bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hyperglycemia Control of the Nil Per Os Patient in the Intensive Care Unit: Introduction of a Simple Subcutaneous Insulin Algorithm
Authors: Kim Sarah , Rushakoff Robert J. , Sullivan Mary , Windham Heidemarie 
Published: January 2014

Background: Diabetes patients in the intensive care unit (ICU) and either nil per os, on enteral feedings, or on total parenteral nutrition are often treated with sliding-scale insulin (despite lack of evidence showing benefit) or intravenous insulin (IVI) infusion, a nursing intensive procedure requiring hourly glucose measurements, and insulin rate adjustments. We introduced a subcutaneous insulin algorithm (SQIA) that would equal the glucose goals for IVI but have the simplicity of q4 hour adjustable sliding-scale insulin. Methods: As part of a quality improvement project, we developed a simple SQIA that titrates insulin to the requirements of the individual patient. Glucoses were monitored q4 h and SQ rapid-acting insulin administered based on both the previous insulin dose and current glucose level. Fourteen consecutive hyperglycemic patients admitted to ICU-A were placed on the SQIA. Glucose and insulin data were also obtained on 18 patients in an identical ICU-B who were treated with the usual IVI protocol, which is q1-2 h. Results: Duration on the SQIA was 4.5 ± 0.6 days (range 0.8–7) and on IVI 1.9 ± 0.6 days (range 0.25–9). Due to difference in length on protocols, only data for the first 3 days could be statistically compared. During this time, the mean ± standard error of glucoses for the SQ and IV groups were 157.3 ± 3.8 and 157.0 ± 2.2 (not significant). No differences were seen in hypoglycemia rates. Conclusions: A simple SQIA allows insulin doses to be adjusted to the individual patient's needs and meet current ICU goals for glycemic control. Its adoption may reduce the workload of nurses.
Effect of Dexamethasone-Loaded Poly(Lactic-Co-Glycolic Acid) Microsphere/Poly(Vinyl Alcohol) Hydrogel Composite Coatings on the Basic Characteristics of Implantable Glucose Sensors
Authors: Wang Yan , Vaddiraju Santhisagar , Qiang Liangliang , Xu Xiaoming , Papadimitrakopoulos Fotios , Burgess Diane J. 
Published: January 2014

Background: Hydrogels alone and in combination with microsphere drug delivery systems are being considered as biocompatible coatings for implantable glucose biosensors to prevent/minimize the foreign body response. Previously, our group has demonstrated that continuous release of dexamethasone from poly(lactic-co-glycolic acid) (PLGA) microsphere/poly(vinyl alcohol) (PVA) hydrogel composites can successfully prevent foreign body response at the implantation site. The objective of this study was to investigate the effect of this composite coating on sensor functionality. Methods: The PLGA microsphere/PVA hydrogel coatings were prepared and applied to glucose biosensors. The swelling properties of the composite coatings and their diffusivity to glucose were evaluated as a function of microsphere loading. Sensor linearity, response time, and sensitivity were also evaluated as a function of coating composition. Results: The PLGA microsphere/PVA hydrogel composite coating did not compromise sensor linearity (sensors were linear up to 30 mM), which is well beyond the physiological glucose range (2 to 22 mM). The sensor response time did increase in the presence of the coating (from 10 to 19 s); however, this response time was still less than the average reported values. Although the sensitivity of the sensors decreased from 73 to 62 nA/mM glucose when the PLGA microsphere loading in the PVA hydrogel changed from 0 to 100 mg/ml, this reduced sensitivity is acceptable for sensor functionality. The changes in sensor response time and sensitivity were due to changes in glucose permeability as a result of the coatings. The embedded PLGA microspheres reduced the fraction of bulk water present in the hydrogel matrix and consequently reduced glucose diffusion. Conclusions: This study demonstrates that the PLGA microsphere/PVA hydrogel composite coatings allow sufficient glucose diffusion and sensor functionality and therefore may be utilized as a smart coating for implantable glucose biosensors to enhance their in vivo functionality.
Detection of Trace Glucose on the Surface of a Semipermeable Membrane Using a Fluorescently Labeled Glucose-Binding Protein: A Promising Approach to Noninvasive Glucose Monitoring
Authors: Ge Xudong , Rao Govind , Kostov Yordan , Kanjananimmanont Sunsanee , Viscardi Rose M. , Woo Hyung , Tolosa Leah 
Published: January 2014

Background: Our motivation for this study was to develop a noninvasive glucose sensor for low birth weight neonates. We hypothesized that the underdeveloped skin of neonates will allow for the diffusion of glucose to the surface where it can be sampled noninvasively. On further study, we found that measurable amounts of glucose can also be collected on the skin of adults. Method: Cellulose acetate dialysis membrane was used as surrogate for preterm neonatal skin. Glucose on the surface was collected by saline-moistened swabs and analyzed with glucose-binding protein (GBP). The saline-moistened swab was also tested in the neonatal intensive care unit. Saline was directly applied on adult skin and collected for analysis with two methods: GBP and high-performance anion-exchange chromatography (HPAEC). Results: The amount of glucose on the membrane surface was found (1) to accumulate with time but gradually level off, (2) to be proportional to the swab dwell time, and (3) the concentration of the glucose solution on the opposite side of the membrane. The swab, however, failed to absorb glucose on neonatal skin. On direct application of saline onto adult skin, we were able to measure by HPAEC and GBP the amount of glucose collected on the surface. Blood glucose appears to track transdermal glucose levels. Conclusions: We were able to measure trace amounts of glucose on the skin surface that appear to follow blood glucose levels. The present results show modest correlation with blood glucose. Nonetheless, this method may present a noninvasive alternative to tracking glucose trends.
First Clinical Evaluation of a New Percutaneous Optical Fiber Glucose Sensor for Continuous Glucose Monitoring in Diabetes
Authors: Müller Achim Josef , Knuth Monika , Nikolaus Katharina Sibylle , Krivánek Roland , Küster Frank , Hasslacher Christoph 
Published: January 2014

Background: This article describes a new fiber-coupled, percutaneous fluorescent continuous glucose monitoring (CGM) system that has shown 14 days of functionality in a human clinical trial. Method: The new optical CGM system (FiberSense) consists of a transdermal polymer optical fiber containing a biochemical glucose sensor and a small fluorescence photometer optically coupled to the fiber. The glucose-sensitive optical fiber was implanted in abdominal and upper-arm subcutaneous tissue of six diabetes patients and remained there for up to 14 days. The performance of the system was monitored during six visits to the study center during the trial. Blood glucose changes were induced by oral carbohydrate intake and insulin injections, and capillary blood glucose samples were obtained from the finger tip. The data were analyzed using linear regression and the consensus error grid analysis. Results: The FiberSense worn at the upper arm exhibited excellent results during 14 wearing days, with an overall mean absolute relative difference (MARD) of 8.3% and 94.6% of the data in zone A of the consensus error grid. At the abdominal application site, FiberSense resulted in a MARD of 11.4 %, with 93.8% of the data in zone A. Conclusions: The FiberSense CGM system provided consistent, reliable measurements of subcutaneous glucose levels in human clinical trial patients with diabetes for up to 14 days.
Hypoglycemia-Associated Electroencephalogram and Electrocardiogram Changes Appear Simultaneously
Authors: Larsen Anine , Højlund Kurt , Poulsen Mikael Kjær , Madsen Rasmus Elsborg , Juhl Claus B. 
Published: January 2014

Background: Tight glycemic control in type 1 diabetes mellitus (T1DM) may be accomplished only if severe hypoglycemia can be prevented. Biosensor alarms based on the body's reactions to hypoglycemia have been suggested. In the present study, we analyzed three lead electrocardiogram (ECG) and single-channel electroencephalogram (EEG) in T1DM patients during hypoglycemia. Materials and Methods: Electrocardiogram and EEG recordings during insulin-induced hypoglycemia in nine patients were used to assess the presence of ECG changes by heart rate, and estimates of QT interval (QTc) and time from top of T wave to end of T wave corrected for heartbeat interval and EEG changes by extraction of the power of the signal in the delta, theta, and alpha bands. These six features were assessed continuously to determine the time between changes and severe hypoglycemia. Results: QT interval changes and EEG theta power changes were detected in six and eight out of nine subjects, respectively. Rate of false positive calculations was one out of nine subjects for QTc and none for EEG theta power. Detection time medians (i.e., time from significant changes to termination of experiments) was 13 and 8 min for the EEG theta power and QTc feature, respectively, with no significant difference (p = .25). Conclusions: Severe hypoglycemia is preceded by changes in both ECG and EEG features in most cases. Electroencephalogram theta power may be superior with respect to timing, sensitivity, and specificity of severe hypoglycemia detection. A multiparameter algorithm that combines data from different biosensors might be considered.
Professional Continuous Glucose Monitoring in Subjects with Type 1 Diabetes: Retrospective Hypoglycemia Detection
Authors: Jensen Morten Hasselstrøm , Christensen Toke Folke , Tarnow Lise , Mahmoudi Zeinab , Johansen Mette Dencker , Hejlesen Ole Kristian 
Published: January 2014

Background: An important task in diabetes management is detection of hypoglycemia. Professional continuous glucose monitoring (CGM), which produces a glucose reading every 5 min, is a powerful tool for retrospective identification of unrecognized hypoglycemia. Unfortunately, CGM devices tend to be inaccurate, especially in the hypoglycemic range, which limits their applicability for hypoglycemia detection. The objective of this study was to develop an automated pattern recognition algorithm to detect hypoglycemic events in retrospective, professional CGM. Method: Continuous glucose monitoring and plasma glucose (PG) readings were obtained from 17 data sets of 10 type 1 diabetes patients undergoing insulin-induced hypoglycemia. The CGM readings were automatically classified into a hypoglycemic group and a nonhypoglycemic group on the basis of different features from CGM readings and insulin injection. The classification was evaluated by comparing the automated classification with PG using sample-based and event-based sensitivity and specificity measures. Results: With an event-based sensitivity of 100%, the algorithm produced only one false hypoglycemia detection. The sample-based sensitivity and specificity levels were 78% and 96%, respectively. Conclusions: The automated pattern recognition algorithm provides a new approach for detecting unrecognized hypoglycemic events in professional CGM data. The tool may assist physicians and diabetologists in conducting a more thorough evaluation of the diabetes patient's glycemic control and in initiating necessary measures for improving glycemic control.
Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models
Authors: Bayrak Elif Seyma , Turksoy Kamuran , Cinar Ali , Quinn Lauretta , Littlejohn Elizabeth , Rollins Derrick 
Published: January 2014

Background: Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Method: A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results: Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions: The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance.
Acceptability and Utility of the mySentry Remote Glucose Monitoring System
Authors: Kaiserman Kevin , Buckingham Bruce A. , Prakasam Gnanagurudasan , Gunville Fred , Slover Robert H. , Wang Yongyin , Nguyen Xuan , Welsh John B. 
Published: January 2014

Background: The mySentry system (Medtronic Inc.) is the first to amplify and relay continuous glucose monitoring (CGM) and insulin pump data to a remote site within the house. Its usability and acceptability were evaluated in families having a child with type 1 diabetes. Methods: Each enrolled family included a child (age 7–17 years) who used a Paradigm REAL-Time Revel sensor-augmented insulin pump (Medtronic). After a 1-week run-in phase, families set up and used the mySentry system for a 3-week study phase. Opinion surveys were completed by parents, and pump and CGM data were collected and analyzed retrospectively. No formal hypothesis testing was performed, and the study was not powered to detect changes in nocturnal glycemia. Results: Thirty-five families completed the study. Enrolled children (61.1% female) had a mean (± standard deviation) age of 11.9 ± 2.70 years and a mean age at initiation of pump therapy of 7.1 ± 3.19 years. Baseline survey results indicated that most parents were fearful of their unawareness of their children's nocturnal glucose excursions. The mySentry system met the predefined acceptability criteria for general experience, product usability, and training materials. There were no unanticipated device-related adverse effects. Among children who experienced nocturnal hypo- or hyperglycemic episodes in both phases of the study, there was a trend toward less frequent and less prolonged episodes during mySentry use. Conclusion: The mySentry system met all predefined criteria for acceptability and did not demonstrate safety issues. Alerting parents to abnormal glucose values or trends may attenuate nocturnal hypoglycemia and hyperglycemia by prompting appropriate and timely intervention.
Performance of a New Meter Designed for Assisted Monitoring of Blood Glucose and Point-of-Care Testing
Authors: MacRury Sandra , Srinivasan Aparna , Mahoney John J. 
Published: January 2014

Background: Blood glucose (BG) meters used for assisted monitoring of blood glucose (AMBG) require different attributes compared with meters designed for home use. These include safety considerations (i.e., minimized risk of blood-borne pathogen transmission), capability for testing multiple blood sample types, and enhanced performance specifications. The OneTouch® Verio™Pro+ BG meter is designed to incorporate all of these attributes. Methods: Meter accuracy was assessed in clinical studies with arterial, venous, and capillary blood samples with a hematocrit range of 22.9–59.8%. The effect of interferents, including anticoagulants, on accuracy was evaluated. The meter disinfection protocol was validated, and instructions for use and user acceptance of the system were assessed. Results: A total of 97% (549/566) of BG measures from all blood sample types and 95.5% (191/200) of arterial blood samples were within ±12 mg/dl or 12.5% of reference measurements. The system was unaffected by 4 anticoagulants and 57 of 59 endogenous and exogenous compounds; it was affected by 2 compounds: Pralidoxime iodide and xylose. Bleach wipes were sufficient to disinfect the meter. Users felt that the meter's quality control (QC) prompts would help them to comply with regulatory requirements. Conclusion: The meter provided accurate measurements of different blood samples over a wide hematocrit range and was not affected by 57 physiologic and therapeutic compounds. The QC prompts and specific infection-mitigating design further aid to make this meter system practical for AMBG in care facilities.
Failure to Control Hyperglycemia in NonCritically Ill Diabetes Patients despite Standard Glycemic Management in a Hospital Setting
Authors: Neubauer Katharina Maria , Schaupp Lukas , Plank Johannes , Augustin Thomas , Mautner Selma Isabella , Tschapeller Bernd , Pieber Thomas Rudolf 
Published: January 2014

Background: Successful control of hyperglycemia has been shown to improve outcomes for diabetes patients in a clinical setting. We assessed the quality of physician-based glycemic management in two general wards, considering the most recent recommendations for glycemic control for noncritically ill patients (<140 mg/dl for premeal glucose). Methods: Quality of glycemic management of 50 patients in two wards (endocrinology, cardiology) was assessed retrospectively by analyzing blood glucose (BG) levels, the glycemic management effort, and the online questionnaire. Results: Glycemic control was clearly above the recommended target (mean BG levels: Endocrinology: 175 ± 62 mg/dl; cardiology: 186 ± 68 mg/dl). When comparing the first half with the second half of the hospital stay, we found no difference in glycemic control (endocrinology: 168 ± 32 vs 164 ± 42 mg/dl, P = .67; cardiology: 174 ± 36 mg/dl vs 170 ± 42 mg/dl, P =.51) and in insulin dose (endocrinology: 15 ± 14 IU vs 15 ± 13 IU per day, P = .87; cardiology: 27 ± 17 IU vs 27 ± 18 IU per day, P = .92), despite frequent BG measurements (endocrinology: 2.7 per day; cardiology: 3.2 per day). A lack of clearly defined BG targets was indicated in the questionnaire. Conclusion: The recommended BG target range was not achieved in both wards. Analysis of routine glycemic management demonstrated considerable glycemic management effort, but also a lack of translation into adequate insulin therapy. Implementation of corrective measures, such as structured treatment protocols, is essential.
An Apparatus to Quantify Anteroposterior and Mediolateral Shear Reduction in Shoe Insoles
Authors: Belmont Barry , Wang Yancheng , Ammanath Peethambaran , Wrobel James S. , Shih Albert 
Published: January 2014

Background: Many of the physiological changes that lead to diabetic foot ulceration, such as muscle atrophy and skin hardening, are manifested at the foot-ground interface via pressure and shear points. Novel shear-reducing insoles have been developed, but their magnitude of shear stiffness has not yet been compared with regular insoles. The aim of this study was to develop an apparatus that would apply shear force and displacement to an insole's forefoot region, reliably measure deformation, and calculate insole shear stiffness. Methods: An apparatus consisting of suspended weights was designed to test the forefoot region of insoles. Three separate regions representing the hallux; the first and second metatarsals; and the third, fourth, and fifth metatarsals were sheared at 20 mm/min for displacements from 0.1 to 1.0 mm in both the anteroposterior and mediolateral directions for two types of insoles (regular and shear reducing). Results: Shear reduction was found to be significant for the intervention insoles under all testing conditions. The ratio of a regular insole's effective stiffness and the experimental insole's effective stiffness across forefoot position versus shear direction, gait instance versus shear direction, and forefoot position versus gait instance was 270% ± 79%, 270% ± 96%, and 270% ± 86%, respectively. The apparatus was reliable with an average measured coefficient of variation of 0.034 and 0.069 for the regular and shear-reducing insole, respectively. Conclusion: An apparatus consisting of suspended weights resting atop three locations of interest sheared across an insole was demonstrated to be capable of measuring the insole shear stiffness accurately, thus quantifying shear-reducing effects of a new type of insole.
Integration of a Mobile-Integrated Therapy with Electronic Health Records: Lessons Learned
Authors: Peeples Malinda M. , Iyer Anand K. , Cohen Joshua L. 
Published: January 2014

Background: Responses to the chronic disease epidemic have predominantly been standardized in their approach to date. Barriers to better health outcomes remain, and effective management requires patient-specific data and disease state knowledge be presented in methods that foster clinical decision-making and patient self-management. Mobile technology provides a new platform for data collection and patient-provider communication. The mobile device represents a personalized platform that is available to the patient on a 24/7 basis. Mobile-integrated therapy (MIT) is the convergence of mobile technology, clinical and behavioral science, and scientifically validated clinical outcomes. In this article, we highlight the lessons learned from functional integration of a Food and Drug Administration-cleared type 2 diabetes MIT into the electronic health record (EHR) of a multiphysician practice within a large, urban, academic medical center. Methods: In-depth interviews were conducted with integration stakeholder groups: Mobile and EHR software and information technology teams, clinical end users, project managers, and business analysts. Interviews were summarized and categorized into lessons learned using the Architecture for Integrated Mobility® framework. Results: Findings from the diverse stakeholder group of a MIT-EHR integration project indicate that user workflow, software system persistence, environment configuration, device connectivity and security, organizational processes, and data exchange heuristics are key issues that must be addressed. Conclusions: Mobile-integrated therapy that integrates patient self-management data with medical record data provides the opportunity to understand the potential benefits of bidirectional data sharing and reporting that are most valuable in advancing better health and better care in a cost-effective way that is scalable for all chronic diseases.