bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virtual Reality Technologies for Research and Education in Obesity and Diabetes: Research Needs and Opportunities
Authors: Ershow Abby G. , Peterson Charles M. , Riley William T. , Rizzo Albert Skip , Wansink Brian 
Published: January 2014

The rising rates, high prevalence, and adverse consequences of obesity and diabetes call for new approaches to the complex behaviors needed to prevent and manage these conditions. Virtual reality (VR) technologies, which provide controllable, multisensory, interactive three-dimensional (3D) stimulus environments, are a potentially valuable means of engaging patients in interventions that foster more healthful eating and physical activity patterns. Furthermore, the capacity of VR technologies to motivate, record, and measure human performance represents a novel and useful modality for conducting research. This article summarizes background information and discussions for a joint July 2010 National Institutes of Health — Department of Defense workshop entitled Virtual Reality Technologies for Research and Education in Obesity and Diabetes. The workshop explored the research potential of VR technologies as tools for behavioral and neuroscience studies in diabetes and obesity, and the practical potential of VR in fostering more effective utilization of diabetes- and obesity-related nutrition and lifestyle information. Virtual reality technologies were considered especially relevant for fostering desirable health-related behaviors through motivational reinforcement, personalized teaching approaches, and social networking. Virtual reality might also be a means of extending the availability and capacity of health care providers. Progress in the field will be enhanced by further developing available platforms and taking advantage of VR's capabilities as a research tool for well-designed hypothesis-testing behavioral science. Multidisciplinary collaborations are needed between the technology industry and academia, and among researchers in biomedical, behavioral, pedagogical, and computer science disciplines. Research priorities and funding opportunities for use of VR to improve prevention and management of obesity and diabetes can be found at agency websites (National Institutes of Health: http://grants.nih.gov/grants/guide/index.html ; Department of Defense: www.tatrc.org ).
The Fixed Combination of Pioglitazone and Metformin Improves Biomarkers of Platelet Function and Chronic Inflammation in Type 2 Diabetes Patients: Results from the PIOfix Study
Authors: Schöndorf Thomas , Musholt Petra B. , Hohberg Cloth , Forst Thomas , Lehmann Ute , Fuchs Winfried , Löbig Mirjam , Müller Jürgen , Pfützner Andreas 
Published: January 2014

Background: Type 2 diabetes mellitus (T2DM) is characterized by a proinflammatory and procoagulant condition. This study investigates the impact of a pioglitazone plus metformin therapy on biomarkers of inflammation and platelet activation in comparison to a treatment with glimepiride plus metformin. Methods: The study was designed as a multicenter, randomized, double-blinded two-arm trial. Patients with T2DM and dyslipidemia under metformin monotherapy with hemoglobin A1c value between 6.5% and 9.0% were eligible for trial participation. Blood was drawn at baseline and after 24 weeks of treatment from patients of five centers. Markers of inflammation and thrombocyte function (soluble CD40 ligand, thromboxane, vWillebrand factor, adhesion molecules, clotting reaction) were evaluated subsequently in a central laboratory. Results: A total of 46 patients were included in the final analyses. Mean (± standard deviation) age was 58.5 ± 9.0 years (13 women, 33 men; disease duration 6.3 ± 5.0 years; body mass index 32.0 ± 4.8 kg/m2). A total of 25 patients were treated with pioglitazone plus metformin, and 21 patients were in the glimepiride arm. There was a significant decline of E-selectin (-3.7 ± 4.8 ng/ml, p < .001 versus baseline), vWillebrand factor (−19.5 ± 32.0%, p < .05), and high-sensitivity C-reactive protein concentrations (−1.08 ± 0.91 mg/liter, p < .05) in the metformin + pioglitazone arm only (metformin + glimepiride, −0.5 ± 3.4 ng/ml, +1.4 ± 33.2%, + 0.08 ± 0.72 mg/liter, respectively, all not significant). Also, all other surrogate markers for platelet function and inflammation showed slight improvements in the metformin + pioglitazone arm but not in the metformin + glimepiride arm. Conclusions: The fixed metformin + pioglitazone combination treatment showed an overall improvement of laboratory surrogate markers, indicating improvement of platelet function and of chronic systemic inflammation, which was not seen with metformin + glimepiride.
Identifying Type 1 and Type 2 Diabetic Cases Using Administrative Data: A Tree-Structured Model
Authors: Lo-Ciganic Weihsuan , Zgibor Janice C. , Ruppert Kristine , Arena Vincent C. , Stone Roslyn A. 
Published: January 2014

Background: To date, few administrative diabetes mellitus (DM) registries have distinguished type 1 diabetes mellitus (T1DM) from type 2 diabetes mellitus (T2DM). Objective: Using a classification tree model, a prediction rule was developed to distinguish T1DM from T2DM in a large administrative database. Methods: The Medical Archival Retrieval System at the University of Pittsburgh Medical Center included administrative and clinical data from January 1, 2000, through September 30, 2009, for 209,647 DM patients aged ≥18 years. Probable cases (8,173 T1DM and 125,111 T2DM) were identified by applying clinical criteria to administrative data. Nonparametric classification tree models were fit using TIBCO Spotfire S+ 8.1 (TIBCO Software), with model size based on 10-fold cross validation. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of T1DM were estimated. Results: The main predictors that distinguished T1DM from T2DM are age <40 years; International classification of Disease, 9th revision, codes of T1DM or T2DM diagnosis; inpatient oral hypoglycemic agent use; inpatient insulin use; and episode(s) of diabetic ketoacidosis diagnosis. Compared with a complex clinical algorithm, the tree-structured model to predict T1DM had 92.8% sensitivity, 99.3% specificity, 89.5% PPV, and 99.5% NPV. Conclusion: The preliminary predictive rule appears to be promising. Being able to distinguish between DM subtypes in administrative databases will allow large-scale subtype-specific analyses of medical care costs, morbidity, and mortality.
Pediatric Diabetes Registries: When Baby Steps are Not Enough
Authors: Malone Chad , Kennedy Gary D. 
Published: January 2014

Effective diabetes research relies on pattern recognition. Although information technology (IT) has been used to aid researchers in recognizing patterns, there are still barriers to effective data collection, analysis, and collaboration inherent in using outdated methods and technology designed to fulfill clinical, not research, purposes. This article discusses seven problems with current research and outlines a solution in which innovative IT can be harnessed to overcome each problem, resulting in better research outcomes. New IT solutions on the market, such as meta-registries, are designed specifically to handle the complex data collection and analysis problems associated with diabetes research. A meta-registry with an ontology automatically harmonizes data from disparate sources, allowing researchers to devote their time to pattern recognition. With all essential data centralized and harmonized, researchers are also provided with a more complete view of each patient or research subject. When researchers can view and report across all data types at the same time, they are able to discover patterns and associations that are indistinguishable using traditional methodologies. This capability proves extremely beneficial, particularly for multifactorial disease research such as diabetes research.
Monitoring of Glucose in Brain, Adipose Tissue, and Peripheral Blood in Patients with Traumatic Brain Injury: A Microdialysis Study
Authors: Rostami Elham , Bellander Bo-Michael 
Published: January 2014

Background: Episodes of hyperglycemia are considered to be a secondary insult in traumatically brain-injured patients and have been shown to be associated with impaired outcome. Intensive insulin therapy to maintain a strict glucose level has been suggested to decrease morbidity and mortality in critically ill patients but this aggressive insulin treatment has been challenged. One aspect of strict glucose control is the risk of developing hypoglycemia. Extracellular intracerebral hypoglycemia monitored by intracerebral microdialysis has been shown to correlate with poor outcome. Monitoring of blood glucose during neurointensive care is important because adequate glucose supply from the systemic circulation is crucial to maintain the brain's glucose demand after brain injury. This study investigates the correlation of glucose levels in peripheral blood, subcutaneous (SC) fat, and extracellular intracerebral tissue in patients with severe traumatic brain injury during neurointensive care. Methods: In this study, we included 12 patients with severe traumatic brain injury. All patients received one microdialysis catheter each, with a membrane length of 10 mm (CMA 70, CMA Microdialysis AB) in the injured hemisphere of the brain and in the noninjured hemisphere of the brain. An additional microdialysis catheter with a membrane length of 30 mm (CMA 60, CMA Microdialysis AB) was placed in the periumbilical subcutaneous adipose tissue. We studied the correlation among levels of glucose measured in peripheral blood, adipose tissue, and the noninjured hemisphere of the brain during the first 12 hours and during 3 consecutive days in neurointensive care. Results: We found a significant positive correlation between levels of glucose in peripheral blood, SC fat, and the noninjured brain during the initial 12 hours but not in injured brain. However, the result varied between the patients during the 3-day measurements. In 7 patients, there was a significant positive correlation between glucose in blood and noninjured brain, while in 4 patients this correlation was poor. In 4 patients, there was a significant positive correlation in injured brain and blood. Furthermore, there was a significant correlation between brain and adipose tissue glucose during the 3-day measurements in 11 out of 12 patients. Conclusion: This study indicates that there is a good correlation between blood glucose and adipose tissue during initial and later time points in the neurointensive care unit whereas the correlation between blood and brain seems to be more individualized among patients. This emphasizes the importance of using intracerebral microdialysis to ensure adequate intracerebral levels of glucose in patients suffering from severe traumatic brain injury and to detect hypoglycemia in the brain despite normal levels of blood glucose.
Benefits of Blinded Continuous Glucose Monitoring during a Randomized Clinical Trial
Authors: Muchmore Douglas , Sharp Melissa , Vaughn Daniel 
Published: January 2014

Background: Real-time, personal continuous glucose monitoring (CGM) is a validated technology that can help patients improve glycemic control. Blinded CGM is a promising technology for obtaining retrospective data in clinical research where the quantity and quality of blood glucose information is important. This study was designed to investigate the use of novel procedures to enhance data capture from blinded CGM. Methods: Following a 4-week run-in, 46 patients with type 1 diabetes were randomized to one of two prandial insulins for a 12-week treatment period, after which they were crossed over to the alternate treatment for 12 weeks. Continuous glucose monitoring was implemented at the end of run-in (practice only) and during the last 2 weeks of each treatment period. Eighty percent of 288 possible daily glucose values were required for at least three days. Continuous glucose monitoring was extended for an additional week if these criteria were not met, and patients were allowed to insert sensors at home when necessary. Continuous glucose monitoring results were compared to reference eight-point self-monitoring of blood glucose (SMBG). Results: Higher than expected sensor failure rate was approximately 25%. During run-in, 12 of 45 attempted profiles failed adequacy criteria. However, treatment periods had only 1 of 82 attempted profiles considered inadequate (6 cases required an additional week of CGM). Using SMBG as reference, 93.7% of 777 CGM values were in Clarke error grid zones A+B. Conclusions: With appropriate training, adequate practice, and opportunity to repeat blinded CGM as needed, nearly 100% of attempted profiles can be obtained successfully.
Reduction of Postprandial Glycemic Excursions in Patients with Type 1 Diabetes: A Novel Human Insulin Formulation versus a Rapid-Acting Insulin Analog and Regular Human Insulin
Authors: Heinemann Lutz , Hompesch Marcus , Flacke Frank , Simms Patrick , Pohl Rody , Albus Kerstin , Pfützner Andreas , Steiner Solomon 
Published: January 2014

Background: Evaluation of postprandial glycemic excursions in patients with type 1 diabetes with three prandial insulins: VIAject™ (Linjeta™), an ultra-fast insulin (UFI); insulin lispro (LIS); and regular human insulin (RHI). Methods: After stabilization of preprandial glycemia, 18 patients received a subcutaneous injection with an individualized insulin dose prior to a meal. Results: Injection of UFI resulted in a more rapid insulin absorption than with either LIS or RHI (time to half-maximal insulin levels: 13.1 ± 5.2 vs 25.4 ± 7.6 and 38.4 ± 19.5 min; p = .001 vs LIS and p < .001 vs RHI, LIS vs. RHI p < .001). Maximal postprandial glycemia was lower with UFI (0–180 min; 157 ± 30 mg/dl; p = .002 vs RHI) and LIS (170 ± 42 mg/dl; p = .668 vs RHI) than after RHI (191 ± 46 mg/dl; RHI vs LIS p = .008). The difference between maximum and minimum glycemia was smaller with UFI (70 ± 17 mg/dl) than with either RHI (91 ± 33 mg/dl; p = .007 vs UFI) or LIS (89 ± 18 mg/dl; p = .011 vs UFI). Also, the area under the blood glucose profile was lower with UFI than with RHI (0–180 min; 21.8 ± 5.8 vs 28.4 ± 7.6 g·min/dl; p < .001). Conclusions: The rapid absorption of UFI results in a reduction of postprandial glycemic excursions.
Creation of the Web-Based University of Chicago Monogenic Diabetes Registry: Using Technology to Facilitate Longitudinal Study of Rare Subtypes of Diabetes
Authors: Greeley Atma W. , Naylor Rochelle N. , Cook Lindsay S. , Tucker Susan E. , Lipton Rebecca B. , Philipson Louis H. 
Published: January 2014

Background: Monogenic diabetes is a group of disorders caused by mutations in any one of a number of genes. Although a monogenic diagnosis—estimated to represent as much as 2% of all diabetes patients—can have a transformational impact on treatment, the majority of monogenic cases remain unidentified and little is known about their natural history. We thus created the first United States Monogenic Diabetes Registry ( http://www.kovlerdiabetescenter.org/registry/ ) for individuals with either neonatal diabetes diagnosed before 1 year of age or with a phenotype suggestive of maturity-onset diabetes of the young. Methods: Inclusion criteria and consent documents are viewable on our Web site, which allows secure collection of contact information to facilitate telephone consent and enrollment. Relevant medical, family, and historical data are collected longitudinally from a variety of sources and stored in our Web-accessible secure database. Results: We have enrolled well over 700 subjects in the registry so far, with steady recruitment of those diagnosed under 1 year of age and increasing enrollment of those diagnosed later in life. Initially, participants were mostly self-referred but are increasingly being referred by their physicians. Comprehensive survey and medical records data are collected at enrollment, with ongoing collection of longitudinal data. Associated private Facebook and email discussion groups that we established have already fostered active participation. Conclusions: Our early success with the Monogenic Diabetes Registry demonstrates the effectiveness of low-cost Web-based tools, including surveys, the Research Electronic Data Capture database program, and discussion groups, for efficient enrollment and support of rare patients, and collection and maintenance of their data.
Hypoglycemia Impairs Quality of Blood Glucose Simulation in a Clinical Decision Support System
Authors: Johansen Mette Dencker , Hejlesen Ole K. , Cavan David A. 
Published: January 2014

Background: Clinical decision support systems allow for decisions based on blood glucose simulations. The DiasNet simulation tool is based on accepted principles of physiology and simulates blood glucose concentrations accurately in type 1 diabetes mellitus (T1DM) patients during periods without hypoglycemia, but deviations appear after hypoglycemia, possibly because of the long-term glucose counter-regulation to hypoglycemia. The purpose of this study was to evaluate the impact of hypoglycemia on blood glucose simulations. Method: Continuous glucose monitoring (CGM) data and diary data (meals, insulin, self-monitored blood glucose) were collected for 2 to 5 days from 17 T1DM patients with poor glycemic control. Hypoglycemic episodes [CGM glucose <63 mg/dl (3.5 mmol/liter) for ≥20 min] were identified in valid (well-calibrated) CGM data. For 24 hours after each hypoglycemic episode, a simulated (DiasNet) glucose profile was compared to the CGM glucose. Results: A total of 52 episodes of hypoglycemia were identified in valid data. All subjects had at least one hypoglycemic episode. Ten episodes of hypoglycemia from nine subjects were eligible for analysis. The CGM glucose was significantly ( p < .05) higher than simulated blood glucose for a period of 13 h, beginning 8 h after hypoglycemia onset. Conclusions: The present data show that hypoglycemia introduces substantial and systematic simulation errors for up to 24 h after hypoglycemia. This underlines the need for further evaluation of mechanisms behind this putative long-term glucose counter-regulation to hypoglycemia. When using blood glucose simulations in decision support systems, the results indicate that simulations for several hours following a hypoglycemic event may underestimate glucose levels by 100 mg/dl (5.6 mmol/liter) or more.
Analysis of the Indian Council of Medical Research—India Diabetes (ICMR-INDIAB) Study
Authors: Narayan K. M. Venkat , Echouffo-Tcheugui Justin B. 
Published: January 2014

The Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study is the first nationally representative survey of diabetes in India. It aims to provide national and regional counts of diabetes and prediabetes and also of cardiovascular risk factors. This ambitious and complex survey uses robust sampling techniques, standardized methods, appropriate quality assurance, and a three-phase data collection. However, the survey should be completed within a reasonable time span to avoid a differential effect of secular trends on regional estimates. A high response rate and low missing values must also be ensured. Reliance on capillary whole blood glucose (CBG) for the diagnosis of hyperglycemic states is a limitation of the survey. However, this is a reasonable compromise given the practical challenges of such a large study. Despite a good correlation between CBG and venous plasma glucose (VPG), the use of CBG may misclassify glycemic status. A better characterization of the CBG-VPG relationship, and the performance of CBG for detecting hyperglycemia, using a much larger sample, seems therefore advisable. This should be possible given that venous blood has been collected on a sizeable subset of participants. The Indian Council of Medical Research and the Madras Diabetes Research Foundation deserve praise for this massive undertaking, which will highlight areas for policy action and establish a national framework for noncommunicable disease (NCD) surveillance. The ICMR-INDIAB survey lays the foundation for effective NCD prevention and control and for applied public health research.
The Use of Optical Coherence Tomography to Determine the Effect of Thiazolidinediones on Retinal Thickness in Patients with Type 2 Diabetes
Authors: Tarbett Aaron K. , VanRoekel Ronald C. , Howard Robin S. , Vigersky Robert A. 
Published: January 2014

Objective: Thiazolidinediones (TZDs) are insulin-sensitizing agents that are associated with peripheral edema and have been reported to be associated with diabetic macular edema (DME). We hypothesized that TZDs produce subclinical increases in retinal thickness that may be detected by optical coherence tomography (OCT) but are not seen on routine dilated funduscopic examination. Research Design and Methods: We used OCT to screen for subclinical DME in a cross-sectional study of patients with type 2 diabetes; 29 patients were taking TZDs and 58 were not taking TZDs. We analyzed data using multiple linear regression analysis to investigate associations of retinal thickness with clinical characteristics. Results: There was no significant difference between the central subfield retinal thickness in the non-TZD group (206.4 ± 28.0 microns; n = 59) and TZD group (204.1 ± 26.1 microns; n = 29) ( p = .72) nor were there significant differences in any other retinal subfield. There was no significant correlation of retinal thickness with laboratory results studies—peripheral edema, gender, age, duration of diabetes, individual, or combinations of medications. Retinal thickness differences between regions displayed normal anatomical variation. However, ethnic differences were found in which African-Americans had thinner retinas in all regions than Caucasians regardless of whether or not they used TZDs. Conclusions: These data suggest that TZDs do not cause subclinical DME in a demographically diverse patient population with diabetes. The established normal ranges for macular thickness may require adjustment based on ethnicity.