Ajenthen Ranjan

An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes

Automated glucose control in patients with Type 1 diabetes is much-coveted by patients, relatives and healthcare professionals. It is the expectation that a system for automated control, also know as an artificial pancreas, will improve glucose control, reduce the risk of diabetes complications and markedly improve patient quality of life. An artificial pancreas consists of portable devices for glucose sensing and insulin delivery which are controlled by an algorithm residing on a computer. The technology is still under development and currently no artificial pancreas is commercially available. This review gives an introduction to recent progress, challenges and future prospects within the field of artificial pancreas research.

Inheritance of the chronic myeloproliferative neoplasms. A systematic review

Ranjan A, Penninga E, Jelsig AM, Hasselbalch HC, Bjerrum OW. Inheritance of the chronic myeloproliferative neoplasms. A systematic review.

Effects of subcutaneous, low-dose glucagon on insulin-induced mild hypoglycaemia in patients with insulin pump treated type 1 diabetes.

To investigate the dose–response relationship of subcutaneous (s.c.) glucagon administration on plasma glucose and on counter‐regulatory hormone responses during s.c. insulin‐induced mild hypoglycaemia in patients with type 1 diabetes treated with insulin pumps.

Short-term effects of a low carbohydrate diet on glycaemic variables and cardiovascular risk markers in patients with type 1 diabetes: A randomized open-label crossover trial

The aim of the present study was to assess the effects of a high carbohydrate diet (HCD) vs a low carbohydrate diet (LCD) on glycaemic variables and cardiovascular risk markers in patients with type 1 diabetes. Ten patients (4 women, insulin pump‐treated, median ± standard deviation [s.d.] age 48 ± 10 years, glycated haemoglobin [HbA1c] 53 ± 6 mmol/mol [7.0% ± 0.6%]) followed an isocaloric HCD (≥250 g/d) for 1 week and an isocaloric LCD (≤50 g/d) for 1 week in random order. After each week, we downloaded pump and sensor data and collected fasting blood and urine samples. Diet adherence was high (225 ± 30 vs 47 ± 10 g carbohydrates/d; P < .0001). Mean sensor glucose levels were similar in the two diets (7.3 ± 1.1 vs 7.4 ± 0.6 mmol/L; P = .99). The LCD resulted in more time with glucose values in the range of 3.9 to 10.0 mmol/L (83% ± 9% vs 72% ± 11%; P = .02), less time with values ≤3.9 mmol/L (3.3% ± 2.8% vs 8.0% ± 6.3%; P = .03), and less glucose variability (s.d. 1.9 ± 0.4 vs 2.6 ± 0.4 mmol/L; P = .02) than the HCD. Cardiovascular markers were unaffected, while fasting glucagon, ketone and free fatty acid levels were higher at end of the LCD week than the HCD week. In conclusion, the LCD resulted in more time in euglycaemia, less time in hypoglycaemia and less glucose variability than the HCD, without altering mean glucose levels.

Low-Carbohydrate Diet Impairs the Effect of Glucagon in the Treatment of Insulin-Induced Mild Hypoglycemia: A Randomized Crossover Study

OBJECTIVE This study compared the ability of glucagon to restore plasma glucose (PG) after mild hypoglycemia in patients with type 1 diabetes on an isocaloric high-carbohydrate diet (HCD) versus a low-carbohydrate diet (LCD). RESEARCH DESIGN AND METHODS Ten patients with insulin pump–treated type 1 diabetes randomly completed 1 week of the HCD (≥250 g/day) and 1 week of the LCD (≤50 g/day). After each week, mild hypoglycemia was induced by a subcutaneous insulin bolus in the fasting state. When PG reached 3.9 mmol/L, 100 µg glucagon was given subcutaneously, followed by 500 µg glucagon 2 h later. RESULTS Compared with the HCD, the LCD resulted in lower incremental rises in PG after the first (mean ± SEM: 1.3 ± 0.3 vs. 2.7 ± 0.4 mmol/L, P = 0.002) and second glucagon bolus (4.1 ± 0.2 vs. 5.6 ± 0.5 mmol/L, P = 0.002). No differences were observed between the diets regarding concentrations of insulin, glucagon, and triglycerides. CONCLUSIONS The LCD reduces the treatment effect of glucagon on mild hypoglycemia. Carbohydrate intake should be considered when low-dose glucagon is used to correct hypoglycemia.

Cross-Validation of a Glucose-Insulin-Glucagon Pharmacodynamics Model for Simulation Using Data From Patients With Type 1 Diabetes:

Background: Currently, no consensus exists on a model describing endogenous glucose production (EGP) as a function of glucagon concentrations. Reliable simulations to determine the glucagon dose preventing or treating hypoglycemia or to tune a dual-hormone artificial pancreas control algorithm need a validated glucoregulatory model including the effect of glucagon. Methods: Eight type 1 diabetes (T1D) patients each received a subcutaneous (SC) bolus of insulin on four study days to induce mild hypoglycemia followed by a SC bolus of saline or 100, 200, or 300 µg of glucagon. Blood samples were analyzed for concentrations of glucagon, insulin, and glucose. We fitted pharmacokinetic (PK) models to insulin and glucagon data using maximum likelihood and maximum a posteriori estimation methods. Similarly, we fitted a pharmacodynamic (PD) model to glucose data. The PD model included multiplicative effects of insulin and glucagon on EGP. Bias and precision of PD model test fits were assessed by mean predictive error (MPE) and mean absolute predictive error (MAPE). Results: Assuming constant variables in a subject across nonoutlier visits and using thresholds of ±15% MPE and 20% MAPE, we accepted at least one and at most three PD model test fits in each of the seven subjects. Thus, we successfully validated the PD model by leave-one-out cross-validation in seven out of eight T1D patients. Conclusions: The PD model accurately simulates glucose excursions based on plasma insulin and glucagon concentrations. The reported PK/PD model including equations and fitted parameters allows for in silico experiments that may help improve diabetes treatment involving glucagon for prevention of hypoglycemia.

Sensor-Augmented Insulin Pumps and Hypoglycemia Prevention in Type 1 Diabetes

Hypoglycemia can lead to seizures, unconsciousness, or death. Insulin pump treatment reduces the frequency of severe hypoglycemia compared with multiple daily injections treatment. The addition of a continuous glucose monitor, so-called sensor-augmented pump (SAP) treatment, has the potential to further limit the duration and severity of hypoglycemia as the system can detect and in some systems act on impending and prevailing low blood glucose levels. In this narrative review we summarize the available knowledge on SAPs with and without automated insulin suspension, in relation to hypoglycemia prevention. We present evidence from randomized trials, observational studies, and meta-analyses including nonpregnant individuals with type 1 diabetes mellitus. We also outline concerns regarding SAPs with and without automated insulin suspension. There is evidence that SAP treatment reduces episodes of moderate and severe hypoglycemia compared with multiple daily injections plus self-monitoring of blood glucose. There is some evidence that SAPs both with and without automated suspension reduces the frequency of severe hypoglycemic events compared with insulin pumps without continuous glucose monitoring.

Effects of alcohol on plasma glucose and prevention of alcohol-induced hypoglycemia in type 1 diabetes-A systematic review with GRADE

Because ethanol is thought to be a risk factor for severe hypoglycemia, patients with type 1 diabetes (T1D) are recommended to limit ethanol intake. However, little is known on how ethanol affects plasma glucose and how ethanol‐induced hypoglycemia can be prevented. In this study, we systematically reviewed the literature for ethanol effects on plasma glucose and for prevention strategies on ethanol‐induced hypoglycemia. Electronic searches on PubMed and Google were conducted in February 2017. Randomized clinical trials and observational studies were included. Studies involved patients with T1D with no history of ethanol abuse. The primary aims were changes in plasma glucose after ethanol intake and prevention strategies for ethanol‐induced hypoglycemia. Quality of the studies was assessed by GRADE. Additionally, we searched for guidelines from diabetes associations on their suggested prevention strategies. We included 13 studies. Eight studies reported that ethanol, regardless of administration intravenously or orally, were associated with an increased risk of hypoglycemia due to decrease in plasma glucose, impaired counter‐regulatory response, awareness of hypoglycemia, and cognitive function. Five studies did not report an increased risk of hypoglycemia. None of the studies investigated prevention strategies for ethanol‐induced hypoglycemia. Recommendations from 13 diabetes associations were included. All associations recommend that ethanol should only be consumed with food intake. The majority of included studies showed that ethanol intake increased the risk of hypoglycemia in patients with T1D. However, the evidence for how to prevent ethanol‐induced hypoglycemia is sparse, and further investigations are needed to establish evidence‐based recommendations.

Effects of Preceding Ethanol Intake on Glucose Response to Low-Dose Glucagon in Individuals With Type 1 Diabetes: A Randomized, Placebo-Controlled, Crossover Study

OBJECTIVE This study investigated whether preceding ethanol intake impairs glucose response to low-dose glucagon in individuals with type 1 diabetes. RESEARCH DESIGN AND METHODS This was a randomized, crossover, placebo-controlled study in 12 insulin pump–treated individuals (median [interquartile range] age, 37 [31–51] years; HbA1c, 57 [51–59] mmol/mol or 7.3% [6.8–7.5]; and BMI, 23.9 [22–25] kg/m2). During two overnight study visits, a 6 p.m. dinner (1 g carbohydrates/kg) was served with diet drink (placebo) or diet drink and ethanol (0.8 g/kg). After 8–9 h, ethanol was estimated to be metabolized, and a subcutaneous (s.c.) insulin bolus was given to induce mild hypoglycemia. When plasma glucose (PG) was ≤3.9 mmol/L, 100 µg glucagon was given s.c., followed by another s.c. 100 µg glucagon 2 h later. Primary end point was incremental peak PG induced by the first glucagon bolus. RESULTS Ethanol was undetectable before insulin administration at both visits. The insulin doses (mean ± SEM: 2.5 ± 0.4 vs. 2.7 ± 0.4 IU) to induce hypoglycemia (3.7 ± 0.1 vs. 3.9 ± 0.1 mmol/L) did not differ and caused similar insulin levels (28.3 ± 4.6 vs. 26.1 ± 4.0 mU/L) before glucagon administration on ethanol and placebo visits (all, P > 0.05). The first glucagon bolus tended to cause lower incremental peak PG (2.0 ± 0.5 vs. 2.9 ± 0.3 mmol/L, P = 0.06), lower incremental area under the curve (87 ± 40 vs. 191 ± 37 mmol/L × min, P = 0.08), and lower 2-h PG level (3.6 ± 1.0 vs. 4.8 ± 0.4 mmol/L, P = 0.05) after ethanol compared with placebo. The second glucagon bolus had similar responses between visits, but PG remained 1.8 ± 0.7 mmol/L lower after ethanol compared with placebo. CONCLUSIONS The ability of low-dose glucagon to treat mild hypoglycemia persisted with preceding ethanol intake, although it tended to be attenuated.

Relationship between Optimum Mini-doses of Glucagon and Insulin Levels when Treating Mild Hypoglycaemia in Patients with Type 1 Diabetes - A Simulation Study

Hypoglycaemia remains the main limiting factor in type 1 diabetes management. We developed an insulin‐dependent glucagon dosing regimen for treatment of mild hypoglycaemia based on simulations. A validated glucose–insulin–glucagon model was used to describe seven virtual patients with insulin pump‐treated type 1 diabetes. In each simulation, one of ten different and individualized subcutaneous insulin boluses was administered to decrease plasma glucose (PG) from 7.0 to ≤3.9 mmol/l. Insulin levels were estimated as ratio of actual to baseline serum insulin concentration (se/ba‐insulin), insulin on board (IOB) or percentage of IOB to total daily insulin dose (IOB/TDD). Insulin bolus sizes were chosen to provide pre‐defined insulin levels when PG reached 3.9 mmol/l, where one of 17 subcutaneous glucagon boluses was administered. Optimum glucagon bolus to treat mild hypoglycaemia at varying insulin levels was the lowest dose that in most patients caused PG peak between 5.0 and 10.0 mmol/l and sustained PG ≥ 3.9 mmol/l for 2 hr after the bolus. PG response to glucagon declined with increasing insulin levels. The glucagon dose to optimally treat mild hypoglycaemia depended exponentially on insulin levels, regardless of how insulin was estimated. A 125‐μg glucagon dose was needed to optimally treat mild hypoglycaemia when insulin levels were equal to baseline levels. In contrast, glucagon doses >500 μg were needed when se/ba‐insulin >2.5, IOB >2.0 U or IOB/TDD >6%. Although the proposed model‐based glucagon regimen needs confirmation in clinical trials, this is the first attempt to develop an insulin‐dependent glucagon dosing regimen for treatment of insulin‐induced mild hypoglycaemia in patients with type 1 diabetes.