bluuebunny/crossref_metadata_2025_split huggingface dataset:
Safe Glycemic Management during Closed-Loop Treatment of Type 1 Diabetes: The Role of Glucagon, Use of Multiple Sensors, and Compensation for Stress Hyperglycemia
Authors: Ward W. Kenneth , Castle Jessica R. , Youssef Joseph El 
Published: January 2014

Patients with type 1 diabetes mellitus (T1DM) must make frequent decisions and lifestyle adjustments in order to manage their disorder. Automated treatment would reduce the need for these self-management decisions and reduce the risk for long-term complications. Investigators in the field of closed-loop glycemic control systems are now moving from inpatient to outpatient testing of such systems. As outpatient systems are developed, the element of safety increases in importance. One such concern is the risk for hypoglycemia, due in part to the delayed onset and prolonged action duration of currently available subcutaneous insulin preparations. We found that, as compared to an insulin-only closed-loop system, a system that also delivers glucagon when needed led to substantially less hypoglycemia. Though the capability of glucagon delivery would mandate the need for a second hormone chamber, glucagon in small doses is tolerated very well. People with T1DM often develop hyperglycemia from emotional stress or medical stress. Automated closed-loop systems should be able to detect such changes in insulin sensitivity and adapt insulin delivery accordingly. We recently verified the adaptability of a model-based closed-loop system in which the gain factors that govern a proportional-integral-derivative-like system are adjusted according to frequently measured insulin sensitivity. Automated systems can be tested by physical exercise to increase glucose uptake and insulin sensitivity or by administering corticosteroids to reduce insulin sensitivity. Another source of risk in closed-loop systems is suboptimal performance of amperometric glucose sensors. Inaccuracy can result from calibration error, biofouling, and current drift. We found that concurrent use of more than one sensor typically leads to better sensor accuracy than use of a single sensor. For example, using the average of two sensors substantially reduces the proportion of large sensor errors. The use of more than two allows the use of voting algorithms, which can temporarily exclude a sensor whose signal is outlying. Elements such as the use of glucagon to minimize hypoglycemia, adaptation to changes in insulin sensitivity, and sensor redundancy will likely increase safety during outpatient use of closed-loop glycemic control systems.
Hemoglobin A1c Testing in an Emergency Department
Authors: Magee Michelle F. , Nassar Carine 
Published: January 2014

Background: Emergency department (ED) visits for hyperglycemia are common and costly. Enhanced strategies for recognizing and managing patients with diabetes in the ED are needed. Hemoglobin A1c (A1C) testing is typically used to assess level of glycemic control in the 2–3 months preceding an office visit. In this article, we report on potential roles for point-of-care (POC) A1C testing in the ED for patients presenting with uncontrolled hyperglycemia. Methods: We enrolled patients presenting to an urban tertiary care hospital ED with blood glucose (BG) ≥200 mg/dl who were otherwise stable for discharge ( n = 86) in a prospective, nonrandomized pilot study. Antihyperglycemic medication management, survival-skills diabetes self-management education, and health system navigation were provided. Followup visits took place at 24–72 hours and at 2 and 4 weeks. Point-of-care A1C testing was performed at baseline and at 2 weeks. Baseline A1C results were used by the ED physician and the educator to inform the patient of likely preadmission glycemic classification, and the potential role that the (diabetes mellitus) DM medication regimen assigned in the ED had in enabling overall progress in glycemic control at 2 weeks post-ED initiation of treatment. Results: At baseline, 50% of POC A1C values were >13%. Mean BG fell from 356 ± 110 mg/dl to 183 ± 103 mg/dl at 4 weeks (average decrease of 173.5 g/dl, p < 0.001). Mean A1C fell by 0.4%, from 12.0 ± 1.5% to 11.6 ± 1.6% at 2 weeks, p = 0.048. There were zero instances of day 1 hypoglycemia and overall hypoglycemia rates were low (1.3%). Conclusions: Point-of-care A1C testing in the ED helped inform both the provider and the patient of likely prior glycemic status, including unrecognized or uncontrolled type 2 diabetes, and allowed emphasis of the importance of timely diabetes self-management education and medication management in preventing acute and chronic complications. Followup POC A1C testing at 2 weeks was used to confirm early improvement in glycemic control postintervention.
The Effect of an Instant Hand Sanitizer on Blood Glucose Monitoring Results
Authors: Mahoney John J. , Ellison John M. , Glaeser Danielle , Price David 
Published: January 2014

Background: People with diabetes mellitus are instructed to clean their skin prior to self-monitoring of blood glucose to remove any dirt or food residue that might affect the reading. Alcohol-based hand sanitizers have become popular when soap and water are not available. The aim of this study was to determine whether a hand sanitizer is compatible with glucose meter testing and effective for the removal of exogenous glucose. Methods: We enrolled 34 nonfasting subjects [14 male/20 female, mean ages 45 (standard deviation, 9.4)] years, 2 with diagnosed diabetes/32 without known diabetes]. Laboratory personnel prepared four separate fingers on one hand of each subject by (1) cleaning the second finger with soap and water and towel drying (i.e., control finger), (2) cleaning the third finger with an alcohol-based hand sanitizer, (3) coating the fourth finger with cola and allowing it to air dry, and (4), coating the fifth finger with cola and then cleaning it with the instant hand sanitizer after the cola had dried. Finger sticks were performed on each prepared finger and blood glucose was measured. Several in vitro studies were also performed to investigate the effectiveness of the hand sanitizer for removal of exogenous glucose. Results: Mean blood glucose values from fingers cleaned with instant hand sanitizer did not differ significantly from the control finger ( p = .07 and .08, respectively) and resulted in 100% accurate results. Blood glucose data from the fourth (cola-coated) finger were substantially higher on average compared with the other finger conditions, but glucose data from the fifth finger (cola-coated then cleaned with hand sanitizer) was similar to the control finger. The data from in vitro experiments showed that the hand sanitizer did not adversely affect glucose meter results, but when an exogenous glucose interference was present, the effectiveness of the hand sanitizer on glucose bias (range: 6% to 212%) depended on the surface area and degree of dilution. Conclusions: In our study, use of an instant hand sanitizer was compatible with the results of a blood glucose monitor and did not affect finger stick blood glucose results. However, depending on surface area, hand sanitizers may not be adequate for cleaning the skin prior to glucose meter testing.
Basic Performance of an Enzymatic Method for Glycated Albumin and Reference Range Determination
Authors: Kohzuma Takuji , Yamamoto Tamotsu , Uematsu Yumiko , Shihabi Zak K. , Freedman Barry I. 
Published: January 2014

Background: Glycated albumin (GA) is a medium-term glycemic control marker of diabetes and may be more sensitive to changes in plasma glucose than hemoglobin A1c. We studied where and how many fructosyl groups bind to albumin, and which glycation sites are measured by the enzymatic method for GA. We also studied the basic performance of the enzymatic method for GA. Methods: Glycated albumin was measured using an enzymatic method (Lucica®GA-L, Asahi Kasei Pharma) on a biochemical autoanalyzer. Molecular weights of purified GA and nonglycated albumin were measured by a mass spectrometry system. Two hundred one healthy volunteers with normal results of oral glucose tolerance testing were recruited to determine the reference range in Americans. Results: The present method measured only glycated amino acids from albumin in serum protein. We estimate that the number of glycated amino acids measured by this method was approximately two per molecule of albumin. The general performance (sensitivity, specificity, reproducibility, linearity, interference) of the method was good. The reference range of GA% in Americans with normal glucose tolerance was determined to be 11.9–15.8% (mean ± 2 standard deviations). Significant differences were not observed between the sexes; however, race differences were observed (higher levels in blacks relative to whites). Conclusions: The method was specific for measuring glycated amino acids in albumin and had good basic performance characteristics. The reference range in Americans was 11.9–15.8%. This method may be a useful indicator for diabetes control.
Needle with a Novel Attachment versus Conventional Screw-Thread Needles: A Preference and Ease-of-Use Test among Children and Adolescents with Diabetes
Authors: Hofman Paul , Lilleøre Søren Kruse , Ter-Borch Gitte 
Published: January 2014

Background: This usability test investigated the overall preference and usability of the novel NovoTwist® insulin pen needle versus conventional screw-thread needles, when used with Next Generation FlexPen®, in children and adolescents with diabetes. Methods: This was an open-label, randomized, crossover usability test in children and adolescents with type 1 diabetes who administered insulin with an insulin pen. Test needles were NovoTwist and the participant's current screw-thread needle (or NovoFine® needle). Following instruction, participants attached the needle to Next Generation FlexPen, made an injection into a foam cushion, and detached the needle. This procedure was conducted three times with both needles in a random order. Responses to 13 questions on user experience with each needle (including overall preference, ease of attachment/detachment of needle/cap, handling, learning, confidence in attachment, and convenience of use) were subsequently recorded on a six-point rating scale (1 = very difficult; 6 = very easy). Results: Fifteen children aged ≥6 to ≤12 years and 15 adolescents aged ≥13 to ≤17 years participated in the test. A significantly higher proportion of children and adolescents (77%) indicated that they would prefer to use NovoTwist compared with screw-thread needles ( p = .005). NovoTwist was preferred by most children and adolescents for overall ease of use (77%; p = .005), for ease of attachment (87%; p < .001) and detachment (83%; p < .001), and as the most appropriate needle to handle for daily injections (73%; p = .016). The mean rating for confidence in correct needle attachment was not significantly different between the two needle types. Seven out of eight parents of children who required assistance for their daily insulin injections stated that they would be “very likely” to allow their child to attach NovoTwist. Conclusions: These factors may promote confidence in this needle, and thus in self-injecting, among younger patients and their parents.
A Spectrum of Dynamic Insulin Sensitivity Test Protocols
Authors: Docherty Paul D. , Chase J. Geoffrey , Morenga Lisa Te , Lotz Thomas F. , Berkeley Juliet E. , Shaw Geoffrey M. , McAuley Kirsten A. , Mann Jim I. 
Published: January 2014

Background: Numerous tests have been developed to estimate insulin sensitivity ( SI). However, most of the established tests are either too expensive for widespread application or do not yield reliable results. The dynamic insulin sensitivity and secretion test (DISST) uses assays of glucose, insulin, and C-peptide from nine samples to quantify SI and endogenous insulin secretion ( UN) at a comparatively low cost. The quick dynamic insulin sensitivity test has shown that the DISST SI values are robust to significant assay omissions. Methods: Eight DISST-based variations of the nine-sample assay regimen are proposed to investigate the effects of assay omission within the DISST-based framework. SI and UN were identified using the fully-sampled DISST and data from 218 nine-sample tests undertaken in 74 female individuals with elevated diabetes risk. This same data was then used with appropriate assay omissions to identify SI and UN with the eight DISST-based assay variations. Results: Median intraprocedure proportional difference between SI values from fully-sampled DISST and the DISST-based variants was in the range of −17.9 to 7.8%. Correlations were in the range of r = 0.71 to 0.92 with the highest correlations between variants with the greatest commonality with the nine-sample DISST. Metrics of UN correlated relatively well between tests when C−peptide was assayed ( r = 0.72 to 1) but were sometimes not well estimated when samples were not assayed for C-peptide ( r = −0.14 to 0.75). Conclusions: The DISST-based spectrum offers a series of tests with very distinct compromises of information yield, accuracy, assay cost, and clinical intensity. Thus, the spectrum of tests has the potential to enable researchers to better allocate funds by selecting an optimal test configuration for their particular application.
Is There a Relationship between Mean Blood Glucose and Glycated Hemoglobin?
Authors: Makris Konstantinos , Spanou Loukia 
Published: January 2014

Measurement of hemoglobin A1c (HbA1c) is considered the gold standard for monitoring chronic glycemia of diabetes patients. Hemoglobin A1c indicates an average of blood glucose levels over the past 3 months. Its close association with the risk for the development of long-term complications is well established. However, HbA1c does not inform patients about blood glucose values on a daily basis; therefore, frequent measurements of blood glucose levels are necessary for the day-to-day management of diabetes. Clinicians understand what HbA1c means and how it relates to glucose, but this is not the case with patients. Therefore, the translation of the HbA1c results into something more familiar to patients seemed a necessity. The scope of this article is to review the literature to search for enough scientific evidence to support the idea of a close relationship between HbA1c and mean blood glucose (MBG), and to justify the translation of HbA1c into something that reflects the MBG. Most studies confirm a close relationship between HbA1c and MBG, although different studies result in different linear equations. Factors affecting this relationship may limit the usefulness and applicability of a unique mathematical equation to all diabetes populations.
Precision, Accuracy, and User Acceptance of the OneTouch SelectSimple Blood Glucose Monitoring System
Authors: Philis-Tsimikas Athena , Chang Anna , Miller Lupe 
Published: January 2014

Background: The OneTouch® SelectSimple™ blood glucose monitoring system (BGMS) is a device for self-monitoring of blood glucose designed for ease of use. Alarms alert subjects to low [20–69 mg/dl (1.1–3.8 mmol/liter)], high [180–239 mg/dl (9.9–13.2 mmol/liter)], and very high [240–600 mg/dl (13.3–33.1 mmol/liter)] blood glucose readings. Methods: Repeatability in blood and intermediate precision with aqueous controls were examined using blood from one donor adjusted to different glucose concentrations, and tested with 10 meters and 1 test-strip lot. System accuracy was evaluated with blood samples from 100 diabetes patients tested on 3 test-strip lots, compared with a reference system (YSI 2300 STAT). To test user accuracy, patients ( n = 156) and health care professionals (HCPs) tested subject blood with the SelectSimple twice. Health care professionals evaluated subject BGMS technique after a 3–5 day home-testing period. Users evaluated the instructions for use and responded to a user acceptance questionnaire. Results: In repeatability and intermediate precision testing, the SelectSimple BGMS had a coefficient of variation of ≤5% or standard deviation of ≤5 mg/dl. In the clinical accuracy study, 100% of measurements <75 mg/dl (4.2 mmol/liter) were within ±15 mg/dl (0.8 mmol/liter) of reference value, and 99.6% of measurements ≥75 mg/dl (4.2 mmol/liter) were within ±20%. Patients were able to use the BGMS appropriately and evaluated it as easy to use. Acceptance of the SelectSimple BGMS was within predefined limits. Conclusions: In these studies, the SelectSimple BGMS met all criteria for precision, system, and user accuracy, was easy to use, and was well accepted by patients.
Evaluation of the Analytical Performance of the Coulometry-Based Optium Omega Blood Glucose Meter
Authors: Solnica Bogdan , Kusnierz-Cabala Beata , Slowinska-Solnica Krystyna , Witek Przemyslaw , Cempa Agnieszka , Malecki Maciej T. 
Published: January 2014

Background: The goal of diabetes treatment is maintaining near normoglycemia based on self-monitoring of blood glucose (SMBG). In this study, an evaluation of the analytical performance of the coulometry-based Optium Omega™ glucose meter designed for SMBG has been carried out. Methods: The assessment of precision and between-lot variability was based on glucose measurements in ethylenediaminetetraacetic acid venous blood samples. Glucose concentrations measured in 289 fresh capillary blood samples using the Omega glucose meter and the Biosen C_line analyzer were compared. Results: Within-run imprecision coefficient of variation for the lower and higher glucose concentrations amounted to 5.09 and 2.1%, respectively. The relative lot-dependent differences found for the lower and higher glucose concentrations were equal to 6.8 and 2.6%, respectively. The glucose meter error calculated for various concentration ranges amounted from 2.22 to 4.48%. The glucose meter error met the accuracy criteria recommended by the International Organization for Standardization and the American Diabetes Association. The Passing-Bablok agreement test and error grid analysis with 96% of results in zone A indicated good concordance of results, including glucose concentrations below 100 mg/dl. Conclusions: The evaluated Optium Omega glucose meter fits the analytical requirements for its use in blood glucose monitoring in diabetes patients.
Stochastic Targeted (STAR) Glycemic Control: Design, Safety, and Performance
Authors: Evans Alicia , Le Compte Aaron , Tan Chia-Siong , Ward Logan , Steel James , Pretty Christopher G. , Penning Sophie , Suhaimi Fatanah , Shaw Geoffrey M. , Desaive Thomas , Chase J. Geoffrey 
Published: January 2014

Introduction: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. STAR (Stochastic TARgeted) is a flexible, model-based TGC approach that directly accounts for intra- and interpatient variability with a stochastically derived maximum 5% risk of blood glucose (BG) below 72 mg/dl. This research assesses the safety, efficacy, and clinical burden of a STAR TGC controller modulating both insulin and nutrition inputs in virtual and clinical pilot trials. Methods: Clinically validated virtual trials using data from 370 patients in the SPRINT (Specialized Relative Insulin and Nutrition Titration) study were used to design the STAR protocol and test its safety, performance, and required clinical effort prior to clinical pilot trials. Insulin and nutrition interventions were given every 1–3 h as chosen by the nurse to allow them to manage workload. Interventions were designed to maximize the overlap of the model-predicted (5–95th percentile) range of BG outcomes with the 72–117 mg/dl band and thus provide a maximum 5% risk of BG <72 mg/dl. Interventions were calculated using clinically validated computer models of human metabolism and its variability in critical illness. Carbohydrate intake (all sources) was selected to maximize intake up to 100% of the American College of Chest Physicians/Society of Critical Care Medicine (ACCP/SCCM) goal (25 kg/kcal/h). Insulin doses were limited (8 U/h maximum), with limited increases based on current rate (0.5–2.0 U/h). Initial clinical pilot trials involved 3 patients covering ~450 h. Approval was granted by the Upper South A Regional Ethics Committee. Results: Virtual trials indicate that STAR provides similar glycemic control performance to SPRINT with 2–3 h (maximum) measurement intervals. Time in the 72–126 mg/dl and 72–145 mg/dl bands was equivalent for all controllers, indicating that glycemic outcome differences between protocols were only shifted in this range. Safety from hypoglycemia was improved. Importantly, STAR using 2–3 h (maximum) intervention intervals reduced clinical burden up to 30%, which is clinically very significant. Initial clinical trials showed glycemic performance, safety, and management of inter- and intrapatient variability that matched or exceeded the virtual trial results. Conclusions: In virtual trials, STAR TGC provided tight control that maximized the likelihood of BG in a clinically specified glycemic band and reduced hypoglycemia with a maximum 5% (or lower) expected risk of light hypoglycemia (BG <72 mg/dl) via model-based management of intra- and interpatient variability. Clinical workload was self-managed and reduced up to 30% compared with SPRINT. Initial pilot clinical trials matched or exceeded these virtual results.
Use of an Automated Bolus Calculator Reduces Fear of Hypoglycemia and Improves Confidence in Dosage Accuracy in Patients with Type 1 Diabetes Mellitus Treated with Multiple Daily Insulin Injections
Authors: Barnard Katharine , Parkin Christopher , Young Amanda , Ashraf Mansoor 
Published: January 2014

Background: Many patients do not intensify their insulin regimens. It is believed that lack of adherence may be largely due to fear of hypoglycemia. We hypothesized that utilization of an automated bolus calculator (bolus advisor) might reduce fear of hypoglycemia and encourage patients to achieve improved glycemic control. Method: We surveyed 1,412 type 1 diabetes mellitus (T1DM) patients treated with multiple daily insulin injection therapy at 270 hospitals in the United Kingdom and Republic of Ireland to assess their attitudes and behaviors regarding insulin therapy after use of a bolus advisor (Accu-Chek® Aviva Expert blood glucose meter and bolus advisor system, Roche Diagnostics). The device automatically calculates bolus dosages based on current blood glucose values, anticipated meal intake, and other parameters. Results: Five hundred eighty-eight T1DM patients responded to the survey. Respondents were predominantly female, age <1 to 70 years, with diabetes duration of <1 to >15 years. Respondents had 4–12 weeks prior experience using the bolus advisor. 76.7% of respondents indicated current bolus advisor use to calculate insulin boluses for meals/snacks always or quite often. 52.0% of respondents indicated that fear of hypoglycemia was reduced (39.0%) or significantly reduced (13.0%). 78.8% indicated that confidence in the insulin dose calculation improved (50.8%) or significantly improved (28.0%). 89.3% indicated that the bolus advisor made bolus calculation easy or very easy compared with manual calculation. Conclusions: Most patients felt that using the bolus advisor was easier than manual bolus calculation, improved their confidence in the accuracy of their bolus dosage, and reduced their fear of hypoglycemia. Randomized trials are needed to confirm these perceptions and determine whether bolus advisor use improves clinical outcomes.