Predictive Low Glucose Suspend Research Articles

Type 1 diabetes mellitus management in young children: implementation of current technologies.

The use of advanced technologies for diabetes management is on the rise among pediatric patients with type 1 diabetes (T1D). Continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring, predictive low glucose suspend, hybrid closed-loop insulin delivery systems-all enable better diabetes management and glycemic control. However, when used by children, and especially very young children, specific aspects must be taken into consideration, including technical parameters, ease of use, parental stress, and satisfaction. The unique characteristics of T1D in children aged <6 years are reviewed and studies of the pros and cons of different technologies in this specific age group are presented. Addressing such issues when implementing advanced technologies among very young children with T1D will enable better diabetes management and will hopefully ease a tremendous burden of both children and families.

A Review of Predictive Low Glucose Suspend and Its Effectiveness in Preventing Nocturnal Hypoglycemia.

To evaluate the effectiveness of predictive low glucose suspend (PLGS) systems within sensor-augmented insulin infusion pumps at preventing nocturnal hypoglycemia in patients with type 1 diabetes (DM1), we performed a systematic review and meta-analysis of randomized crossover trials. Pubmed and Google Scholar were searched for randomized crossover trials, published between January 2013 and July 2018, in nonpregnant outpatients with DM1, which compared event rates during PLGS overnight periods and non-PLGS overnight periods. The primary outcome was the proportion of overnight periods with one or more hypoglycemic measurement. When available, individual patient data were used to assess the effect of clustering measurements within patients. Four studies (272 patients, 10,735 patient-nights: 5422 PLGS and 5313 non-PLGS) were included in the meta-analysis. Two studies reported patient-level data that permitted assessment of the effect of clustering measurements within patients. The effect on the risk difference was minimal. The proportion of overnight periods with one or more episodes of hypoglycemia was 19.6% for the PLGS periods and 27.8% for the non-PLGS periods. Based on the pooled estimate, PLGS overnight periods were associated with an 8.8% lower risk of hypoglycemia (risk difference -0.088; 95% CI -0.119 to -0.056, I2 = 67.4%, τ2 = 0.0006, 4 studies). PLGS systems can reduce nocturnal hypoglycemic events in patients with DM1.

1038-P: Results of Interim Analysis of a Randomized Crossover Study in Type 1 Diabetes (T1D) of a Dual-Hormone Closed-Loop System with Xerisol™ Glucagon vs. Insulin-Only Closed-Loop System vs. a Predictive Low Glucose Suspend System

Dual-hormone systems show promise to reduce hypoglycemia, but require a stable liquid glucagon formulation. XeriSol™ glucagon is a shelf-stable glucagon product for this use. Nineteen subjects with T1D are completing a single-center three-day outpatient study comparing control modes of the Oregon Artificial Pancreas system: 1) dual hormone (DH) closed-loop with Novolog™ insulin and XeriSol™ glucagon, 2) insulin-only single hormone (SH) closed-loop, 3) insulin-only predictive low glucose suspend system (PLGS). In clinic aerobic exercise (45 minutes at 60% VO2max) and home exercise was completed with each arm. SH and DH used automated exercise detection to adaptively dose insulin/glucagon for predicted hypoglycemia and tailored mealtime dosing based on past meal responses with an adaptive algorithm. An interim analysis after 7 subjects was completed for safety. The primary outcome measures are % time 70-180 mg/dL and % time &amp;lt;70 mg/dL for the 3-day study and the 4-hour period from start of exercise until the next meal. From start of exercise until the next meal, DH showed a clinically meaningful reduction of time in hypoglycemia compared with PLGS and SH. For the entire study, DH showed a clinically meaningful lower time &amp;lt;70mg/dL. No serious events or unexpected side effects occurred. Disclosure L.M. Wilson: None. P.G. Jacobs: Stock/Shareholder; Self; Pacific Diabetes Technologies. N. Resalat: None. R. Reddy: None. J. El Youssef: None. D. Branigan: None. J.A. Leitschuh: Other Relationship; Self; AgaMatrix. B. Senf: None. V. Gabo: None. J.R. Castle: Advisory Panel; Self; Novo Nordisk Inc., Zealand Pharma A/S. Consultant; Self; Dexcom, Inc. Research Support; Self; Dexcom, Inc., Xeris Pharmaceuticals, Inc. Funding JDRF

The road from intermittently scanned glucose monitoring to hybrid closed-loop systems: Part A. Keys to success: subject profiles, choice of systems, education.

Managing type 1 diabetes (T1DM) is challenging and requires intensive glucose monitoring and titration of insulin in order to reduce the risk of complications. The use of continuous glucose monitoring (CGM) systems, either flash or intermittently scanned glucose monitoring (isCGM) or real-time (RT) CGM, has positively affected the management of type 1 diabetes with the potential to lower HbA1c, enhance time spent in range, reduce frequency and time spent in hypoglycemia and hyperglycemia, lower glycemic variability, and improve quality of life. In recent years, both CGM and pump technology have advanced, with improved functional features and integration, including low glucose suspend (LGS), predictive low glucose suspend (PLGS), and hybrid closed-loop (HCL) systems. In this review, we highlight the benefits and limitations of use of isCGM/RT-CGM for open-loop control and recent progress in closed-loop control systems. We also discuss different subject profiles for the different systems, and focus on educational aspects that are key to successful use of the systems.

Effect of predicted low suspend pump treatment on improving glycaemic control and quality of sleep in children with type 1 diabetes and their caregivers: the QUEST randomized crossover study

BackgroundIn attempting to achieve optimal metabolic control, the day-to-day management is challenging for a child with type 1 diabetes (T1D) and his family and can have a major negative impact on their quality of life. Augmenting an insulin pump with glucose sensor information leads to improved outcomes: decreased haemoglobin A1c levels, increased time in glucose target and less hypoglycaemia. Fear of nocturnal hypoglycaemia remains pervasive amongst parents, leading to chronic sleep interruption and lack of sleep for the parents and their children.The QUEST study, an open-label, single-centre randomized crossover study, aims to evaluate the impact on time in target, in hypoglycaemia and hyperglycaemia and the effect on sleep and quality of life in children with T1D, comparing a sensor-augmented pump (SAP) with predictive low glucose suspend and alerts to the use of the same insulin pump with a flash glucose measurement (FGM) device not interacting with the pump.Methods/designSubjects meeting the inclusion criteria are randomized to treatment with the SAP or treatment with an insulin pump and independent FGM for 5 weeks. Following a 3-week washout period, the subjects cross over to the other study arm for 5 weeks. During the week before and in the last week of treatment, the subjects and one of their caregivers wear a sleep monitor in order to obtain sleep data. The primary endpoint is the between-arm difference in percentage of time in glucose target during the final 6 days of each treatment arm, measured by a blinded continuous glucose measurement (CGM).Additional endpoints include comparison of quantity and quality of sleep as well as quality of life perception of the subjects and one of their caregivers in the two different treatment arms.Recruitment started in February 2017. A total of 36 patients are planned to be randomized. The study recruitment was completed in April 2018.DiscussionWith this study we will provide more information on whether insulin pump treatment combined with more technology (SmartGuard® feature and alerts) leads to better metabolic control. The inclusion of indicators on quality of sleep with less sleep interruption, less lack of sleep and perception of quality of life in both children and their primary caregivers is essential for this study and might help to guide us to further treatment improvement.Trial registrationClinicalTrials.gov, NCT03103867. Registered on 6 April 2017.

Predictive Low-Glucose Suspend Reduces Hypoglycemia in Adults, Adolescents, and Children With Type 1 Diabetes in an At-Home Randomized Crossover Study: Results of the PROLOG Trial.

This study evaluated a new insulin delivery system designed to reduce insulin delivery when trends in continuous glucose monitoring (CGM) glucose concentrations predict future hypoglycemia. Individuals with type 1 diabetes (n = 103, age 6-72 years, mean HbA1c 7.3% [56 mmol/mol]) participated in a 6-week randomized crossover trial to evaluate the efficacy and safety of a Tandem Diabetes Care t:slim X2 pump with Basal-IQ integrated with a Dexcom G5 sensor and a predictive low-glucose suspend algorithm (PLGS) compared with sensor-augmented pump (SAP) therapy. The primary outcome was CGM-measured time <70 mg/dL. Both study periods were completed by 99% of participants; median CGM usage exceeded 90% in both arms. Median time <70 mg/dL was reduced from 3.6% at baseline to 2.6% during the 3-week period in the PLGS arm compared with 3.2% in the SAP arm (difference [PLGS - SAP] = -0.8%, 95% CI -1.1 to -0.5, P < 0.001). The corresponding mean values were 4.4%, 3.1%, and 4.5%, respectively, represent-ing a 31% reduction in the time <70 mg/dL with PLGS. There was no increase in mean glucose concentration (159 vs. 159 mg/dL, P = 0.40) or percentage of time spent >180 mg/dL (32% vs. 33%, P = 0.12). One severe hypoglycemic event occurred in the SAP arm and none in the PLGS arm. Mean pump suspension time was 104 min/day. The Tandem Diabetes Care Basal-IQ PLGS system significantly reduced hypoglycemia without rebound hyperglycemia, indicating that the system can benefit adults and youth with type 1 diabetes in improving glycemic control.

Technology in the management of type 1 diabetes mellitus - current status and future prospects.

Type 1 diabetes mellitus (T1DM) represents 5-10% of diabetes cases worldwide. The incidence of T1DM is increasing, and there is no immediate prospect of a cure. As such, lifelong management is required, the burden of which is being eased by novel treatment modalities, particularly from the field of diabetes technologies. Continuous glucose monitoring has become the standard of care and includes factory-calibrated subcutaneous glucose monitoring and long-term implantable glucose sensing. In addition, considerable progress has been made in technology-enabled glucose-responsive insulin delivery. The first hybrid insulin-only closed-loop system has been commercialized, and other closed-loop systems are under development, including dual-hormone glucose control systems. This Review focuses on well-established diabetes technologies, including glucose sensing, pen-based insulin delivery, data management and data analytics. We also cover insulin pump therapy, threshold-based suspend, predictive low-glucose suspend and single-hormone and dual-hormone closed-loop systems. Clinical practice recommendations for insulin pump therapy and continuous glucose monitoring are presented, and ongoing research and future prospects are highlighted. We conclude that the management of T1DM is improved by diabetes technology for the benefit of the majority of people with T1DM, their caregivers and guardians and health-care professionals treating patients with T1DM.

Randomized Outpatient Trial of Single- and Dual-Hormone Closed-Loop Systems That Adapt to Exercise Using Wearable Sensors.

OBJECTIVEAutomated insulin delivery is the new standard for type 1 diabetes, but exercise-related hypoglycemia remains a challenge. Our aim was to determine whether a dual-hormone closed-loop system using wearable sensors to detect exercise and adjust dosing to reduce exercise-related hypoglycemia would outperform other forms of closed-loop and open-loop therapy.RESEARCH DESIGN AND METHODSParticipants underwent four arms in randomized order: dual-hormone, single-hormone, predictive low glucose suspend, and continuation of current care over 4 outpatient days. Each arm included three moderate-intensity aerobic exercise sessions. The two primary outcomes were percentage of time in hypoglycemia (<70 mg/dL) and in a target range (70–180 mg/dL) assessed across the entire study and from the start of the in-clinic exercise until the next meal.RESULTSThe analysis included 20 adults with type 1 diabetes who completed all arms. The mean time (SD) in hypoglycemia was the lowest with dual-hormone during the exercise period: 3.4% (4.5) vs. 8.3% (12.6) single-hormone (P = 0.009) vs. 7.6% (8.0) predictive low glucose suspend (P < 0.001) vs. 4.3% (6.8) current care where pre-exercise insulin adjustments were allowed (P = 0.49). Time in hypoglycemia was also the lowest with dual-hormone during the entire 4-day study: 1.3% (1.0) vs. 2.8% (1.7) single-hormone (P < 0.001) vs. 2.0% (1.5) predictive low glucose suspend (P = 0.04) vs. 3.1% (3.2) current care (P = 0.007). Time in range during the entire study was the highest with single-hormone: 74.3% (8.0) vs. 72.0% (10.8) dual-hormone (P = 0.44).CONCLUSIONSThe addition of glucagon delivery to a closed-loop system with automated exercise detection reduces hypoglycemia in physically active adults with type 1 diabetes.

Evaluating optimal utilisation of technology in type 1 diabetes mellitus from a clinical and health economic perspective: protocol for a systematic review

BackgroundTechnology has been implemented since the 1970s with the hope of improving glycaemic control and reducing the burden of complications for those living with type 1 diabetes. A clinical and cost-effectiveness comparison of all available technologies including continuous subcutaneous insulin infusion (CSII), continuous glucose monitors (CGMs), sensor-augmented pump therapy (including either low-glucose suspend or predictive low-glucose suspend), hybrid closed-loop systems, closed-loop (single-hormone or dual-hormone) systems, flash glucose monitoring (FGM), insulin bolus calculators, and ‘smart-device’ applications is currently lacking. This systematic review, network meta-analysis, and narrative synthesis aims to summarise available evidence regarding the clinical and cost-effectiveness of available technologies in the management of patients with type 1 diabetes.MethodsRelevant studies will be searched using a comprehensive strategy through MEDLINE, MEDLINE in-process and other non-indexed citations, EMBASE, PubMed, all evidenced-based medicine reviews, EconLit, Cost-effectiveness Analysis Registry, Research Papers in Economics, Web of Science, PsycInfo, CINAHL, and PROSPERO for randomised controlled trials and economic evaluations. The search strategy will assess if there are combinations of currently available technologies that are superior to each other or to insulin injections and capillary blood glucose testing with regard to glycaemic control, morbidity/mortality, quality of life, and cost-effectiveness. Two reviewers will screen all articles for eligibility and then independently evaluate risk of bias, complete quality assessment, and extract data for included studies. Network meta-analyses will be performed where there is sufficient homogenous clinical data. Narrative synthesis will be performed for heterogeneous clinical data that cannot be pooled for network meta-analysis with critical appraisal of economic evaluations.DiscussionThis systematic review protocol utilises rigorous methodology and pre-determined eligibility criteria to provide a uniquely comprehensive search for a broad spectrum of clinical and economic outcomes in comparing multiple currently available technologies for managing type 1 diabetes. Evidence on which technologies may be most appropriate for particular patient groups will be examined as well as the economic justification for funding of different technologies.Systematic review registrationPROSPERO (CRD42017077221)

Sensor-augmented CSII therapy with predictive low-glucose suspend following total pancreatectomy.

Pancreatogenic diabetes is characterised by recurrent severe hypoglycaemia due to changes in both endocrine and exocrine functions. There are no guidelines to manage these individuals. Herein, we describe the post-operative management of two people who developed pancreatogenic diabetes following total pancreatectomy for neuroendocrine malignancy. In both individuals, diabetes was managed using sensor-augmented predictive low-glucose suspend continuous subcutaneous insulin infusion (CSII). We demonstrate the benefit of sensor-augmented CSII in averting hypoglycaemia whilst optimising glycaemic control. Expected rates of severe hypoglycaemia in individuals with pancreatogenic diabetes can be averted with the use of continuous glucose monitoring (CGM) technology, optimising quality of life and reducing the risk of diabetes-related complications.Learning points:There are no clear guidelines to manage people with pancreatogenic diabetes.We describe the use of CGM with predictive low-glucose suspend continuous subcutaneous insulin infusion (CSII) in the management of two individuals post-pancreatectomy.Predictive low-glucose suspend technology can achieve excellent glycaemic control whilst avoiding recurrent and severe hypoglycaemia in people with pancreatogenic diabetes.Predictive low-glucose suspend CGM should be considered as an effective therapeutic option for the management of pancreatogenic diabetes.

Continuous Glucose Monitoring: A Review of Recent Studies Demonstrating Improved Glycemic Outcomes.

Continuous Glucose Monitoring (CGM) has been demonstrated to be clinically valuable, reducing risks of hypoglycemia and hyperglycemia, glycemic variability (GV), and improving patient quality of life for a wide range of patient populations and clinical indications. Use of CGM can help reduce HbA1c and mean glucose. One CGM device, with accuracy (%MARD) of approximately 10%, has recently been approved for self-adjustment of insulin dosages (nonadjuvant use) and approved for reimbursement for therapeutic use in the United States. CGM had previously been used off-label for that purpose. CGM has been demonstrated to be clinically useful in both type 1 and type 2 diabetes for patients receiving a wide variety of treatment regimens. CGM is beneficial for people using either multiple daily injections (MDI) or continuous subcutaneous insulin infusion (CSII). CGM is used both in retrospective (professional, masked) and real-time (personal, unmasked) modes: both approaches can be beneficial. When CGM is used to suspend insulin infusion when hypoglycemia is detected until glucose returns to a safe level (low-glucose suspend), there are benefits beyond sensor-augmented pump (SAP), with greater reduction in the risk of hypoglycemia. Predictive low-glucose suspend provides greater benefits in this regard. Closed-loop control with insulin provides further improvement in quality of glycemic control. A hybrid closed-loop system has recently been approved by the U.S. FDA. Closed-loop control using both insulin and glucagon can reduce risk of hypoglycemia even more. CGM facilitates rigorous evaluation of new forms of therapy, characterizing pharmacodynamics, assessing frequency and severity of hypo- and hyperglycemia, and characterizing several aspects of GV.

Predictive Low-Glucose Suspend to Prevent Hypoglycemia.

Diabetes Technology & TherapeuticsVol. 19, No. 5 CommentariesPredictive Low-Glucose Suspend to Prevent HypoglycemiaJordan E. Pinsker and Eyal DassauJordan E. PinskerWilliam Sansum Diabetes Center, Santa Barbara, California.Search for more papers by this author and Eyal DassauWilliam Sansum Diabetes Center, Santa Barbara, California.Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts.Search for more papers by this authorPublished Online:1 May 2017https://doi.org/10.1089/dia.2017.0064AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetailsCited byPredictive Low-Glucose Suspend Necessitates Less Carbohydrate Supplementation to Rescue Hypoglycemia: Need to Revisit Current Hypoglycemia Treatment Guidelines Jordan E. Pinsker, Amy Bartee, Michelle Katz, Amy Lalonde, Richard Jones, Eyal Dassau, and Howard Wolpert29 June 2021 | Diabetes Technology & Therapeutics, Vol. 23, No. 7The Predictive Low Glucose Management System in Prevention of Clinically Significant Hypoglycemia in Type 1 Diabetes. A Preliminary Study Identifying the Most Common Events Leading Up to Hypoglycemia During Insulin Pump Therapy15 April 2019 | Experimental and Clinical Endocrinology & Diabetes, Vol. 129, No. 05Accuracy of CGM systemsA Review of Predictive Low Glucose Suspend and Its Effectiveness in Preventing Nocturnal Hypoglycemia Ethan Chen, Fraya King, Michael A. Kohn, Elias K. Spanakis, Marc Breton, and David C. Klonoff6 September 2019 | Diabetes Technology & Therapeutics, Vol. 21, No. 10Meso-Cellular Silicate Foam-Modified Reduced Graphene Oxide with a Sandwich Structure for Enzymatic Immobilization and Bioelectrocatalysis26 July 2019 | ACS Applied Materials & Interfaces, Vol. 11, No. 33Optimal predictive low glucose management settings during physical exercise in adolescents with type 1 diabetes22 November 2018 | Pediatric Diabetes, Vol. 20, No. 1 Volume 19Issue 5May 2017 InformationCopyright 2017, Mary Ann Liebert, Inc.To cite this article:Jordan E. Pinsker and Eyal Dassau.Predictive Low-Glucose Suspend to Prevent Hypoglycemia.Diabetes Technology & Therapeutics.May 2017.271-276.http://doi.org/10.1089/dia.2017.0064Published in Volume: 19 Issue 5: May 1, 2017Online Ahead of Print:April 20, 2017KeywordsHypoglycemiaType 1 diabetesLow glucose suspendPredictive low glucose suspendAutomated insulin deliveryArtificial pancreasPDF download

Efficacy of an Overnight Predictive Low-Glucose Suspend System in Relation to Hypoglycemia Risk Factors in Youth and Adults With Type 1 Diabetes.

We developed a system to suspend insulin pump delivery overnight when the glucose trend predicts hypoglycemia. This predictive low-glucose suspend (PLGS) system substantially reduces nocturnal hypoglycemia without an increase in morning ketosis. Evaluation of hypoglycemia risk factors that could potentially influence the efficacy of the system remains critical for understanding possible problems with the system and identifying patients that may have the greatest benefit when using the system. The at-home randomized trial consisted of 127 study participants with hemoglobin A1c (A1C) of ≤8.5% (mmol/mol) for patients aged 4-14 years and ≤8.0% for patient aged 15-45 years. Factors assessed included age, gender, A1C, diabetes duration, daily percentage basal insulin, total daily dose of insulin (units/kg-day), bedtime BG, bedtime snack, insulin on board, continuous glucose monitor (CGM) rate of change (ROC), day of the week, time system activated, daytime exercise intensity, and daytime CGM-measured hypoglycemia. The PLGS system was effective in preventing hypoglycemia for each factor subgroup. There was no evidence that the PLGS system was more or less effective in preventing hypoglycemia in any one subgroup compared with the other subgroups based on that factor. In addition, the effect of the system on overnight hyperglycemia did not differ in subgroups. The PLGS system tested in this study effectively reduced hypoglycemia without a meaningful increase in hyperglycemia across a variety of factors.

In-home nighttime predictive low glucose suspend experience in children and adults with type 1 diabetes.

Overnight predictive low glucose suspend (PLGS) reduces hypoglycemia across all ages; however, there are no reports on behavior or experience differences across age groups, especially in pediatrics. As run-in for a subsequent randomized clinical trial (RCT), 127 subjects (50% male) ages 4-45 yr utilized the experimental PLGS system nightly for 5-10 nights (PLGS active phase). We analyzed the number of blood glucose (BG) checks and boluses given per age group. During the subsequent 42 night RCT phase, we analyzed sensor use, skin reactions, errors, and reasons why the experimental system was not used. In 821 nights of active PLGS, subjects ages 4-6 yr (and their parents) tested BG levels 75% of nights compared with 65% of nights (7-10 yr), 53% of nights (11-14 yr), 33% of nights (15-25 yr), and 28% of nights (26-45 yr), respectively (p < 0.001). Likewise, youngest subjects (and parents) administered insulin boluses 56% of nights during active PLGS use compared with 48%, 33%, 20%, and 25%, respectively (p < 0.001). This was unrelated to study requirements. During the RCT phase, subjects 4-6 yr experienced more frequent and severe skin reactions (p = 0.02), while adult subjects (26-45 yr) wore individual sensors a median of 26 h longer than the youngest subjects (p < 0.001). Technical problems with the sensor (errors, miscalibrations, etc.), traveling, and BG levels >270 at bedtime (study requirement) were primary contributors to non-system use. Understanding the different use patterns and challenges in pediatrics and adolescence is needed to direct patient education to optimize use of PLGS and future artificial pancreas systems.

The Artificial Pancreas in 2016: A Digital Treatment Ecosystem for Diabetes.

With the increasing availability of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII), the artificial pancreas (AP) (the commonly accepted term for closed-loop control [CLC] of blood glucose [BG] levels in diabetes) has become a hot area in translational research and industrial development. After a prolonged period of inpatient, clinical research center trials using cumbersome systems, the field has progressed rapidly over the past 2 years to long-term, free-living studies running AP algorithms on smartphones. Although it is still not a cure, the AP is the most promising advance in the treatment of diabetes at this time. This issue of Diabetes Care presents today’s AP state of the art, including reports on multinational home-use AP trials, studies in young children, the use of multihormonal approaches to mitigate meal-related hyperglycemia, and discussions of AP study designs and outcome measures. This collection of articles establishes the AP as a new diabetes treatment paradigm—not a single-function CGM or CSII device but an adaptable wearable network encompassing the patient in a digital treatment ecosystem. In its May 2014 issue, Diabetes Care featured the progress in the AP field in a series of articles labeled “Advances in Artificial Pancreas Development.” In addition to an editorial discussing the state of the art of AP development in 2014 (1), the issue included original articles that covered a broad range of topics including analyses of the possible physiological inputs to CLC (2), real-time estimation of insulin sensitivity from CGM and insulin pump data (3), engineering of the AP algorithms (4), reports of predictive low-glucose suspend (LGS) systems (5), studies of overnight CLC at home (6), feasibility of the AP in type 2 diabetes (7), and the first around-the-clock outpatient CLC running a model predictive control (MPC) algorithm on a portable AP system (8). Since then, …

Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis.

OBJECTIVENocturnal hypoglycemia can cause seizures and is a major impediment to tight glycemic control, especially in young children with type 1 diabetes. We conducted an in-home randomized trial to assess the efficacy and safety of a continuous glucose monitor–based overnight predictive low-glucose suspend (PLGS) system.RESEARCH DESIGN AND METHODSIn two age-groups of children with type 1 diabetes (11–14 and 4–10 years of age), a 42-night trial for each child was conducted wherein each night was assigned randomly to either having the PLGS system active (intervention night) or inactive (control night). The primary outcome was percent time <70 mg/dL overnight.RESULTSMedian time at <70 mg/dL was reduced by 54% from 10.1% on control nights to 4.6% on intervention nights (P < 0.001) in 11–14-year-olds (n = 45) and by 50% from 6.2% to 3.1% (P < 0.001) in 4–10-year-olds (n = 36). Mean overnight glucose was lower on control versus intervention nights in both age-groups (144 ± 18 vs. 152 ± 19 mg/dL [P < 0.001] and 153 ± 14 vs. 160 ± 16 mg/dL [P = 0.004], respectively). Mean morning blood glucose was 159 ± 29 vs. 176 ± 28 mg/dL (P < 0.001) in the 11–14-year-olds and 154 ± 25 vs. 158 ± 22 mg/dL (P = 0.11) in the 4–10-year-olds, respectively. No differences were found between intervention and control in either age-group in morning blood ketosis.CONCLUSIONSIn 4–14-year-olds, use of a nocturnal PLGS system can substantially reduce overnight hypoglycemia without an increase in morning ketosis, although overnight mean glucose is slightly higher.

Abstracts from ATTD 20158th International Conference on Advanced Technologies &amp; Treatments for DiabetesParis, France—February 18–21, 2015

Abstracts from ATTD 20158th International Conference on Advanced Technologies &amp; Treatments for DiabetesParis, France—February 18–21, 2015

A novel method to detect pressure-induced sensor attenuations (PISA) in an artificial pancreas.

Continuous glucose monitors (CGMs) provide real-time interstitial glucose concentrations that are essential for automated treatment of individuals with type 1 diabetes. Miscalibration, noise spikes, dropouts, or pressure applied to the site (e.g., lying on the site while sleeping) can cause inaccurate glucose signals, which could lead to inappropriate insulin dosing decisions. These studies focus on the problem of pressure-induced sensor attenuations (PISAs) that occur overnight and can cause undesirable pump shut-offs in a predictive low glucose suspend system. The algorithm presented here uses real-time CGM readings without knowledge of meals, insulin doses, activity, sensor recalibrations, or fingerstick measurements. The real-time PISA detection technique was tested on outpatient "in-home" data from a predictive low-glucose suspend trial with over 1125 nights of data. A total of 178 sets were created by using different parameters for the PISA detection algorithm to illustrate its range of available performance. The tracings were reviewed via a web-based analysis tool by an engineer with an extensive expertise on analyzing clinical datasets and ~3% of the CGM readings were marked as PISA events which were used as the gold standard. It is shown that 88.34% of the PISAs were successfully detected by the algorithm, and the percentage of false detections could be reduced to 1.70% by altering the algorithm parameters. Use of the proposed PISA detection method can result in a significant decrease in undesirable pump suspensions overnight, and may lead to lower overnight mean glucose levels while still achieving a low risk of hypoglycemia.

The Impact of Accelerometer Use in Exercise-Associated Hypoglycemia Prevention in Type 1 Diabetes

Exercise-associated hypoglycemia is a common adverse event in people with type 1 diabetes. Previous in silico testing by our group demonstrated superior exercise-associated hypoglycemia mitigation when a predictive low glucose suspend (PLGS) algorithm was augmented to incorporate activity data. The current study investigates the effectiveness of an accelerometer-augmented PLGS algorithm in an outpatient exercise protocol. Subjects with type 1 diabetes on insulin pump therapy participated in two structured soccer sessions, one utilizing the algorithm and the other using the subject's regular basal insulin rate. Each subject wore their own insulin pump and a Dexcom G4™ Platinum continuous glucose monitor (CGM); subjects on-algorithm also wore a Zephyr BioHarness™ 3 accelerometer. The algorithm utilized a Kalman filter with a 30-minute prediction horizon. Activity and CGM readings were manually entered into a spreadsheet and at five-minute intervals, the algorithm indicated whether the basal insulin infusion should be on or suspended; any changes were then implemented by study staff. The rate of hypoglycemia during and after exercise (until the following morning) was compared between groups. Eighteen subjects (mean age 13.4 ± 3.7 years) participated in two separate sessions 7-22 days apart. The difference in meter blood glucose levels between groups at each rest period did not achieve statistical significance at any time point. Hypoglycemia during the session was recorded in three on-algorithm subjects, compared to six off-algorithm subjects. In the postexercise monitoring period, hypoglycemia occurred in two subjects who were on-algorithm during the session and four subjects who were off-algorithm. The accelerometer-augmented algorithm failed to prevent exercise-associated hypoglycemia compared to subjects on their usual basal rates. A larger sample size may have achieved statistical significance. Further research involving an automated system, a larger sample size, and an algorithm design that favors longer periods of pump suspension is necessary.

A randomized trial of a home system to reduce nocturnal hypoglycemia in type 1 diabetes.

OBJECTIVEOvernight hypoglycemia occurs frequently in individuals with type 1 diabetes and can result in loss of consciousness, seizure, or even death. We conducted an in-home randomized trial to determine whether nocturnal hypoglycemia could be safely reduced by temporarily suspending pump insulin delivery when hypoglycemia was predicted by an algorithm based on continuous glucose monitoring (CGM) glucose levels.RESEARCH DESIGN AND METHODSFollowing an initial run-in phase, a 42-night trial was conducted in 45 individuals aged 15–45 years with type 1 diabetes in which each night was assigned randomly to either having the predictive low-glucose suspend system active (intervention night) or inactive (control night). The primary outcome was the proportion of nights in which ≥1 CGM glucose values ≤60 mg/dL occurred.RESULTSOvernight hypoglycemia with at least one CGM value ≤60 mg/dL occurred on 196 of 942 (21%) intervention nights versus 322 of 970 (33%) control nights (odds ratio 0.52 [95% CI 0.43–0.64]; P < 0.001). Median hypoglycemia area under the curve was reduced by 81%, and hypoglycemia lasting >2 h was reduced by 74%. Overnight sensor glucose was >180 mg/dL during 57% of control nights and 59% of intervention nights (P = 0.17), while morning blood glucose was >180 mg/dL following 21% and 27% of nights, respectively (P < 0.001), and >250 mg/dL following 6% and 6%, respectively. Morning ketosis was present <1% of the time in each arm.CONCLUSIONSUse of a nocturnal low-glucose suspend system can substantially reduce overnight hypoglycemia without an increase in morning ketosis.