 3 ± 8 and 6 ± 5 minutes, respectively. BG change from start of exercise to detection time was 1 ± 6 and −1 ± 3 mg/dL, and, from the end of exercise to detection time was 6 ± 4 and −17 ± 13 mg/dL, respectively, for the 2 exercise sessions. False positive and negative ratios were 4 ± 2% and 21 ± 22%. Conclusions: The novel method for exercise detection identified the onset and end of exercise in approximately 5 minutes, with an average BG change of only −6 mg/dL.

الإتاحة: https://doi.org/10.1177/1932296815592409Test

المؤلفون: Colberg, Sheri R., Bevier, Wendy C., Pinsker, Jordan E., Lee, Joon Bok, Ehrlich, Brigid, Dassau, Eyal, Doyle, Francis J., Chen, Kong Y., Kerr, David

المصدر: Journal of Diabetes Science and Technology ; volume 10, issue 4, page 993-994 ; ISSN 1932-2968 1932-2968

مصطلحات موضوعية: Biomedical Engineering, Bioengineering, Endocrinology, Diabetes and Metabolism, Internal Medicine

الإتاحة: https://doi.org/10.1177/1932296815625084Test

المؤلفون: Harvey, Rebecca A, Dassau, Eyal, Bevier, Wendy C, Seborg, Dale E, Jovanovič, Lois, Doyle, Francis J, Zisser, Howard C

المصدر: Diabetes Technology & Therapeutics, vol 16, iss 6

مصطلحات موضوعية: Prevention, Diabetes, Bioengineering, Autoimmune Disease, Patient Safety, Clinical Research, Metabolic and endocrine, Adult, Algorithms, Blood Glucose, Blood Glucose Self-Monitoring, Diabetes Mellitus, Type 1, Female, Humans, Hypoglycemia, Hypoglycemic Agents, Insulin, Insulin Infusion Systems, Male, Meals, Middle Aged, Monitoring, Physiologic, Pancreas, Artificial, Predictive Value of Tests, Clinical Sciences, Medical Physiology, Endocrinology & Metabolism

جغرافية الموضوع: 348 - 357

الوصف: BackgroundThis study was performed to evaluate the safety and efficacy of a fully automated artificial pancreas using zone-model predictive control (zone-MPC) with the health monitoring system (HMS) during unannounced meals and overnight and exercise periods.Subjects and methodsA fully automated closed-loop artificial pancreas was evaluated in 12 subjects (eight women, four men) with type 1 diabetes (mean±SD age, 49.4±10.4 years; diabetes duration, 32.7±16.0 years; glycosylated hemoglobin, 7.3±1.2%). The zone-MPC controller used an a priori model that was initialized using the subject's total daily insulin. The controller was designed to keep glucose levels between 80 and 140 mg/dL. A hypoglycemia prediction algorithm, a module of the HMS, was used in conjunction with the zone controller to alert the user to consume carbohydrates if the glucose level was predicted to fall below 70 mg/dL in the next 15 min.ResultsThe average time spent in the 70-180 mg/dL range, measured by the YSI glucose and lactate analyzer (Yellow Springs Instruments, Yellow Springs, OH), was 80% for the entire session, 92% overnight from 12 a.m. to 7 a.m., and 69% and 61% for the 5-h period after dinner and breakfast, respectively. The time spent < 60 mg/dL for the entire session by YSI was 0%, with no safety events. The HMS sent appropriate warnings to prevent hypoglycemia via short and multimedia message services, at an average of 3.8 treatments per subject.ConclusionsThe combination of the zone-MPC controller and the HMS hypoglycemia prevention algorithm was able to safely regulate glucose in a tight range with no adverse events despite the challenges of unannounced meals and moderate exercise.

وصف الملف: application/pdf

العلاقة: qt5024f7jq; https://escholarship.org/uc/item/5024f7jqTest

الإتاحة: https://escholarship.org/uc/item/5024f7jqTest

المؤلفون: Percival, Matthew W., Bevier, Wendy C., Wang, Youqing, Dassau, Eyal, Zisser, Howard C., Jovanovič, Lois, Doyle, Francis J.

المصدر: Journal of Diabetes Science and Technology ; volume 4, issue 5, page 1214-1228 ; ISSN 1932-2968 1932-2968

مصطلحات موضوعية: Biomedical Engineering, Bioengineering, Endocrinology, Diabetes and Metabolism, Internal Medicine

الوصف: Background: Estimation of the magnitude and duration of effects of carbohydrate (CHO) and subcutaneously administered insulin on blood glucose (BG) is required for improved BG regulation in people with type 1 diabetes mellitus (T1DM). The goal of this study was to quantify these effects in people with T1DM using a novel protocol. Methods: The protocol duration was 8 hours: A 1–3 U subcutaneous (SC) insulin bolus was administered and a 25-g CHO meal was consumed, with these inputs separated by 3–5 hours. The DexCom SEVEN® PLUS continuous glucose monitor was used to obtain SC glucose measurements every 5 minutes and YSI 2300 Stat Plus was used to obtain intravenous glucose measurements every 15 minutes. Results: The protocol was tested on 11 subjects at Sansum Diabetes Research Institute. The intersubject parameter coefficient of variation for the best identification method was 170%. The mean percentages of output variation explained by the bolus insulin and meal models were 68 and 69%, respectively, with root mean square error of 14 and 10 mg/dl, respectively. Relationships between the model parameters and clinical parameters were observed. Conclusion: Separation of insulin boluses and meals in time allowed unique identification of model parameters. The wide intersubject variation in parameters supports the notion that glucose-insulin models and thus insulin delivery algorithms for people with T1DM should be personalized. This experimental protocol could be used to refine estimates of the correction factor and the insulin-to-carbohydrate ratio used by people with T1DM.

الإتاحة: https://doi.org/10.1177/193229681000400522Test

المؤلفون: Finan, Daniel A., Doyle, Francis J., Palerm, Cesar C., Bevier, Wendy C., Zisser, Howard C., Jovanovič, Lois, Seborg, Dale E.

المصدر: Journal of Diabetes Science and Technology ; volume 3, issue 5, page 1192-1202 ; ISSN 1932-2968 1932-2968

مصطلحات موضوعية: Biomedical Engineering, Bioengineering, Endocrinology, Diabetes and Metabolism, Internal Medicine

الوصف: Background: A model-based controller for an artificial β cell requires an accurate model of the glucose—insulin dynamics in type 1 diabetes subjects. To ensure the robustness of the controller for changing conditions (e.g., changes in insulin sensitivity due to illnesses, changes in exercise habits, or changes in stress levels), the model should be able to adapt to the new conditions by means of a recursive parameter estimation technique. Such an adaptive strategy will ensure that the most accurate model is used for the current conditions, and thus the most accurate model predictions are used in model-based control calculations. Methods: In a retrospective analysis, empirical dynamic autoregressive exogenous input (ARX) models were identified from glucose—insulin data for nine type 1 diabetes subjects in ambulatory conditions. Data sets consisted of continuous (5-minute) glucose concentration measurements obtained from a continuous glucose monitor, basal insulin infusion rates and times and amounts of insulin boluses obtained from the subjects' insulin pumps, and subject-reported estimates of the times and carbohydrate content of meals. Two identification techniques were investigated: nonrecursive, or batch methods, and recursive methods. Batch models were identified from a set of training data, whereas recursively identified models were updated at each sampling instant. Both types of models were used to make predictions of new test data. For the purpose of comparison, model predictions were compared to zero-order hold (ZOH) predictions, which were made by simply holding the current glucose value constant for p steps into the future, where p is the prediction horizon. Thus, the ZOH predictions are model free and provide a base case for the prediction metrics used to quantify the accuracy of the model predictions. In theory, recursive identification techniques are needed only when there are changing conditions in the subject that require model adaptation. Thus, the identification and validation techniques were ...

الإتاحة: https://doi.org/10.1177/193229680900300526Test

المؤلفون: Zisser, Howard, Palerm, Cesar C., Bevier, Wendy C., Doyle, Francis J., Jovanovic, Lois

المصدر: Journal of Diabetes Science and Technology ; volume 3, issue 3, page 487-491 ; ISSN 1932-2968 1932-2968

مصطلحات موضوعية: Biomedical Engineering, Bioengineering, Endocrinology, Diabetes and Metabolism, Internal Medicine

الوصف: Background: This article provides a clinical update using a novel run-to-run algorithm to optimize prandial insulin dosing based on sparse glucose measurements from the previous day's meals. The objective was to use a refined run-to-run algorithm to calculate prandial insulin-to-carbohydrate ratios (I:CHO) for meals of variable carbohydrate content in subjects with type 1 diabetes (T1DM). Method: The open-labeled, nonrandomized study took place over a 6-week period in a nonprofit research center. Nine subjects with T1DM using continuous subcutaneous insulin infusion participated. Basal insulin rates were optimized using continuous glucose monitoring, with a target fasting blood glucose of 90 mg/dl. Subjects monitored blood glucose concentration at the beginning of the meal and at 60 and 120 minutes after the start of the meal. They were instructed to start meals with blood glucose levels between 70 and 130 mg/dl. Subjects were contacted daily to collect data for the previous 24-hour period and to give them the physician-approved, algorithm-derived I:CHO ratios for the next 24 hours. Subjects calculated the amount of the insulin bolus for each meal based on the corresponding I:CHO and their estimate of the meal's carbohydrate content. One- and 2-hour postprandial glucose concentrations served as the main outcome measures. Results: The mean 1-hour postprandial blood glucose level was 104 ± 19 mg/dl. The 2-hour postprandial levels (96.5 ± 18 mg/dl) approached the preprandial levels (90.1 ± 13 mg/dl). Conclusions: Run-to-run algorithms are able to improve postprandial blood glucose levels in subjects with T1DM.

الإتاحة: https://doi.org/10.1177/193229680900300312Test

المؤلفون: Bevier, Wendy C., Zisser, Howard C., Jovanovič, Lois, Finan, Daniel A., Palerm, Cesar C., Seborg, Dale E., Doyle, Francis J.

المصدر: Journal of Diabetes Science and Technology ; volume 2, issue 4, page 578-583 ; ISSN 1932-2968 1932-2968

الوصف: Background: Insulin requirements to maintain normoglycemia during glucocorticoid therapy and stress are often difficult to estimate. To simulate insulin resistance during stress, adults with type 1 diabetes mellitus (T1DM) were given a three-day course of prednisone. Methods: Ten patients (7 women, 3 men) using continuous subcutaneous insulin infusion pumps wore the Medtronic Minimed CGMS® (Northridge, CA) device. Mean (standard deviation) age was 43.1 (14.9) years, body mass index 23.9 (4.7) kg/m 2 , hemoglobin A1c 6.8% (1.2%), and duration of diabetes 18.7 (10.8) years. Each patient wore the CGMS for one baseline day (day 1), followed by three days of self-administered prednisone (60 mg/dl; days 2–4), and one post-prednisone day (day 5). Results: Analysis using Wilcoxon signed rank test (values are median [25th percentile, 75th percentile]) indicated a significant difference between day 1 and the mean of days on prednisone (days 2–4) for average glucose level (110.0 [81.0, 158.0] mg/dl vs 149.2 [137.7, 168.0] mg/dl; p = .022), area under the glucose curve and above the upper limit of 180 mg/dl per day (0.5 [0, 8.0] mg/dl·d vs 14.0 [7.7, 24.7] mg/dl·d; p = .002), and total daily insulin dose (TDI), (0.5 [0.4, 0.6] U/kg·d vs 0.9 [0.8, 1.0] U/kg·d; p = .002). In addition, the TDI was significantly different for day 1 vs day 5 (0.5 [0.4, 0.6] U/kg·d vs 0.6 [0.5, 0.8] U/kg·d; p = .002). Basal rates and insulin boluses were increased by an average of 69% (range: 30–100%) six hours after the first prednisone dose and returned to baseline amounts on the evening of day 4. Conclusions: For adults with T1DM, insulin requirements during prednisone induced insulin resistance may need to be increased by 70% or more to normalize blood glucose levels.

الإتاحة: https://doi.org/10.1177/193229680800200408Test