bluuebunny/crossref_metadata_2025_split huggingface dataset:
Are Type 2 Diabetes Patients Who Self-Monitor Blood Glucose Special? The Role of Confounders in the Observational ROSSO Study
Authors: Kolb Hubert , Martin Stephan , Lodwig Volker , Heinemann Lutz , Scherbaum Werner A. , Schneider Berthold 
Published: January 2014

Background: In the German multicenter, retrospective cohort study (ROSSO), those patients with type 2 diabetes who performed self-monitoring of blood glucose (SMBG) had a better long-term clinical outcome. We analyzed whether confounders accounted for the lower rate of clinical events in the SMBG cohort. Methods: ROSSO followed 3268 persons from diagnosis of type 2 diabetes for a mean of 6.5 years. Data were retrieved from patient files of randomly contacted primary care practices. Results: In total, more than 60 potential confounders were documented, including nondisease-associated parameters such as patient's health insurance, marital status, habitation, and characteristics of diabetes centers. There were only modest differences for these parameters between groups with versus without SMBG, and multiple adjustments did not weaken the association of SMBG use with better outcome (odds ratio 0.65, 95% confidence interval 0.53–0.81, p < .001). This was also true for subgroups of patients defined by type of antidiabetes treatment. Propensity score analysis confirmed the association of SMBG use with outcome. Using key baseline parameters, 813 matching pairs of patients were identified. The analysis again showed a better long-term outcome in the SMBG group (hazard ratio 0.67 p = .004). Conclusion: An influence of nonrecognized confounders on better outcome in the SMBG group is rendered improbable by similar results obtained with adjustments for disease-associated or disease-independent parameters, by the analysis of patient subgroups, by propensity score analysis and by performing a matched-pair analysis. The higher flexibility in pharmacological antidiabetes treatment regimens in the SMBG cohort suggests a different attitude of treating physicians and patients in association with SMBG.
Methods of Evaluating the Utility of Continuous Glucose Monitor Alerts
Authors: Kamath Apurv , Mahalingam Aarthi , Brauker James 
Published: January 2014

Background: The evaluation of continuous glucose monitor (CGM) alert performance should reflect patient use in real time. By evaluating alerts as real-time events, their ability to both detect and predict low and high blood glucose (BG) events can be examined. Method: True alerts (TA) were defined as a CGM alert occurring within ± 30 minutes from the beginning of a low or a high BG event. The TA time to detection was calculated as [time of CGM alert] - [beginning of event]. False alerts (FA) were defined as a BG event outside of the alert zone within ± 30 minutes from a CGM alert. Analysis was performed comparing DexCom™ SEVEN® PLUS CGM data to BG measured with a laboratory analyzer. Results: Of 49 low glucose events (BG <70 mg/dl), with the CGM alert set to 90 mg/dl, the TA rate was 91.8%. For 50% of TAs, the CGM alert preceded the event by at least 21 minutes. The FA rate was 25.0%. Similar results were found for high alerts. Conclusion: Continuous glucose monitor alerts are capable of both detecting and predicting low and high BG events. The setting of alerts entails a trade-off between predictive ability and FA rate. Realistic analysis of this trade-off will guide patients in the effective utilization of CGM.
Simulation Environment to Evaluate Closed-Loop Insulin Delivery Systems in Type 1 Diabetes
Authors: Wilinska Malgorzata E. , Chassin Ludovic J. , Acerini Carlo L. , Allen Janet M. , Dunger David B. , Hovorka Roman 
Published: January 2014

Background: Closed-loop insulin delivery systems linking subcutaneous insulin infusion to real-time continuous glucose monitoring need to be evaluated in humans, but progress can be accelerated with the use of in silico testing. We present a simulation environment designed to support the development and testing of closed-loop insulin delivery systems in type 1 diabetes mellitus (T1DM). Methods: The principal components of the simulation environment include a mathematical model of glucose regulation representing a virtual population with T1DM, the glucose measurement model, and the insulin delivery model. The simulation environment is highly flexible. The user can specify an experimental protocol, define a population of virtual subjects, choose glucose measurement and insulin delivery models, and specify outcome measures. The environment provides graphical as well as numerical outputs to enable a comprehensive analysis of in silico study results. The simulation environment is validated by comparing its predictions against a clinical study evaluating overnight closed-loop insulin delivery in young people with T1DM using a model predictive controller. Results: The simulation model of glucose regulation is described, and population values of 18 synthetic subjects are provided. The validation study demonstrated that the simulation environment was able to reproduce the population results of the clinical study conducted in young people with T1DM. Conclusions: Closed-loop trials in humans should be preceded and concurrently guided by highly efficient and resource-saving computer-based simulations. We demonstrate validity of population-based predictions obtained with our simulation environment.
Extended Prandial Glycemic Profiles of Foods as Assessed Using Continuous Glucose Monitoring Enhance the Power of the 120-Minute Glycemic Index
Authors: Chlup Rudolf , Peterson Karolina , Zapletalová Jana , Kudlová Pavla , Seč;kař; Pavel 
Published: January 2014

Background: The glycemic index (GI) is routinely measured 120 minutes after food intake (GI120). The purpose of this prospective open label study was to assess (1) the dynamics of glycemia over the 210 minutes following food consumption and (2) the evolution of GIs based on 120-, 150-, 180-, and 210-minute glycemic profiles. Method: Twenty healthy subjects (mean ± SE; 21.9 ± 1.39 years of age; body mass index 23.6 ± 0.63 kg/m2; 7 men and 13 women) completed the study. Each subject consumed 10 different foods with known GI120 on three separate occasions at four different times of day according to a defined meal plan over a 9-day period; 32 meals were evaluated. The GIs for intervals of 120, 150, 180 and 210 minutes after food consumption were determined using a continuous glucose monitoring system (CGMS) to measure glycemia. The Wilcoxon signed-rank test was applied to compare the GIs. Results: Glycemia returned to baseline within 120 minutes for honey and tomato soup; within 210 minutes for white bread, choco-rice cookies, fish and potatoes, wafers, and meat ravioli with cheese; and later for dark chocolate, apricot dumplings, and choco-wheat cookies. The extended GIs were higher than the respective GI120s in eight of the foods. Conclusions: The 120-minute glycemic index fails to fully account for changes in glycemia after ingestion of a mixed meal because glycemia remains above baseline for a longer period. The CGMS is a convenient method to determine the glucose response/GIs over intervals extended up to 210 minutes, which is adequate time for the absorption of most foods.
Continuous Glucose Monitors and the Burden of Tight Glycemic Control in Critical Care: Can They Cure the Time Cost?
Authors: Signal Matthew , Pretty Christopher G. , Chase J. Geoffrey , Le Compte Aaron , Shaw Geoffrey M. 
Published: January 2014

Background: Tight glycemic control (TGC) in critical care has shown distinct benefits but has also proven to be difficult to obtain. The risk of severe hypoglycemia (<40 mg/dl) raises significant concerns for safety. Added clinical burden has also been an issue. Continuous glucose monitors (CGMs) offer frequent automated measurement and thus the possibility of using them for early detection and intervention of hypoglycemic events. Additionally, regular measurement by CGM may also be able to reduce clinical burden. Aim: An in silico study investigates the potential of CGM devices to reduce clinical effort in a published TGC protocol. Methods: This study uses retrospective clinical data from the Specialized Relative Insulin Nutrition Titration (SPRINT) TGC study covering 20 patients from a benchmark cohort. Clinically validated metabolic system models are used to generate a blood glucose (BG) profile for each patient, resulting in 33 continuous, separate BG episodes (6881 patient hours). The in silico analysis is performed with three different stochastic noise models: Two Gaussian and one first-order autoregressive. The noisy, virtual CGM BG values are filtered and used to drive the SPRINT TGC protocol. A simple threshold alarm is used to trigger glucose interventions to avert potential hypoglycemia. The Monte Carlo method was used to get robust results from the stochastic noise models. Results: Using SPRINT with simulated CGM noise, the BG time in an 80–110 mg/dl band was reduced no more than 4.4% to 45.2% compared to glucometer sensors. Antihypoglycemic interventions had negligible effect on time in band but eliminated all recorded hypoglycemic episodes in these simulations. Assuming 4–6 calibration measurements per day, the nonautomated clinical measurements are reduced from an average of 16 per day to as low as 4. At 2.5 min per glucometer measurement, a daily saving of ~25–30 min per patient could potentially be achieved. Conclusions: This paper has analyzed in silico the use of CGM sensors to provide BG input data to the SPRINT TGC protocol. A very simple algorithm was used for early hypoglycemic detection and prevention and tested with four different-sized intravenous glucose boluses. Although a small decrease in time in band (still clinically acceptable) was experienced with the addition of CGM noise, the number of hypoglycemic events was reduced. The reduction to time in band depends on the specific CGM sensor error characteristics and is thus a trade-off for reduced nursing workload. These results justify a pilot clinical trial to verify this study.
Serum Total Adiponectin is Associated with Impaired Glucose Tolerance in Asian Indian Females but Not in Males
Authors: Luo Menghua , Oza-Frank Reena , Narayan K. M. Venkat , Gokulakrishnan Kuppan , Mohan Viswanathan 
Published: January 2014

Objective: Adiponectin may play a role in the development of type 2 diabetes and cardiovascular disease (CVD). However, little is known about the relationship between adiponectin and impaired glucose tolerance (IGT). We investigated the association between adiponectin and IGT and between adiponectin and cardiovascular risk factors among subjects with IGT. Research Design and Methods: Subjects with normal glucose tolerance (NGT)( n = 571) and impaired glucose tolerance ( n = 167) were recruited from the Chennai Urban Rural Epidemiology Study in south India. Serum total adiponectin levels were measured using a radioimmunoassay (Linco Research, St. Charles, MO). High sensitivity C-reactive protein (hsCRP) was estimated by nephelometry. Results: In sex-stratified analyses, adiponectin was significantly associated with IGT in females [odds ratio (OR): 0.93, 95% confidence interval (CI): 0.872–0.991, p = 0.026] after controlling for age, waist circumference, blood pressure, alcohol consumption, smoking, lipid profile, and glycemic indices; in males there was no significant association (OR = 0.90, 95% CI: 0.798–1.012, p = 0.078). In prediabetic females, adiponectin was not associated with any CVD risk factors (age, waist circumference, blood pressure, cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, fasting glucose, fasting insulin, and insulin resistance level), but was associated negatively with 2-hour postplasma glucose levels ( r = −0.243, p < 0.05) and hsCRP ( r = −0.219, p < 0.05) after adjusting for demographic and biomedical indices. No associations with CVD risk factors were observed in males with IGT. Conclusion: Serum total adiponectin levels are associated with IGT, 2-hour postplasma glucose, and hsCRP in Asian Indian females but not in males.
Patient Perceptions of Different Lancing Sites for Self-Monitoring of Blood Glucose: A Comparison of Fingertip Site with Palm Site Using the OneTouch® Ultra® Blood Glucose Monitoring System
Authors: Ito Takao , Kamoi Kyuzi , Minagawa Shinichi , Kimura Keita , Kobayashi Akane 
Published: January 2014

Background: Alternate-site testing (AST) for self-monitoring of blood glucose leads to improved glycemic control for treatment of diabetes mellitus. The aim of this randomized, open-label, two-period, crossover study was to compare the comfort of two different lancing sites, fingertip and palm sites, for AST in diabetes patients. Methods: Patients injected insulin four times a day. Self-monitoring of blood glucose was carried out more than thrice daily with fingertip measurements for at least three months using apparatuses except the OneTouch® Ultra® Blood Glucose Monitoring System (OneTouch) before examination. The comfort of two lancing sites using OneTouch were compared. In two randomized groups that used one fingertip lancing site for one week followed by the alternate lancing site for another week, patients completed 11-item questionnaires assessing usability of the site before and after each week. Each item was scored on a visual analogue scale from −100 (most negative) to +100 (most positive). Results: Most patients desired to continue AST, which was insignificantly different between the two lancing sites (fingertip and palm AST) in 43 diabetes patients aged 57.3 ± 13.8 years, body mass index of 23.1 ± 2.5 kg/m2, diabetes duration of 19.6 ± 9.7 years, and hemoglobin A1c of 7.4 ± 1.1%. However, patients were less ( p < .01) satisfied with using the palm lancing site as compared to the fingertip lancing site because of difficulties in inserting the needle, drawing blood samples, and applying enough blood into the test strip. Conclusions: These results suggest that patients desire to use the palm for AST, but more technological advances in AST of a palm site is required to reduce patient discomfort.
Proposed Clinical Application for Tuning Fuzzy Logic Controller of artificial Pancreas Utilizing a Personalization Factor
Authors: Mauseth Richard , Wang Youqing , Dassau Eyal , Kircher Robert , Matheson Donald , Zisser Howard , Jovanovič Lois , Doyle Francis J. 
Published: January 2014

Background: Physicians tailor insulin dosing based on blood glucose goals, response to insulin, compliance, lifestyle, eating habits, daily schedule, and fear of and ability to detect hypoglycemia. Method: We introduce a method that allows a physician to tune a fuzzy logic controller (FLC) artificial pancreas (AP) for a particular patient. It utilizes the physician's judgment and weighing of various factors. The personalization factor (PF) is a scaling of the dose produced by the FLC and is used to customize the dosing. The PF has discrete values of 1 through 5. The proposed method was developed using a database of results from 30 University of Virginia/Padova Metabolic Simulator in silico subjects (10 adults, 10 adolescents, and 10 children). Various meal sizes and timing were used to provide the physician information on which to base an initial dosing regimen and PF. Future decisions on dosing aggressiveness using the PF would be based on the patient's data at follow-up. Results: Three examples of a wide variation in diabetes situations are given to illustrate the physician's thought process when initially configuring the AP system for a specific patient. Conclusions: Fuzzy logic controllers are developed by encoding human expertise into the design of the controller. The FLC methodology allows for the real-time scaling of doses without compromising the integrity of the dosing rules matrix. The use of the PF to individualize the AP system is enabled by the fuzzy logic development methodology.
Postprandial Glycemic Excursions with the Use of a Closed-Loop Platform in Subjects with Type 1 Diabetes: A Pilot Study
Authors: van Bon Arianne C. , Hermanides Jeroen , Koops Robin , Hoekstra Joost B. L. , DeVries J. Hans 
Published: January 2014

Background: The aim of this study was to evaluate the efficacy of a proportional derivative algorithm closed-loop system to control postprandial glucose concentrations in subjects with type 1 diabetes. Methods: Six subjects treated with continuous subcutaneous insulin infusion received a standardized meal on three days. The first day served as control, the second day as learning experiment for the algorithm, and the third day to compare the closed loop to the control day. Venous blood glucose was measured as reference until 300 min postprandially. The artificial pancreas platform consisted of a subcutaneous continuous glucose monitor (CGM), the GlucoDay® S (Menarini Diagnostics), two D-Tron+ pumps (Disetronic Medical Systems) for subcutaneous insulin, and glucagon administration connected to a personal computer. Results: One subject was excluded due to technical failure of the CGM. Two of five subjects were male, mean age was 50.8 years (range 38–60), and mean hemoglobin A1c was 8.7% (range 7.0–12.2). The mean postprandial venous blood glucose concentration of day 1 was 205 mg/dl (range 94–265 mg/dl) compared with 128 mg/dl (range 128–158 mg/dl) on day 3 ( p = .14). Percentage of time spent in euglycemia postprandially on day 1 was 31% versus 60% on day 3 ( p = .08). Time spent below 3.9 mmol/liter (70 mg/dl) was 19% on day 1 compared with 11% on day 3 ( p = 1.0). Time above 10 mmol/liter (180 mg/dl) on day 1 was 60% versus 29% on day 3 ( p = .22). Conclusion: The artificial pancreas provided comparable postprandial glycemic control to usual care.
Missing Elements Revisited: Information Engineering for Managing Quality of Care for Patients with Diabetes
Authors: Connor Matthew J. , Connor Michael J. 
Published: January 2014

Introduction: Advances in information technology offer new avenues for assembling data about diet and care regimens of diabetes patients “in the field.” This creates a challenge for their doctors and the diabetes care community—how to organize and use new data to produce better long-term outcomes for diabetes patients. Methods: iAbetics approaches the challenge as a quality management problem, drawing on total quality concepts, which in turn are grounded in application of the scientific method. We frame the diabetes patient's quality-of-care problem as an ongoing scientific investigation aimed at quantifying and predicting relationships between specific care-management actions and their outcomes for individual patients in their ordinary course of life. Results: Framing diabetes quality-of-care management as a scientific investigation leads to a seven-step model termed “adaptive empirical iteration.” Adaptive empirical iteration is a deliberate process to perfect the patient's choices, decisions, and actions in routine situations that make up most day-to-day life and to systematically adapt across differences in individual patients and/or changes in their physiology, diet, or environment. The architecture incorporates care-protocol management and version control, structured formats for data collection using mobile smart phones, statistical analysis on secure Web sites, tools for comparing alternative protocols, choice architecture technology to improve patient decisions, and information sharing for doctor review. Conclusions: Adaptive empirical iteration is a foundation for information architecture designed to systematically improve quality-of-care provided to diabetes patients who act as their own day-to-day care provider under supervision and with support from their doctor. The approach defines “must-have” capabilities for systems using new information technology to improve long-term outcomes for diabetes patients.
Multicenter User Evaluation of ACCU-CHEK® Combo, an Integrated System for Continuous Subcutaneous Insulin Infusion
Authors: Kerr David , Hoogma Roel P.L.M. , Buhr Andreas , Petersen Bettina , Storms Fred E.M.G. ,   for the study investigators
Published: January 2014

Background: The aim of this study was to evaluate a newly developed system for insulin delivery incorporating a multifunctional blood glucose meter and a remotely controlled insulin pump (ACCU-CHEK® Combo system) in established pump users with type 1 diabetes. The technology was assessed both from device performance and subject usability perspectives. Method: A multicenter, prospective, single group study was carried out in five centers in the Netherlands and four centers in the United Kingdom for more than 6 months. The study was divided into two phases: Phase 1 (4 weeks) for device validation purposes and phase 2 (22 weeks) to observe the impact of the system on metabolic control, patient satisfaction [using the Diabetes Treatment Satisfaction Questionnaire (DTSQ)] and device safety. Results: Eighty subjects completed the planned study period. There were no unexpected device errors. Treatment satisfaction was high at baseline and further increased to study end (DTSQ change version: Sum score, 10.6 ± 7.2; scale score range, −18 to +18, p < 0.0001). Hemoglobin A1c improved continuously over time, from 7.9% (±0.9%) to 7.7% (±0.8%) at month 3 ( p < 0.001) and 7.6% (±0.8%) at month 6 ( p < 0.0001). The frequency of severe hypoglycemia was 0.08 per patient years. There was no case of ketoacidosis. Conclusions: The new system was evaluated by experienced continuous subcutaneous insulin infusion users as safe in daily practice and associated with favorable treatment satisfaction and a modest improvement in glycemic control.
Estimates of Total Analytical Error in Consumer and Hospital Glucose Meters Contributed by Hematocrit, Maltose, and Ascorbate
Authors: Lyon Martha E. , DuBois Jeffrey A. , Fick Gordon H. , Lyon Andrew W. 
Published: January 2014

Background: Patients and physicians expect accurate whole blood glucose monitoring even when patients are anemic, are undergoing peritoneal dialysis, or have slightly elevated ascorbate levels. The objective of this study was to estimate analytical error in two consumer and two hospital glucose meters contributed by variations in hematocrit, maltose, ascorbate, and imprecision. Method: The Influence of hematocrit (20–60%), maltose, and ascorbate were tested alone and in combination with each glucose meter and with a reference plasma glucose method at three concentrations of glucose. Precision was determined by consecutive analysis ( n = 20) at three levels of glucose. Multivariate regression analysis was used to estimate the bias associated with the interferences, alone and in combination. Total analytical error was estimated as |% bias| + 1.96 (% imprecision). Results: Three meters demonstrated hematocrit bias that was dependent upon glucose concentration. Maltose had profound concentration-dependent positive bias on the consumer meters, and the extent of maltose bias was dependent on hematocrit. Ascorbate produced small but statistically significant biases on three meters. Coincident low hematocrit, presence of maltose, and presence of ascorbate increased the observed bias and was summarized by estimation of total analytical error. Among the four glucose meter devices assessed, estimates of total analytical error in glucose measurement ranged from 6 to 68% under the conditions tested. Conclusions: The susceptibility of glucose meters to clinically significant analytical biases is highly device-dependent, and low hematocrit exacerbated the observed analytical error.