Blood Glucose Differences Between Left Arm and Right Arm Using a Continuous Glucose Monitor

2019 ◽  
Author(s):  
Keyword(s):  
Blood Glucose ◽  
Continuous Glucose Monitor

scholarly journals Delays in Minimally Invasive Continuous Glucose Monitoring Devices: A Review of Current Technology

2009 ◽  
Vol 3 (5) ◽  
pp. 1207-1214 ◽  
Author(s):  
D. Barry Keenan ◽  
John J. Mastrototaro ◽  
Gayane Voskanyan ◽  
Garry M. Steil
Keyword(s):  
Blood Glucose ◽  
Minimally Invasive ◽  
Continuous Glucose Monitoring ◽  
Ex Vivo ◽  
Time Lag ◽  
Glucose Monitoring ◽  
Time Lags ◽  
Continuous Glucose Monitor ◽  
Continuous Glucose Monitors

Through the use of enzymatic sensors—inserted subcutaneously in the abdomen or ex vivo by means of microdialysis fluid extraction—real-time minimally invasive continuous glucose monitoring (CGM) devices estimate blood glucose by measuring a patient's interstitial fluid (ISF) glucose concentration. Signals acquired from the interstitial space are subsequently calibrated with capillary blood glucose samples, a method that has raised certain questions regarding the effects of physiological time lags and of the duration of processing delays built into these devices. The time delay between a blood glucose reading and the value displayed by a continuous glucose monitor consists of the sum of the time lag between ISF and plasma glucose, in addition to the inherent electrochemical sensor delay due to the reaction process and any front-end signal-processing delays required to produce smooth traces. Presented is a review of commercially available, minimally invasive continuous glucose monitors with manufacturer-reported device delays. The data acquisition process for the Medtronic MiniMed (Northridge, CA) continuous glucose monitoring system—CGMS® Gold—and the Guardian® RT monitor is described with associated delays incurred for each processing step. Filter responses for each algorithm are examined using in vitro hypoglycemic and hyperglycemic clamps, as well as with an analysis of fast glucose excursions from a typical meal response. Results demonstrate that the digital filters used by each algorithm do not cause adverse effects to fast physiologic glucose excursions, although nonphysiologic signal characteristics can produce greater delays.

scholarly journals Sensor-Augmented Insulin Pumps and Hypoglycemia Prevention in Type 1 Diabetes

2016 ◽  
Vol 11 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Isabelle Steineck ◽  
Ajenthen Ranjan ◽  
Kirsten Nørgaard ◽  
Signe Schmidt
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Insulin Pump ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Insulin Pumps ◽  
Continuous Glucose Monitor ◽  
Insulin Suspension ◽  
Multiple Daily Injections

Hypoglycemia can lead to seizures, unconsciousness, or death. Insulin pump treatment reduces the frequency of severe hypoglycemia compared with multiple daily injections treatment. The addition of a continuous glucose monitor, so-called sensor-augmented pump (SAP) treatment, has the potential to further limit the duration and severity of hypoglycemia as the system can detect and in some systems act on impending and prevailing low blood glucose levels. In this narrative review we summarize the available knowledge on SAPs with and without automated insulin suspension, in relation to hypoglycemia prevention. We present evidence from randomized trials, observational studies, and meta-analyses including nonpregnant individuals with type 1 diabetes mellitus. We also outline concerns regarding SAPs with and without automated insulin suspension. There is evidence that SAP treatment reduces episodes of moderate and severe hypoglycemia compared with multiple daily injections plus self-monitoring of blood glucose. There is some evidence that SAPs both with and without automated suspension reduces the frequency of severe hypoglycemic events compared with insulin pumps without continuous glucose monitoring.

scholarly journals An Intensive Longitudinal Study of the Association of Stress With Hyperglycemia Using Real-Time Data Collection

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 180-180
Author(s):  
Brent Mausbach
Keyword(s):  
Blood Glucose ◽  
Linear Models ◽  
Significant Risk ◽  
Low Grade ◽  
Time Data ◽  
Continuous Glucose Monitor ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Ecological Momentary ◽  
Low Grade Inflammation

Abstract Caregivers of persons with dementia (PWD) are at significantly elevated risk for cardiovascular disease (CVD)s. A higher risk for diabetes is one potential mechanism of morbidity in caregivers. Diabetes has been associated with dyslipidemia, hypertension, oxidative stress, increased low-grade inflammation, and endothelial dysfunction, which all place individuals at risk for CVD. Elevated blood glucose, even in the nondiabetic range, is a significant risk marker for the development of CVD. The current study examined the semi-continuous association between stress and glucose. Participants wore a continuous glucose monitor that measured blood glucose every 5 minutes for a period of 10 days (n = 2,880/participant). Ecological Momentary Assessment (EMA) was used to measure stress, positive affect, negative affect, and dietary intake 3x/day over the 10-day period. Hierarchical linear models indicated significant within-person associations between stress and blood glucose levels (t = 3.88, df = 3.92, p = .018; R2 = 26.2%).

Continuous Glucose Monitoring Versus Self-monitoring of Blood Glucose in Children with Type 1 Diabetes—The Pros and Cons

2012 ◽  
Vol 08 (01) ◽  
pp. 27 ◽  
Author(s):  
Susana R Patton ◽  
Mark A Clements ◽  
◽  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Insulin Dose ◽  
Healthcare Providers ◽  
Glucose Monitoring ◽  
Continuous Glucose Monitor ◽  
Self Monitoring ◽  
Advantages And Disadvantages ◽  
Pros And Cons

Glucose monitoring is essential for modern diabetes treatment and the achievement of near-normal glycemic levels. Monitoring of blood glucose provides the data necessary for patients to make daily management decisions related to food intake, insulin dose, and physical exercise and it can enable patients to avoid potentially dangerous episodes of hypo- and hyperglycemia. Additionally, monitoring can provide healthcare providers with the information needed to identify glycemic patterns, educate patients, and adjust insulin. Presently, youth with type 1 diabetes can self-monitor blood glucose via home blood glucose meters, or monitor glucose concentrations nearly continuously using a continuous glucose monitor. There are advantages and disadvantages to the use of either of these technologies. This article describes the two technologies and the research supporting their use in the management of youth with type 1 diabetes in order to weigh their relative pros and cons.

scholarly journals A Comparison of Discovered Regularities in Blood Glucose Readings across Two Data Collection Approaches Used with a Type 1 Diabetic Youth

2017 ◽  
Vol 56 (S 01) ◽  
pp. e84-e91 ◽  
Author(s):  
Victor Lee ◽  
Travis Thurston ◽  
Chris Thurston
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Blood Sugar ◽  
Data Visualization ◽  
Continuous Glucose Monitor ◽  
The Third ◽  
The Family ◽  
Data Visualizations ◽  
Blind Spots

Summary Background: Type 1 diabetes requires frequent testing and monitoring of blood glucose levels in order to determine appropriate type and dosage of insulin administration. This can lead to thousands of individual measurements over the course of a lifetime of a single individual, of which very few are retained as part of a permanent record. The third author, aged 9, and his family have maintained several years of written records since his diagnosis with Type 1 diabetes at age 20 months, and have also recently begun to obtain automated records from a continuous glucose monitor. Objectives: This paper compares regularities identified within aggregated manually-collected and automatically-collected blood glucose data visualizations by the family involved in monitoring the third author’s diabetes. Methods: 7,437 handwritten entries of the third author’s blood sugar readings were obtained from a personal archive, digitized, and visualized in Tableau data visualization software. 6,420 automatically collected entries from a Dexcom G4 Platinum continuous glucose monitor were obtained and visualized in Dexcom’s Clarity data visualization report tool. The family was interviewed three times about diabetes data management and their impressions of data as presented in data visualizations. Interviews were audiorecorded or recorded with handwritten notes. Results: The aggregated visualization of manually-collected data revealed consistent habitual times of day when blood sugar measurements were obtained. The family was not fully aware that their existing life routines and the third author’s entry into formal schooling had created critical blind spots in their data that were often unmeasured. This was realized upon aggregate visualization of CGM data, but the discovery and use of these visualizations were not realized until a new healthcare provider required the family to find and use them. The lack of use of CGM aggregate visualization was reportedly because the default data displays seemed to provide already abundant information for in-the-moment decision making for diabetes management. Conclusions: Existing family routines and school schedules can shape if and when blood glucose data are obtained for T1D youth. These routines may inadvertently introduce blind spots in data, even when it is collected and recorded systematically. Although CGM data may be superior in its overall density of data collection, families do not necessarily discover nor use the full range of useful data visualization features. To support greater awareness of youth blood sugar levels, families that manually obtain youth glucose data should be advised to avoid inadvertently creating data blind spots due to existing schedules and routines. For families using CGM technology, designers and healthcare providers should consider implementing better cues and prompts that will encourage families to discover and utilize aggregate data visualization capabilities.

scholarly journals Enabling the Internet of Mobile Crowdsourcing Health Things: A Mobile Fog Computing, Blockchain and IoT Based Continuous Glucose Monitoring System for Diabetes Mellitus Research and Care

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3319 ◽  
Author(s):  
Tiago M. Fernández-Caramés ◽  
Iván Froiz-Míguez ◽  
Oscar Blanco-Novoa ◽  
Paula Fraga-Lamas
Keyword(s):  
Blood Glucose ◽  
Fog Computing ◽  
Storage System ◽  
Glucose Monitoring ◽  
Continuous Glucose Monitor ◽  
Self Monitoring ◽  
Mobile Crowdsourcing ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Diabetes Patients

Diabetes patients suffer from abnormal blood glucose levels, which can cause diverse health disorders that affect their kidneys, heart and vision. Due to these conditions, diabetes patients have traditionally checked blood glucose levels through Self-Monitoring of Blood Glucose (SMBG) techniques, like pricking their fingers multiple times per day. Such techniques involve a number of drawbacks that can be solved by using a device called Continuous Glucose Monitor (CGM), which can measure blood glucose levels continuously throughout the day without having to prick the patient when carrying out every measurement. This article details the design and implementation of a system that enhances commercial CGMs by adding Internet of Things (IoT) capabilities to them that allow for monitoring patients remotely and, thus, warning them about potentially dangerous situations. The proposed system makes use of smartphones to collect blood glucose values from CGMs and then sends them either to a remote cloud or to distributed fog computing nodes. Moreover, in order to exchange reliable, trustworthy and cybersecure data with medical scientists, doctors and caretakers, the system includes the deployment of a decentralized storage system that receives, processes and stores the collected data. Furthermore, in order to motivate users to add new data to the system, an incentive system based on a digital cryptocurrency named GlucoCoin was devised. Such a system makes use of a blockchain that is able to execute smart contracts in order to automate CGM sensor purchases or to reward the users that contribute to the system by providing their own data. Thanks to all the previously mentioned technologies, the proposed system enables patient data crowdsourcing and the development of novel mobile health (mHealth) applications for diagnosing, monitoring, studying and taking public health actions that can help to advance in the control of the disease and raise global awareness on the increasing prevalence of diabetes.

Results of a Multicenter Feasibility Study of an Automated Bedside Glucose Monitoring System in the Burn Intensive Care Setting

2019 ◽  
Vol 41 (3) ◽  
pp. 535-538
Author(s):  
Craig T Elder ◽  
Tera Thigpin ◽  
Rachel Karlnoski ◽  
David Smith ◽  
David Mozingo ◽  
...  
Keyword(s):  
Intensive Care ◽  
Blood Glucose ◽  
Critically Ill ◽  
Care Setting ◽  
Glucose Monitoring ◽  
Relative Difference ◽  
Serum Glucose ◽  
Burn Patients ◽  
Intensive Care Setting ◽  
Continuous Glucose Monitor

Abstract Intensive blood glucose regimens required for tight glycemic control in critically ill burn patients carry risk of hypoglycemia and are ultimately limited by the frequency of which serum glucose measurements can be feasibly monitored. Continuous inline glucose monitoring has the potential to significantly increase the frequency of serum glucose measurement. The objective of this study was to assess the accuracy of a continuous glucose monitor with inline capability (Optiscanner) in the burn intensive care setting. A multicenter, observational study was conducted at two academic burn centers. One hundred and six paired blood samples were collected from 10 patients and measured on the Optiscanner and the Yellow Springs Instrument. Values were plotted on a Clarke Error Grid and mean absolute relative difference calculated. Treatment was guided by existing hospital protocols using separately obtained values. 97.2% of results obtained from Optiscanner were within 25% of corresponding Yellow Springs Instrument values and 100% were within 30%. Mean absolute relative difference was calculated at 9.6%. Our findings suggest that a continuous glucose monitor with inline capability provides accurate blood glucose measurements among critically ill burn patients.

scholarly journals Improved Methods for Mid-Term Blood Glucose Level Prediction Using Dietary and Insulin Logs

Medicina ◽  
2021 ◽  
Vol 57 (7) ◽  
pp. 676
Author(s):  
Rebaz A. H. Karim ◽  
István Vassányi ◽  
István Kósa
Keyword(s):  
Blood Glucose ◽  
Blood Glucose Level ◽  
Glucose Level ◽  
Glucose Monitoring ◽  
Training Sample ◽  
Small Scale ◽  
Total Carbohydrate ◽  
Continuous Glucose Monitor ◽  
Lifestyle Management ◽  
Insulin Dependent

Background and Objectives: The daily lifestyle management of diabetes requires accurate predictions of the blood glucose level between meals. The objective of this study was to improve the accuracy achieved by previous work, especially on the mid-term, i.e., 120 to 180 min prediction horizons, for insulin-dependent patients. Materials and Methods: An absorption model-based method is proposed to train an artificial neural network with the bolus and basal insulin dosing and timing, the baseline blood glucose level, the maximal glucose infusion rate, and the total carbohydrate content as parameters. The approach was implemented in various algorithmic setups, and it was validated on data from a small-scale clinical trial with continuous glucose monitoring. Results: Root mean square error results for the mid-term horizons are 1.72 mmol/L (120 min) and 1.95 mmol/L (180 min). The accuracy of the proposed model measured on the clinical data is better than the accuracy reported by any other currently available and comparable models. Conclusions: A relatively short (ca. two weeks) training sample of a continuous glucose monitor and dietary/insulin log is sufficient to provide accurate predictions. For the outpatient application in practice, a hybrid model is proposed that combines the present mid-term method with the authors’ previous work for short-term predictions.

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