bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diabetic Autonomic Imbalance and Glycemic Variability
Authors: Fleischer Jesper 
Published: January 2014

Diabetic autonomic neural imbalance is a severe complication of long-term diabetes patients and may progress to diabetic autonomic neuropathy (DAN). The prevalence of DAN is reported to be between 20 and 70%, depending on the studies. The pathogenesis of DAN remains unresolved. However, emerging evidence suggests that glycemic variability (GV) may be associated with autonomic imbalance in patients with both type 1 and type 2 diabetes. As symptoms are initially weak and uncharacteristic, the condition often remains undiagnosed until late manifestations present themselves. Predominant symptoms may include nausea, vomiting, gastroparesis, involuntary diarrhea, postural hypotension, voiding difficulties, and sexual dysfunction. Analyzing the patterns of heart rate variability carries the potential for detection of autonomic imbalance in the subclinical and asymptomatic stages. In this context, GV may affect the sympathovagal balance by increasing oxidative stress and proinflammatory cytokines. Establishing a GV risk profile could therefore be important in determining risk factors in diabetes patients. This review addresses the issues above and in particular the possible association between diabetic autonomic imbalance and GV.
Simultaneous Noninvasive Clinical Measurement of Lens Autofluorescence and Rayleigh Scattering Using a Fluorescence Biomicroscope
Authors: Burd John , Lum Stephen , Cahn Frederick , Ignotz Keith 
Published: January 2014

Background: Lens autofluorescence increases with the age of the subject, and the fluorophores responsible are associated with cataract, retinopathy, and other complications of diabetes. We built a scanning confocal lens fluorescence biomicroscope suitable for routine clinical measurement of lens autofluorescence and light scattering and report data from 127 healthy subjects. Method: The fluorescence biomicroscope focuses a beam of light from a blue light-emitting diode on the lens and measures fluorescent green light and blue scattered light using a sensitive silicon photomultiplier. The system includes a target fixation light and a video camera for alignment and automatic pupil tracking. Under software control, a volume of measurement is scanned from behind the posterior lens capsule, through the lens to the aqueous humor, and then back again. Software computes the average ratio of lens autofluorescence to scattered light in the central portion of the lens. Self-reported healthy nondiabetic subjects were examined by an optometrist; if their eyes were healthy and without significant cataract, they were entered into the study. Results: Valid lens autofluorescence data were collected from 127 subjects between 21 and 70 years of age. A linear model for lens autofluorescence intensity with age was highly statistically significant, and the improvement in fit for higher-order polynomial models was not statistically significant. The ratio of lens autofluorescence to light scatter was also calculated; regression analysis showed significant curvature for the relationship of the fluorescence ratio to age, so a nonlinear model was used to estimate the mean ratio of autofluorescence to scatter and its prediction intervals as a function of age. Conclusions: Our observation of a strongly significant linear regression of fluorescence intensity with age of the subjects agrees with the results from previous studies, as does a nonlinear model for the fluorescence ratio. The fluorescence biomicroscope enables the clinician to identify patients with fluorescence ratio significantly higher than expected for their age.
Diabetes Connect: An Evaluation of Patient Adoption and Engagement in a Web-Based Remote Glucose Monitoring Program
Authors: Jethwani Kamal , Ling Evelyn , Mohammed Misbah , Myint-U Khinlei , Pelletier Alexandra , Kvedar Joseph C. 
Published: January 2014

Background: We determine whether Diabetes Connect (DC), a Web-based diabetes self-management program, can help patients effectively manage their diabetes and improve clinical outcomes. Methods: Diabetes Connect is a 12-month program that allows patients with type 2 diabetes mellitus to upload their blood glucose readings to a database, monitor trends, and share their data with their providers. To examine the impact of the program, we analyzed patient utilization and engagement data, clinical outcomes, as well as qualitative feedback from current and potential users through focus groups. Results: We analyzed 75 out of 166 patients. Mean age was 61 years (range 27–87). Patients engaged in DC had an average hemoglobin A1c (HbA1c) change of 1.5%, while nonengaged patients had a HbA1c change of 0.4% ( p = .05). Patients with the best outcomes (HbAlc decline of at least 0.8%) typically took less than 10 days to upload, while patients with the worst outcomes (a rise in HbAlc) took an average of 65 days to upload. Patients with more engaged providers had a better HbA1c change (1.39% versus 0.87%) for practices with an average of 74 versus 30 logins/providers. Conclusions: Patient engagement in the program has a positive impact on the outcomes of this collaborative Web-based diabetes self-management tool. Patients who engage early and remain active have better clinical outcomes than unengaged patients. Provider engagement, too, was found critical in engaging patients in DC.
Hypoglycemia-Related Electroencephalogram Changes are Independent of Gender, Age, Duration of Diabetes, and Awareness Status in Type 1 Diabetes
Authors: Remvig Line Sofie , Elsborg Rasmus , Sejling Anne-Sophie , Sørensen Jens Ahm , Snogdal Lena Sønder , Folkestad Lars , Juhl Claus B. 
Published: January 2014

Introduction: Neuroglycopenia in type 1 diabetes mellitus (T1DM) results in reduced cognition, unconsciousness, seizures, and possible death. Characteristic changes in the electroencephalogram (EEG) can be detected even in the initial stages. This may constitute a basis for a hypoglycemia alarm device. The aim of the present study was to explore the characteristics of the EEG differentiating normoglycemia and hypoglycemia and to elucidate potential group differences. Methods: We pooled data from experiments in T1DM where EEG was available during both normoglycemia and hypoglycemia for each subject. Temporal EEG was analyzed by quantitative electroencephalogram (qEEG) analysis with respect to absolute amplitude and centroid frequency of the delta, theta, alpha, and beta bands, and the peak frequency of the unified theta-alpha band. To elucidate possible group differences, data were subsequently stratified by age group (± 50 years), gender, duration of diabetes (± 20 years), and hypoglycemia awareness status (normal/impaired awareness of hypoglycemia). Results: An increase in the log amplitude of the delta, theta, and alpha band and a decrease in the alpha band centroid frequency and the peak frequency of the unified theta-alpha band constituted the most significant hypoglycemia indicators (all p < .0001). The size of these qEEG changes remained stable across all strata. Conclusions: Hypoglycemia-associated EEG changes remain stable across age group, gender, duration of diabetes, and hypoglycemia awareness status. This indicates that it may be possible to establish a general algorithm for hypoglycemia detection based on EEG measures.
Design of the Health Monitoring System for the Artificial Pancreas: Low Glucose Prediction Module
Authors: Harvey Rebecca A. , Dassau Eyal , Zisser Howard , Seborg Dale E. , Jovanovič Lois , Doyle Francis J. 
Published: January 2014

Background: The purpose of this study was to design and evaluate a safety system for the artificial pancreas device system (APDS). Safe operation of the APDS is a critical task, where the safety system is engaged only as needed to ensure reliable operation without positive feedback to the controller. Methods: The Health Monitoring System (HMS) was designed as a modular system to ensure the safety of the APDS and the user. It was designed using a large set of ambulatory data and evaluated in silico by inducing hypoglycemia with a missed meal [bolus for a 65 g carbohydrate (CHO) meal] and administering rescue CHOs per HMS alerting. The HMS was validated in-clinic with a real-life challenge of a subject who overdosed insulin prior to admission. Results: The HMS was evaluated for clinical use with a 15 min prediction horizon. Retrospectively, 93.5% of episodes were detected with 2.9 false alarms per day. During in silico evaluation, the HMS reduced the time spent <70 mg/dl from 15% to 3%. When the HMS was first tested in-clinic, the subject overdosed ∼3 U of insulin prior to her arrival to a closed-loop session (against protocol). The controller reduced insulin delivery, and the HMS gave four alerts that were successfully received via clinical software and text and multimedia messages. Even with insulin reduction and CHO supplements, hypoglycemia was unavoidable but manageable due to the HMS, confirming that a safety system to detect adverse events is an essential part of the APDS. Conclusions: The ability of the HMS to be an effective alert system that provides a safety layer to the APDS controller has been demonstrated in a clinical setting.
Minimizing the Impact of Time Lag Variability on Accuracy Evaluation of Continuous Glucose Monitoring Systems
Authors: Scuffi Cosimo , Lucarelli Fausto , Valgimigli Francesco 
Published: January 2014

Background: Despite all commercially available continuous glucose monitoring (CGM) systems being designed to operate in the extracellular interstitial fluid, and even though there is a well-recognized time lag between the interstitial and the venous compartments, the accuracy of the CGM device readings is still evaluated against the glucose concentration in venous blood (VB) samples, thus resulting in a perceived decrease in accuracy. This article explains how different time lag compensation methods (no compensation, compensation with a fixed delay, compensation with a variable delay based on an intercompartmental diffusional model) have an impact on how CGM accuracy is evaluated. Methods: The data set used consisted of 210 CGM/blood glucose data pairs from 18 diabetes subjects (15 type 1 and 3 type 2) selected from a data base collected during two independent clinical trials. All CGM measurements were performed using the GlucoMen®Day CGM system (A. Menarini Diagnostics, Italy), and the reference VB glucose measurements by means of a standard laboratory instrument. For each applied time lag compensation method, the CGM accuracy evaluation was performed as recommended by the POCT05-A consensus guideline. Results: The perceived accuracy of the CGM device significantly improved when applying both the fixed or the variable delay compensation method. However, it is worth noting how the variable delay method, which relies on a closer description of the intercompartmental diffusion processes, provided the best perception of the clinical accuracy of the device. Conclusions: When assessing the accuracy of a CGM system, a crucial step in data analysis is to account for time lag, which enables minimization of the apparent decline in system accuracy.
A Simple Indian Diabetes Risk Score Could Help Identify Nondiabetic Individuals at High Risk of Non-Alcoholic Fatty Liver Disease (CURES-117)
Authors: Anbalagan Viknesh Prabu , Venkataraman Vijayachandrika , Vamsi Mamilla , Deepa Mohan , Mohan Viswanathan 
Published: January 2014

Objective: We aim to determine whether a simple Indian diabetes risk score (IDRS) is associated with individuals with non-alcoholic fatty liver disease (NAFLD) among nondiabetic Asian Indians. Methods: Nondiabetic participants ( n = 409) were selected from the Chennai Urban Rural Epidemiology Study. Mean age was 40 ± 11.9 years, mean body mass index was 23.2 ± 3.9 kg/m2, and 224 (54.8%) were women. The IDRS was classified as high (≥60), medium (30–50), and low (<30) risk. Non-alcoholic atty liver disease was assessed by high-resolution β mode ultrasonography. To determine the factors associated with NAFLD, a univariate analysis was first done and a stepwise logistic regression analysis was done based on the factors associated with NAFLD. Biochemical and anthropometric measurements were obtained using standardized procedures. Results: The overall prevalence of NAFLD was 24.7% (101/409 participants), and it was significantly higher among those with a high (30.4%) and medium IDRS (21%) compared with the low IDRS group (15.8%; trend chi square; p = .022). In stepwise logistic regression, IDRS was associated with NAFLD with an adjusted odds ratio of 1.78 (95% confidence interval 1.04–3.06), even after adjusting for potential confounders. Conclusions: The IDRS can be used as the initial step to screen individuals at high risk of NAFLD in the community.
Gender Differences in Diabetes Self-Management: A Mixed-Methods Analysis of a Mobile Health Intervention for Inner-City Latino Patients
Authors: Burner Elizabeth , Menchine Michael , Taylor Elena , Arora Sanjay 
Published: January 2014

Background: The benefit of mobile health (mHealth) on diabetes management among low-income, inner-city patients is largely unknown, particularly for Latino patients. TExT-MED (Trial to Examine Text Message for Emergency Department Patients with Diabetes) is a text message-based program designed to improve disease knowledge, self-efficacy, and glycemic control among low-income, inner-city Latinos. In phase I, 23 patients participated in an acceptability and feasibility study. Contrary to our model, there was no increase in knowledge despite increases in self-efficacy and healthy behaviors. In phase II, we performed a mixed-methods analysis to understand how TExT-MED achieved these seemingly contradictory findings. Method: We performed a qualitative analysis of focus groups with patients from phase I. We explored patients' receipt of health information from TExT-MED and other information sources. We used these qualitative findings to perform a mixed-methods analysis of the outcomes from phase I, reanalyzing the quantitative measures of self-efficacy, diabetes knowledge, and healthy behaviors. Results: We conducted two focus groups, one in English and one in Spanish. Through qualitative analysis, we found gender differences in information sources, dietary self-efficacy, and desired educational content. Applying this knowledge, we re-stratified phase I outcomes by gender and found differential changes in diabetes knowledge, self-efficacy, and behaviors. Men had increased self-efficacy while women showed increased knowledge. Conclusions: The efficacy of mHealth on diabetes management was affected by gender. Specifically, men and women differ in their dietary self-efficacy, information sources, and desired topics in future mHealth interventions. To achieve maximal impact, future mHealth interventions should be mindful of this gender difference.
Changing Prescribing Patterns of Type 2 Diabetes Medications from 2002–2010: An Electronic Health Record-Based Evaluation
Authors: Mehta Sanjeev N. , Goldfine Allison B. , Abrahamson Martin J. , DiVincenzo Richard , Laffel Lori M. B. 
Published: January 2014

Background: The implementation of electronic health records (EHRs) may support evaluations of health care delivery, such as the prescription of newly approved medications, to adults with diabetes. We aimed to evaluate prescribing patterns of thiazolidinediones and novel glucose-lowering drug classes using electronic prescribing data contained in an outpatient EHR from 2002–2010. Methods: We identified adults with type 2 diabetes seen from 2002–2010 who were newly prescribed rosiglitazone (ROSI), pioglitazone (PIO), or a novel glucose-lowering drug class (other). The annual number of new prescriptions and their relative percentages (per 1000 patients) were calculated. Results: From 2002–2010, 6209 patients with type 2 diabetes were newly prescribed 8858 eligible medications. In 2006, ROSI and PIO accounted for 44% and 37% of new prescriptions, respectively. After 2007, the relative percentage of new ROSI prescriptions declined more rapidly than PIO prescriptions, falling to 7% and 47% of peak levels, respectively, by 2010. By 2010, the relative percentages of new ROSI, PIO, and other prescriptions were 2%, 18%, and 80%, respectively. Conclusions: Evaluations of EHR data represent a cost-effective method for evaluating diabetes medications with new Food and Drug Administration warnings or indications. Validation of demographic and clinical data will expand the scope of EHR-based evaluations of health care delivery and outcomes for adults with diabetes.
Performance Variability of Seven Commonly Used Self-Monitoring of Blood Glucose Systems: Clinical Considerations for Patients and Providers
Authors: Brazg Ronald L. , Klaff Leslie J. , Parkin Christopher G. 
Published: January 2014

Background: Blood glucose data are frequently used in clinical decision making, thus it is critical that self-monitoring of blood glucose (SMBG) systems consistently provide accurate results. Concerns about SMBG accuracy have prompted the development of newly proposed International Organization for Standardization (ISO) standards: ≥95% of individual glucose results shall fall within ±15 mg/dl of the results of the manufacturer's reference procedure at glucose concentrations <100 mg/dl and within ±15% for values >100 mg/dl. We evaluated seven marketed systems against the current and proposed ISO criteria (criterion A). Method: Capillary blood samples were collected from 100 subjects and tested on seven systems: Accu-Chek Aviva Plus, Advocate Redi-Code, Element, Embrace, Prodigy Voice, TRUEbalance, and WaveSense Presto. Results were compared with manufacturer's documented reference system, YSI or perchloric acid hexokinase; three different strip lots from each system were tested on each subject, in duplicate. Results: Compared against current ISO criteria (≥95% within ±15 mg/dl for values <75 mg/dl and ±20% for values ≥75 mg/dl) the Accu-Chek Aviva Plus, Element, and WaveSense Presto systems met accuracy criteria. However, only the Accu-Chek Aviva Plus met the proposed ISO criteria (criterion A) in all three lots. The other six systems failed to meet the criteria in at least two of the three lots, showing lot-to-lot variability, high/low bias, and variations due to hematocrit. Conclusions: Inaccurate SMBG readings can potentially adversely impact clinical decision making and outcomes. Clinicians can reduce controllable variables by prescribing accurate SMBG systems. Adherence to the proposed ISO criteria should enhance patient safety by improving the accuracy of SMBG systems.
Self-Adjustment of Insulin Dose Using Graphically Depicted Self-Monitoring of Blood Glucose Measurements in Patients with Type 1 Diabetes Mellitus
Authors: Reichel Andreas , Rietzsch Hannes , Ludwig Barbara , Röthig Katrin , Moritz Annette , Bornstein Stefan R. 
Published: January 2014

Background: There is a need for patients to be able to adjust their insulin doses accurately and independently during continuous subcutaneous insulin infusion (CSII) therapy in order to avoid glycemic excursions and improve glycemic control. Use of new technology has the potential to aid patients in visualizing their circadian patterns and improving their understanding of data provided by self-monitored blood glucose (SMBG) measurements. Methods: A 24-week crossover study was performed in 25 patients with type 1 diabetes mellitus using CSII and SMBG. Patients were randomized either to entering blood glucose data into handwritten logbooks or to using the Accu-Chek SmartPix information management system (IMS) coupled with instructions from a training manual to aid interpretation of the IMS readings. Patients analyzed these chart readings every 2 weeks, and outpatient visits were scheduled for both arms every 6 weeks. Results: There was a significantly lower mean overall blood glucose level with the IMS compared with use of a logbook (139 ± 16.2 versus 150 ± 19.8 mg/dl; Δ = 10.8 mg/dl; p < .01), and a significantly higher proportion of blood glucose values was in the target range compared with use of a logbook (43.6% versus 38.5%; p < .001). Hypoglycemic events were also significantly lower with the IMS compared with logbooks (3.7 fewer events/6 weeks; p < .05). There was no significant difference between groups in the daily frequency of SMBG measurements. Conclusions: The use of an IMS, coupled with an easily understood training manual, enables patients to improve glycemic control by performing accurate and timely self-adjustments to their insulin regimens.
In Silico Evaluation of an Artificial Pancreas Combining Exogenous Ultrafast-Acting Technosphere Insulin with Zone Model Predictive Control
Authors: Lee Justin J. , Dassau Eyal , Zisser Howard , Harvey Rebecca A. , Jovanovič Lois , Doyle Francis J. 
Published: January 2014

Background: Because of the slow pharmacokinetics of subcutaneous (SC) insulin, avoiding postprandial hyperglycemia has been a major challenge for an artificial pancreas (AP) using SC insulin without a meal announcement. Methods: A semiautomated AP with Technosphere® Insulin (TI; MannKind Corporation, Valencia, CA) was designed to combine pulmonary and SC insulin. Manual inhalation of 10 U ultrafast-absorbing TI at mealtime delivers the first, or cephalic, phase of insulin, and an SC insulin pump controlled by zone model predictive controller delivers second-phase and basal insulin. This AP design was evaluated on 100 in silico subjects from the University of Virginia/Padova metabolic simulator using a protocol of two 50 g carbohydrate (CHO) meals and two 15 g CHO snacks. Results: Simulation analysis shows that the semiautomated AP with TI provides 32% and 16% more time in the controller target zone (80–140 mg/dl) during the 4 h postprandial period, with 39 and 20 mg/dl lower postprandial blood glucose peak on average than the pure feedback AP and the AP with manual feed-forward SC bolus, respectively. No severe hypoglycemia (<50 mg/dl) was observed in any cases. Conclusions: The semiautomated AP with TI provides maximum time in the clinically accepted region when compared with pure feedback AP and AP with manual feed-forward SC bolus. Furthermore, the semiautomated AP with TI provides a flexible operation (optional TI inhalation) with minimal user interaction, where the controller design can be tailored to specific user needs and abilities to interact with the device.