bluuebunny/crossref_metadata_2025 huggingface dataset:
Exercise and Glucose Metabolism in Persons with Diabetes Mellitus: Perspectives on the Role for Continuous Glucose Monitoring
Authors: Riddell Michael , Perkins Bruce A.
Published: January 2014

Exercise causes profound changes in glucose homeostasis. For people with type 1 diabetes, aerobic exercise usually causes blood glucose concentration to drop rapidly, while anaerobic exercise may cause it to rise, thereby making glycemic control challenging. Having the capacity to know their glucose levels and the direction of change during exercise increases self-efficacy in these persons who are prone to hypo- and hyperglycemia. For people with type 2 diabetes, learning first hand that regular exercise improves glucose levels may be a motivating factor in getting them to be more active. Continuous glucose monitoring is a potentially useful adjunct to diabetes management for the active person with either forms of diabetes. This review aims to guide the reader to use this technology to its maximum advantage by providing an overview of technical features, performance characteristics, and clinical utility, all balanced against the limitations that may be more prominent during physical activity.
Numerical and Clinical Accuracy of a Continuous Glucose Monitoring System during Intravenous Insulin Therapy in the Surgical and Burn Intensive Care Units
Authors: Rabiee Atoosa , Andreasik Virginia , Abu-Hamdah Rania , Galiatsatos Panagis , Khouri Zeina , Gibson B. Robert , Andersen Dana K. , Elahi Dariush
Published: January 2014

Background:

Intensive insulin therapy (IIT) for glycemic control in critically ill patients has been shown to be beneficial. Continuous glucose monitoring systems (CGMSs) have been approved as an adjunct to complement standard glucose monitoring in type 2 diabetes mellitus. This study was designed to evaluate the accuracy of a real-time CGMS (DexCom™ STS) in the intensive care unit (ICU). We also evaluated its reliability and accuracy using a hyperinsulinemic-euglycemic and a hyperglycemic clamp study.

Methods:

Nineteen patients were enrolled in this 7-day study [13 = surgical intensive care unit (SICU), 6 = burn intensive care unit (BICU)]. The patients were on IIT for at least 2 h prior the subcutaneous sensor insertion. Mean age and body mass index for SICU and BICU patients were 60.3 ± 3.7 and 64.5 ± 6.2 years and 36.6 ± 5.0 and 33.85 ± 3.4 kg/m2, respectively. DexCom accuracy was analyzed separately for the Johnson & Johnson (J&J) calibration finger sticks, Roche Accucheck finger sticks, and the Hitachi 917 analyzer measurements on serum using Clarke error grid analysis and Bland—Altman analysis. In the clamp studies, 20 patients were enrolled, and the data were analyzed similarly.

Results:

There were 1065 pairs of DexCom—Accucheck, 232 pairs of DexCom—J&J, and 84 pairs of DexCom—Hitachi in ICU patients. For DexCom—Accucheck, 68.26% of the pairs fell into zone A, 31.83% into zone B, and 0.75% into zone C. There were no values in zones D or E. From the 1102 matching DexCom—Beckman pairs in clamp studies, 42.29% were in zone A, 55.90% were in zone B, and 4.08% were in zone C.

Conclusions:

Despite the high percentage of measurements in zones A and B, underestimation of hypoglycemia by DexCom measurements makes it an unreliable device in the ICU setting.
Continuous Glucose Monitoring and Clinical Trials
Authors: Heinemann Lutz
Published: January 2014

The use of glucose sensors during clinical trials seems like a great idea at first glance. Continuous glucose monitoring (CGM) should allow the gathering of more detailed information about metabolic control, without requiring much additional effort. In principle, CGM can reduce the duration of such studies and the number of participants required. The aim of this commentary is to highlight some of the reasons why, in practice, at least some of these hopes have not been realized. It is not only that a new technology requires extensive training of the study personnel; the practical handling of the devices and the time and effort required to download and analyze the data are often grossly underestimated initially. In addition, one must select the best endpoints for describing the level of metabolic control in view of the overwhelming amount of information provided by CGM. Several measures and endpoints were proposed as (potential) parameters that would be more meaningful than the standard parameters currently used to describe glucose profiles. Unfortunately, most of these proposed parameters have not, as yet, been proven to be more meaningful. Calibration is another critical aspect of using CGM that must be addressed. How this procedure is handled in practice has a profound impact on the quality of the glucose recordings. Finally, shall the current measurement results be displayed to the study participant or not? CGM can help prevent severe hypoglycemic episodes, but this can profoundly affect the study outcome in a manner that is unrelated to basic aim of the study (e.g., comparing medications that are designed to control glycemia). Therefore, the use of CGM in clinical trials requires much more careful consideration than was initially thought.
Sources of Glycemic Variability—What Type of Technology is Needed?
Authors: Kildegaard Jonas , Christensen Toke Folke , Hejlesen Ole Kristian
Published: January 2014

People on insulin therapy are challenged with evaluation of numerous factors affecting the blood glucose in order to select the optimal dose for reaching their glucose target. Following medical recommendations precisely still results in considerable blood glucose unpredictability, often resulting in frustration in the short term due to hypoglycemia and hyperglycemia, and, in the long term, will likely result in complications.

The kinetics of insulin do indeed vary significantly and have become an important focus when developing new insulin analogues and delivery systems; however, numerous of other factors impact glycemic variability. These have different dependences and interactions and are therefore difficult to characterize. Some of the factors are highly dependent and influenced by the type of insulin and devices used in therapy. Development of future therapy products is therefore highly focused on how to minimize glycemic variability.
The Role of Reimbursement in the Adoption of Continuous Glucose Monitors
Authors: Bartelme Amanda , Bridger Perry
Published: January 2014

Continuous glucose monitors are a clinically meaningful addition to treatment plans for patients with diabetes who are actively managing their care. Since they first became commercially available, much progress has been made to ensure coverage of these devices for patients, but inadequate reimbursement of clinicians' time continues to serve as a barrier to adoption.
Glucose Clamp Algorithms and Insulin Time-Action Profiles
Authors: Bequette B. Wayne
Published: January 2014

Motivation:

Most current insulin pumps include an insulin-on-board (IOB) feature to help subjects avoid problems associated with “insulin stacking.” In addition, many control algorithms proposed for a closed-loop artificial pancreas make use of IOB to reduce the probability of hypoglycemic events that often occur due to the integral action of the controller. The IOB curves are generated from the pharmacodynamic (time-activity profiles) actions of subcutaneous insulin, which are obtained from glycemic clamp studies.

Methods:

Glycemic clamp algorithms are reviewed and in silico studies are performed to analyze the effect of glucose meter bias and noise on glycemic control and the manipulated glucose infusion rates. The glucose infusion rates are used to obtain insulin time-activity profiles, which are then used to generate IOB curves.

Results:

A model-based, three-step-ahead controller is shown to be equivalent to a proportional-integral control algorithm with time-delay compensation. A systematic glucose meter bias of +6 mg/dl results in a decrease in the glucose area under the curve of 3% but no change in the IOB profiles.

Conclusions:

Based on these preliminary simulation studies, a substantial amount of glucose meter bias and noise during a glycemic clamp can be tolerated with little net effect on the IOB curves. It is suggested that handheld glucose meters can therefore be used in clamp studies if the measurements are filtered (averaged) before processing by the control algorithm. Clinical studies are needed to confirm these preliminary results.
Closed-Loop Artificial Pancreas Using Subcutaneous Glucose Sensing and Insulin Delivery and a Model Predictive Control Algorithm: Preliminary Studies in Padova and Montpellier
Authors: Bruttomesso Daniela , Farret Anne , Costa Silvana , Marescotti Maria Cristina , Vettore Monica , Avogaro Angelo , Tiengo Antonio , Dalla Man Chiara , Place Jerome , Facchinetti Andrea , Guerra Stefania , Magni Lalo , De Nicolao Giuseppe , Cobelli Claudio , Renard Eric , Maran Alberto
Published: January 2014

New effort has been made to develop closed-loop glucose control, using subcutaneous (SC) glucose sensing and continuous subcutaneous insulin infusion (CSII) from a pump, and a control algorithm. An approach based on a model predictive control (MPC) algorithm has been utilized during closed-loop control in type 1 diabetes patients. Here we describe the preliminary clinical experience with this approach.

In Padova, two out of three subjects showed better performance with the closed-loop system compared to open loop. Altogether, mean overnight plasma glucose (PG) levels were 134 versus 111 mg/dl during open loop versus closed loop, respectively. The percentage of time spent at PG > 140 mg/dl was 45% versus 12%, while postbreakfast mean PG was 165 versus 156 mg/dl during open loop versus closed loop, respectively. Also, in Montpellier, two patients out of three showed a better glucose control during closed-loop trials. Avoidance of nocturnal hypoglycemic excursions was a clear benefit during algorithm-guided insulin delivery in all cases.

This preliminary set of studies demonstrates that closed-loop control based entirely on SC glucose sensing and insulin delivery is feasible and can be applied to improve glucose control in patients with type 1 diabetes, although the algorithm needs to be further improved to achieve better glycemic control.

Six type 1 diabetes patients (three in each of two clinical investigation centers in Padova and Montpellier), using CSII, aged 36 ± 8 and 48 ± 6 years, duration of diabetes 12 ± 8 and 29 ± 4 years, hemoglobin A1c 7.4% ± 0.1% and 7.3% ± 0.3%, body mass index 23.2 ± 0.3 and 28.4 ± 2.2 kg/m2, respectively, were studied on two occasions during 22 h overnight hospital admissions 2–4 weeks apart. A Freestyle Navigator® continuous glucose monitor and an OmniPod® insulin pump were applied in each trial. Admission 1 used open-loop control, while admission 2 employed closed-loop control using our MPC algorithm.
Automatic Data Processing to Achieve a Safe Telemedical Artificial Pancreas
Authors: Hernando M. Elena , García-Sáez Gema , Martínez-Sarriegui Iñaki , Rodríguez-Herrero Agustín , Pérez-Gandía Carmen , Rigla Mercedes , de Leiva Alberto , Capel Ismael , Pons Belén , Gómez Enrique J.
Published: January 2014

Background:

The use of telemedicine for diabetes care has evolved over time, proving that it contributes to patient self-monitoring, improves glycemic control, and provides analysis tools for decision support. The timely development of a safe and robust ambulatory artificial pancreas should rely on a telemedicine architecture complemented with automatic data analysis tools able to manage all the possible high-risk situations and to guarantee the patient's safety.

Methods:

The Intelligent Control Assistant system (INCA) telemedical artificial pancreas architecture is based on a mobile personal assistant integrated into a telemedicine system. The INCA supports four control strategies and implements an automatic data processing system for risk management (ADP-RM) providing short-term and medium-term risk analyses. The system validation comprises data from 10 type 1 pump-treated diabetic patients who participated in two randomized crossover studies, and it also includes in silico simulation and retrospective data analysis.

Results:

The ADP-RM short-term risk analysis prevents hypoglycemic events by interrupting insulin infusion. The pump interruption has been implemented in silico and tested for a closed-loop simulation over 30 hours. For medium-term risk management, analysis of capillary blood glucose notified the physician with a total of 62 alarms during a clinical experiment (56% for hyperglycemic events). The ADP-RM system is able to filter anomalous continuous glucose records and to detect abnormal administration of insulin doses with the pump.

Conclusions:

Automatic data analysis procedures have been tested as an essential tool to achieve a safe ambulatory telemedical artificial pancreas, showing their ability to manage short-term and medium-term risk situations.
Blood Glucose Controller for Neonatal Intensive Care: Virtual Trials Development and First Clinical Trials
Authors: Compte Aaron Le , Chase J. Geoffrey , Lynn Adrienne , Hann Chris , Shaw Geoffrey , Wong Xing-Wei , Lin Jessica
Published: January 2014

Background:

Premature neonates often experience hyperglycemia, which has been linked to worsened outcomes. Insulin therapy can assist in controlling blood glucose (BG) levels. However, a reliable, robust control protocol is required to avoid hypoglycemia and to ensure that clinically important nutrition goals are met.

Methods:

This study presents an adaptive, model-based predictive controller designed to incorporate the unique metabolic state of the neonate. Controller performance was tested and refined in virtual trials on a 25-patient retrospective cohort. The effects of measurement frequency and BG sensor error were evaluated. A stochastic model of insulin sensitivity was used in control to provide a guaranteed maximum 4% risk of BG < 72 mg/dl to protect against hypoglycemia as well as account for patient variability over 1–3 h intervals when determining the intervention. The resulting controller is demonstrated in two 24 h clinical neonatal pilot trials at Christchurch Women's Hospital.

Results:

Time in the 72–126 mg/dl BG band was increased by 103–161% compared to retrospective clinical control for virtual trials of the controller, with fewer hypoglycemic measurements. Controllers were robust to BG sensor errors. The model-based controller maintained glycemia to a tight target control range and accounted for interpatient variability in patient glycemic response despite using more insulin than the retrospective case, illustrating a further measure of controller robustness. Pilot clinical trials demonstrated initial safety and efficacy of the control method.

Conclusions:

A controller was developed that made optimum use of the very limited available BG measurements in the neonatal intensive care unit and provided robustness against BG sensor error and longer BG measurement intervals. It used more insulin than typical sliding scale approaches or retrospective hospital control. The potential advantages of a model-based approach demonstrated in simulation were applied to initial clinical trials.
A Closed-Loop Artificial Pancreas Using Model Predictive Control and a Sliding Meal Size Estimator
Authors: Lee Hyunjin , Buckingham Bruce A. , Wilson Darrell M. , Bequette B. Wayne
Published: January 2014

The objective of this article is to present a comprehensive strategy for a closed-loop artificial pancreas. A meal detection and meal size estimation algorithm is developed for situations in which the subject forgets to provide a meal insulin bolus. A pharmacodynamic model of insulin action is used to provide insulin-on-board constraints to explicitly include the future effect of past and currently delivered insulin boluses. In addition, a supervisory pump shut-off feature is presented to avoid hypoglycemia. All of these components are used in conjunction with a feedback control algorithm using model predictive control (MPC). A model for MPC is developed based on a study of 20 subjects and is tested in a hypothetical clinical trial of 100 adolescent and 100 adult subjects using a Food and Drug Administration-approved diabetic subject simulator. In addition, a performance comparison of previously and newly proposed meal size estimation algorithms using 200 in silico subjects is presented. Using the new meal size estimation algorithm, the integrated artificial pancreas system yielded a daily mean glucose of 138 and 132 mg/dl for adolescents and adults, respectively, which is a substantial improvement over the MPC-only case, which yielded 159 and 145 mg/dl.
Run-to-Run Tuning of Model Predictive Control for Type 1 Diabetes Subjects: In Silico Trial
Authors: Magni Lalo , Forgione Marco , Toffanin Chiara , Dalla Man Chiara , Kovatchev Boris , De Nicolao Giuseppe , Cobelli Claudio
Published: January 2014

Background:

The technological advancements in subcutaneous continuous glucose monitoring and insulin pump delivery systems have paved the way to clinical testing of artificial pancreas devices. The experience derived by clinical trials poses technological challenges to the automatic control expert, the most notable being the large interpatient and intrapatient variability and the inherent uncertainty of patient information.

Methods:

A new model predictive control (MPC) glucose control system is proposed. The starting point is an MPC algorithm applied in 20 type 1 diabetes mellitus (T1DM) subjects. Three main changes are introduced: individualization of the ARX model used for prediction; synthesis of the MPC law on top of the open-loop basal/bolus therapy; and a run-to-run approach for implementing day-by-day tuning of the algorithm. In order to individualize the ARX model, a sufficiently exciting insulin profile is imposed by splitting the premeal bolus into two smaller boluses (40% and 60%) injected 30 min before and 30 min after the meal.

Results:

The proposed algorithm was tested on 100 virtual subjects extracted from an in silico T1DM population. The trial simulates 44 consecutive days, during which the patient receives breakfast, lunch, and dinner each day. For 10 days, meals are multiplied by a random variable uniformly distributed in [0.5, 1.5], while insulin delivery is based on nominal meals. Moreover, for 10 days, either a linear increase or decrease of insulin sensitivity (±25% of nominal value) is introduced.

Conclusions:

The ARX model identification procedure offers an automatic tool for patient model individualization. The run-to-run approach is an effective way to auto-tune the aggressiveness of the closed-loop control law, is robust to meal variation, and is also capable of adapting the regulator to slow parameter variations, e.g., on insulin sensitivity.
Clinically Significant Disagreement between Mean Blood Glucose and Estimated Average Glucose in Two Populations: Implications for Diabetes Management
Authors: Chalew Stuart A. , Hempe James M. , McCarter Robert
Published: January 2014

Background:

Hemoglobin A1c (HbA1c) is highly correlated with mean blood glucose (MBG) levels and widely used in assessment of diabetes therapy. It has been proposed to report HbA1c in terms of an estimated average glucose (eAG) derived from the population regression of MBG on HbA1c. Pertinent to the clinical utility of eAG would be the degree of agreement between eAG and MBG estimated from multiple sampled glucose measurements over time.

Methods:

We examined agreement between eAG and MBG by Bland-Altman analysis from two different populations of type 1 diabetes patients: 150 children at our clinic in New Orleans and publicly available data from 1440 participants in the Diabetes Control and Complications Trial (DCCT). In New Orleans, MBG was derived from the mean of each patient's self-monitored glucose records over the 3 months before the HbA1c was obtained at the patient's clinic visit. Hemoglobin A1c was traceable to the DCCT. In DCCT participants, MBG was calculated from the patient's seven-sample glucose profile set submitted during each quarterly visit. Estimated average glucose was calculated from each individual's HbA1c using a previously reported regression equation of MBG versus HbA1c, eAG = (HbA1c * 28.7) − 47.7, derived from a continuous glucose monitoring protocol over a 12-week period.

Results:

The analysis showed that there is frequent and clinically significant disagreement between MBG and eAG. Estimated average glucose over or under estimated MBG by 28.7 mg/dl or greater (HbA1c difference of 1% or greater) in approximately 33% of patients from both populations. The eAG overestimation of MBG was highest at lower MBG. The difference between eAG and MBG was skewed upward with increasing mean of eAG and MBG in the DCCT.

Conclusions:

Frequent discordance between eAG and MBG in clinical practice will likely be confusing to patients and clinicians. In patients where eAG overestimates MBG, intensive management based on eAG alone will likely lead to greater frequency of hypoglycemic episodes. To overcome these limitations of eAG, a customized assessment of HbA1c with respect to a patient's MBG should be performed using directly monitored patient glucose levels over time.
Analysis of the Comparison of Lancing Devices for Self-Monitoring of Blood Glucose regarding Lancing Pain
Authors: Lekarcyk Joyce , Ghiloni Suzanne
Published: January 2014

Reducing barriers to self-monitoring of blood glucose (SMBG) remains an ongoing goal. One major reported barrier is lancing pain. This analysis was written in response to the article by Kocher and associates in this issue of Journal of Diabetes Science and Technology in which 157 patients with diabetes experienced in the use of SMBG compared high market share blood glucose monitoring systems and lancing devices.

Upon review of their findings, we found that their conclusions—Accu-check systems and lancing devices were preferred—were valid within the limitations of the study. However, we noted some factors that would warrant further study and possibly change the outcome. Information from this and other studies on the topic will be useful as a reference for patients and providers in working towards removing barriers to SMBG.
Accuracy of the SEVEN® Continuous Glucose Monitoring System: Comparison with Frequently Sampled Venous Glucose Measurements
Authors: Zisser Howard C. , Bailey Timothy S. , Schwartz Sherwyn , Ratner Robert E. , Wise Jonathan
Published: January 2014

Background:

The purpose of this study was to compare the accuracy of measurements obtained from the DexCom™ SEVEN® system with Yellow Springs Instrument (YSI) laboratory measurements of venous blood glucose.

Methods:

Seventy-two subjects with insulin-requiring diabetes, aged 18–71, were enrolled in a multicenter, prospective single-arm study. All participants wore the SEVEN continuous glucose monitoring (CGM) system for one, 7-day wear period. Calibration with capillary finger stick measurements was performed 2 hours after sensor insertion and once every 12 hours thereafter. A subset of subjects (28) wore two systems simultaneously to assess precision. All subjects participated in one, 10-hour in-clinic session on day 1, 4, or 7 of the study to compare CGM measurements against a laboratory method (YSI analyzer) using venous measurements taken once every 20 minutes. Carbohydrate consumption and insulin dosing were adjusted in order to obtain a broad range of glucose values.

Results:

Comparison of CGM measurements with the laboratory reference method ( n = 2318) gave mean and median absolute relative differences (ARDs) of 16.7 and 13.2%, respectively. The percentage was 70.4% in the clinically accurate Clarke error grid A zone and 27.5% in the benign error B zone. Performance of the SEVEN system was consistent over time with mean and median ARD lowest on day 7 as compared to YSI (13.3 and 10.2%, respectively). Average sensor time lag was 5 minutes.

Conclusions:

Measurements of the DexCom SEVEN system were found to be consistent and accurate compared with venous measurements made using a laboratory reference method over 7 days of wear.
Analysis Article on the Performance Analysis of the OneTouch® UltraVue™ Blood Glucose Monitoring System
Authors: Solnica Bogdan
Published: January 2014

In this issue of Journal of Diabetes Science and Technology, Chang and colleagues present the analytical performance evaluation of the OneTouch® UltraVue™ blood glucose meter. This device is an advanced construction with a color display, used-strip ejector, no-button interface, and short assay time. Accuracy studies were performed using a YSI 2300 analyzer, considered the reference. Altogether, 349 pairs of results covering a wide range of blood glucose concentrations were analyzed. Patients with diabetes performed a significant part of the tests. Obtained results indicate good accuracy of OneTouch UltraVue blood glucose monitoring system, satisfying the International Organization for Standardization recommendations and thereby locating >95% of tests within zone A of the error grid. Results of the precision studies indicate good reproducibility of measurements. In conclusion, the evaluation of the OneTouch UltraVue meter revealed good analytical performance together with convenient handling useful for self-monitoring of blood glucose performed by elderly diabetes patients.
Measurement of Glycated Hemoglobin A1c from Dried Blood by Turbidimetric Immunoassay
Authors: Lakshmy Ramakrishnan , Gupta Ruby
Published: January 2014

Background:

Glycated hemoglobin A1c (A1C) is an important marker in the diagnosis and treatment of diabetes. Dried blood measurement of A1C is useful in large scale epidemiological evaluation of A1C, especially to assess the impact of intervention programs. The possibility of using dried blood for measurement of A1C by the immunoturbidimetric method was explored in the present study.

Method:

Blood was collected from 30 patients, and blood spots were prepared and dried. The dried blood spot samples were kept for different lengths of time at 4°C to assess stability. Glycated hemoglobin was measured in whole blood and dried blood on the day of collection as well as on days 10 and 15 by immunoturbidimetric method.

Results:

The A1C values of 30 samples analyzed for comparison between whole blood estimation and dried blood ranged from 4.6% to 9.9%. The mean A1C on the day of sample collection was 6.01% ± 1.58% in fresh whole blood samples and 5.94% ± 1.58 % in dried blood spots. A linear and highly correlated relationship was observed between dried blood A1C values and those in whole blood ( r = 0.986 and intraclass correlation value = 0.993). Glycated hemoglobin values on day 10 and day 15 were comparable with the values on day 1 with a shift in mean of just 1% on day 10 and 3.04% on day 15.

Conclusion:

In conclusion, dried blood can be used for measurement of A1C by immunoturbidimetric method, and further stability of A1C measurement from dried blood for up to 15 days at 4°C makes it an ideal matrix for transportation in developing countries like India.
Delays in Minimally Invasive Continuous Glucose Monitoring Devices: A Review of Current Technology
Authors: Keenan D. Barry , Mastrototaro John J. , Voskanyan Gayane , Steil Garry M.
Published: January 2014

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.
The Business of Self-Monitoring of Blood Glucose: A Market Profile
Authors: Hughes Mark D.
Published: January 2014

The market for self-monitoring of blood glucose (SMBG) approached $8.8 billion worldwide in 2008. Yet despite dramatic double-digit growth in sales of SMBG products since 1980, the business is now facing declining prices and slower dollar growth. Given that SMBG meters and test strips are viewed by consumers and insurers as essentially generic products, it will be extremely challenging for new market entrants to displace well-entrenched existing competitors without a truly innovative technology. Also, in the face of declining glucose test strip prices, market expansion can only occur through identification of more of the undiagnosed diabetes population and convincing existing diabetes patients to adopt glucose testing or to test more frequently. Ultimately, a combination of technology innovations, patient education, and economic incentives may be needed to significantly expand the SMBG market and build sustainable long-term dollar growth for SMBG vendors.
Pilot Evaluation of a Prototype Critical Care Blood Glucose Monitor in Normal Volunteers
Authors: Torjman Marc C. , Goldberg Michael E. , Littman Jeffrey J. , Hirsh Robert A. , Dellinger Richard P.
Published: January 2014

Background:

Availability of a highly accurate in-hospital automated blood glucose (BG) monitor could facilitate implementation of intensive insulin therapy protocols through effective titration of insulin therapy, improved BG control, and avoidance of hypoglycemia. We evaluated a functional prototype BG monitor designed to perform frequent automated blood sampling for glucose monitoring.

Methods:

Sixteen healthy adult volunteer subjects had intravenous catheter insertions in a forearm or hand vein and were studied for 8 hours. The prototype monitor consisted of an autosampling unit with a precise computer-controlled reversible syringe pump and a glucose analytical section. BG was referenced against a Yellow Springs Instrument (YSI) laboratory analyzer. Sampling errors for automated blood draws were assessed by calculating the percent of failed draws, and BG data were analyzed using the Bland and Altman technique.

Results:

Out of 498 total sample draws, unsuccessful draws were categorized as follow: 11 (2.2%) were due to autosampler technical problems, 21 (4.2%) were due to catheter-related failures, and 37 (7.4%) were BG meter errors confirmed by a glucometer-generated error code. Blood draw difficulties or failures related to the catheter site (e.g., catheter occlusion or vein collapse) occurred in 6/15 (40%) subjects. Mean BG bias versus YSI was 0.20 ± 12.6 mg/dl, and mean absolute relative difference was 10.4%.

Conclusions:

Automated phlebotomy can be performed in healthy subjects using this prototype BG monitor. The BG measurement technology had suboptimal accuracy based on a YSI reference. A more accurate BG point-of-care testing meter and strip technology have been incorporated into the future version of this monitor. Development of such a monitor could alleviate the burden of frequent BG testing and reduce the risk of hypoglycemia in patients on insulin therapy.
Challenges to Glycemic Measurement in the Perioperative and Critically Ill Patient: A Review
Authors: Pitkin Andrew D. , Rice Mark J.
Published: January 2014

Accurate monitoring of glucose in the perioperative environment has become increasingly important over the last few years. Because of increased cost, turnaround time, and sample volume, the use of central laboratory devices for glucose measurement has been somewhat supplanted by point-of-care (POC) glucose devices. The trade-off in moving to these POC systems has been a reduction in accuracy, especially in the hypoglycemic range. Furthermore, many of these POC devices were originally developed, marketed, and received Food and Drug Administration regulatory clearance as home use devices for patients with diabetes. Without further review, many of these POC glucose measurement devices have found their way into the hospital environment and are used frequently for measurement during intense insulin therapy, where accurate measurements are critical. This review covers the technology behind glucose measurement and the evidence questioning the use of many POC devices for perioperative glucose management.
Glycemic Variability and Mortality in Critically 111 Patients: The Impact of Diabetes
Authors: Krinsley James Stephen
Published: January 2014

Background:

Glycemic variability (GV) has recently been associated with mortality in critically ill patients. The impact of diabetes or its absence on GV as a risk factor for mortality is unknown.

Methods:

A total of 4084 adult intensive care unit (ICU) patients admitted between October 15, 1999, and June 30, 2009, with at least three central laboratory measurements of venous glucose samples during ICU stay were studied retrospectively. The patients were analyzed according to treatment era and presence or absence of diabetes: 1460 admitted before February 1, 2003, when there was no specific treatment protocol for hyperglycemia (“PRE”) and 2624 patients admitted after a glycemic control protocol was instituted (“GC”). 3142 were patients without diabetes (“NON”), and 942 were patients with diabetes (“DM”). The coefficient of variation (CV) [standard deviation (SD)/mean glucose level (MGL)] of each patient was used as a measure of GV. Patients were grouped by MGL (mg/dl) during ICU stay (70–99, 100–119, 120–139, 140–179, and 180+) as well as by CV (<15%, 15–30%, 30–50%, and 50%+).

Results:

Patients with diabetes had higher MGL, SD, and CV than did NON (p < .0001 for all comparisons). Mean glucose level was lower among both GC groups compared to their corresponding PRE groups (p < .0001), but CV did not change significantly between eras. Multivariable logistic regression analysis demonstrated that low CV was independently associated with decreased risk of mortality and high CV was independently associated with increased risk of mortality among NON PRE and GC patients, even after exclusion of patients with severe (<40 mg/dl) or moderate (40–59 mg/dl) hypoglycemia. There was no association between CV and mortality among DM using the same multivariable model. Mortality among NON from the entire cohort, with MGL 70–99 mg/dl during ICU stay, was 10.2% for patients with CV < 15% versus 58.3% for those with CV 50%+; for NON with MGL 100–119 mg/dl, corresponding rates were 10.6% and 55.6%.

Conclusions:

Low GV during ICU stay was associated with increased survival among NON, and high GV was associated with increased mortality, even after adjustment for severity of illness. There was no independent association of GV with mortality among DM. Attempts to minimize GV may have a significant beneficial impact on outcomes of critically ill patients without diabetes.
A Review of Perioperative Glucose Control in the Neurosurgical Population
Authors: Atkins Joshua H. , Smith David S.
Published: January 2014

Significant fluctuations in serum glucose levels accompany the stress response of surgery or acute injury and may be associated with vascular or neurologic morbidity. Maintenance of euglycemia with intensive insulin therapy (IIT) continues to be investigated as a therapeutic intervention to decrease morbidity associated with derangements in glucose metabolism. Hypoglycemia is a common side effect of IIT with potential for significant morbidity, especially in the neurologically injured patient. Differences in cerebral versus systemic glucose metabolism, the time course of cerebral response to injury, and heterogeneity of pathophysiology in neurosurgical patient populations are important to consider in evaluating the risks and benefits of IIT. While extremes of glucose levels are to be avoided, there are little data to support specific use of IIT for maintenance of euglycemia in the perioperative management of neurosurgical patients. Existing data are summarized and reviewed in this context.
Development of Computer-Based Training to Enhance Resident Physician Management of Inpatient Diabetes
Authors: Cook Curtiss B. , Wilson Rebecca D. , Hovan Michael J. , Hull Bryan P. , Gray Richard J. , Apsey Heidi A.
Published: January 2014

Background:

Treating hyperglycemia promotes better outcomes among inpatients. Knowledge deficits about management of inpatient diabetes are prevalent among resident physicians, which may affect the care of a substantial number of these patients.

Methods:

A computer-based training (CBT) curriculum on inpatient diabetes and hyperglycemia was developed and implemented for use by resident physicians and focuses on several aspects of the management of inpatient diabetes and hyperglycemia: (1) review of importance of inpatient glucose control, (2) overview of institution-specific data, (3) triaging and initial admission actions for diabetes or hyperglycemia, (4) overview of pharmacologic management, (5) insulin-dosing calculations and ordering simulations, (6) review of existing policies and procedures, and (7) discharge planning. The curriculum was first provided as a series of lectures, then formatted and placed on the institutional intranet as a CBT program.

Results:

Residents began using the inpatient CBT in September 2008. By August 2009, a total of 29 residents had participated in CBT: 8 in family medicine, 12 in internal medicine, and 9 in general surgery. Most of the 29 residents confirmed that module content met stated objectives, considered the information valuable to their inpatient practices, and believed that the quality of the online modules met expectations. The majority reported that the modules took just the right amount of time to complete (typically 30 min each).

Conclusions:

Improvement in inpatient diabetes care requires continuous educational efforts. The CBT format and curriculum content were well accepted by the resident physicians. Ongoing assessment must determine whether resident practice patterns are influenced by such training.
Treatment Satisfaction and Quality of Life for an Integrated Continuous Glucose Monitoring/Insulin Pump System Compared to Self-Monitoring plus an Insulin Pump
Authors: Rubin Richard R. , Peyrot Mark
Published: January 2014

Background:

Little is known about how the most advanced technology affects treatment satisfaction and health-related quality of life (HRQOL) in adults with diabetes. This study was designed to assess treatment satisfaction and HRQOL among users of an integrated real-time (RT) continuous glucose monitoring (CGM)/continuous subcutaneous insulin infusion (CSII) system compared with those using self-monitoring of blood glucose (SMBG) with CSII.

Methods:

Participants were 311 adult respondents to an Internet survey, 162 using RT-CGM/CSII, 149 using SMBG + CSII (median age 43 years; type 1 diabetes 94%; diabetes duration >15 years 61%; median insulin use 15 years). Respondents completed instruments assessing glucose monitoring system and insulin delivery system convenience, interference, burden, glucose control efficacy, cost satisfaction, overall satisfaction, and treatment preference, as well as quality of life (diabetes-related worries, social burden, and psychological well-being). Real-time CGM/CSII users also assessed specific elements of the RT-CGM/CSII system. Group differences were assessed using analysis of covariance controlling for respondent characteristics.

Results:

The RT-CGM/CSII group gave significantly better ratings than the SMBG + CSII group for their glucose monitoring system's glucose control efficacy, overall satisfaction, desire to switch, and willingness to recommend, and significantly worse ratings for interference with daily activities. The RT-CGM/CSII group gave significantly better ratings than the SMBG + CSII group for their insulin delivery system's convenience and glucose control efficacy, overall satisfaction, desire to switch, and willingness to recommend. Real-time CGM/CSII users gave positive ratings of all system features.

Conclusions:

Users of the integrated RT-CGM/CSII system reported more benefits of treatment, higher treatment satisfaction and quality of life, and greater preference for this system than SMBG + CSII users.
A Benchtop Closed-loop System Controlled by a Bio-Inspired Silicon Implementation of the Pancreatic β Cell
Authors: Oliver Nick , Georgiou Pantelis , Johnston Desmond , Toumazou Christofer
Published: January 2014

The normal pancreatic f-cell membrane depolarizes in response to increasing concentrations of glucose in a bursting pattern. At <7 mM (126 mg/dl), the cell is electrically silent. The bursting pulse width increases as glucose rises >7 m M (126 mg/dl) until a continuous train of bursting is seen at >25 m M (450 mg/dl). A bio-inspired silicon device has been developed using analogue electronics to implement membrane depolarization of the β cell. The device is ultralow powered, miniaturized (5 × 5 mm), and produces a bursting output identical to that characterized in electrophysiological studies.

Objective:

The goal of this study was to demonstrate the ability of silicon implementation of β-cell electrophysiology to respond to a simulated glucose input and to drive an infusion pump in vitro.

Method:

The silicon device response to a current source was recorded at varying simulated glucose concentrations. Subsequently, the bursting response to a changing analyte concentration measured by an amperometric enzyme electrode was converted to a voltage, driving a syringe pump loaded with a 50-ml syringe containing water.

Results:

Bursting responses are comparable to those recorded in electrophysiology. Silicon β-cell implementation bursts with a pulse width proportional to concentration and is able to drive an infusion pump.

Conclusion:

This is the first in vitro demonstration of closed loop insulin delivery utilizing miniaturized silicon implementation of β-cell physiology in analogue electronics.
Combined Pioglitazone and Metformin Treatment Maintains the Beneficial Effect of Short-Term Insulin Infusion in Patients with Type 2 Diabetes: Results from a Pilot Study
Authors: Musholt Petra B. , Schöndorf Thomas , Pfützner Andreas , Hohberg Cloth , Kleine Iris , Fuchs Winfried , Hehenwarter Silvia , Dikta Gerhard , Kerschgens Benedikt , Forst Thomas
Published: January 2014

Background:

The aim of our study was to examine the efficacy of short-term intravenous insulin intervention followed by oral pioglitazone/metformin therapy to prevent patients from continuous insulin application.

Methods:

This prospective, open-label, 4-month pilot study comprised of 14 diabetes patients (5 female, 9 male; age 60 ± 2 years; body mass index 29 ± 3.2 kg/m2; hemoglobin A1c [HbAlc] 7.6 ± 1.1%) with (1) insufficient glycemic control under a dose of metformin >1700 mg/day and/or metformin plus additional oral antidiabetes drugs (OADs) and (2) appropriate residual β-cell function. Initially, an inpatient 34 h continuous intravenous insulin infusion was performed, and metformin was given (2× 850 mg/day). Insulin was stopped, and pioglitazone 30 mg/day was added at the second inpatient day. Patients were followed for four months. Efficacy parameters [change of HbA1c, fasting blood glucose [FBG], intact proinsulin, adiponectin, and high-sensitivity C-reactive protein (hsCRP)] were assessed after initial normalization of blood glucose values by intravenous insulin and at the study end point.

Results:

During the acute insulin intervention, FBG levels were stabilized in all study subjects. In the following OAD treatment period, five patients showed an improvement of HbA1c > 0.5% [35.7%; seven patients remained stable (50.0%), two patients were nonresponders (14.3%)]. Fasting glucose values dropped after insulin infusion (−17.7%; p < .001). This effect was maintained during the consecutive OAD treatment period (glucose +0.3%, not significant (NS); HbA1c −6.0%; p < .05). The initial decrease in fasting intact proinsulin levels was also maintained during the study (end value −41%, p < .05). Improvements in hsCRP values (postinsulin value, −15%, NS; end value −37%; p < .05) and adiponectin values (postinsulin value +15%, NS; end value +128%; p < .001) were demonstrated at end point only after continued glitazone intake.

Conclusions:

Our pilot study demonstrated that a beneficial effect of a short-term intravenous insulin application on glycemic control was effectively maintained by pioglitazone/metformin treatment for at least 4 months. In addition, the oral therapy significantly improved cardiovascular risk parameters.
Hepatic-Directed Vesicle Insulin: A Review of Formulation Development and Preclinical Evaluation
Authors: Geho W. Blair , Geho Hans C. , Lau John R. , Gana Theophilus J.
Published: January 2014

Hepatic-directed vesicle insulin (HDV-I), a novel investigational vesicle (<150 nm diameter) insulin delivery system that carries insulin and a specific hepatocyte-targeting molecule (HTM) in its phospholipid bilayer and has the ability to mimic a portal vein insulin infusion remotely [subcutaneous (SC) HDV-I] and noninvasively (oral HDV-I), has been developed. This review summarizes formulation development, subsequent refinements, and results of preclinical evaluation studies, including biodistribution, mechanistic, and toxicology studies of predominantly SC HDV-I, in various animal models. Studies conducted to date have confirmed the hepatocyte specificity of HDV and HDV-I and revealed that HDV-I can stimulate the conversion of hepatic glucose output to uptake at a dose that is <1% of the dose of regular insulin (RI) required for liver stimulation; suggest that the enhanced antihyperglycemic effect of HDV-I is due to hepatic glucose uptake; and in pancreatectomized dogs during an oral glucose tolerance test, HDV-I normalized blood glucose curves when compared to control curves in intact dogs and prevented secondary hypoglycemia in contrast to the same dose of RI. A 28-day SC HDV toxicity study in rats revealed no clinical, clinical laboratory, or histopathological findings, and the battery of three genetic toxicology studies was negative. Results support the hypothesis that HDV-I works by stimulating hepatic glucose uptake and/or glycogen storage in insulin-deficient animals. The ability to target the delivery of HDV-I to the liver reestablishes the liver as a major metabolic modulator of glucose metabolism. The future of HDV-I depends on the results of ongoing development and longer term clinical trials.