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• W2604519612 abstract "Diabetes Technology & TherapeuticsVol. 17, No. S1 Original ArticlesFree AccessClosing the LoopArianne Caudal, Matt Mulroy, Wesley Wagers, Eran Atlas, and Eyal DassauArianne CaudalWilliam Sansum Diabetes Center, Santa Barbara, CA.Search for more papers by this author, Matt MulroyWilliam Sansum Diabetes Center, Santa Barbara, CA.Search for more papers by this author, Wesley WagersWilliam Sansum Diabetes Center, Santa Barbara, CA.Search for more papers by this author, Eran AtlasDiabetes Technology Center, Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel.Search for more papers by this author, and Eyal DassauDepartment of Chemical Engineering and the Institute for Collaborative Biotechnologies, University of California at Santa Barbara, Santa Barbara, CA.William Sansum Diabetes Center, Santa Barbara, CA.Search for more papers by this authorPublished Online:13 Feb 2015https://doi.org/10.1089/dia.2015.1504AboutSectionsPDF/EPUB ToolsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail IntroductionFor individuals living with diabetes, monitoring blood glucose has classically been accomplished in an open-loop fashion through the utilization of a continuous glucose monitor (CGM), finger stick method, or both. A closed-loop artificial pancreas (AP) system has the potential to significantly reduce the burdens of type 1 diabetes (T1DM) patients.Creating a fully closed-loop automated insulin delivery system involves a progression from in silico studies, to clinical trials, and finally to outpatient studies to assess the system's ability to cope with the challenges of daily life. Outpatient studies are currently being performed to evaluate the difficulties presented by meals, exercise, and nighttime glycemic control. Other studies are attempting to determine if benefit lies in a dual-chamber system that delivers both insulin and glucagon.Three components constitute an AP system: a CGM, an insulin pump, and a control algorithm that calculates insulin dosing based on the input from the CGM. There are currently three leading algorithms in the field of AP research: model predictive control (MPC), proportional-integral-derivative (PID), and fuzzy logic (FL). All three algorithms have shown high success rates in the field of AP research and are being studied in order to fine-tune control of blood glucose variability. In addition, the development of auxiliary safety systems is being pursued as means of diminishing insulin dosing error (1,2).In making the AP system a highly mobile, outpatient device, consumer electronics and technology such as 3G and Wi-Fi are being leveraged in the development of remote monitoring platforms to assist those living with diabetes. Smartphones may be used as a platform for the AP system, while 3G and Wi-Fi allow physicians to monitor patients with diabetes online from distant locations. However, the usefulness and costs of such remote monitoring features remain a controversial subject in healthcare.The past year has brought notable advancements in the field of AP research. Systems currently in development and testing phases may transform diabetes care from an open-loop, self-monitoring routine to a fully automated closed-loop process where an individual with diabetes may be relieved from paying constant attention to their condition. Past clinical trials are being moved to outpatient studies, representing a significant leap toward a marketable AP consumer product. As current studies are constantly challenging AP technology, new limitations reveal areas for progression, innovation, and improvement. The following articles highlight this year's most significant and intriguing strides toward “closing the loop” and show promise for the future of diabetes care.CLINICAL STUDIESNight glucose control with MD-Logic artificial pancreas in home setting: a single, blind, randomized, crossover trial-interim analysisNimri R1, Muller I1, Atlas E1, Miller S1, Kordonouri O2, Bratina N3, Tsioli C2, Stefanija MA3, Danne T2, Battelino T3,4, Phillip M1,51The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel; 2Diabetes Centre for Children and Adolescents, AUF DER BULT, Kinder- und Jugendkrankenhaus, Hannover, Germany; 3Department of Pediatric Endocrinology, Diabetes and Metabolism, University Medical Centre–University Children's Hospital, Ljubljana, Slovenia; 4Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia; and 5Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, IsraelPediatr Diabetes 2014;15: 91–99This manuscript is also discussed in article on Diabetes Technology and Therapy in the Pediatric Age Group, p. S-103–S-104.BackgroundAP systems have exemplified substantial progress in regulating the blood glucose levels of people with T1DM and reducing nocturnal hypoglycemia (<70 mg/dL) in tightly controlled environments. However, the technology had yet to be tested in a patient's home environment to ensure application to daily life situations.MethodsThe MD-Logic AP (“closed-loop” arm) was compared with sensor-augmented pump therapy (“control” arm) in this two-arm, randomized, single-blind study covering four consecutive nights (11 pm to 7 am) in the patient's home. Fifteen patients were randomly assigned to either Group A (first closed-loop, then control arm) or Group B (vice versa). Boluses were administered 10 minutes prior to each meal. Primary endpoints included the time spent with glucose levels below 70 mg/dL and the percentage of nights where the mean overnight glucose levels were between 90–140 mg/dL.ResultsTime spent with glucose levels below 70 mg/dL was significantly shorter on closed-loop nights than control nights: median and interquartile range 3.8 (0, 11.6) and 48.7 (0.6, 67.9) min, respectively; p=0.0034. A glucose range of 90–140 mg/dL was achieved under closed loop 67% of the time, with control nights experiencing 50% with no statistical difference. The total overnight insulin doses per individual were similar during closed loop (8±3.3 units) to those during control nights (9.2±3.9 units; p=0.19), although significantly more insulin boluses were delivered on the closed-loop nights (3.6±1.8 vs. 2±1.7 units, respectively; p=0.02). No serious adverse events were reported.ConclusionThe feasibility, safety, and efficiency of the MD-Logic AP system in home use demonstrate an improvement over sensor-augmented pump therapy. Interim findings illustrate a significant step forward toward management of T1DM, and the possible implementation of the closed loop as standard overnight treatment.CommentThe study design succeeds in encompassing the spontaneity of real life, allowing patients' choice in alarms, meals, physical activity, and connection time, demonstrating that the transfer of closed-loop systems from protected hospital environments into home use is safe and achievable. While the system requires meal announcements, the 10-minute bolus prior to meals and snacks appears to be a minimally invasive task to the 15 patients' daily routine, as all of them completed protocol. Inclusion of adults and adolescents of both genders provides a diverse study group, as closed-loop control is typically better accomplished in adults but less prominent during the nighttime. Twenty-one out of the 120 nights were dubbed nonvalid (time of active controller less than 67% of night) and excluded from data analysis. Therefore, the quality control between these subgroups is worth further investigation and would add power to the study. Although the use of unmodified sensor data may overestimate the benefit of closed-loop systems when evaluating target range time, this method of collection caters well to daily-life application and raises awareness to the need for sensor and insulin delivery improvement. Overall, this one-center analysis of an ongoing multicenter trial shows promise at providing closed-loop control to a wider range of variability in the lives of people with T1DM. Areas of interest for future studies include expanding the study period past 4 consecutive nights, requiring pump and infusion set replacement and adjustments, but providing an even more realistic view into closed-loop capabilities.Overnight closed-loop insulin delivery in young people with type 1 diabetes: a free-living, randomized clinical trialHovorka R1,2, Elleri D1,2, Thabit H1, Allen JM1,2, Leelarathna L1,3, El-Khairi R1,2, Kumareswaran K1,3, Caldwell K1,2, Calhoun P4, Kollman C4, Murphy HR1, Acerini CL2, Wilinska ME1,2, Nodale M1, Dunger DB1,21Wellcome Trust-Medical Research Council Institute of Metabolic Science; 2Department of Pediatrics, and 3Department of Medicine, University of Cambridge, Cambridge, UK; and 4The Jaeb Center for Health Research, Tampa, FLDiabetes Care 2014;37: 1204–11This manuscript is also discussed in article on Diabetes Technology and Therapy in the Pediatric Age Group, p. S-102.BackgroundTight glycemic control in T1DM is difficult to obtain due to nocturnal hypoglycemia unawareness. The overnight closed-loop delivery system was evaluated for feasibility, safety, and efficacy in free-living youth with T1DM.MethodsSixteen adolescents (aged 12–18 years) with T1DM using continuous subcutaneous insulin infusion were evaluated at home using an overnight intervention arm in an open-label, randomized, crossover study. Overnight insulin delivery was directed by a closed-loop system over a 3-week period; a sensor-augmented therapy was applied on another 3-week period. The order of interventions was random. The primary end point was time when adjusted sensor glucose spent between 70 and 140 mg/dL from 11 pm to 7 am.ResultsClosed-loop was applied constantly over at least 4 hours on 269 nights (80%); sensor data were collected over at least 4 hours on 282 control nights (84%). Closed-loop increased time spent with target glucose range by a median 15% (interquartile range −9 to 43; p<0.001). Mean overnight glucose was reduced by a mean of 14 (SD 58) mg/dL (p<0.001). Time when glucose was <70 mg/dL was low in both groups, but nights with glucose <63 mg/dL for at least 20 minutes were less frequent during closed loop (10% vs. 17%; p=0.01). Despite lower total daily insulin doses by a median of 2.3 (interquartile range −4.7 to 9.3) units (p=0.009), overall 24-hour glucose was reduced by a mean of 9 (SD 41) mg/dL (p=0.006) during closed loop.ConclusionGlucose control was improved while nocturnal hypoglycemia and total daily insulin requirements were reduced. Closed loop increased time spent when glucose was in the target range by a median 15% and reduced both 24-hour and overnight glucose levels by a mean of 14 and 9 mg/dL, respectively. Unsupervised closed-loop control is safe for adolescents with T1DM and feasible for overnight home environments.CommentThe 3-week study duration employing unrestricted meals, exercise, school, and other daily activities provides insight into real-world closed-loop application. Adolescents were able to conduct equipment replacement and adjustment, while resolving connectivity issues on their own. The design required telemonitoring supervision for the first night and optional attention for the following 20 nights, raising awareness for the necessity of such technology with AP prescription. It appears that telemonitoring provides a safety net in the early stages of use, but may benefit less technologically savvy groups more than others. Emphasis on trouble-shooting training before AP use may be more cost-efficient for an adolescent audience. In this study, an 8-day run-in insulin pump optimization phase was conducted before data analysis, creating an effective starting point less reliant on supervision. The study shed light on the tradeoff between tight glycemic control and greater insulin delivery variation. The lack of weekly trends during closed-loop systems shows rapidly occurring and sustainable control. However, since approximately 25% of study days were excluded from analysis—due to replacement of faulty devices, loss of pump connectivity, or sensor data unavailability—more power may be a future area of interest.Use of a “fuzzy logic” controller in a closed-loopMauseth R1, Hirsch IB2, Bollyky J3, Kircher R4, Matheson D4, Sanda S3, Greenbaum C3Departments of 1Pediatrics and 2Endocrinology, University of Washington, Seattle, WA; 3Benaroya Research Institute, Seattle, WA; and 4Dose Safety, Inc., Seattle, WADiabetes Technol Ther 2013;15: 628–33BackgroundIn order for a closed-loop AP system to function properly, the controller algorithm is required to calculate and administer the proper doses of insulin to respond to both current and anticipated glucose levels. A fuzzy logic control that is designed based on expert medical opinion was evaluated.MethodsUsing a highly controlled, bedrest environment, 10 subjects (5 men and 5 women, aged 18–45 years with T1DM competent insulin pump users, HbA1c<9.0%) were enrolled in the pilot study for a period of 24 hours. Meals were unannounced to the controller (small meals of 30 gCHO and moderate meals of 60 gCHO) in order to challenge the system and evaluate the ability to avoid postprandial hypoglycemia. The fuzzy logic controller determined insulin dosing based on the three previous blood glucose readings. Blood samples were drawn every 15 minutes and compared against the Yellow Springs Instrument (YSI) reference.ResultsOf the 10 subjects, 7 completed the study with no hypoglycemic episodes. Two subjects experienced hypoglycemia as a result of overly aggressive dosing and miscalibration, while another subject had both sensors fail 18 hours into the study. For the 7 subjects completing the study, the average blood glucose value was 165 mg/dL and values were within the range of 70–200 mg/dL for 76% of the 24 hours. Blood glucose values for all subjects were within the range of 70–180 mg/dL for 65% of the overall study with zero hypoglycemic events (blood glucose <60 mg/dL) occurring across all patients.ConclusionThe use of a fuzzy logic control algorithm in an AP system can adequately control insulin dosage with the constraint of moderate-sized meals. The controller allows insulin to be adjusted for the subject's needs and may present a viable alternative to model-based controllers.CommentThe fuzzy logic controller kept blood glucose values in the range of 70–200 mg/dL for 76% of trial time, showing good success for a proof-of-concept study even with the high range being at 200 mg/dL. No patient input was required, even at mealtimes with medium-sized meals and moderate exercise. While the success rate is on the low side, the study attempted to tackle many of the real-life challenges (unannounced meals, exercise, etc.) that have proved to be the most cumbersome for the development of the AP system thus far. The range set by the study used a high upper bound (200 mg/dL); however, with the study using unannounced meals, the system demonstrated satisfactory control to maintain glucose levels within this range. The results produced by the study were as good as a pilot study with only 10 subjects. Only 7 subjects completed the study, but as an initial design with the focus on a more outpatient AP system, the study showed successful results. The ultimate goal of the AP system is to be able to function in a real-world setting and to reduce the burden for people with diabetes. This fuzzy logic system took on many of those realistic challenges, and the system showed good versatility in handling those challenges.Day and night closed-loop control in adults with type 1 diabetes: a comparison of two closed-loop algorithms driving continuous subcutaneous insulin infusion versus patient self-managementLuijf YM1, DeVries JH1, Zwinderman K2, Leelarathna L3, Nodale M3, Caldwell K3, Kumareswaran K3, Elleri D3, Allen JM3, Wilinska ME3, Evans ML3, Hovorka R3, Doll W4, Ellmerer M4, Mader JK4, Renard E5, Place J5, Farret A5, Cobelli C6, Del Favero S6, Dalla Man C6, Avogaro A7, Bruttomesso D7, Filippi A7, Scotton R7, Magni L8, Lanzola G8, Di Palma F8, Soru P8, Toffanin C8, De Nicolao G8, Arnolds S9, Benesch C9, Heinemann L91Department of Internal Medicine and 2Department of Statistics, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands; 3Wellcome Trust-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK; 4Endocrinology and Metabolism, Department of Internal Medicine, Medical University of Graz, Graz, Austria; 5Department of Endocrinology, Diabetes, and Nutrition and INSERM Clinical Investigation Center CIC 1001, Centre Hospitalier Regional Universitaire Montpellier and University of Montpellier I, Montpellier, France; 6Department of Information Engineering; 7Department of Medicine, University of Padova, Padova, Italy; 8Department of Computer Engineering and System Sciences, University of Pavia, Pavia, Italy; and 9Profil Institute for Metabolic Research, Neuss, GermanyDiabetes Care 2013;36: 3882–87BackgroundClinical trials of closed-loop (CL) systems have focused on overnight glucose control, and CL efficacy for full-day periods needs to be demonstrated for experimentation in home settings. Luijf et al. compare two validated CL algorithms versus patient self-control with continuous subcutaneous insulin infusion (CSII) in terms of glycemic control for overnight and daytime periods that include meal and exercise challenges.MethodsThis study was a multicenter, randomized, three-arm crossover, open-label trial in 48 individuals with T1DM who used CSII for at least 6 months prior to the study. Blood glucose (BG) was controlled by the MPC algorithm of the Universities of Pavia and Padova with a Safety Supervision Module developed at the Universities of Virginia and California at Santa Barbara (international artificial pancreas [iAP]), by the MPC algorithm of University of Cambridge (CAM), or by patients themselves in open-loop (OL). The study took place during three 23-hour hospital admissions that included meals and exercise. Meal size, exercise duration, and exercise intensity were controlled, and meals were announced to the CL system 15 minutes prior to eating. The main analysis was on an intention-to-treat basis, which included all data, and the secondary analysis was on a per-protocol basis, which excluded times of poor performance of any system component. Main outcome measures included time spent in target (glucose levels between 70 and 144 mg/dL or between 70 and 180 mg/dL after meals).ResultsTime spent in normoglycemia (BG, 70–144 mg/dL) during the nocturnal period (12 am to 8 am), expressed as median (interquartile range), increased from 66.6% (8.3–75%) with OL to 95.8% (73–100%) using the CL algorithm (p<0.05). Median time in hypoglycemia (BG, <70 mg/dL) was reduced from 4.2% (0–21%) in the OL night to 0.0% (0.0–0.0%) in the CL night (p<0.05). Nine hypoglycemic events (<70 mg/dL) were recorded with OL compared with one using CL. The postprandial glycemic excursion was not lower when the CL system was used in comparison with conventional preprandial bolus: time in target (72–180 mg/dL) 58.3% (29.1–87.5%) versus 50.0% (50–100%).ConclusionFull-day CL glucose control can be achieved using currently available sensors and pumps combined with CAM or iAP algorithms. CL and OL glycemic control are comparable, with CL control resulting in less time spent in hypoglycemia at the expense of high mean blood glucose.CommentLuijf et al. evaluated the safety of CL systems in a hospital setting through comparison of CL with standard CSII. The study is a large, multicenter (n=48) experiment that tests both daytime and nighttime control, which incorporated an exercise challenge. The study was limited by the 23-hour duration of trials. Particularly, data from the post exercise period were limited to 3 hours at which point the trial ended. The CL system demonstrated increased safety by producing a significantly lower incidence of hypoglycemia, but the added safety came at the cost of increased hyperglycemia in the CL arms. Overall, the study showed comparable glucose control achieved by CL and OL; however, other studies testing different tunings of MPC showed superiority of CL over OL (3,4). Tuning and personalization of algorithms are factors to be considered when moving to outpatient environments, and the authors bring attention to the fact that the CL algorithms were detuned for this trial in order to enhance safety. Specifically, algorithms were detuned to compensate for glucose sensor inaccuracy, which may have contributed to the suboptimal glucose results. While studies should aim to minimize the duration of hypoglycemia, this raises the question as to whether studies should suffer from limitations in order to reduce hypoglycemia frequency. With the anticipated releases of more accurate CGM technology, the authors expect that detuning to compensate for inaccuracy in blood glucose readings may not be needed in future outpatient trials.Clinical evaluation of an automated artificial pancreas using zone-model predictive control and health monitoring systemHarvey RA1,2, Dassau E1–3, Bevier WC1, Seborg DE1,2, Jovanovic L1,2, Doyle III FJ1–3, Zisser HC1,21Sansum Diabetes Research Institute, Santa Barbara, CA; 2Department of Chemical Engineering, University of California, Santa Barbara, CA; and 3Institute for Collaborative Biotechnologies, University of California–Santa Barbara, Santa Barbara, CADiabetes Technol Ther 2014;16: 348–57BackgroundIn regulating blood glucose levels with an AP system, a zone-model predictive control (zone-MPC) algorithm works to keep the blood glucose levels within a given range of acceptable values rather than at a specific set point. This zone MPC is paired with a parallel health monitoring system (HMS) to improve subject and system safety.MethodsThe closed-loop AP system with the zone-MPC and HMS was tested in 12 patients (8 women, 4 men; age 49.4±10.4 years) with T1DM (duration, 32.7±16.0 years) for a period of 24 hours. Meals were unannounced and the system was tested with moderate exercise and overnight usage. The controller was set to keep the blood glucose levels between 80 and 140 mg/dL and was initialized with the subject's total daily insulin dosage. The HMS predicted if a hypoglycemic episode would occur in the next 15 minutes and if so sent an alert to the caregiver/user.ResultsThe average time in the 70–180 mg/dL range was 80% for the 24-hour session and 92% from 12 am until 7 am. For the 5 hours following dinner and breakfast, the time in the given range was 69% and 61%, respectively. No time was spent in hypoglycemia as defined by below 60 mg/dL, with no safety events occurring. The HMS sent an average of 3.8 alerts per subject for the 24-hour period of testing.ConclusionThe use of the zone-MPC control algorithm and HMS hypoglycemia prevention algorithm regulated blood glucose levels within a safe range and with no adverse events (in any subject) for a 24-hour trial with unannounced meals and moderate exercise. The zone-MPC system kept the blood glucose level around a certain range instead of at an exact set point despite the challenges of unannounced meals and moderate exercise.CommentThe use of the zone-MPC in parallel to the health monitoring system in the AP system was demonstrated in this study with unannounced small to medium-sized meals and moderate exercise. The use of this system with the zone-MPC may present one of the best AP systems for future implementation with the condition that carbohydrate intake at mealtimes stays around 50 g. Control around meal times still needs to be improved in the model since 69% and 61% of the glycemic values were within the range of 70–180 mg/dL for the 5 hours following dinner and breakfast, respectively. The study suggests that in order to use a truly closed-loop system without having to bolus for meals, a cap of 50 gCHO may have to exist for the amount of carbohydrates consumed at each meal, as carbohydrates in excess of this amount produced more negative results. More education about nutritional information and food portioning along with this closed-loop system may prove to be a good solution for many living with diabetes. This may not prove to be a good solution for all, and individuals with diabetes who tend to eat in excess of 50 gCHO may simply have to be more involved in their therapy than those who can better control their meal size. The controller design in this study demonstrated the ability to attenuate faster and to also minimize the number of overnight hypoglycemic alerts while helping with user compliance. The study shows that a fully closed-loop design (unannounced meals and unannounced exercise) is a possibility for outpatient AP systems in the future as long as the users recognize the limitations that it comes with by not consuming excess carbohydrates. The HMS system provides a valuable auxiliary system to help prevent adverse events from occurring, and the pairing of the zone-MPC and HMS systems has produced some of the best results in AP studies thus far. Future studies should evaluate this system in a home setting and should work to further minimize the need for carbohydrate supplementations during nighttime.Feasibility of outpatient fully integrated closed-loop controlKovatchev BP1, Renard E2, Cobelli C3, Zisser HC4, Keith-Hynes P1, Anderson SM1, Brown SA1, Chernavvsky DR1, Breton MD1, Farret A2, Pelletier MJ2, Place J2, Bruttomesso D3, Del Favero S3, Visentin R3, Filippi A3, Scotton R3, Avogaro A3, Doyle III FJ51Department of Psychiatry and Neurobehavioral Sciences, Center for Diabetes Technology, and Division of Endocrinology, Department of Medicine, University of Virginia, Charlottesville, VA; 2Montpellier University Hospital, Department of Endocrinology, Diabetes, and Nutrition, INSERM Clinical Investigation Centre 1001, Institute of Functional Genomics, CNRS UMR 5203, INSERM U661, University of Montpellier 1, Montpellier, France; 3Department of Information Engineering and Unit of Metabolic Disease, Department of Internal Medicine, University of Padova, Padova, Italy; 4Sansum Diabetes Research Institute, Santa Barbara, CA; and 5University of California–Santa Barbara, Santa Barbara, CADiabetes Care 2013;36: 1851–58BackgroundIn order to make an AP system commercially available, studies of the system have to first be performed in clinical settings and with improvements the trials can be moved to outpatient studies. The Diabetes Assistant (DiAs) system provides the communication link between the continuous glucose monitor (CGM), insulin pump, and the algorithm that is run on the mobile device.MethodsThe study involved 20 subjects (ages 21–65 years) with T1DM and was performed at 4 clinical sites. Subjects were required to have a prestudy HbA1c of 6–9% and be competent insulin pump users without other major complications. The outpatient study was run as an open-loop system for the first 14 hours of the study and then switched to a closed loop for the remaining 28 hours, and was closely monitored by the researchers via 3G and Wi-Fi. Meals were announced and alerts were sent to warn of predicted future hypoglycemia.ResultsThe system functioned and communicated properly for 274 hours in the open-loop segment and 533.5 hours in the closed-loop segment, representing a combined 807.5 hours of proper function (97.7% of time from admission to discharge). This exceeded the set goal of proper control for 80% of the total time while minimizing glycemic episodes. Blood glucose levels remained within the range of 70–180 mg/dL from 7 am until 11 pm for 68% of the time under closed loop and within the same range from 11 pm until 7 am for 80% of the open-loop segment and 72% of the closed-loop segment.ConclusionThe use of an outpatient AP system is a step toward making the AP system commercially available since it has been shown that the closed-loop system can function and communicate properly in outpatient studies where meals were announced. This study demonstrates that it is feasible to use a closed-loop system to control blood glucose levels outside of a clinical setting and for subjects to go through real-life routines while maintaining normal blood glucose values due to the AP system. The study also demonstrates that smartphones may have a future in being a platform for the AP system.CommentTo allow individuals with diabetes to conveniently use the AP system, the design has to be studied first in clinical trials and then in outpatient studies before it can be made commercially available. This study examined the use of consumer electronics such as cell phones as platforms to control the AP system. While the subjects were very closely monitored by medical personnel, the move to outpatient trials with a mobile system is a good step in the right direction for the future of the AP. There are also limitations to the use of consumer electronics that have to be considered in the selection of the device such as cross-platform talk, battery life, user interface, security, functionality, etc. In the modern era, the majority of the population already carries a cell phone with them, and so this system with the control of the AP integrated into the cell phone would simplify the amount of equipment that individuals with diabetes have to carry. Health professionals can also monitor their patients via Wi-Fi and 3G even from distant locations, although there remains the issue of what happens if the phone's battery dies or the person with diabetes forgets his/her cell phone. Portability is a necessity for having an outpatient AP design, and in the world of consumer electronics there are many limitations regarding design and selection that need to be" @default.
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