Portal de Periódicos da CAPES

Closing the Loop

2017; Mary Ann Liebert, Inc.; Volume: 19; Issue: S1 Linguagem: Inglês

10.1089/dia.2017.2504

1557-8593

Revital Nimri, Nathan Murray, Alexander Ochs, Jordan E. Pinsker, Eyal Dassau,

Diet and metabolism studies

Diabetes Technology & TherapeuticsVol. 19, No. S1 Original ArticlesFree AccessClosing the LoopRevital Nimri, Nathan Murray, Alexander Ochs, Jordan E. Pinsker, and Eyal DassauRevital NimriDiabetes 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, Nathan MurrayWilliam Sansum Diabetes Center, Santa Barbara, CA.Search for more papers by this author, Alexander OchsWilliam Sansum Diabetes Center, Santa Barbara, CA.Search for more papers by this author, Jordan E. PinskerWilliam Sansum Diabetes Center, Santa Barbara, CA.Search for more papers by this author, and Eyal DassauWilliam Sansum Diabetes Center, Santa Barbara, CA.Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.Search for more papers by this authorPublished Online:1 Feb 2017https://doi.org/10.1089/dia.2017.2504AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail IntroductionManagement of type 1 diabetes (T1D) remains a major challenge for health-care systems and a full-time commitment for those with the condition. Devastating complications related to T1D can be reduced or postponed through tight blood glucose control. However, increased hypoglycemia risk, limitations with glucose monitoring, and difficulties with insulin administration technologies make this task difficult to attain. One of the main reason is the current artificial pancreas (AP) systems technologies (pump and sensor therapy) necessitate user involvement that still requires significant effort, compliance, and some medical decision-making capability. An automated insulin delivery system (closed-loop or AP) can close this gap, but additional development is still needed. AP links an insulin pump and glucose sensor via novel computerized control algorithms, which command insulin delivery in response to real-time sensor data or prediction of the glucose trend. These systems have the potential to release patients and their caregivers from some of the burden of daily treatment of a chronic disease and improve their metabolic control. Much progression of the AP has been seen in recent years with several groups around the world focusing in testing this novel technology with different control strategies. The first studies have shown the safety and efficacy of the technology in controlling blood glucose levels. Based on these studies, AP systems are gaining recognition as the next progression of insulin management platforms for patients with type 1 diabetes. In the last 5 years, closed-loop studies are focusing on testing the system in patient's homes in daily life conditions, for day-and-night use, with longer study duration, and a larger number of patients accumulating the data needed for regulation and reimbursement of AP.This year's research contained large-scale, multicenter, outpatient studies and very promising results were obtained. This article aims to highlight the most important achievement in AP research in the past year.Key Articles Reviewed for the ArticleRandomized crossover comparison of personalized MPC and PID control algorithms for the artificial pancreasPinsker JE, Lee JB, Dassau E, Seborg DE, Bradley PK, Gondhalekar R, Bevier WC, Huyett L, Zisser HC, Doyle III FJDiabetes Care 2016;39: 1135–1142Randomized summer camp crossover trial in 5- to 9-year-old children: outpatient wearable artificial pancreas is feasible and safeDel Favero S, Boscari F, Messori M, Rabbone I, Bonfanti R, Sabbion A, Iafusco D, Schiaffini R, Visentin R, Calore R, Moncada YL, Galasso S, Galderisi A, Vallone V, Di Palma F, Losiouk E, Lanzola G, Tinti D, Rigamonti A, Marigliano M, Zanfardino A, Rapini N, Avogaro A, Chernavvsky D, Magni L, Cobelli C, Bruttomesso DDiabetes Care 2016;39: 1180–1185Mitigating meal-related glycemic excursions in an insulin-sparing manner during closed-loop insulin delivery: the beneficial effects of adjunctive pramlintide and liraglutideSherr JL, Patel NS, Michaud CI, Palau-Collazo MM, Van Name MA, Tamborlane WV, Cengiz E, Carria LR, Tichy EM, Weinzimer SADiabetes Care 2016;39: 1127–1134Day-and-night closed-loop glucose control in patients with type 1 diabetes under free-living conditions: results of a single-arm 1-month experience compared with a previously reported feasibility study of evening and night at homeRenard E, Farret A, Kropff J, Bruttomesso D, Messori M, Place J, Visentin R, Calore R, Toffanin C, Di Palma F, Lanzola G, Magni P, Boscari F, Galasso S, Avogaro A, Keith-Hynes P, Kovatchev B, Del Favero S, Cobelli C, Magni L, DeVries JH; for the AP@home ConsortiumDiabetes Care 2016;39: 1151–1160A simplified semi-quantitative meal bolus strategy combined with single- and dual-hormone closed-loop delivery in patients with type 1 diabetes: a pilot studyGingras V, Haidar A, Messier V, Legault L, Ladouceur M, Rabasa-Lhoret RDiabetes Technol Ther 2016;18: 464–471Automated hybrid closed-loop control with a proportional-integral-derivative based system in adolescents and adults with type 1 diabetes: individualizing settings for optimal performanceLy TT, Weinzimer SA, Maahs DM, Sherr JL, Roy A, Grosman B, Cantwell M, Kurtz N, Carria L, Messer L, von Eyben R, Buckingham BAPediatr Diabetes 2016;[Epub ahead of print] DOI 10.1111/pedi.12399Variability of insulin requirements over 12 weeks of closed-loop insulin delivery in adults with type 1 diabetesRuan Y, Thabit H, Leelarathna L, Hartnell S, Willinska ME, Dellweg S, Benesch C, Mader JK, Holzer M, Kojzar H, Evans ML, Pieber TR, Arnolds S, Hovorka R; on behalf of the AP@home ConsortiumDiabetes Care 2016;39: 830–832Day-and-night hybrid closed-loop insulin delivery in adolescents with type 1 diabetes: a free-living, randomized clinical trialTauschmann M, Allen JM, Wilinska ME, Thabit H, Stewart Z, Cheng P, Kollman C, Acerini CL, Dunger DB, Hovorka RDiabetes Care 2016;39: 1168–11742 month evening and night closed-loop glucose control in patients with type 1 diabetes under free-living conditions: a randomised crossover trialKropff J, Del Favero S, Place J, Toffanin C, Visentin R, Monaro M, Messori M, Di Palma F, Lanzola G, Farret A, Boscari F, Galasso S, Magni P, Avogaro A, Keith-Hynes P, Kovatchev BP, Bruttomesso D, Cobelli C, DeVries JH, Renard E, Magni L; for the AP@home consortiumLancet Diabetes Endocrinol 2015;3: 939–947Home use of an artificial beta cell in type 1 diabetesThabit H, Tauschmann M, Allen JM, Leelarathna L, Hartnell S, Wilinska ME, Acerini CL, Dellweg S, Benesch C, Heinemann L, Mader JK, Holzer M, Kojzar H, Exall J, Yong J, Pichierri J, Barnard KD, Kollman C, Cheng P, Hindmarsh PC, Campbell FM, Arnolds S, Pieber TR, Evans ML, Dunger DB, Hovorka R; for the APCam Consortium and AP@home ConsortiumN Engl J Med 2015;373: 2129–2140Adjustment of open-loop settings to improve closed-loop results in type 1 diabetes: a multicenter randomized trialDassau E, Brown SA, Basu A, Pinsker JE, Kudva YC, Gondhalekar R, Patek S, Lv D, Schiavon M, Lee JB, Dalla Man C, Hinshaw L, Castorino K, Mallad A, Dadlani V, McCrady-Spitzer SK, McElwee-Malloy M, Wakeman CA, Bevier WC, Bradley PK, Kovatchev B, Cobelli C, Zisser HC, Doyle III FJJ Clin Endocrinol Metab 2015;100: 3878–3886Multinational home use of closed-loop control is safe and effectiveAnderson SM, Raghinaru D, Pinsker JE, Boscari F, Renard E, Buckingham BA, Nimri R, Doyle III FJ, Brown SA, Keith-Hynes P, Breton MD, Chernavvsky D, Bevier WC, Bradley PK, Bruttomesso D, Del Favero S, Calore R, Cobelli C, Avogaro A, Farret A, Place J, Ly TT, Shanmugham S, Phillip M, Dassau E, Dasanayake IS, Kollman C, Lum JW, Beck RW, Kovatchev B; for the Control to Range Study GroupDiabetes Care 2016;39: 1143–1150Reduced worries of hypoglycaemia, high satisfaction, and increased perceived ease of use after experiencing four nights of MD-Logic artificial pancreas at home (DREAM4)Ziegler C, Liberman A, Nimri R, Muller I, Klemenčič S, Bratina N, Bläsig S, Remus K, Phillip M, Battelino T, Kordonouri O, Danne T, LangeJ Diabetes Res 2015;2015: 590308Stress testing of an artificial pancreas system with pizza and exercise leads to improvements in the system's fuzzy logic controllerMauseth R, Lord SM, Hirsch IB, Kircher RC, Matheson DP, Greenbaum CJJ Diabetes Sci Technol 2015;9: 1253–1259Day and night glycaemic control with a bionic pancreas versus conventional insulin pump therapy in preadolescent children with type 1 diabetes: a randomised crossover trialRussell SJ, Hillard MA, Balliro C, Magyar KL, Selagamsetty R, Sinha M, Grennan K, Mondesir D, Ehklaspour L, Zheng H, Damiano ER, El-Khatib FHLancet Diabetes Endocrinol 2016;4: 233–243Randomized crossover comparison of personalized MPC and PID control algorithms for the artificial pancreasPinsker JE1, Lee JB1,2, Dassau E1,2,3, Seborg DE1,2, Bradley PK1, Gondhalekar R1,2, Bevier WC1, Huyett L1,2, Zisser HC1,2, Doyle FJIII1,2,31William Sansum Diabetes Center, Santa Barbara, CA2Department of Chemical Engineering, University of California, Santa Barbara, CA3John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MADiabetes Care 2016;39: 1135–1142BackgroundTwo widely used artificial pancreas (AP) control algorithms are the model predictive control (MPC) and the proportional integral derivative (PID) algorithms. Numerous studies across different settings have used both algorithms with positive results, but there has never been a randomized clinical trial directly comparing the effectiveness of each. This study aimed to compare individual-personalized MPC and PID controls under nonideal but comparable clinical conditions.MethodsAfter a pilot safety and feasibility study (n=10), closed-loop control (CLC) was conducted and evaluated in a randomized, crossover trial that included 20 additional adults with type 1 diabetes. Both the MPC and PID algorithms were compared during supervised 27.5 hour CLC sessions. The algorithms were tested by evaluating control performance following a 65 g dinner, 50 g breakfast, and unannounced 65 g lunch. The announced breakfast and dinner meals were accompanied with the appropriate boluses. The primary outcome was time in the glucose range 70–180 mg/dL (3.9 to 10 mmol/L).ResultsThe primary outcome was better for MPC than PID as mean time in the 70–180 mg/dL range was greater (74.4% compared to 63.7%, P=0.020). MPC also produced lower mean glucose than PID for the entire trial duration (138 vs. 160 mg/dL, P=0.012) and 5 hours after the unannounced 65 g meal (181 vs. 220 mg/dL, P=0.019). No significant difference was found for time with glucose levels less than 70 mg/dL during the trial period.ConclusionThis study acted as the first to comprehensively compare MPC and PID control algorithms. It was found that MPC performed particularly well, achieving nearly 75% time in the target range even when an unannounced meal was included. While PID provided safe and effective glucose management, MPC performed as well as, or better than, PID in all metrics.CommentThere are several types of control algorithms for AP systems. The question of which technology is ideal probably depends on the expected outcomes. Comparison between the different controllers are difficult to obtain from existing studies as a result of differences in the studies design, intended use, and endpoint evaluation. Furthermore, direct comparisons between existing AP algorithms had not yet been studied prior to this study. Finding differences in efficacy between two algorithms is significant for developers and future studies should continue to examine algorithms that are currently used in AP systems. The study design included an unannounced 65 g lunch to simulate missed bolus and test algorithm robustness to this common event. Limiting factors include a single site and the duration of the study, as well as the lack of free-living conditions and exercise. It will be interesting to see an outpatient study that compares the two main algorithms for AP in free-living conditions.Randomized summer camp crossover trial in 5- to 9-year-old children: outpatient wearable artificial pancreas is feasible and safeDel Favero S1, Boscari F2, Messori M3, Rabbone I4, Bonfanti R5, Sabbion A6, Iafusco D7, Schiaffini R8, Visentin R1, Calore R1, Moncada YL1, Galasso S2, Galderisi A9, Vallone V2, Di Palma F3, Losiouk E10, Lanzola G10, Tinti D4, Rigamonti A5, Marigliano M6, Zanfardino A7, Rapini N11, Avogaro A2, Chernavvsky D12, Magni L3, Cobelli C1, Bruttomesso D21Department of Information Engineering, University of Padua, Padua, Italy2Unit of Metabolic Diseases, Department of Internal Medicine, University of Padua, Padua, Italy3Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy4Department of Pediatrics, University of Turin, Turin, Italy5Pediatric Department and Diabetes Research Institute, Scientific Institute, Hospital San Raffaele, Milan, Italy6Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, Azienda Ospedaliera Universitaria Integrata of Verona, Verona, Italy7Department of Pediatrics, Second University of Naples, Naples, Italy8Unit of Endocrinology and Diabetes, Bambino Gesu Children's Hospital, Rome, Italy9Department of Women's and Children's Health, University of Padua, Padua, Italy10Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy11Pediatric Diabetology Unit, Policlinico di Tor Vergata, University of Rome Tor Vergata, Rome, Italy12Center for Diabetes Technology, University of Virginia, Charlottesville, VADiabetes Care 2016;39: 1180–1185.BackgroundParents of young children with type 1 diabetes often struggle to manage their children's blood glucose (BG) levels successfully. The artificial pancreas (AP) could provide a safe and effective solution that would reduce the burden of treatment for both the children and their parents. In this study, a children-specific version of the modular model predictive control (MMPC) algorithm was tested in 5- to 9-year-old children by the Pediatric Artificial Pancreas (PedArPan) during a supervised camp with parents present.MethodsAn outpatient, randomized, open-labeled, crossover trial was completed by 30 children with type 1 diabetes, aged 5–9 and with a median of 7.6 years and a standard deviation (SD) of 1.2 years. Seventy-two hours of parent-managed sensor-augmented pump (SAP) use was compared to 72 hours of AP management, with a 24 hour washout period in between. Activities during the camp involved static, school-like activities in the morning and 90–120 min of structured moderate to high intensity exercise in the afternoon. Meals were given at constant intervals and snack was provided before bed and exercise.ResultsTime spent in hypoglycemia overnight was reduced with the AP compared to the SAP, median (25th–75th percentiles): 0.0% (0.0–2.2) vs. 2.2% (0.0–12.3) (P=0.002), without a significant difference in mean time spent in target range: 56.0% (SD 22.5) vs. 59.7% (21.2) (P=0.430), but there was an increased mean glucose 173 mg/dL (36) vs. 150 mg/dL (39) (P=0.002). Overall, the AP was three times as effective at keeping participants out of hypoglycemia (P<0.001), but this came at the cost of a decreased time spent in the target range, 56.8% (13.5) vs. 63.1% (11.0) (P=0.022) and increased mean glucose 169 mg/dL (23) vs. 147 mg/dL (23) (P<0.001).ConclusionThe findings of the outpatient single-hormone AP trial in a population of preadolescent children showed that the AP is feasible and safe in young children, similar to findings on adolescent and adult usage of AP systems. Overall, the incidence of hypoglycemia was significantly reduced, especially at night, but at the cost of lower in-range blood glucose levels and higher mean blood glucose levels. The authors point out that the efficacy of the AP system used in the study was reduced by prudent tuning of the algorithm for safety reasons, since this was their first study of AP in young children and is expected to be improved by using the data from this study.CommentAn effective AP holds significant implications towards preadolescent children with type 1 diabetes who are dependent on guardians/caretakers for treatment. This is also the population of caregivers that have the greatest concerns related to hypoglycemia. This fear of hypoglycemia translates to negative impact on parental health and quality of life and sometimes parents choose hypoglycemia avoidance strategies at the expense of good glycemic control. Although closed-loop outpatient trials are not uncommon, there had been little literature on age groups outside of adolescents and adults. This study shows that it is possible to significantly reduce the risk of hypoglycemia in this age group however, with a trade-off of an elevated mean blood glucose levels and increased time spent out-of-range by participants. Future improvements of the algorithm's blood glucose regulation may also help to limit hyperglycemia as well. Further studies should seek longer durations in preadolescents and aim to reduce the risk of hypo- and hyperglycemia concurrently.Mitigating meal-related glycemic excursions in an insulin-sparing manner during closed-loop insulin delivery: the beneficial effects of adjunctive pramlintide and liraglutideSherr JL1, Patel NS1, Michaud CI1, Palau-Collazo MM1, Van Name MA1, Tamborlane WV1, Cengiz E1, Carria LR1, Tichy EM1, Weinzimer SA11Yale School of Medicine, New Haven, CTDiabetes Care 2016;39: 1127–1134.BackgroundOne of the most challenging tasks of diabetes management in general, and closed-loop (CL) systems in particular, is the treatment of meal and postprandial excursions. While during the night closed-loop systems perform well, during the day time, with food consumption, these systems still struggle to maintain euglycemia. Therefore, different strategies are being evaluated as adjunctive therapy to reduce postprandial hyperglycemia. This study evaluates the postprandial glucose excursions with use of pramlintide or liraglutide.MethodsThe authors performed two CL studies. Study A included 10 subjects aged 16–23 years with average hemoglobin A1c of 7.2% evaluating the use of pramlintide. Study B included 11 subjects aged 18–27 years with average A1c of 7.5% evaluating the use of liraglutide. In both studies, subjects completed two sessions of CL control for 24 hours each. The first session was baseline assessment with no adjuvant medication followed by 3–4 week outpatient dose escalation of the assigned adjuvant therapy. At the end of this period, subjects completed the second CL session with 60 μg of pramlintide in study A and 1.8 mg liraglutide in study B. The timing and content of meals during CL were identical in both experiments and meals were unannounced.ResultsThe use of pramlintide during CL control was associated with a 39% reduction in the peak increment in postprandial glucose levels (PG), significant delay in time to PG (2.6±0.9 h with use of pramlintide compared to 1.6±0.5 without) and reduction in postmeal incremental PG area under the curve (AUC). The use of liraglutide also led to significant reductions in PG excursions and incremental PG AUC, although less than pramlintide. No change was found in time to PG with a 28% reduction in prandial insulin delivery. Outpatient liraglutide therapy led to approximately 5% loss in body weight and 26% reduction in total daily insulin dose. These changes were greater than those observed with pramlintide outpatient use.ConclusionsBoth adjunctive pramlintide and liraglutide were found to reduce postprandial hyperglycemia during CL control. The effect was more pronounced with pramlintide, but only liraglutide resulted in weight loss and less insulin usage. Longer term studies are needed on these adjunctive medications in long-term CL outpatient situations.CommentThere is a need to explore ways to reduce postprandial hyperglycemia during CL operation in order to create a full CL control without meal announcement. In that way, the CL will be fully automated and lessen the need for patient inputs. In a previous trial the authors studied CL control with 30 μg of pramlintide and showed a benefit of only 22% and 26% in reducing peak PG excursions and incremental PG AUC respectively and little effect in post breakfast glucose excursions (1). The pre-escalation of the pramlintide dose to a full effective dose caused an additional benefit of approximately 13% in the previously mentioned postprandial parameters and significant lowering of postbreakfast glucose excursion. Nevertheless, the cost of adding pramlintide to CL control is the need to add an injection before each meal. This was also the main motivation of the authors to test liraglutide that can be used once a day or in once weekly injections. Nevertheless, its effect on postprandial glucose excursions was found to be of lesser extent than pramlintide. The comparison between the glycemic control of the two medications is hindered by the fact that the set point of the CL system was different (the target was higher during pramlintide use) and less aggressive insulin delivery was given during the liraglutide use because of reduced total daily dose of insulin entered for the initiation of the CL control. In addition, the studies were not powered to provide direct comparison between the two medications used. Therefore, additional inpatient and outpatient studies are needed to evaluate the full efficacy and safety of these two adjuvants for CL control. A significant reduction in weight and insulin requirements were observed during the open-loop short term use of liraglutide. This interesting finding may have an important implication for treatment of overweight subjects with type 1 diabetes.Day-and-night closed-loop glucose control in patients with type 1 diabetes under free-living conditions: results of a single-arm 1-month experience compared with a previously reported feasibility study of evening and night at homeRenard E1, Farret A1, Kropff J2, Bruttomesso D3, Messori M4, Place J1, Visentin R5, Calore R5, Toffanin C4, Di Palma F4, Lanzola G6, Magni P6, Boscari F3, Galasso S3, Avogaro A3, Keith-Hynes P7, Kovatchev B7, Del Favero S5, Cobelli C5, Magni L4, DeVries JH2; for the AP@home Consortium1Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital; INSERM Clinical Investigation Centre 1411; Institute of Functional Genomics, CNRS UMR 5203, INSERM U1191, University of Montpellier, Montpellier, France2Department of Endocrinology, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands3Unit of Metabolic Diseases, Department of Internal Medicine, University of Padova, Padova, Italy4Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy5Department of Information Engineering, University of Padova, Padova, Italy6Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy7Center for Diabetes Technology, University of Virginia, Charlottesville, VADiabetes Care 2016;39: 1151–1160BackgroundIn a past study, the effects of an artificial pancreas (AP) under free-living conditions were investigated during evening and night (E/N-AP) in patients with type 1 diabetes. This study uses the same E/N-AP cohort group and extends the AP usage by another four weeks while testing day-and-night (D/N-AP) use.MethodsTwenty out of 32 adult patients with T1D that had previously completed a randomized crossover study comparing two month E/N-AP with two month sensor augmented pump (SAP) now volunteered for a one month uncontrolled extension phase of day-and-night closed-loop use. The AP use was monitored and managed by a model predictive control algorithm run from a modified smartphone wirelessly connected to an insulin pump and continuous glucose monitor (CGM). The data analysis was done by the intention-to-treat method and the primary endpoint was the proportion of CGM time spent in the target range (3.9–10.0 mmol/L) over 24 h.ResultsTime spent in the target range (mean ± SD, %) was similar over 24 h with D/N-AP compared to the past E/N-AP study: 64.7±7.6 vs. 63.6±9.9 (P=0.79), and both spent longer in range than SAP: 59.7±9.6 (P=0.01 and P=0.06, respectively). Time spent in hypoglycemia below 3.9 mmol/L was similarly and significantly reduced by D/N-AP and E/N-AP vs. SAP (both P<0.001). Blood glucose variability measured by SD (mmol/L) was lower with D/N-AP vs. E/N-AP during whole daytime: 3.2±0.6 vs. 3.4±0.7 (P=0.003), morning: 2.7±0.5 vs. 3.1±0.5 (P=0.02), and afternoon: 3.3 ±0.6 vs. 3.5±0.8 (P=0.07), and was lower with D/N-AP vs. SAP over 24 h: 3.1±0.5 vs. 3.3±0.6 (P=0.049). Overall insulin delivery (IU) during the 24 h period was higher with D/N-AP and SAP than with E/N-AP: 40.6 ±15.5 and 42.3±15.5 vs. 36.6±11.6 (P=0.03 and P=0.0004, respectively).ConclusionsD/N-AP and E/N-AP both achieved better glucose control than SAP therapy under free-living conditions. Although time in the different glycemic ranges was similar between D/N-AP and E/N-AP, D/N-AP was found to further reduce glucose variability.CommentThis study addressed an important issue of add on value of day-and-night closed-loop vs. evening and night use only. Having automated blood glucose (BG) control overnight is especially relevant since there are significant risks towards having hypoglycemic events while sleeping, although the ultimate goal of AP systems is still 24/7, day-and-night functionality. The results of this study are somewhat surprising. The glycemic control for day-and-night use of outpatient closed-loop control was similar to that of evening and night use only. The add on value of 24 hours closed-loop use was small and included reduced mild hypoglycemia occurrence and glucose variability. This may point out the significance of overnight control as first and attainable goal for AP systems or to the fact that the controller was not active enough during the day. The major limitation of this study was the lack of control group of evening and night use only during the extension period. Therefore, the conclusions of this study may be biased. Larger, randomized studies will more accurately demonstrate the differences in efficacy and safety between E/N-AP and D/N-AP.A simplified semi-quantitative meal bolus strategy combined with single- and dual-hormone closed-loop delivery in patients with type 1 diabetes: a pilot studyGingras V1,2, Haidar A1,3, Messier V1, Legault L4, Ladouceur M5, Rabasa-Lhoret R1,2,3,5,61Institut de Recherches Cliniques de Montréal, Montreal, Canada2Department of Nutrition, Université de Montréal, Montreal, Canada3Division of Experimental Medicine, McGill University, Montreal, Canada4Montreal Children's Hospital, McGill University Health Center, Montreal, Canada5Research Center of the Université de Montréal Hospital Center, Montreal, Canada6Montreal Diabetes Research Center, Montreal, CanadaDiabetes Technol Ther 2016;18: 464–471.BackgroundBoth single- and dual-hormone closed-loop systems have the potential of improving glycemic control and mitigating the hardship of regular carbohydrate counting. This paper looks at whether a simplification of meal insulin calculations would compromise glycemic control in patients with type 1 diabetes using single and dual hormone closed-loop systems.MethodsA randomized outpatient pilot trial compared a single-hormone closed-loop system with accurate carbohydrate boluses, the same using a simplified meal bolus strategy, a dual-hormone system with accurate carbohydrate boluses, and the same using the simplified meal bolus strategy. The accurate carbohydrate boluses were calculated from each participant's carbohydrate meal content estimation whereas the simplified strategy involved participant classification of meals based on carb load: snack, regular, large, or very large carb meals. Each participant also spent time on a sensor-augmented therapy as a control. Basal insulin delivery was more aggressive in the simplified bolus strategy. The primary outcome was mean sensor glucose level over a 15 h daytime period.ResultsTwelve adult subjects aged 48.2±16.0 years and had A1c of 7.4%±0.9% were recruited to the study in order to compare the two bolus strategies during single- and dual-hormone closed-loop delivery. A similar mean sensor glucose level (15 h) was achieved with the carbohydrate-matched boluses and simplified strategy using single-hormone (median [interquartile]: 7.6 [7.2–8.1] vs. 8.0 [7.0–8.6] mmol/L; P=0.90) and dual-hormone closed-loop systems (7.6 [6.7–9.1] vs. 7.0 [6.4–8.2] mmol/L; P=0.08). Exploratory analyses showed that, as compared with sensor-augmented pump therapy, there was an increased time spent in hypoglycemia with the simplified strategy but not with the carbohydrate-matched boluses.ConclusionsAlthough the simplified meal bolus strategy left subjects at an increased risk of hypoglycemia, this strategy has the potential to reduce the carbohydrate-counting burden in patients with type 1 diabetes while acceptably managing glucose levels. Longer outpatient studies with an improved algorithm are needed.CommentThis pilot study represents initial steps towards improving artificial pancreas algorithms to incorporate meal boluses and further alleviate patient carb-counting burden. Ultimately meal boluses should be incorporated into autonomous glycemic control so that everything is run through the AP. Their use of aggressive basal insulin delivery in the simplified bolus group was effective in both single- and dual-hormone devices in reaching lower mean blood glucose levels and less hyperglycemia, but at the cost of more hypoglycemia. Larger multicenter patient studies and algorithm improvement are crucial for more validity in this area. This study still demonstrates the