Journal of diabetes science and technology

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ISSN 1932-2968

Publications in this journal

  • D. C. Klonoff

    No preview · Article · Feb 2016 · Journal of diabetes science and technology
  • A. Pfu tzner · D. Sachsenheimer · M. Grenningloh

    No preview · Article · Feb 2016 · Journal of diabetes science and technology
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    ABSTRACT: Background: This analysis models the cost-effectiveness of real-time continuous glucose monitoring (RT-CGM) using evidence from a randomized controlled trial (RCT) that demonstrated RT-CGM reduced A1C, for up to 9 months after using the technology, among patients with type 2 diabetes not on prandial insulin. RT-CGM was offered short-term and intermittently as a self-care tool to inform patients' behavior. Method: The analyses projected lifetime clinical and economic outcomes for RT-CGM versus self-monitoring of blood glucose by fingerstick only. The base-case analysis was consistent with the RCT (RT-CGM for 2 weeks on/1 week off over 3 months). A scenario analysis simulated outcomes of an RT-CGM "refresher" after the active intervention of the RCT. Analyses used the IMS CORE Diabetes Model and were conducted from a US third-party payer perspective, including direct costs obtained from published sources and inflated to 2011 US dollars. Costs and health outcomes were discounted at 3% per annum. Results: Life expectancy (LE) and quality-adjusted life expectancy (QALE) from RT-CGM were 0.10 and 0.07, with a cost of $653/patient over a lifetime. Incremental LE and QALE from a "refresher" were 0.14 and 0.10, with a cost of $1312/patient over a lifetime, and incremental cost-effectiveness ratios were $9319 and $13 030 per LY and QALY gained. Conclusions: RT-CGM, as a self-care tool, is a cost-effective disease management option in the US for people with type 2 diabetes not on prandial insulin. Repeated use of RT-CGM may result in additional cost-effectiveness.
    No preview · Article · Feb 2016 · Journal of diabetes science and technology
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    ABSTRACT: Background: Orthogonal redundancy for glucose sensing (multiple sensing elements utilizing distinct methodologies) may enhance performance compared to nonredundant sensors, and to sensors with multiple elements utilizing the same technology (simple redundancy). We compared the performance of a prototype orthogonal redundant sensor (ORS) combining optical fluorescence and redundant electrochemical sensing via a single insertion platform to an electrochemical simple redundant sensor (SRS). Methods: Twenty-one adults with type 1 diabetes wore an ORS and an SRS concurrently for 7 days. Following sensor insertion, and on Day 4 with a standardized meal, frequent venous samples were collected for reference glucose measurement (laboratory [YSI] and meter) over 3 and 4 hours, respectively. Between study visits reference capillary blood glucose testing was undertaken. Sensor data were processed prospectively. Results: ORS mean absolute relative difference (MARD) was (mean ± SD) 10.5 ± 13.2% versus SRS 11.0 ± 10.4% (P = .34). ORS values in Clarke error grid zones A and A+B were 88.1% and 97.6%, respectively, versus SRS 86.4% and 97.8%, respectively (P = .23 and P = .84). ORS Day 1 MARD (10.7 ± 10.7%) was superior to SRS (16.5 ± 13.4%; P < .0001), and comparable to ORS MARD for the week. ORS sensor survival (time-averaged mean) was 92.1% versus SRS 74.4% (P = .10). ORS display time (96.0 ± 5.8%) was equivalent to SRS (95.6 ± 8.9%; P = .87). Conclusions: Combining simple and orthogonal sensor redundancy via a single insertion is feasible, with accuracy comparing favorably to current generation nonredundant sensors. Addition of an optical component potentially improves sensor reliability compared to electrochemical sensing alone. Further improvement in optical sensing performance is required prior to clinical application.
    No preview · Article · Feb 2016 · Journal of diabetes science and technology
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    ABSTRACT: Background: Inexpensive screening tools are needed to identify individuals predisposed to developing diabetes mellitus (DM). Such early identification coupled with an effective intervention could help many people avoid the substantial health costs of this disease. We investigated the hypothesis that fluctuating asymmetry (FA) in fingerprints is an indicator of type 2 diabetes mellitus (T2DM). Methods: Participants with T2DM, with T1DM, and without any indication or known family history of diabetes were fingerprinted with a Crossmatch Verifier 320 LC scanner. Asymmetry scores for each finger pair were assessed using both pattern analysis (ridge counts), and a wavelet-based analysis. Results: Both methods for scoring asymmetry predicted risk of T2DM for finger pair IV, controlling for gender and age. AUC scores were significantly greater than the null for pattern asymmetry scores (finger IV AUC = 0.74), and wavelet asymmetry scores for finger pair IV (AUC = 0.73) and finger pair V (AUC = 0.73), for predicting T2DM. In addition, wavelet asymmetry scores for finger pair IV (AUC = 0.80) and finger pair V (AUC = 0.85) significantly predicted risk of T1DM. Conclusions: A diagnostic tool based on FA in the fingerprints of finger pair IV, measured using a wavelet analysis could be developed for predicting risk prior to associated health problems for both T2DM and T1DM. In addition, given that that the prints for fingers IV and V develop during the 14-17 weeks of gestation, we predict that interventions during this time period of pregnancy will be most successful.
    No preview · Article · Feb 2016 · Journal of diabetes science and technology
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    ABSTRACT: Due to the increasing prevalence of diabetes mellitus, demand for diabetic retinopathy (DR) screening platforms is steeply increasing. Early detection and treatment of DR are key public health interventions that can greatly reduce the likelihood of vision loss. Current DR screening programs typically employ retinal fundus photography, which relies on skilled readers for manual DR assessment. However, this is labor-intensive and suffers from inconsistency across sites. Hence, there has been a recent proliferation of automated retinal image analysis software that may potentially alleviate this burden cost-effectively. Furthermore, current screening programs based on 2-dimensional fundus photography do not effectively screen for diabetic macular edema (DME). Optical coherence tomography is becoming increasingly recognized as the reference standard for DME assessment and can potentially provide a cost-effective solution for improving DME detection in large-scale DR screening programs. Current screening techniques are also unable to image the peripheral retina and require pharmacological pupil dilation; ultra-widefield imaging and confocal scanning laser ophthalmoscopy, which address these drawbacks, possess great potential. In this review, we summarize the current DR screening methods using various retinal imaging techniques, and also outline future possibilities. Advances in retinal imaging techniques can potentially transform the management of patients with diabetes, providing savings in health care costs and resources.
    No preview · Article · Feb 2016 · Journal of diabetes science and technology
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    ABSTRACT: Abstract The future biosimilar insulin marketplace could be a bane, benefit, or something in between, to patients under our care in the United States. Formulary preferred product status, with or without FDA interchangeability designation, coupled with current and proposed state pharmacy substitution laws may lead to an environment with as many as 50 different substitution guidelines depending on in which state a patient presents his or her prescription to be filled. If online global prescription supply options, often referred to as “Canada Drug,” are utilized, other country substitution guidelines come into play, which may yield a recipe for confusion, if not disaster.
    No preview · Article · Jan 2016 · Journal of diabetes science and technology
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    ABSTRACT: Since satiety is largely due to stretch of the stomach and people tend to eat a consistent weight of food, increasing food volume and mass increases satiety. This can be achieved without increasing the calories of food by mixing food with a material that cannot be metabolized. Such a material should be inert, safe, resistant to stomach acid, lack taste, available in powder form, smooth, resistant to heat, and cost effective. Polytetrafluoroethylene (PTFE) is an ideal substance for this purpose. It is a soft plastic that is widely considered to be the most inert material known and is extremely stable. Animal feeding trials showed that rats fed a diet of 25% PTFE for 90 days had no signs of toxicity and that the rats lost weight. This article publishes the data from these subchronic animal feeding trials, reviews the relevant available literature, and hypothesizes that increasing the volume of food by mixing the food with PTFE powder at a ratio of 3 parts food to 1 part PTFE by volume will substantially improve satiety and reduce caloric consumption in people.
    No preview · Article · Jan 2016 · Journal of diabetes science and technology
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    ABSTRACT: Manual calculation of bolus insulin dosages can be challenging for individuals treated with multiple daily insulin injections (MDI) therapy. Automated bolus calculator capability has recently been made available via enhanced blood glucose meters and smartphone apps. Use of this technology has been shown to improve glycemic control and reduce glycemic variability without changing hypoglycemia; however, the clinical utility of app-based bolus calculators has not been demonstrated. Moreover, recent evidence challenges the safety and efficacy of these smartphone apps. Although the ability to automatically calculate bolus insulin dosages addresses a critical need of MDI-treated individuals, this technology raises concerns about efficacy of treatment and the protection of patient safety. This article discusses key issues and considerations associated with automated bolus calculator use.
    No preview · Article · Jan 2016 · Journal of diabetes science and technology
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    ABSTRACT: Background: After a subcutaneous injection fluid might leak out of the skin, commonly referred to as leakage or backflow. The objective was to examine the influence of needle design and injection technique on leakage after injections in the subcutaneous tissue of humans and pigs. Method: Leakage data were obtained from a post hoc analysis of clinical trial data and from a pig study. Data from the clinical study were used to determine leakage as a function of injection volume, speed and region. Data from the pig study were used to determine leakage as a function of needle wall thickness, needle taper, injection angle, and wait time from end of injection to withdrawal of needle from skin. Results: Leakage volume was positively related to injection volume. Injections in the abdomen caused less leakage than thigh injections. A 32G needle caused less leakage than a 31G and a 32G tip (tapered) needle, and a "straight in" 90° needle insertion angle caused less leakage than an angled (~45°) insertion. Wait times of minimum 3 seconds caused less leakage than immediate withdrawal of the needle after injection. Needle wall thickness and injection speed did not influence leakage. Conclusions: Leakage will be minimized using a thin needle, using 90° needle insertion in the abdomen, injecting maximum 800 µL at a time, and waiting at least 3 seconds after the injection until the needle is withdrawn from the skin.
    No preview · Article · Jan 2016 · Journal of diabetes science and technology
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    ABSTRACT: Glucose meters often have similar performance when compared by error grid analysis. This is one reason that other statistics such as mean absolute relative deviation (MARD) are used to further differentiate performance. The problem with MARD is that too much information is lost. But additional information is available within the A zone of an error grid by using the Taguchi loss function. Applying the Taguchi loss function gives each glucose meter difference from reference a value ranging from 0 (no error) to 1 (error reaches the A zone limit). Values are averaged over all data which provides an indication of risk of an incorrect medical decision. This allows one to differentiate glucose meter performance for the common case where meters have a high percentage of values in the A zone and no values beyond the B zone. Examples are provided using simulated data.
    No preview · Article · Dec 2015 · Journal of diabetes science and technology
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    ABSTRACT: Purpose: Patients afflicted with ocular complications of diabetes represent a diverse demographic who often cannot undergo spectral-domain optical coherence tomography (SD-OCT) imaging of the retina due to postural restraints. Our pilot study compared imaging acquisition methods using SD-OCT in the handheld (HH) mode versus the conventional tabletop (TT) method. Methods: Our study included 22 undilated eyes of 22 subjects (mean ± SD age, 35.8 ± 16.8 years) imaged using HH and TT iVue SD-OCT (Optovue, Fremont, CA). Statistical analysis was performed using Microsoft Excel 12.2.7 (Microsoft Corporation, Redmond, WA) software with an accepted significance of P < .05. Results: Strong intraclass correlation coefficient was observed for (1) overall (.97), superior (.93), and inferior (.94) ganglion cell complex thickness, and (2) central (.98), inferior (.90), superior (.92), nasal (.94), and temporal (.93) macular retinal thickness. Mean scan quality index was adequate but lower in HH versus TT SD-OCT (62.8 vs 68.1, respectively; P < .0001). Multiple attempts for adequate imaging were required more frequently in HH versus TT SD-OCT (34% vs 5%, respectively; P < .001). Conclusion: HH SD-OCT may be a feasible alternative to TT SD-OCT in select situations, especially in patients suffering from diabetic complications with limited mobility.
    No preview · Article · Dec 2015 · Journal of diabetes science and technology

  • No preview · Article · Dec 2015 · Journal of diabetes science and technology

  • No preview · Article · Dec 2015 · Journal of diabetes science and technology
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    ABSTRACT: Background: The speed of insulin absorption after subcutaneous delivery is highly variable. Incorrect assumptions about insulin pharmacokinetics compromise effective glycemic regulation. Our ultimate goal is to develop a system to monitor insulin levels in vivo continuously, allowing pharmacokinetic parameters to be calculated in real time. We hypothesize that a bead-based detection system can be run on a flow-through microfluidic platform to measure insulin in subcutaneous fluid sampled via microdialysis. As a first step in development, we focused on microsphere-based measurement of insulin. Methods: Polystyrene microspheres coated with an anti-insulin monoclonal antibody were exposed to insulin-containing solutions, and after addition of a fluorescently labeled anti-insulin monoclonal antibody with a distinct epitope, bead-associated fluorescence was detected by fluorescence microscopy in 96-well plates or in a flow-through, microfluidic platform. Results: The bead detection system in plates had a linear range in buffer for regular human insulin (RHI), insulin lispro, and insulin aspart of 15-1115 µIU/ml, 14-976 µIU/ml, and 25-836 µIU/ml, respectively. Measurement on plasma samples demonstrated proportionality between basal and peak insulin levels similar to the laboratory reference method. Preliminary results in a polydimethylsiloxane-based, flow-through, microfluidic platform showed a strong signal at peak insulin levels. Conclusions: We have developed a microsphere-based system to rapidly measure levels of insulin and insulin analogs. We have further demonstrated proof of concept that this bead detection system can be implemented in a lab-on-a-chip format, which will be further developed and combined with microdialysis for real-time monitoring of insulin in vivo.
    No preview · Article · Dec 2015 · Journal of diabetes science and technology
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    ABSTRACT: Background: Application of novel machine learning approaches to electronic health record (EHR) data could provide valuable insights into disease processes. We utilized this approach to build predictive models for progression to prediabetes and type 2 diabetes (T2D). Methods: Using a novel analytical platform (Reverse Engineering and Forward Simulation [REFS]), we built prediction model ensembles for progression to prediabetes or T2D from an aggregated EHR data sample. REFS relies on a Bayesian scoring algorithm to explore a wide model space, and outputs a distribution of risk estimates from an ensemble of prediction models. We retrospectively followed 24 331 adults for transitions to prediabetes or T2D, 2007-2012. Accuracy of prediction models was assessed using an area under the curve (AUC) statistic, and validated in an independent data set. Results: Our primary ensemble of models accurately predicted progression to T2D (AUC = 0.76), and was validated out of sample (AUC = 0.78). Models of progression to T2D consisted primarily of established risk factors (blood glucose, blood pressure, triglycerides, hypertension, lipid disorders, socioeconomic factors), whereas models of progression to prediabetes included novel factors (high-density lipoprotein, alanine aminotransferase, C-reactive protein, body temperature; AUC = 0.70). Conclusions: We constructed accurate prediction models from EHR data using a hypothesis-free machine learning approach. Identification of established risk factors for T2D serves as proof of concept for this analytical approach, while novel factors selected by REFS represent emerging areas of T2D research. This methodology has potentially valuable downstream applications to personalized medicine and clinical research.
    No preview · Article · Dec 2015 · Journal of diabetes science and technology