bluuebunny/crossref_metadata_2025_split huggingface dataset:
Feasibility of Overnight Closed-Loop Control Based on Hourly Blood Glucose Measurements
Authors: Patte Caroline , Pleus Stefan , Galley Paul , Weinert Stefan , Haug Cornelia , Freckmann Guido 
Published: January 2014

Introduction: Safe and effective closed-loop control (artificial pancreas) is the ultimate goal of insulin delivery. In this study, we examined the performance of a closed-loop control algorithm used for the overnight time period to safely achieve a narrow target range of blood glucose (BG) concentrations prior to breakfast. The primary goal was to compare the quality of algorithm control during repeated overnight experiments. Materials and Methods: Twenty-three subjects with type 1 diabetes performed 2 overnight experiments on each of three visits at the study site, resulting in 138 overnight experiments. On the first evening, the subject's insulin therapy was applied; on the second, the insulin was delivered by an algorithm based on subcutaneous continuous glucose measurements (including meal control) until midnight. Overnight closed-loop control was applied between midnight and 6 a.m. based on hourly venous BG measurements during the first and second nights. Results: The number of BG values within the target range (90–150 mg/dl) increased from 52.9% (219 out of 414 measurements) during the first nights to 72.2% (299 out of 414 measurements) during the second nights ( p < .001, X2-test). The occurrence of hypoglycemia interventions was reduced from 14 oral glucose interventions, the latest occurring at 2:36 a.m. during the first nights, to 1 intervention occurring at 1:02 a.m. during the second nights ( p < .001, X2-test). Conclusions: Overnight controller performance improved when optimized initial control was given; this was suggested by the better metabolic control during the second night. Adequate controller run-in time seems to be important for achieving good overnight control. In addition, the findings demonstrate that hourly BG data are sufficient for the closed-loop control algorithm tested to achieve appropriate glycemic control.
Comparison of Patient Preference for Two Insulin Injection Pen Devices in Relation to Patient Dexterity Skills
Authors: Pfützner Andreas , Schipper Christina , Niemeyer Marcus , Qvist Marianne , Löffler Andrea , Forst Thomas , Musholt Petra B. 
Published: January 2014

Background: Impaired dexterity has been reported to be prevalent in diabetes patients independent from the existence of diabetic neuropathy. This study was performed to investigate the impact of dexterity impairment on patient preference for two insulin pen injection devices (InnoLet and FlexTouch). Methods: Ninety patients [54 male/36 female; age (mean ± standard deviation), 62 ± 8 years; disease duration, 18 ± 11 years; hemoglobin A1c, 7.2 ± 1.0%] were included in this investigation and were stratified into four different groups based on the results of a dexterity test (Jebsen—Taylor Hand Function Test) and assessment of visual impairment: 15 type 1 (group A) and 30 type 2 (group B) patients with impaired dexterity, 30 type 1/type 2 patients with visual impairment (group C), and 15 type 1/type 2 patients without any impairment (group D). The patients performed a cognitive function test (number connection test), were introduced to the devices in random order, and were asked to perform some mock injections before completing a six-item standardized preference questionnaire. Results: There was a strong preference for FlexTouch in all groups. All unimpaired patients (100%, group D) preferred FlexTouch, as did the vast majority in all other groups. Only 11% of the patients with impaired cognitive function preferred InnoLet, as did a few patients with more severely impaired dexterity or with visual impairment (group A, 13%; group B, 3%; group C, 14%). Conclusions: Patient dexterity skills may have an influence on device preference, especially if the impairment is more pronounced.
Performance of a New Speech Translation Device in Translating Verbal Recommendations of Medication Action Plans for Patients with Diabetes
Authors: Soller R. William , Chan Philip , Higa Amy 
Published: January 2014

Background: Language barriers are significant hurdles for chronic disease patients in achieving self-management goals of therapy, particularly in settings where practitioners have limited nonprimary language skills, and in-person translators may not always be available. S-MINDS© (Speaking Multilingual Interactive Natural Dialog System), a concept-based speech translation approach developed by Fluential Inc., can be applied to bridge the technologic gaps that limit the complexity and length of utterances that can be recognized and translated by devices and has the potential to broaden access to translation services in the clinical settings. Methods: The prototype translation system was evaluated prospectively for accuracy and patient satisfaction in underserved Spanish-speaking patients with diabetes and limited English proficiency and was compared with other commercial systems for robustness against degradation of translation due to ambient noise and speech patterns. Results: Accuracy related to translating the English-Spanish-English communication string from practitioner to device to patient to device to practitioner was high (97–100%). Patient satisfaction was high (means of 4.7–4.9 over four domains on a 5-point Likert scale). The device outperformed three other commercial speech translation systems in terms of accuracy during fast speech utterances, under quiet and noisy fluent speech conditions, and when challenged with various speech disfluencies (i.e., fillers, false starts, stutters, repairs, and long pauses). Conclusions: A concept-based English-Spanish speech translation system has been successfully developed in prototype form that can accept long utterances (up to 20 words) with limited to no degradation in accuracy. The functionality of the system is superior to leading commercial speech translation systems.
Self-Monitoring of Blood Glucose: One STeP Forward?
Authors: Schramm Wendelin 
Published: January 2014

Introduction: In times of short health care budgets, reimbursement for self-monitoring of blood glucose (SMBG) in diabetes patients without insulin treatment is subject to debate. The Structured Testing Program (STeP) trial found a positive correlation of test frequency and improved hemoglobin A1c (HbA1c) levels in poorly controlled type 2 diabetes patients not treated with insulin. Methods: A structured literature search for other clinical studies reporting on SMBG frequency was performed. Results: There is scarce evidence: Three trials, including STeP, noted a significant and relevant correlation between testing frequency and improved HbA1c levels (FA effect), whereas two studies did not. The comparability between the identified studies is problematic. Conclusion: Future research should consider correlations between testing frequency and level of glycemic control. More emphasis should be placed on a structured approach to use SMBG and to address adherence to testing and therapy.
Continuous Glucose Monitoring Accuracy Results Vary between Assessment at Home and Assessment at the Clinical Research Center
Authors: Luijf Yoeri M. , Avogaro Angelo , Benesch Carsten , Bruttomesso Daniela , Cobelli Claudio , Ellmerer Martin , Heinemann Lutz , Mader Julia K. , DeVries J. Hans 
Published: January 2014

Background: Continuous glucose monitoring system (CGMS) accuracy is of critical importance both in delivering therapeutic value and as a component of a closed-loop system. This study aims at assessing the differences between accuracy assessments of CGMS at home and at the clinical research center (CRC). Methods: Twelve patients with type 1 diabetes used the Dexcom® SEVEN® PLUS (DexCom, Inc.) CGMS for 7 days. Patients performed ≥6 finger pricks [self-measurement of blood glucose (SMBG)] per day while at home. Reference blood glucose measurements were taken during a 24 h CRC admission (YSI 2300 STAT Plus™). Continuous glucose monitoring system data were compared with YSI and SMBG values. Outcome measures included mean absolute relative difference (MARD) and Clarke error grid analysis (CEGA). Results: During CRC admission, the MARD of CGMS vs YSI glucose values was 19.2% ( n = 509)—significantly higher than 16.8% at home ( n = 611) ( p = .004). In the hypoglycemic range, MARD was 23.9% at CRC ( n = 26)—not significantly different from 41.6% at home ( n = 39) ( p = .269). In the hyperglycemic range, CRC MARD at 20.3% ( n = 115) was significantly higher than home MARD at 11.2% ( n = 118) ( p = .001). Clarke error grid analysis showed no significant difference in distribution of data pairs (overall p = .317). Conclusions: This study illustrates the importance of the setting used when assessing CGMS accuracy. Continuous glucose monitoring system accuracy at home appeared better than at the CRC. This is probably due to the higher sampling rate of reference measurements, feasible only in the CRC. Testing CGMS accuracy in the CRC provides valuable information over and above home testing.
Inpatient Studies of a Kalman-Filter-Based Predictive Pump Shutoff Algorithm
Authors: Cameron Fraser , Wilson Darrell M. , Buckingham Bruce A. , Arzumanyan Hasmik , Clinton Paula , Chase H. Peter , Lum John , Maahs David M. , Calhoun Peter M. , Bequette B. Wayne 
Published: January 2014

Background: An insulin pump shutoff system can prevent nocturnal hypoglycemia and is a first step on the pathway toward a closed-loop artificial pancreas. In previous pump shutoff studies using a voting algorithm and a 1 min continuous glucose monitor (CGM), 80% of induced hypoglycemic events were prevented. Methods: The pump shutoff algorithm used in previous studies was revised to a single Kalman filter to reduce complexity, incorporate CGMs with different sample times, handle sensor signal dropouts, and enforce safety constraints on the allowable pump shutoff time. Results: Retrospective testing of the new algorithm on previous clinical data sets indicated that, for the four cases where the previous algorithm failed (minimum reference glucose less than 60 mg/dl), the mean suspension start time was 30 min earlier than the previous algorithm. Inpatient studies of the new algorithm have been conducted on 16 subjects. The algorithm prevented hypoglycemia in 73% of subjects. Suspension-induced hyperglycemia is not assessed, because this study forced excessive basal insulin infusion rates. Conclusions: The new algorithm functioned well and is flexible enough to handle variable sensor sample times and sensor dropouts. It also provides a framework for handling sensor signal attenuations, which can be challenging, particularly when they occur overnight.
Autonomic Markers of Impaired Glucose Metabolism: Effects of Sleep-Disordered Breathing
Authors: Wang Wenli , Redline Susan , Khoo Michael C. K. 
Published: January 2014

Background: The association between diabetes and abnormalities in autonomic function is well-known, but it is not clear if this association can be extended to subjects with prediabetic impaired glucose metabolism (IGM). Sleep-disordered breathing (SDB), which commonly occurs in this population, is often overlooked. We sought to determine how autonomic function, monitored in an overnight sleep study setting, may be impaired in subjects with IGM and/or SDB. Methods: Polysomnograms (PSGs) selected from the Cleveland Family Study database were categorized into four groups: normal, SDB (respiratory disturbance index > 5/h), IGM, and both SDB and IGM. Impaired glucose metabolism was defined as an oral glucose tolerance test (OGTT) level > 140 mg/dl. Time-domain and frequency-domain indices of heart rate variability were used to quantify autonomic impairment. Baroreflex sensitivity determined using pulse transit time (BRSPTT), an indirect measure of baroreflex sensitivity based on spontaneous pulse transit time fluctuations, was used as a surrogate measure of baroreflex sensitivity. Results: Based on 31 PSGs from subjects (16 males, 15 females) ages 20.8–61.2 years, both SDNN and BRSPTT were found to be 20–25% lower in SDB and ∼40% lower in IGM and SDB + IGM as compared to subjects without either condition. In analyses of continuous measures, mean standard deviation of 5 min R-R intervals (SDNN) and BRSPTT were found to be negatively correlated with OGTT following adjustment for age and body mass index. Oral glucose tolerance test and age were the two most significant factors for predicting SDNN and BRSPTT. Conclusions: Our analyses suggest that cardiac autonomic control is impaired in IGM, regardless of whether SDB is present. The abnormal autonomic function involves degradation of baroreflex regulation.
Pilot Study of the SPRINT Glycemic Control Protocol in a Hungarian Medical Intensive Care Unit
Authors: Benyo Balazs , Illyés Attila , Némedi Noémi Szabó , Le Compte Aaron J. , Havas Attila , Kovacs Levente , Fisk Liam , Shaw Geoffrey M. , Chase J. Geoffrey 
Published: January 2014

Introduction: Stress-induced hyperglycemia increases morbidity and mortality. Tight control can reduce mortality but has proven difficult to achieve. The SPRINT (Specialized Relative Insulin and Nutrition Tables) protocol is the only protocol that reduced both mortality and hypoglycemia by modulating both insulin and nutrition, but it has not been tested in independent hospitals. Methods: SPRINT was used for 12 adult intensive care unit patients (949 h) at Kálmán Pándy Hospital (Gyula, Hungary) as a clinical practice assessment. Insulin recommendations (0–6 U/h) were administered via constant infusion rather than bolus delivery. Nutrition was administered per local standard protocol, weaning parenteral to enteral nutrition, but was modulated per SPRINT recommendations. Measurement was every 1 to 2 h, per protocol. Glycemic performance is assessed by percentage of blood glucose (BG) measurements in glycemic bands for the cohort and per patient. Safety from hypoglycemia is assessed by numbers of patients with BG <2.2 (severe) and %BG <3.0 and <4.0 mmol/liter (moderate and light). Clinical effort is assessed by measurements per day. Results are median (interquartile range). Results: There were 742 measurements over 1088 h of control (16.4 measurements/day), which is similar to clinical SPRINT results (16.2/day). Per-patient hours of control were 65 (50–95) h. Initial per-patient BG was 10.5 (7.9–11.2) mmol/liter. All patients (100%) reached 6.1 mmol/liter. Cohort BG was 6.3 (5.5–7.5) mmol/liter, with 42.2%, 65.1% and 77.6% of BG in the 4.0–6.1, 4.0–7.0, and 4.0–8.0 mmol/liter bands. Per-patient, median percentage time in these bands was 40.2 (26.7–51.5)%, 62.5 (46.0–75.7)%, and 74.7 (61.6.8–87.8)%, respectively. No patients had BG <2.2 mmol/liter, and the %BG <4.0 mmol/liter was 1.9%. These results were achieved using 3.0 (3.0–5.0) U/h of insulin with 7.4 (4.4–10.2) g/h of dextrose administration (all sources) for the cohort. Per-patient median insulin administration was 3.0 (3.0–3.0) U/h and 7.1 (3.4–9.6) g/h dextrose. Higher carbohydrate nutrition formulas than were used in SPRINT are offset by slightly higher insulin administration in this study. Conclusions: The glycemic performance shows that using the SPRINT protocol to guide insulin infusions and nutrition administration provided very good glycemic control in initial pilot testing, with no severe hypoglycemia. The overall design of the protocol was able to be generalized with good compliance and outcomes across geographically distinct clinical units, patients, and clinical practice.
Stepwise Self-Titration of Oral Glucose-Lowering Medication Using a Mobile Telephone-Based Telehealth Platform in Type 2 Diabetes: A Feasibility Trial in Primary Care
Authors: Nagrebetsky Alexander , Larsen Mark , Craven Anthea , Turner Jane , McRobert Nicky , Murray Elizabeth , Gibson Oliver , Neil Andrew , Tarassenko Lionel , Farmer Andrew 
Published: January 2014

Background: Telehealth-supported clinical interventions may improve diabetes self-management. We explored the feasibility of stepwise self-titration of oral glucose-lowering medication guided by a mobile telephone-based telehealth platform for improving glycemic control in type 2 diabetes. Methods: We recruited 14 type 2 diabetes patients to a one-year feasibility study with 1:1 randomization. Intervention group patients followed a stepwise treatment plan for titration of oral glucose-lowering medication with self-monitoring of glycemia using real-time graphical feedback on a mobile telephone and remote nurse monitoring using a Web-based tool. We carried out an interim analysis at 6 months. Results: We screened 3476 type 2 diabetes patients; 94% of the ineligible did not meet the eligibility criteria for hemoglobin A1c (HbA1c) or current treatment. Mean (standard deviation) patient age at baseline was 58 (11) years, HbA1c was 65 (12) mmol/mol (8.1% [1.1%]), body mass index was 32.9 (6.4) kg/m2, median [interquartile range (IQR)] diabetes duration was 2.6 (0.6 to 4.7) years, and 10 (71%) were men. The median (IQR) change in HbA1c from baseline to six months was −10 (−21 to 3) mmol/mol (−0.9% [-1.9% to 0%]) in the intervention group and −5 (−13 to 6) mmol/mol (−0.5% [-1.2% to 0.6%]) in the control group. Six out of seven intervention group patients and four out of seven control group patients changed their oral glucose-lowering medication ( p = .24). Conclusions: Self-titration of oral glucose-lowering medication in type 2 diabetes with self-monitoring and remote monitoring of glycemia is feasible, and further studies using adapted recruitment strategies are required to evaluate whether it improves clinical outcomes.
Multilevel Model of Type 1 Diabetes Mellitus Patients for Model-Based Glucose Controllers
Authors: Garcia-Gabin Winston , Jacobsen Elling W. 
Published: January 2014

Background: Glucose homeostasis is the result of complex interactions across different biological levels. This multilevel characteristic should be considered when analyzing and designing closed-loop glucose control algorithms. Classic control schemes use only a pharmacokinetic-pharmacodynamic (PKPD) perspective to describe the glucoregulatory system. Methods: A multilevel model combining a PKPD model with an insulin signaling model is proposed for patients with type 1 diabetes mellitus T1DM (T1DM). The PKPD Dalla Man model for T1DM is expanded to include an intracellular level involving insulin signaling to control glucose uptake through glucose transporter type 4 (GLUT4) translocation. A model-based controller is then designed and used as an example to illustrate the feasibility of the proposal. Results: Two significant results were obtained for the controller explicitly utilizing multilevel information. No hypoglycemic events were registered and an excellent performance for interpatient variability was achieved. Controller performance was evaluated using two indexes. The glucose was kept inside the range (70–180) mg/dl more than 99% of the time, and the intrapatient variability measured using control variability grid analysis was solid with 90% of the population inside the target zone. Conclusions: Multilevel models open new possibilities for designing glucose control algorithms. They allow controllers to take into account variables that have a strong influence on glucose homeostasis. A model-based controller was used for demonstrating how improved knowledge of the multilevel nature of diabetes increases the robustness and performance of glucose control algorithms. Using the proposed multilevel approach, a reduction of the hypoglycemic risk and robust behaviour for intrapatient variability was demonstrated.
Mobile Applications for Diabetes Self-Management: Status and Potential
Authors: El-Gayar Omar , Timsina Prem , Nawar Nevine , Eid Wael 
Published: January 2014

Background: Advancements in smartphone technology coupled with the proliferation of data connectivity has resulted in increased interest and unprecedented growth in mobile applications for diabetes self-management. The objective of this article is to determine, in a systematic review, whether diabetes applications have been helping patients with type 1 or type 2 diabetes self-manage their condition and to identify issues necessary for large-scale adoption of such interventions. Methods: The review covers commercial applications available on the Apple App Store (as a representative of commercially available applications) and articles published in relevant databases covering a period from January 1995 to August 2012. The review included all applications supporting any diabetes self-management task where the patient is the primary actor. Results: Available applications support self-management tasks such as physical exercise, insulin dosage or medication, blood glucose testing, and diet. Other support tasks considered include decision support, notification/alert, tagging of input data, and integration with social media. The review points to the potential for mobile applications to have a positive impact on diabetes self-management. Analysis indicates that application usage is associated with improved attitudes favorable to diabetes self-management. Limitations of the applications include lack of personalized feedback; usability issues, particularly the ease of data entry; and integration with patients and electronic health records. Conclusions: Research into the adoption and use of user-centered and sociotechnical design principles is needed to improve usability, perceived usefulness, and, ultimately, adoption of the technology. Proliferation and efficacy of interventions involving mobile applications will benefit from a holistic approach that takes into account patients' expectations and providers' needs.
Safety Events during an Automated Telephone Self-Management Support Intervention
Authors: Lyles Courtney R. , Schillinger Dean , Lopez Andrea , Handley Margaret , Ratanawongsa Neda , Sarkar Urmimala 
Published: January 2014

Background: Interactive health information technology (HIT) can support the complex self-management tasks for diabetes. However, less is known about between-visit interactions and patient safety among chronic illness patients treated in the outpatient setting. Methods: We classified 13 categories for safety events and potential safety events within a larger trial evaluating a multilingual automated telephone self-management support system for diabetes using interactive voice response. Participants could trigger safety concerns by reporting hyperglycemia or hypoglycemia, inability to obtain medications, medication nonadherence and side effects, and needing appointments and/or supplies. We then examined these triggers across patient demographic and health characteristics to determine which patients were most likely to experience safety events. Results: Overall, there were 360 safety triggers that occurred among 155 participants, which represented 53% of individuals and 7.6% of all automated calls over the 27-week intervention. The most common triggers were for pain or medication side effects (22%) and not checking blood sugars (13%). In adjusted models, race/ethnicity and language were related to safety triggers; Spanish-speaking participants were significantly ( p = .02) more likely than English-speaking participants to experience a safety trigger, and black participants were marginally more likely ( p = .09) than white participants to experience a safety trigger. Conclusion: About half of patients enrolled in a self-management technology intervention triggered at least one potential safety event over the course of the trial, and this was more frequent among some patients. Systems implementing HIT strategies to improve self-care and remote monitoring should consider specific program design elements to address these potential safety events.