Basal Insulin Infusion Rate Research Articles

Reducing exercise-related hypoglycemia in automated insulin delivery with reinforcement learning

Exercise is an important component for glucose management in type 1 diabetes, but remains challenging for automated insulin delivery systems as altered glucose dynamics are difficult to model explicitly. Glucose monitoring data might enable data-driven approaches for learning these dynamics implicitly. We propose combining model predictive control with a reinforcement learning component to adjust basal insulin infusion rates for exercise. We train our model on a variety of exercise scenarios and demonstrate improved glucose control using a generically trained model. We further improve performance by personalizing the model with a small number of additional individual-specific training episodes.

Prospective External Validation of an Algorithm Predicting Hourly Basal Insulin Infusion Rates from Characteristics of Patients with Type 1 Diabetes Treated with Insulin Pumps.

We previously published an algorithm predicting 24 h basal insulin infusion profiles in insulin pump-treated subjects with type 1 diabetes profiles from six subject characteristics. This algorithm was to be externally validated in an independent environment and patient population. Thirty-two patients with pump-treated type diabetes were switched to their individually algorithm-derived basal insulin infusion profile, and the appropriateness of fasting glycemic control was scrutinized by means of a supervised 24 h fast. Primary endpoint was appropriate fasting glycemic control according to pre-defined criteria in at least 80% of the cohort. In 24 out of 32 patients switching to the algorithm-derived basal insulin infusion rate and undergoing a 24-h fasting period, appropriate glycemic control was achieved (=75%, lower than the pre-defined threshold of 80%), two patients discontinued the fast due to hyperglycemia, and six finished the fasting period, however, with inappropriate fasting glycemic control (entirely due to hyperglycemic episodes). There were no obvious differences in baseline characteristics between those with appropriate vs. inappropriate fasting glycemic control on the basal insulin infusion rate provided by the algorithm. In conclusion, when testing fasting glycemic control with an algorithm-derived individual basal insulin infusion profile during a 24 h fasting period in a cohort unrelated in terms of the hospital environment and catchment area, the success rate was lower than a pre-defined threshold for concluding utility of this algorithm. Therefore, applying this algorithm in order to initiate or optimize basal insulin infusion profiles in type 1 diabetes cannot be generally recommended.

Nutrient Uptake by the Hindlimb of Growing Pigs Treated with Porcine Somatotropin and Insulin

The shift in nutrient partitioning induced by porcine somatotropin (pST) is accompanied by a decrease in insulin sensitivity for whole-body glucose uptake. The relative contribution of metabolic changes in the hindlimb was investigated in eight pigs (55 kg) that had received recombinant pST (120 μg/kg) or excipient (control) for 7 d. Uptake of metabolites by the hindlimb was measured under basal conditions and during hyperinsulinemic-euglycemic clamps at low [14 ng/(kg·min)] and high [360 ng/(kg·min)] insulin infusion rates. Dextrose infusion rate required to maintain euglycemia was used as an index of whole-body glucose uptake in response to exogenous insulin. Effects of pST on hindlimb and whole-body glucose uptake were evident only at physiological levels of insulin (basal and low insulin infusion rate). During the low rate of insulin infusion, dextrose infusion rate was 79% lower for pST-treated pigs and glucose uptake by the hindlimb was 59% lower compared with control pigs. The decrease in glucose uptake by the hindlimb was entirely accounted for by the estimated reduction in glucose utilization by adipose tissue of the hindlimb. Glucose:oxygen quotients were reduced during basal (57%) and low insulin infusion (63%) with pST treatment, indicating a change in the pattern of substrate utilization. This is consistent with the concept that pST directs nutrients away from adipose and towards muscle growth by altering the response of tissues to homeostatic signals such as insulin.

791-P: Clinical Data of a New Insulin Micropump System in Children with Type 1 Diabetes Mellitus (T1DM)

Background: To maintain glucose control in T1DM is especially difficult in children that have unpredictable amounts of physical activity and broad eating patterns. Advances in diabetes technology include Continuous Subcutaneous Insulin Infusion (CSII) and patch/tubeless micropumps are newer options available. Patch pumps are free of tubing, small and lightweight. We aimed to report the initial clinical effect of an insulin micropump therapy in a cohort of children with T1DM. Method: We studied pediatric patients (5-years old) , converting from multiple daily injections of insulin (MDI) to Roche Accu-chek Solo tubeless micropump system. Nine children (5 female/4 male) were followed during 1 and 3 months. All patients used Continuous Glucose Monitoring (CGM) and data was collected to learn time spent in hypoglycemia, normoglycemia and hyperglycemia, as well the glucose variability. Results: Data from this small cohort showed that basal insulin infusion rates at baseline and 3 months were similar (7.7U to 7.6U) and insulin bolus requirements reduced from 14.3U to 12.7U, respectively. Based on CGM analysis the table below shows the % of time spent at different glycemia values (mean/SD) , as well its variability. HbA1c was 7.3% at baseline and 7.4% after 3 months, and there were no emergency room admissions due to severe hypoglycemia. Conclusion: The initial results of this new insulin micropump therapy in children showed an improvement on glucose control and variability, without increasing hypoglycemia. Additional studies are necessary to demonstrate the medium and long-term effect of this new device in this population. Disclosure L. Rista: Advisory Panel; Roche Diabetes Care. Speaker's Bureau; AstraZeneca, Novo Nordisk. A. Flores: Speaker's Bureau; Novo Nordisk, Roche Diabetes Care, Sanofi. M. Rivers: Employee; Roche Diabetes Care. C. Vulcano: Employee; Roche Diabetes Care. E. Repetto: Employee; Roche Diabetes Care.

The choice of the insulin basal rate regimen at initiation of insulin pump therapy in routine clinical practice

Background: Numbers of patients with diabetes mellitus using insulin pumps have been increasing every year. Successful achievement of glycemic targets with continuous subcutaneous insulin infusion (CSII) is based on an adequate basal rate of infusion, carbohydrate coefficient and insulin sensitivity index. There are two approaches to basal insulin infusion rate, namely the flat one and the circadian; however, at present there is no convincing data on which one should be chosen at the start of insulin pump therapy.Aim: To compare two regimens of basal insulin infusion rate at initiation of insulin pump therapy in routine clinical practice.Materials and methods: We analyzed data from 120 patients with Type 1 diabetes mellitus, who were switched on insulin pump therapy in the Department of Endocrinology from 2017 to 2018. At initiation of CSII, 60 patients used the flat basal rate profile and the other 60 patients used the circadian basal rate, calculated with the Renner's scale. Safety of the two basal rate regimens was assessed based on glucose variability measured with continuous glucose monitoring during the first two days after the start of insulin pump therapy.Results: Mean (± SD) coefficients of variation in the groups with circadian and flat basal rate at Day 1 were 31.06±12.13 and 32.74±10.7, respectively (p=0.423); at Day 2, 26.78±11.27 and 28.83±10.7 (p=0.309). Median [Q1; Q3] areas under glucose curve (AUC) values above the glucose targets in the groups with circadian and flat basal rate at Day 1 were 0.37 [0.03; 0.89] and 0.48 [0.08; 1.75], respectively, at Day 2 0.44 [0.03; 1.57] and 0.31 [0.1; 1.5], respectively (p>0.05). Median glucose AUC values below the goal in groups with circadian basal rate and flat basal rate on the first day were 0.01 [0; 0.06] and 0.02 [0; 0.1], respectively (p=0.855), on the second day – 0.00 [0; 0.01] and 0.00 [0; 0.02], respectively (р=0.085). We also haven’t found any between-group differences in the prevalence of glucose deviations below and above the target, as well as in the time spent in normoglycaemia.Conclusion: The comparative analysis of two basal insulin rate regimens in Type 1 diabetic patients switched to insulin pump therapy has shown no significant differences between them. The use of Renner’s scale has no clinical advantages over the fixed basal insulin regimen at initiation of insulin pump therapy in adults.

Paraneoplastic Hypoglycemia Leading to Insulin Independence in a Patient With Type 1 Diabetes

Introduction: Hypoglycemia is a rare paraneoplastic manifestation of several non-islet cell tumors (NICT) that is rarely reported in individuals with diabetes. We report the first case of a patient with type 1 diabetes (T1D) and a recurrent gastrointestinal stromal tumor (GIST) who required discontinuation of all insulin therapy with continuous parenteral glucose infusions to avoid hypoglycemia. Case: The patient is an underweight (BMI 14.9 kg/m2) 59-year-old female with a 24-year history of T1D treated with insulin pump therapy who was diagnosed with GIST in 2003. Following surgical resection with postoperative adjuvant therapy, she remained tumor free until 2012 when she had disease recurrence unresponsive to several tyrosine kinase inhibitors. In 2014, she reported frequent episodes of documented hypoglycemia despite continued reductions in basal insulin infusion rates. Laboratory testing following several hours of insulin discontinuation revealed undetectable insulin and C-peptide levels, low IGF-1, normal IGF-2, and an IGF-2: IGF-1 ratio of 7.86. Thyroid, kidney and adrenal tests were normal. Initiation of prednisone alone then in combination with octreotide did not abate the hypoglycemia. During a hospitalization for hypoglycemia, exogenous insulin therapy was discontinued and 10% dextrose infusions started. Attempts at weaning the dextrose infusions resulted in hypoglycemia, prompting insertion of a PICC line prior to discharge home with continuous 25% dextrose infusions at 40-60 mg per hour. Discussion: NICT hypoglycemia (NICTH) is characterized by excessive tumor production of IGF-2 or pro-IGF-2. The structure of IGF-2 is similar to insulin, allowing cross reactivity at the insulin receptor. IGF binding proteins (IGFBPs) are responsible for transporting IGF-2 in plasma. Abnormal processing of the gene for IGF-2 results in increased production of the more biologically active pro-IGF-2 that does not form a complex with IGFBP3 and is available to interact with insulin receptors. In patients with normal IGF-2 (chronic kidney disease, poor nutritional status), an IGF-2: IGF-1 ratio >3 can be used to confirm NICTH. IGFBP-3 was not measured in this patient but it is likely this was low due to her poor nutritional status. The most definitive treatment for NICTH is resection of the tumor. Pharmacological management can be considered in patients who are not surgical candidates, but is not always successful as was observed in this patient. Conclusion:This is an unusual case of malignancy associated hypoglycemia in a woman with type 1 diabetes who required discontinuation of all insulin therapy as well as continuous dextrose infusions to achieve euglycemia and briefly maintain an acceptable quality of life over a period of several months.

Управление и поддержка принятия решений в системе персонализированной инсулинотерапии

Insulin therapy automation is an actual research line in the glycemic control of diabetes mellitus type 1 patients. Development of closed-loop systems and methods will allow blood glucose maintaining in the physiological range. The work proposes the personalized insulin therapy system considered as a closed-loop control system based on feedback and external disturbances compensation principles. Automatic feedback-based glycemic control includes proportional reg-ulation of basal insulin infusion rate in relation to optimized thresholds inside the target range. To achieve bidirectional glycemic regulation the author proposes model predictive control for calculation of not only optimal profile of bolus infusion but also recommended corrective dose of carbohydrates. Besides, the comparative analysis of trends in measured and predicted profiles of blood glucose allows detecting and compensation of its unpredicted deviations. In silico testing of developed algorithms on nine virtual adults for 72 hours shows an ability for glucose maintaining in the target range for whole system operation time.

Initial titration for people with type 1 diabetes using an artificial pancreas

For people with type 1 diabetes and some with type 2 diabetes, the problem of insulin titration, i.e. finding an adequate basal rate of insulin, is a complex and time-consuming task. This paper proposes a simple model-free algorithm and a procedure for fast initial titration in people with type 1 diabetes (T1D). A modified proportional-integral-derivative (PID) controller (i) updates the estimated insulin basal rate, and (ii) administers micro-boli of insulin every 5 minutes using glucose measurements from a continuous glucose monitor (CGM). A bolus calculator mitigates the effect of meals and reduces postprandial peaks. We evaluate the performance of our system qualitatively and numerically using a virtual clinic of 1,000 T1D patients with a broad inter-patient variability representative of a real population of people with T1D. We let the titration phase run for three consecutive days, followed by a three-day test phase using the newly computed basal insulin infusion rate. The proposed algorithm is able to provide a safe titration and individualized treatment for people with T1D.

Patients with Type 1 Diabetes Treated with Insulin Pumps Need Widely Heterogeneous Basal Rate Profiles Ranging from Negligible to Pronounced Diurnal Variability

Pump-treated patients with type 1 diabetes have widely differing basal insulin infusion profiles. We analyzed consequences of such heterogeneity for glycemic control under fasting conditions. Data from 339 adult patients with type 1 diabetes on insulin pump therapy undergoing a 24-hour fast (basal rate test) were retrospectively analyzed. Hourly programmed basal insulin infusion rates and plasma glucose concentrations as well as their proportions within, below, or above arbitrarily defined target ranges were assessed for specific periods of the day (eg, 1-7 hours, "dawn" period, 16-19 hours, "dusk" period, reference period 20-1 hours/10-14 hours), by tertiles of a predefined "dawn" index (mean basal insulin infusion rate during the "dawn" divided by the reference periods). The "dawn" index varied interindividually from 0.7 to 4.4. Basal insulin infusion profiles exhibited substantial differences (P = .011), especially overnight. Despite higher insulin infusion rates at 4 and 6.45 hours, patients with the most pronounced "dawn" phenomenon exhibited higher plasma glucose concentrations at those time points (P < .012). Patients with a marked "dawn" phenomenon exhibited a lower probability for low (<4.4 mmol/L) and a higher probability of high values (>7.2 mmol/L) during the dawn period (all P values <.01). We observe substantial interindividual heterogeneity in the "dawn" phenomenon. However, widely different empirically derived basal insulin infusion profiles appear appropriate for individual patients, as indicated by similar plasma glucose concentrations, mainly in the target range, during a 24-hour fasting period.

Twenty-Four Hour Fasting (Basal Rate) Tests to Achieve Custom-Tailored, Hour-by-Hour Basal Insulin Infusion Rates in Patients With Type 1 Diabetes Using Insulin Pumps (CSII).

Twenty-four hour fasting periods are being used to scrutinize basal insulin infusion rates for pump-treated patients with type 1 diabetes. Data from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy undergoing a 24-hour fast as a basal rate test were retrospectively analyzed. Hourly programmed basal insulin infusion rates and plasma glucose concentrations within, below, or above arbitrarily defined target ranges were assessed for periods of the day of special interest (eg, 01:00-07:00 am, "dawn" period, 04:00-07:00 pm, and "dusk" period). Statistics: χ2-tests, paired t-tests were used. Basal rates (mean: 0.90 ± 0.02 IU/h) showed circadian variations with peaks corresponding to "dawn" (1.07 ± 0.02 IU/h from 01:00 to 07:00 am) and, less prominently, "dusk" (0.95 ± 0.02 IU/h from 03:00 to 07:00 pm). Individual mean plasma glucose concentrations averaged 6.6 ± 0.1 mmol/L, with 53.1% in the predefined "strict" (4.4-7.2 mmol/L) target range. Interestingly, during the "dawn" period, plasma glucose was significantly higher (by 0.5 ± 0.1 mmol/L [95% confidence interval: 0.3-0.8 mmol/L; P < .0001]) and the odds ratio for hypoglycemia was significantly lower compared to the reference period. Twenty-four hour fasting periods as basal rate tests frequently unravel periods with inappropriate basal insulin infusion rates potentially responsible for fasting hyper- or hypoglycemia. Notably, the higher basal insulin infusion rate found during the "dawn" period seems to be justified and may need to be accentuated.

724-P: Timing of Basal Insulin Reduction to Prevent Hypoglycemia during Exercise in Adults and Adolescents with Type 1 Diabetes Using Insulin Pump Therapy: Preliminary Results

Background We have shown that the reduction of basal insulin (-80%) 40-min before exercise is insufficient to reduce the time spent on hypoglycemia (Roy-Fleming et al., 2018. Diabetes and Metabolism). These results suggest that earlier basal insulin reductions need to be tested. We compared the efficacy of two timings to decrease basal insulin infusion rate to reduce exercise-induced hypoglycemia in patients with T1D using insulin pump therapy. Furthermore, we explored if decreased muscle vasoreactivity (secondary to decreased insulin levels) is associated with a reduced time spent in hypoglycemia. Methods: 13 adults and adolescents (10 adults; 5 adolescents; mean A1C: 8,2±1,0%) practiced 60-min exercise sessions (ergocyle) at 60% VO2peak, 240 minutes after a standardized lunch. In randomized order, we compared an 80% reduction of basal insulin applied 40-min (T-40) and 90-min (T-90) before exercise onset. Near-infrared spectroscopy (NIRS) was used to investigate muscle hemodynamic at vastus lateralis. Venous blood samples for glycemia measurement were drawn every 10 min during exercise. Results: T-90 strategy could reduce hypoglycemia risk during exercise: glycemic drop during exercise tend to be more important during T-40 vs. T-90 strategy (-41.44 ± 57.65 mg/dl vs. -14.05 ± 34.23 mg/dl respectively; p=0.09). This trend is confirmed by the repeated measures ANOVA test, which shows a significant interaction effects (blood glucose level during exercise × strategy “T90 vs. T-40”) (p = 0.01). However, contrary to our hypothesis, the estimation of local muscle perfusion measured by NIRS shows comparable results between 2-strategies. Conclusion: Our preliminary results in 15 DT1 patients (planned 20) show that decreasing basal insulin infusion rate by 80% up to 90 minutes before exercise onset tend to reduce exercise-induced hypoglycemia. This drop does not seem to be related to a decrease in local muscle perfusion. Disclosure S. Tagougui: None. N. Taleb: None. E. Heyman: None. V. Messier: Other Relationship; Self; Eli Lilly and Company. C. Suppere: None. S. Berthoin: None. R. Rabasa-Lhoret: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Merck &amp; Co., Inc., Novo Nordisk A/S, Sanofi. Research Support; Self; AstraZeneca, Janssen Pharmaceuticals, Inc., Novo Nordisk A/S.

Timing of insulin basal rate reduction to reduce hypoglycemia during late post-prandial exercise in adults with type 1 diabetes using insulin pump therapy: A randomized crossover trial

AimsTo compare the efficacy of three timings to decrease basal insulin infusion rate to reduce exercise-induced hypoglycaemia in patients with type 1 diabetes (T1D) using pump therapy. MethodsA single-blinded, randomized, 3-way crossover study in 22 adults that had T1D > 1 year and using insulin pump > 3 months (age, 40 ± 15 years; HbA1c, 56.3 ± 10.2 mmol/mol). Participants practiced three 45-min exercise sessions (ergocyle) at 60% VO2peak 3 hours after lunch comparing an 80% reduction of basal insulin applied 40 minutes before (T-40), 20 minutes before (T-20) or at exercise onset (T0). ResultsNo significant difference was observed for percentage of time spent < 4.0 mmol/L (T-40: 16 ± 25%; T-20: 26 ± 27%; T0: 24 ± 29%) (main outcome) and time spent in target range 4.0–10.0 mmol/L (T-40: 63 ± 37%; T-20: 66 ± 25%; T0: 65 ± 31%). With T-40 strategy, although not significant, starting blood glucose (BG) was higher (T-40: 8.6 ± 3.6 mmol/L; T-20: 7.4 ± 2.5 mmol/L ; T0: 7.4 ± 2.7 mmol/L), fewer patients needed extra carbohydrates consumption prior to exercise for BG < 5.0 mmol/L (T-40: n = 3; T-20: n = 5; T0: n = 6) as well as during exercise for BG < 3.3 mmol/L [T-40: n = 6 (27%); T-20: n = 12 (55%); T0: n = 11 (50%)] while time to first hypoglycaemic episode was delayed (T-40: 28 ± 14 min; T-20: 24 ± 10 min; T0: 22 ± 11 min). ConclusionDecreasing basal insulin infusion rate by 80% up to 40 minutes before exercise onset is insufficient to reduce exercise-induced hypoglycaemia.

In Silico Modeling of Minimal Effective Insulin Doses Using the UVA/PADOVA Type 1 Diabetes Simulator.

Background:The objective of this study was to identify the minimum basal insulin infusion rates and bolus insulin doses that would result in clinically relevant changes in blood glucose levels in the most insulin sensitive subjects with type 1 diabetes.Methods:The UVA/PADOVA Type 1 Diabetes Simulator in silico population of children, adolescents, and adults was administered a basal insulin infusion rate to maintain blood glucose concentrations at 120 mg/dL (6.7 mmol/L). Two scenarios were modeled independently after 1 hour of simulated time: (1) basal insulin infusion rates in increments of 0.01 U/h were administered and (2) bolus doses in increments of 0.01 U were injected. Subjects were observed for 4 hours to determine insulin delivery required to change blood glucose by 12.5 mg/dL (0.7 mmol/L) and 25 mg/dL (1.4 mmol/L) in only 5% of the in silico population.Results:The basal insulin infusion rates required to change blood glucose by 12.5 mg/dL and 25 mg/dL in 5% of children, adolescents, and adults were 0.03, 0.11, and 0.10 U/h and 0.06, 0.21, and 0.19 U/h, respectively. The bolus insulin doses required to change blood glucose by the target amounts in the respective populations were 0.10, 0.28, and 0.30 U and 0.19, 0.55, and 0.60 U.Conclusions:In silico modeling suggests that only a very small percentage of individuals with type 1 diabetes, corresponding to children with high insulin sensitivity and low body weight, will exhibit a clinically relevant change in blood glucose with very low basal insulin rate changes or bolus doses.

Adjustment of basal insulin infusion rate in T1DM by hybrid PSO

Basal insulin infusion rate which should be adjusted to increase or decrease insulin delivery with the varying blood sugar level plays a key role in type 1 diabetes mellitus (T1DM) patients for maintaining the blood glucose level approximately steady within reference range in order to avoid the complications developed from diabetes. This paper proposes an effective hybrid particle swarm optimization (HPSO) algorithm for solving the basal insulin infusion rate problem. In HPSO, bad experience lesson learning scheme and local search based on chaotic dynamics are proposed to make a good balance between global exploration and local exploitation. Simulation results based on a set of well-known optimization benchmark instances and the basal insulin infusion rate adjustment problem for T1DM demonstrate the effectiveness of the proposed HPSO. In silico tests on standard virtual subject via HPSO show that under nominal condition the blood glucose concentrations could be kept within a range of 80---150 mg/dL within less than 5 days; meanwhile, in case of random variations in meal timings within $$\pm $$±60 min or meal amounts within $$\pm $$±75 % deviation from the nominal values, the blood glucose concentrations could be kept within the safe regions.

In Silico Optimization of Basal Insulin Infusion Rate during Exercise: Implication for Artificial Pancreas

Several clinical trials have been performed to assess safety and efficacy of closed-loop control. Some included physical activity (PA), with the goal of challenging the control algorithms with a rapid change in insulin sensitivity while reducing the risk of hypoglycemia. However, the question remains as to the necessity to inform the control algorithm on the imminent PA. The aim here is to assess in silico (i) if it is necessary to announce upcoming PA and (ii) if this is the case, what is the safest strategy of basal insulin reduction in the context of the closed-loop control. We modified the University of Virginia/Padova type 1 diabetes simulator to incorporate the effect of PA based on a study in healthy subjects that demonstrated an almost doubling of insulin sensitivity during PA versus rest. Two in silico experiments, including a PA session, have been simulated on the virtual adult population: one in the absence of and one with different degrees of reductions and durations of basal insulin infusion rates. Most in silico subjects experienced hypoglycemia in the absence of basal insulin adjustment. We show that, in the absence of patient-specific information, a safe and effective strategy is to reduce basal insulin by 50% starting 90 min before exercise and by 30% during exercise. Our results suggest that control algorithms could benefit by knowing an upcoming PA. Ideally, the control algorithm should be informed about the patient-specific basal insulin reduction pattern. An alternative strategy that has been proposed here has been deemed safe and effective in in silico experiments.

Model-Based Closed-Loop Glucose Control in Type 1 Diabetes: The DiaCon Experience

To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific parameters: insulin sensitivity factor, insulin action time, and basal insulin infusion rate. The stochastic part is identical for all patients but identified from data from a single patient. Results of the first clinical feasibility test of the algorithm are presented. We conducted two randomized crossover studies. Study 1 compared CL with open-loop (OL) control. Study 2 compared glucose control after CL initiation in the euglycemic (CL-Eu) and hyperglycemic (CL-Hyper) ranges, respectively. Patients were studied from 22:00-07:00 on two separate nights. Each study included six T1DM patients (hemoglobin A1c 7.2% ± 0.4%). In study 1, hypoglycemic events (plasma glucose < 54 mg/dl) occurred on two OL and one CL nights. Average glucose from 22:00-07:00 was 90 mg/dl [74-146 mg/dl; median (interquartile range)] during OL and 108 mg/dl (101-128 mg/dl) during CL (determined by continuous glucose monitoring). However, median time spent in the range 70-144 mg/dl was 67.9% (3.0-73.3%) during OL and 80.8% (70.5-89.7%) during CL. In study 2, there was one episode of hypoglycemia with plasma glucose <54 mg/dl in a CL-Eu night. Mean glucose from 22:00-07:00 and time spent in the range 70-144 mg/dl were 121 mg/dl (117-133 mg/dl) and 69.0% (30.7-77.9%) in CL-Eu and 149 mg/dl (140-193 mg/dl) and 48.2% (34.9-72.5%) in CL-Hyper, respectively. This study suggests that our novel MPC algorithm can safely and effectively control glucose overnight, also when CL control is initiated during hyperglycemia.

Predicting the Optimal Basal Insulin Infusion Pattern in Children and Adolescents on Insulin Pumps

OBJECTIVEWe aimed at developing and cross-validating a mathematical prediction model for an optimal basal insulin infusion pattern for children with type 1 diabetes on continuous subcutaneous insulin infusion therapy (CSII).RESEARCH DESIGN AND METHODSWe used the German/Austrian DPV-Wiss database for quality control and scientific surveys in pediatric diabetology and retrieved all CSII patients <20 years of age (November 2009). A total of 1,248 individuals from our previous study were excluded (dataset 1), resulting in 6,063 CSII patients (dataset 2) (mean age 10.6 ± 4.3 years). Only the most recent basal insulin infusion rates (BRs) were considered. BR patterns were identified and corresponding patients sorted by unsupervised clustering. Logistic regression analysis was applied to calculate the probabilities for each BR pattern. Equations were based on both independent datasets separately, and probabilities for BR patterns were cross-validated using typical test patients.RESULTSOf the 6,063 children, 5,903 clustered in one of four major circadian BR patterns, confirming our previous study. The oldest age-group (mean age 12.8 years) was represented by 2,490 patients (42.18%) with a biphasic dawn-dusk pattern (BC). A broad single insulin maximum at 9–10 p.m. (F) was unveiled by 853 patients (14.45%) (mean age 6.3 years). Logistic regression analysis revealed that age, to a lesser extent duration of diabetes, and partly sex predicted BR patterns. Cross-validation revealed almost identical probabilities for BR patterns BC and F in the two datasets but some variation in the remaining two BR patterns.CONCLUSIONSReconfirmation of four key BR patterns in two very large independent cohorts supports that these patterns are realistic approximations of the circadian distribution of insulin needs in children with type 1 diabetes. Prediction of an optimal pattern a priori can improve initiation and clinical follow-up of CSII in children and adolescents. In addition, these BR patterns represent valuable information for insulin-infusion algorithms in closed-loop CSII.

Closing the loop

Closing the loop

Catamenial hyperglycaemia: an important cause of recurrent diabetic ketoacidosis

AbstractWe report the case of a female patient with type 1 diabetes mellitus with recurrent episodes of diabetic ketoacidosis (DKA ) despite previously good control and treatment with continuous subcutaneous insulin infusion (CSII ). It was noted that her episodes of uncontrolled hyperglycaemia with DKA were occurring monthly and before her menstrual periods. This effect required an increase in her basal insulin infusion rate by as much as four‐fold. The phenomenon of DKA associated with the menstrual cycle has been recognised previously and is termed ‘catamenial’ DKA. We discuss the prevalence, possible causes and clinical management of catamenial DKA. Copyright © 2010 John Wiley &amp; Sons.

Use of Insulin Pumps in India: Suggested Guidelines Based on Experience and Cultural Differences

All type 1 diabetes mellitus (T1DM) subjects and the majority of type 2 diabetes mellitus (T2DM) subjects at one time or another require insulin to sustain life. Syringes and pens are presently the most popular insulin delivery devices. Though in use for more than 3 decades, insulin pumps are now being more commonly used because of their unique ability to continuously infuse insulin, closely mimicking that of physiological secretion from a normal pancreas. Unlike insulin shots with syringes, pump infusion sites need to be changed less frequently. Scientific evidence from published studies have proven added benefit of insulin pumps in improving quality of life, normalizing sugars in recalcitrant diabetes, improving sexual function, and relieving the intractable pain of neuropathy. In the western world, pumps are commonly used with T1DM subjects, whereas in India 80% of pumpers are T2DM subjects. The success of insulin pump therapy depends on selection of the right candidate, extensive education, motivation, and implementing the sophisticated programs with skill. However, all affordable patients are not ideal candidates for pump therapy because for successful continuation of pump therapy other inclusion criteria should also be fulfilled. Among the other indications discussed are a high level of insulin resistance, brittle diabetes, chronic kidney disease on renal replacement therapy, and continuous glucose monitoring pattern strongly suggesting need for a variable basal insulin infusion rate. In International Diabetes Foundation data released in 2009, estimated diabetes prevalence for 2010 is 285 million, representing 6.4% of the world's adult population, with a prediction that by 2030 the number of people with diabetes will have increased to 438 million. Considering this massive growth in T2DM and its propensity after 10–15 years to lead to an insulin-deficient state, available evidence from studies is a compelling indication not to deny the benefits of continuous subcutaneous insulin infusion in selected T2DM subjects. This article aims at suggesting guidelines based on clinical experience and cultural diversity for India and developing countries.