bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pharmacokinetic Characterization of the Novel Pulmonary Delivery Excipient Fumaryl Diketopiperazine
Authors: Potocka Elizabeth , Cassidy James P. , Haworth Pamela , Heuman Douglas , van Marle Sjoerd , Baughman Robert A. 
Published: January 2014

Background: Technosphere® [Bis-3, 6(4-fumarylaminobutyl)-2, 5-diketopiperazine (FDKP)] microparticles, the integral component of the Technosphere inhalation system, deliver drugs to the deep lung and have been used to administer insulin and glucagon-like peptide-1 via inhalation in clinical studies. Three studies were conducted to characterize FDKP pharmacokinetics, including assessments in subjects with diabetic nephropathy (DNP), in subjects with chronic liver disease (CLD), and in healthy subjects. Methods: An open-label, nonrandomized, two-period, fixed-sequence crossover absorption, distribution, metabolism, and excretion (ADME) study was conducted in six healthy nonsmoking men who received single intravenous and oral doses of [14C]FDKP solution, with serial sampling of blood, urine, feces, and expired air. Additionally, two single-dose, open-label, parallel-design studies with 20 mg of inhaled FDKP were conducted in (1) 12 diabetic subjects with normal renal function and 24 DNP subjects and (2) 12 healthy subjects and 21 CLD subjects. Results: In the ADME study, >95% of the intravenous dose and <3% of the oral dose were recovered in urine, with no evidence of metabolism. No significant pharmacokinetic differences were observed between healthy subjects and CLD subjects [geometric mean (% coefficient of variation) area under the curve from time 0 to 480 minutes (AUC0-480): 26,710 (34.8) and 31,477 (28.8) ng/ml·min, respectively]. Maximum observed drug concentration ( Cmax) and AUC0-480 were higher in DNP subjects than in subjects with normal renal function [ Cmax: 159.9 (59.4) ng/ml versus 147.0 (44.3) ng/ml; AUC0-480: 36,869 (47.2) ng/ml·min versus 30,474 (31.8) ng/ml·min]. None of the differences observed were considered clinically significant. Conclusions: Fumaryl diketopiperazine is predominantly cleared unchanged by the kidney with essentially no oral bioavailability. Technosphere is a safe delivery vehicle for medications administered via inhalation.
Glucose Information for Tight Glycemic Control: Different Methods with Different Challenges
Authors: Weber Christian , Neeser Kurt 
Published: January 2014

Rigorous glucose control is essential for prevention of diabetes-related complications in diabetes patients. Even without diabetes, tight glucose control is beneficial in hospitalized, critically ill patients. Actually, three different glucose measurement methods are used: (1) hand held devices, (2) blood-gas analyzers, and (3) laboratory analyzers in core laboratories. Each method is subject to specific challenges and limitations that can affect the overall system performance. In this article, we aim to demonstrate that even glucose measurement results from core laboratories (professional laboratory systems) do not necessarily reflect the absolute “true” glucose level of a patient.
The Physiology of Glucagon
Authors: Taborsky Gerald J. 
Published: January 2014

This short review outlines the physiology of glucagon in vivo, with an emphasis on its neural control, the author's area of interest. Glucagon is secreted from alpha cells, which are a minority of the pancreatic islet. Anatomically, they are down stream from the majority islet beta cells. Beta-cell secretory products restrain glucagon secretion. Activation of the autonomic nerves, which innervate the islet, increases glucagon secretion. Glucagon is secreted into the portal vein and thus has its major physiologic action at the liver to break down glycogen. Glucagon thereby maintains hepatic glucose production during fasting and increases hepatic glucose production during stress, including the clinically important stress of hypoglycemia. Three different mechanisms proposed to stimulate glucagon secreted during hypoglycemia are discussed: (1) a stimulatory effect of low glucose directly on the alpha cell, (2) withdrawal of an inhibitory effect of adjacent beta cells, and (3) a stimulatory effect of autonomic activation. In type 1 diabetes (T1DM), increased glucagon secretion contributes to the elevated ketones and acidosis present in diabetic ketoacidosis (DKA). It also contributes to the hyperglycemia seen with or without DKA. The glucagon response to insulin-induced hypoglycemia is impaired soon after the development of T1DM. The mediators of this impairment include loss of beta cells and loss of sympathetic nerves from the autoimmune diabetic islet.
Benchmarking Glucose Results through Automation: The 2009 Remote Automated Laboratory System Report
Authors: Anderson Marcy , Zito Denise , Kongable Gail 
Published: January 2014

Background: Hyperglycemia in the adult inpatient population remains a topic of intense study in U.S. hospitals. Most hospitals have established glycemic control programs but are unable to determine their impact. The 2009 Remote Automated Laboratory System (RALS) Report provides trends in glycemic control over 4 years to 576 U.S. hospitals to support their effort to manage inpatient hyperglycemia. Methods: A proprietary software application feeds de-identified patient point-of-care blood glucose (POC-BG) data from the Medical Automation Systems RALS-Plus data management system to a central server. Analyses include the number of tests and the mean and median BG results for intensive care unit (ICU), non-ICU, and each hospital compared to the aggregate of the other hospitals. Results: More than 175 million BG results were extracted from 2006–2009; 25% were from the ICU. Mean range of BG results for all inpatients in 2006, 2007, 2008, and 2009 was 142.2–201.9, 145.6–201.2, 140.6–205.7, and 140.7–202.4 mg/dl, respectively. The range for ICU patients was 128–226.5, 119.5–219.8, 121.6–226.0, and 121.1–217 mg/dl, respectively. The range for non-ICU patients was 143.4–195.5, 148.6–199.8, 145.2–201.9, and 140.7–203.6 mg/dl, respectively. Hyperglycemia rates of >180 mg/dl in 2008 and 2009 were examined, and hypoglycemia rates of <40 mg/dl (severe) and <70 mg/dl (moderate) in both 2008 and 2009 were calculated. Conclusions: From these data, hospitals can determine the current state of glycemic control in their hospital and in comparison to other hospitals. For many, glycemic control has improved. Automated POC-BG data management software can assist in this effort.
No Relevant Relationship between Glucose Variability and Oxidative Stress in Well-Regulated Type 2 Diabetes Patients
Authors: Siegelaar Sarah E. , Barwari Temo , Kulik Wim , Hoekstra Joost B. , DeVries J. Hans 
Published: January 2014

Background: A strong relationship between glycemic variability and oxidative stress in poorly regulated type 2 diabetes (T2DM) on oral medication has been reported. However, this relationship was not seen in type 1 diabetes. The purpose of this study is to reexamine the relation between glycemic variability and oxidative stress in a cohort of T2DM patients on oral medication. Methods: Twenty-four patients with T2DM on oral glucose lowering treatment underwent 48 hours of continuous glucose monitoring (CGMS® System Gold™, Medtronic MiniMed) and simultaneous collection of two consecutive 24-hour urine samples for determination of 15( S)-8-iso-prostaglandin F2α (PGF2α) using high-performance liquid chromatography tandem mass spectrometry. Standard deviation (SD) and mean amplitude of glycemic excursions (MAGE) were calculated as markers of glycemic variability. Results: Included in the study were 66.7% males with a mean age (range) of 59 (36–76) years and a mean (SD) HbA1c of 6.9% (0.7). Median [interquartile range (IQR)] urinary 15( S)-8-iso-PGF2α excretion was 176.1 (113.6–235.8) pg/mg creatinine. Median (IQR) SD was 31 (23–40) mg/dl and MAGE 85 (56–106) mg/dl. Spearman correlation did not show a significant relation for SD (ρ = 0.15, p = .49) or MAGE (ρ = 0.23, p = .29) with 15( S)-8-iso-PGF2α excretion. Multivariate regression analysis adjusted for age, sex, HbA1c, and exercise did not alter this observation. Conclusions: We did not find a relevant relationship between glucose variability and 15( S)-8-iso-PGF2α excretions in T2DM patients well-regulated with oral medication that would support an interaction between hyperglycemia and glucose variability with respect to the formation of reactive oxygen species.
FreeStyle Navigator Continuous Glucose Monitoring System with TRUstart Algorithm, a 1-Hour Warm-up Time
Authors: McGarraugh Geoffrey , Brazg Ronald , Weinstein Richard 
Published: January 2014

Background: The first-generation FreeStyle Navigator® Continuous Glucose Monitoring System (FreeStyle Navigator CGM) requires a 10 h warm-up period to avoid inaccurate glucose readings caused by sensor insertion trauma and wound-healing processes. The performance of a second-generation FreeStyle Navigator CGM that begins reporting glucose 1 h after sensor insertion is described. Methods: Second-generation FreeStyle Navigator CGM performance was evaluated in an in-clinic study using the YSI Model 2300 STATPlus Glucose Analyzer as reference with 47 subjects with type 1 diabetes. The reference readings were taken at 15 min intervals, and the study was designed to emphasize the first 10 h of use. Results: The second-generation FreeStyle Navigator CGM exhibited continuous glucose error grid analysis ratings of 93.7% “clinically accurate”, 3.6% “benign errors”, and 2.8% “clinical errors” and a mean and median absolute relative difference of 14.5% and 10.7%, respectively. The second-generation algorithm detected signal instability in the first 10 h of use and suspended the reporting of 14.1% of first day continuous glucose readings. The clinical accuracy of the second-generation FreeStyle Navigator CGM was similar for the first 10 h versus subsequent hours, with 92.6% and 94.2% “clinically accurate” readings, respectively. Conclusion: The warm-up period for the second-generation FreeStyle Navigator CGM was reduced from 10 to 1 h, with minimal interruption of glucose reporting and without sacrificing clinical performance.
H.E.A.L.T.H.: Efficacy of an Internet/Population-Based Behavioral Weight Management Program for the U.S. Army
Authors: Stewart Tiffany , Han Hongmei , Allen H. Raymond , Bathalon Gaston , Ryan Donna H. , Newton Robert L. , Williamson Donald A. 
Published: January 2014

Background: A Significant number of soldiers exceed the maximum allowable weight standards or have body weights approaching the maximum allowable weight standards. This mandates development of scalable approaches to improve compliance with military weight standards. Methods: We developed an intervention that included two components: (1) an Internet-based weight management program (Web site) and (2) a promotion program designed to promote and sustain usage of the Web site. The Web site remained online for 37 months, with the Web site promotion program ending after 25 months. Results: Soldiers' demographics were as follows: Mean age, 32 years; body mass index (BMI), 28 kg/m2; 31% female; and 58% Caucasian. Civilian demographics were as follows: Mean age, 38 years; BMI, 30 kg/m2; 84% female; and 55% Caucasian. Results indicated that 2417 soldiers and 2147 civilians ( N = 4564) registered on the Web site. In the first 25 months (phase 1) of the study, new participants enrolled on the Web site at a rate of 88 (soldiers) and 80 (civilians) per month. After the promotion program was removed (phase 2), new participants enrolled at a rate of 18 (soldiers) and 13 (civilians) per month. Utilization of the Web site was associated with self-reported weight loss ( p < .0001). Participants who utilized the Web site more frequently lost more weight ( p < .0001). Participants reported satisfaction with the Web site. Conclusions: The Web site and accompanying promotion program, when implemented at a military base, received satisfactory ratings and benefited a subset of participants in promoting weight loss. This justifies further examination of effectiveness in a randomized trial setting.
Cost-Effectiveness of Implementing the Chronic Care Model for Diabetes Care in a Military Population
Authors: Kuo Shihchen , Bryce Cindy L. , Zgibor Janice C. , Wolf Donna L. , Roberts Mark S. , Smith Kenneth J. 
Published: January 2014

Background: Applying the chronic care model (CCM) for diabetes management helps improve health outcomes and patient care. The CCM was implemented at U.S. Air Force Wilford Hall Medical Center through the Diabetes Outreach Clinic (DOC) in 2006, but its cost-effectiveness in this setting is unknown. Methods: We constructed a Markov decision model to estimate DOC cost-effectiveness compared with usual care (UC) over a 20-year period. Based on empirical, post-intervention demographic and clinical data, we applied United Kingdom Prospective Diabetes Study risk equations to predict long-term probabilities of developing microvascular or macrovascular complications. Health care system and societal perspectives were considered, discounting costs and benefits at 3% annually. Intervention costs and outcomes were obtained from military data, while other costs, disease progression data, and utilities were drawn from published literature. Results: From a health care system perspective, the DOC cost $45,495 per quality-adjusted life-year (QALY) compared with UC; from a societal perspective, the DOC compared with UC cost $42,051/QALY (when the model started with the uncomplicated diabetes cohort), $61,243/QALY (when starting with the DOC cohort), or $61,813/QALY (when starting with the UC cohort). In one-way sensitivity analyses, results were most sensitive to yearly costs for specialty care visits. In probabilistic sensitivity analysis, the DOC was favored in 51% of model iterations using an acceptability threshold of $50,000/QALY and in 72% at a threshold of $100,000/QALY. Conclusions: The DOC strategy for diabetes care, performed with the CCM methodology in a military population, appears to be economically reasonable compared with UC.
Characterizing Blood Glucose Variability Using New Metrics with Continuous Glucose Monitoring Data
Authors: Marling Cynthia R. , Shubrook Jay H. , Vernier Stanley J. , Wiley Matthew T. , Schwartz Frank L. 
Published: January 2014

Objective: Glycemic variability contributes to oxidative stress, which has been linked to the pathogenesis of the long-term complications of diabetes. Currently, the best metric for assessing glycemic variability is mean amplitude of glycemic excursion (MAGE); however, MAGE is not in routine clinical use. A glycemic variability metric in routine clinical use could potentially be an important measure of overall glucose control and a predictor of diabetes complication risk not detected by glycosylated hemoglobin (A1C) levels. This study aimed to develop and evaluate new automated metrics of glycemic variability that could be routinely applied to continuous glucose monitoring (CGM) data to assess and enhance glucose control. Method: Individual 24 h CGM tracings from our clinical diabetes research database were scored for MAGE and two additional metrics designed to compensate for aspects of variability not captured by MAGE: (1) number of daily glucose fluctuations >75 mg/dl that leave the normal range (70–175 mg/dl), or excursion frequency, and (2) total daily fluctuation, or distance traveled. These scores were used to train machine learning algorithms to recognize excessive variability based on physician ratings of daily CGM charts, producing a third metric of glycemic variability: perceived variability. Finger stick A1C (average) and serum 1,5-anhydroglucitol (postprandial) levels were used as clinical markers of overall glucose control for comparison. Results: Mean amplitude of glycemic excursion, excursion frequency, and distance traveled did not adequately quantify the glycemic variability visualized by physicians who evaluated the daily CGM plots. A naive Bayes classifier was developed that characterizes CGM tracings based on physician interpretations of tracings. Preliminary results suggest that the number of excessively variable days, as determined by this naive Bayes classifier, may be an effective way to automatically assess glycemic variability of CGM data. This metric more closely reflects 90-day changes in serum 1,5-anhydroglucitol levels than does MAGE. Conclusion: We have developed a new automated metric to assess overall glycemic variability in people with diabetes using CGM, which could easily be incorporated into commercially available CGM software. Additional work to validate and refine this metric is underway. Future studies are planned to correlate the metric with both urinary 8-iso-prostaglandin F2 alpha excretion and serum 1,5-anhydroglucitol levels to see how well it identifies patients with high glycemic variability and increased markers of oxidative stress to assess risk for long-term complications of diabetes.
The Indian Council of Medical Research—India Diabetes (ICMR-INDIAB) Study: Methodological Details
Authors: Anjana Ranjit Mohan , Pradeepa Rajendra , Deepa Mohan , Datta Manjula , Sudha Vasudevan , Unnikrishnan Ranjit , Nath Lalith M. , Das Ashok Kumar , Madhu Venkata , Rao Paturi Vishnupriya , Shukla Deepak Kumar , Kaur Tanvir , Ali Mohammed K. , Mohan Viswanathan 
Published: January 2014

Background: Currently available estimates of diabetes prevalence in India are based on published data derived from very few studies. The Indian Council of Medical Research-India Diabetes (ICMR-INDIAB) study is a community-based survey conceived with the aim of obtaining the prevalence rates of diabetes in India as a whole, covering all 28 states, the National Capital Territory of Delhi, and two of the union territories in the mainland of India, with a total sample size of 124,000 individuals. Methods: A stratified multistage sampling design has been used. In all study subjects, a structured questionnaire was administered and anthropometric parameters and blood pressure were measured. Fasting capillary blood glucose was first determined using a glucose meter. An oral glucose load was then administered to all subjects except those with self-reported diabetes, and the 2 h post-load capillary blood glucose was estimated. In every fifth subject, a fasting venous sample was collected for measurement of lipids and creatinine, a resting 12-lead electrocardiogram was performed, and dietary assessment questionnaire was administered. In all diabetic subjects, an additional diabetes questionnaire was used and a fasting venous sample drawn for glycated hemoglobin. Results: All biological samples collected were analyzed in a central laboratory. All data collected were stored electronically. Quality control was achieved through multiple tiers of checks. Conclusions: The ICMR-INDIAB study is the first of its kind attempting to provide accurate and comprehensive state- and national-level data on diabetes prevalence in India.
Remote Monitoring Technologies for the Prevention of Metabolic Syndrome: The Diabetes and Technology for Increased Activity (DaTA) Study
Authors: Stuckey Melanie , Fulkerson Robyn , Read Emily , Russell-Minda Elizabeth , Munoz Claudio , Kleinstiver Peter , Petrella Robert 
Published: January 2014

Objectives: Remote monitoring technologies are ideally suited for rural communities with limited access to health care. In an 8-week pilot study, we examined the feasibility of implementing and conducting a technology-intensive intervention in an underserviced rural setting. Our goal was to test the utility of self-monitoring technologies, physical activity, and education as tools to manage health indicators for the development of the cardiovascular complications (CVCs) of type 2 diabetes. Research Design and Methods: The Diabetes and Technology for Increased Activity study was an open single-center study conducted in a community-based research setting. All 24 participants were provided with a Blackberry™ Smartphone, blood pressure monitor, glucometer, and pedometer. Smartphones transmitted measurements and survey results to the database, interfaced participants with the clinical team, and allowed for self-monitoring. Results: Outcomes were improved body composition, improved markers of CVC risk factors, increased daily exercise, and interest in or awareness of lifestyle changes that impact health outcomes. Participants had excellent compliance for measurements, as self-monitoring provided a sense of security that improved from week 4 to week 8. Conclusions: Our team gained substantial insight into the operational requirements of technology-facilitated health care, including redefined hours of service; data reporting, management, and access protocols; and the utility of real-time clinical measures by remote monitoring. We developed an understanding of knowledge translation strategies as well as successful motivational and educational tools. Importantly, remote monitoring technology was found to be feasible and accepted in a rural setting.
Usage and Effectiveness of the Low Glucose Suspend Feature of the Medtronic Paradigm Veo Insulin Pump
Authors: Agrawal Pratik , Welsh John B. , Kannard Brian , Askari Sina , Yang Qingqing , Kaufman Francine R. 
Published: January 2014

Background: Sensor-augmented insulin pumps may be programmed to suspend insulin delivery in response to hypoglycemia. The Medtronic Paradigm® Veo™ pump with automatic low glucose suspend (LGS) was released in 2009. Data from 7 months of real-world use of the system were analyzed to assess usage patterns and effectiveness of LGS. Method: Data from 935 patients totaling 49,867 patient days were collected; the LGS feature was on for 82% of these days. A subset of 278 subjects who used the pump for ≥3 months was analyzed separately; these subjects provided 28,401 patient days of data, with LGS used for 92% of the time. Results: The LGS threshold was most commonly set between 50 and 60 mg/dl. A total of 27,216 LGS events occurred, and 60% began in the afternoon or evening. The median duration of LGS events was 9.87 min, 45% lasted for <5 min, and 11% lasted for >115 min (equivalent to the full extent of the LGS event between 115 and 120 min). Among the episodes lasting for >115 min, the mean sensor glucose (SG) was 58.8 ± 12.4 mg/dl at LGS activation (time 0), rose to 102.2 ± 52.8 mg/dl by the end of the LGS episode (when insulin delivery was automatically resumed), and was 150.1 ± 68.6 mg/dl at 240 min. In the 278-subject subgroup, LGS usage significantly reduced the number of SG readings <50 mg/dl ( p = 0.001) and >300 mg/dl ( p = 0.001). Conclusions: The LGS feature was on for most of the patient days in the study. Most LGS episodes lasted for <10 min. Use of the LGS feature significantly reduced exposure to hypoglycemia. Profound hyperglycemia resulting from LGS episodes lasting >115 min was not observed.