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Current insulin infusion sets are approved for only 2-3 days. The novel ConvaTec infusion set with Lantern technology is designed to extend infusion set wear time. The goal of this pilot study was to evaluate the duration of wear for this set. This was a pilot safety study in adults with type 1 diabetes using tethered insulin pumps. Participants inserted the set and wore it for 10 days or until failure. Among 24 participants, two were excluded. Forty-five per cent of the sets lasted 10 days. Median wear time was 9.1 (7.1, 10.0) days. Among 12 premature failures, six (50%) involved adhesive failures, four (33%) hyperglycaemia unresponsive to correction, one (8%) hyperglycaemia with ketones and one (8%) infection. Average CGM glucose per day of infusion set wear showed a statistically significant increase over time, while total daily insulin over the same period did not change. In this pilot study, the duration of wear for the novel infusion set exceeded previously reported commercial sets (P < .001). This extended wear technology may eventually allow for a combined glucose sensor and infusion set.

Treatment strategies for hypertriglyceridemia-induced acute pancreatitis are not well defined in the current literature or guidelines. One therapeutic option is an insulin infusion accompanied by a dextrose infusion to avoid hypoglycemia. The purpose of this case report is to highlight dosing considerations for dextrose infusions in nondiabetic patients. We describe a case of hypertriglyceridemia-induced acute pancreatitis in a 34-year-old nondiabetic woman treated with a reduced-dose insulin infusion that was complicated by hypoglycemic episodes requiring dextrose infusion titrations. Empirical initiation of a higher dextrose concentration infusion with glucose level titrations should be considered to avoid hypoglycemia for nondiabetic patients treated with an insulin infusion to lower triglyceride levels. In this case, clinical pharmacy assistance was imperative for successful treatment with a reduced-dose insulin infusion and titrated dextrose infusion in the management of hypertriglyceridemia-induced acute pancreatitis.

In critical care setting, insulin infusion rather than subcutaneous insulin is recommended to maintain the blood glucose (BG) level in the target range. We have devised an insulin infusion protocol which requires monitoring of blood glucose and insulin dose adjustment one hourly. In this study, we have studied the efficacy of our insulin infusion protocol (IIP) in terms of bringing and maintaining blood glucose to target range, and its safety in terms of preventing hypoglycemia. It is a retrospective review of all patients who received insulin infusion from the 1st of July 2017 to the 30th of June 2018. A total of 231 were included and data pertaining to demographic details and related to insulin infusion was documented in a predefined questionnaire. Insulin infusion was continued for a mean duration of 26.3 ± 13.7 h taking 5.7 ± 3.1 h to reach the target BG level 180 mg/dl) but the mean BG remains 168.95 ± 45.52 within the desired target range. Our insulin infusion protocol not only achieved and maintained the blood glucose in the target range, it is safe with a very low risk of hypoglycemia.

A method and a system for automatic regulation of the basal insulin administration rate for maintenance of glycemia in the target range are proposed. The method is based on proportional regulation of the infusion rate using feedback. It suspends the insulin delivery when the glucose level falls below a threshold value. According to the modeling results, the proposed method can be used to compensate hyperglycemia of different etiologies with reduction of the settling time in comparison with constant rate insulin infusion.

In type 2 diabetes (T2D), injections with long-acting insulin can become necessary to regulate blood glucose and avoid long-term complications. However, finding a safe and effective insulin dose, a process known as titration, is both challenging and time demanding. In this paper, we propose a new method for safe and rapid identification of a personalized insulin dose with long-acting insulin through short-term use of fast-acting insulin in an artificial pancreas (AP). To illustrate this novel concept, we simulate our method by modelling the glucose response to fast-and long-acting insulin in people with T2D. We apply a simple control-algorithm for the AP to adjust the insulin infusion rate during fasting periods. In this case-study, we simulate an insulin naive T2D patient on AP treatment for one week, gradually adjusting the insulin infusion rate. After one week, we convert the insulin infusion rate, unit-to-unit, to a daily injection of long-acting insulin. We compare our method to titration with the standard of care 2-0-2 algorithm. Our simulations indicate that we can reduce the titration period from five weeks to a single week, whilst easing the burden on the patient.

Metaheuristic search algorithms are used to develop new protocols for optimal intravenous insulin infusion rate recommendations in scenarios involving hospital in-patients with Type 1 Diabetes. Two metaheuristic search algorithms are used, namely, Particle Swarm Optimization and Covariance Matrix Adaption Evolution Strategy. The Glucose Regulation for Intensive Care Patients (GRIP) serves as the starting point of the optimization process. We base our experiments on a methodology in the literature to evaluate the favorability of insulin protocols, with a dataset of blood glucose level/insulin infusion rate time series records from 16 patients obtained from the Waikato District Health Board. New and significantly better insulin infusion strategies than GRIP are discovered from the data through metaheuristic search. The newly discovered strategies are further validated and show good performance against various competitive benchmarks using a virtual patient simulator.

ntroducción: la glucosa es una variable dinámica en el paciente crítico. La hiperglucemia (mayor a 140 mg/dL) es frecuente en este grupo de pacientes, existiendo distintos enfoques terapéuticos para el control adecuado de la misma. Objetivo: revisar los aspectos clínicos de la glucemia y la importancia del control glucémico en el paciente crítico adulto. Metodología de búsqueda: en base de datos Pubmed, utilizando los términos MeSH: “critical illness”, “insulin infusion”, “insulin protocol”, “hyperglycemia”. Se incluyeron artículos de revisión y originales, en inglés y español. Conclusiones: el manejo de la hiperglucemia en el paciente crítico es un objetivo primordial en el enfoque integral del paciente de la unidad de cuidados intensivos, dada su asociación con mortalidad, morbilidad y estancia hospitalaria. MÉD.UIS.2020;33(2): 49-54

The integrated minimal model allows assessment of clinical diagnosis indices, for example, insulin sensitivity (SI ) and glucose effectiveness (SG ), from data of the insulin-modified intravenous glucose tolerance test (IVGTT), which is laborious with an intense sampling schedule, up to 32 samples. The aim of this study was to propose a more informative, although less laborious, IVGTT design to be used for model-based assessment of SI and SG . The IVGTT design was optimized simultaneously for all design variables: glucose and insulin infusion doses, time of glucose dose and start of insulin infusion, insulin infusion duration, sampling times, and number of samples. Design efficiency was used to compare among different designs. The simultaneously optimized designs showed a profound higher efficiency than both standard rich (32 samples) and sparse (10 samples) designs. The optimized designs, after removing replicate sample times, were 1.9 and 7.1 times more efficient than the standard rich and sparse designs, respectively. After including practical aspects of the designs, for example, sufficient duration between samples and avoidance of prolonged hypoglycemia, we propose 2 practical designs with fewer sampling times and lower input of glucose and insulin than standard designs, constrained to prevent hypoglycemia. The optimized practical rich design is equally efficient in assessing SI and SG as the rich standard design, but with half the number of the samples, while the optimized practical sparse design has 1 less sample and requires 4.6 times fewer individuals for equal certainty when assessing SI and SG than the sparse standard design.

Purpose Successful use of a subcutaneous insulin pump to administer regular insulin to a preterm infant with neonatal hyperglycemia is described. Summary A 520-g female infant born at 23 weeks’ gestational age via caesarian section was noted to have elevated blood glucose concentrations ranging up to 180 mg/dL (in SI units, 10 mmol/L) on day of life (DOL) 3 and peaking on DOL 9 at 250 mg/dL (13.9 mmol/L) despite conservative glucose infusion rates. Continuous infusion of regular insulin was begun on DOL 8 and continued through DOL 44, with an average insulin infusion rate of 0.08 units/kg/h. The patient experienced blood glucose concentration lability due to multiple factors, resulting in the need for frequent and routine blood glucose concentration monitoring to minimize hypoglycemia events. On DOL 44, a subcutaneous insulin pump was placed and used to provide diluted regular insulin (25 units/mL). After 1 week, the patient’s blood glucose concentration normalized, which led to a reduction in the frequency of glucose monitoring. After 3 weeks, insulin pump use was discontinued. The patient remained euglycemic thereafter. Conclusion The use of an insulin pump resulted in decreased blood glucose checks, discontinuation of central line access, and overall better patient care.

Background: Pancreatitis secondary to hypertriglyceridaemia is rare, accounting for less than 5% of pancreatitis presentations. We reviewed our institutional experience with triglyceridaemia induced acute pancreatitis to report the clinical presentation, patient demographics and clinical management. Methods: The Acute Surgical Unit database at a high-volume general surgical referral centre was queried to identify cases of acute pancreatitis secondary to hypertriglyceridaemia between 2016 and 2019. Patient demographics, clinical manifestations, biochemical derangements and treatment regimens were analysed. Current related literature was reviewed. Results: There were 496 presentations for acute pancreatitis of which 14 presentations (2.8%), amongst 12 patients were due to hypertriglyceridaemia. The mean triglyceride level at presentation was 92.46 (standard deviation 46.9) mmol/L. Ten patients (83%) had poorly controlled type 2 diabetes. All patients were managed using conservative therapy combined with a restricted fat diet and commenced on long-term anti-lipid therapy to manage associated risk factors. In addition, 10 patients received an insulin infusion and one patient received insulin infusion, plasmapheresis and heparin infusion in combination. The median length of hospital stay was 5.5 (range 3–13) days. Two patients (16%) developed a recurrent episode related to non-compliance to medical therapy. Conclusion: Hypertriglyceridaemia is a rare cause of acute pancreatitis. Successful management involves the treatment of acute pancreatitis in conjunction with long-term anti-lipid therapy and optimisation of associated risk factors.

Background: Initiation of continuous subcutaneous insulin therapy (CSII) in type 1 diabetes requires conversion of a basal insulin dose into a continuous infusion regimen. There are limited data to guide the optimal insulin profile to rapidly achieve target glucose and minimize healthcare professional input. The aim of this pilot study was to compare circadian and flat insulin infusion rates in CSII naïve adults with type 1 diabetes. Methods: Adults with type 1 diabetes commencing CSII were recruited. Participants were randomized to circadian or flat basal profile calculated from the total daily dose. Basal rate testing was undertaken on days 7, 14 and 28 and basal rates were adjusted. The primary outcome was the between-group difference in absolute change in insulin basal rate over 24 hours following three rounds of basal testing. Secondary outcomes included the number of basal rate changes and the time blocks. Results: Seventeen participants (mean age 33.3 (SD 8.6) years) were recruited. There was no significant difference in absolute change in insulin basal rates between groups ( P = .85). The circadian group experienced significant variation in the number of changes made with the most changes in the morning and evening ( P = .005). The circadian group received a greater reduction in total insulin (−14.1 (interquartile range (IQR) −22.5-12.95) units) than the flat group (−7.48 (IQR −11.90-1.23) units) ( P = .021). Conclusion: The initial insulin profile does not impact on the magnitude of basal rate changes during optimization. The circadian profile requires changes at specific time points. Further development of the circadian profile may be the optimal strategy.

Insulin infusion protocol is the standard protocol that has been practiced in Malaysia’s intensive care unit (ICU) for controlling the hyperglycemia. Multiple sliding scale method of the insulin infusion protocol may drive conflict in selecting an appropriate scale to be applied to the patient. The objective of this paper is to analyse the blood glucose outcome of eight sliding scales insulin infusion protocol adopted in the Universiti Sains Malaysia Hospital (HUSM). A retrospective data of 78 ICU patients of HUSM were fitted using a validated glucose-insulin system to identify insulin sensitivity profiles of the patients. Then, these SI profiles were simulated on various scale protocols. The results obtained from this study showed that among eight scales, Scale 4 had the highest percentage of BG within the HUSM’s target of 6.0–10.0 mmol/L. Scale 1 had the highest percentage of BG for the BG measurement more than 10.0 mmol/L while Scale 8 had the highest percentage of BG measurement of less than 6.0 mmol/L. However, none of the scale shown better performance than the current clinical practice. Furthermore, all of the eight scales had a more substantial number of BG measurement compared to the clinical. This study shows that Scale 2 and Scale 3 result in a similar outcome. Similarly, Scale 5 is almost the same as Scale 6. Thus, at least two sets of scale can be combined to reduce the number of scales. The reduction of scales consequently avoid confusion and helps the clinician in selecting the appropriate scale to be applied to the patients. From this study, it can be concluded that the HUSM protocol is a combination of scales. The scales may be shifted from one to another scale depending on patient condition and clinician judgement. A proper guideline for the scale shifting seems necessary to allow optimum glycemic management in the ICU.

Objective: Diabetes patients are increasingly using a continuous glucose sensor to monitor blood glucose and an insulin pump connected to an infusion cannula to administer insulin. Applying these devices requires two separate insertion sites, one for the sensor and one for the cannula. Integrating sensor with cannula to perform glucose sensing and insulin infusion through a single insertion site would significantly simplify and improve diabetes treatment by reducing the overall system size and the number of necessary needle pricks. Presently, several research groups are pursuing the development of combined glucose sensing and insulin infusion devices, termed single-port devices, by integrating sensing and infusion technologies created from scratch. Methods: Instead of creating the device from scratch, we utilized already existing technologies and introduced three design concepts of integrating commercial glucose sensors and infusion cannulas. We prototyped and evaluated each concept according to design simplicity, ease of insertion, and sensing accuracy. Results: We found that the best single-port device is the one in which a Dexcom sensor is housed inside a Medtronic cannula so that its glucose sensitive part protrudes from the cannula tip. The low degree of component modification required to arrive at this configuration allowed us to test the efficiency and safety of the device in humans. Conclusion: Results from these studies indicate the feasibility of combining commercial glucose sensing and insulin delivery technologies to realize a functional single-port device. Significance: Our development approach may be generally useful to provide patients with innovative medical devices faster and at reduced costs.

This investigation presents a smart artificial pancreas (AP) for treating Type 1 Diabetes Mellitus (T1DM) in elderly which simultaneously automates the insulin administration but also diet recommender system using implicit carbohydrate (CHO) measurements. Three main components of the AP are: (i) long-term model of physiological dynamics, (ii) model predictive controller and (iii) a diet recommender algorithm which uses implicit CHO measurements. We first show that long-term dynamics are important for capturing the food influences on blood glucose levels and to maintain within admissive bands. The diet recommender algorithm fuses the insulin infusion information of the MPC, long-term model, average CHO and its variations to recommend diet and its pattern. The proposed artificial pancreas with diet recommender system is illustrated using studies conducted on elderly patients with T1DM based on clinical trials conducted at Jothydev’s Diabetes Research Centre, Trivandrum, India. Our studies shows that the proposed AP not only automates the insulin infusion but also provides a recommender system for diet.

The administration of high-alert medications requires the use of enhanced systems to prevent errors. One commonly used system relies on independent verification of dose changes by a second clinicia...

Background and Aims: Sensor-augmented pump therapy (SAP) combines continuous glucose monitoring with continuous subcutaneous insulin infusion (CSII). SAP is costlier than CSII but provides...

Continuous subcutaneous insulin infusion (CSII) is a widely used treatment for diabetes patients. Insulin infusion sets (CSII-catheters) are continuously optimized regarding size, handling and safety, but recurring dysfunction (kinking or occlusion), due to different user situations, behavior or chain of events, demand new ways to improve the functionality and safety in patients experiencing these issues. A novel CSII-catheter design (Lantern) features additional lateral perforations, which guarantee functionality even in case of kinking or occlusion. This study aimed to compare functionality, insulin distribution, and failure rate of Lantern and standard catheters using excised human adipose tissue samples. Novel Lantern CSII-catheters (open and artificially occluded) and commercially available standard CSII-catheters were inserted into adipose tissue samples. A mixture of insulin and contrast agent was infused as single bolus (7 IU) with an insulin infusion pump at highest flow rate (1 IU/s). Microtomography images and surface-to-volume ratios were used to assess insulin distribution and depot volume indicating the functionality of CSII-catheters. Failure rate was measured by flow-stop alerts of the pump. We found no difference in the volume of insulin depots compared with the nominal volume of 70 μL. Surface-to-volume ratios showed no significant difference among CSII-catheters. None of the catheters triggered any flow-stop alarm. The novel Lantern CSII-catheter design achieved similar insulin distribution as commercially available CSII-catheters. Moreover, functionality of Lantern CSII-catheters was guaranteed during occlusion, which is an improvement compared with standard CSII-catheters. We conclude that the novel CSII-catheter design has the potential to provide a valuable contribution to patient well-being and safety.

Aims 1. Audit the current variable rate insulin infusion (VRII) practice per local guidelines. 2. Understand barriers to good VRII practice to create an intervention. 3. Re-Audit the VRII practice following intervention. Methods Junior doctors were surveyed using Likert scales (1 to 5: not at all confident to very confident) as well as closed and open questions. Chain action reaction (CAR) theory was used. Six domains were identified against a local proforma. Initial audit and questionnaire were collected from November 2019 to January 2020 and analysed using Microsoft Excel. Intervention consisted of a condensed one-page algorithm with group teaching. Re-audit data was collected between June 2020 to August 2020 for comparison. Results Questionnaire – 53.6% (15/28) of juniors responded. Challenges included conversion oral hypoglycaemics and complexity of the guidance. Group teaching and a condensed portable format were the most popular modalities for delivery of further education. Initial Audit – 12 VRII charts were audited. 33.3% (4/12) were completed correctly. Areas of significant need for improvement were as follows: ensuring long-acting insulin is prescribed, transferring from a VRII back to oral medications and appropriate fluid prescribing. Re-Audit – 18 charts were audited following intervention. Of these, 66.7% (12/18) were completed correctly. There was a significant improvement in appropriate fluid prescribing and long-acting insulin prescriptions. Conclusions Understanding the factors involved throughout the chain of how VRIIs are prescribed has helped to implement a positive intervention in our department. The improvement has been significant (100% better) however there is still further work required to improve compliance.

In this retrospective analysis, we examine the impact of the lockdown of the coronavirus pandemic (COVID-19) on eating habits in individuals with type 1 diabetes (T1D) on a hybrid artificial pancreas (HAP). Dietary composition before and during lockdown was assessed by 7-day food records of 12 participants with T1D on HAP (three men and nine women, ages 38 ± 13 years, HbA1c 6.8 ± 0.3%, M ± SD). Continuous glucose monitoring (CGM) metrics and lifestyle changes (online questionnaire) were also assessed. Compared to prelockdown, reported body weight tended to increase during lockdown with no changes in total energy intake. Participants significantly decreased animal protein intake (−2.1 ± 3.7% of total energy intake, p = 0.048), but tended to increase carbohydrate intake (+17 ± 28 g/day, p = 0.052). These changes were induced by modifications of eating habits at breakfast and lunch during weekdays. Patients consumed more cereals (+21 ± 33 g/day, p = 0.038), whole grain (+22 ± 32 g/day, p = 0.044), and sweets (+13 ± 17 g/day, p = 0.021), and less animal protein sources (−42 ± 67 g/day, p = 0.054). Participants showed a more regular meal timing and decreased physical activity. Blood glucose control remained optimal (time-in-range 76 ± 8 vs. 75 ± 7% before lockdown), and daily total insulin infusion increased (42 ± 10 vs. 39 ± 12 I.U., p = 0.045). During the lockdown, patients with T1D on HAP modified dietary habits by decreasing animal protein and increasing carbohydrate intake. This increase, mainly concerning whole grain and low-glycemic-index products, did not influence blood glucose control.

Technology advances have made possible improvements such as Continuous Glucose Monitors, giving the patient a glucose reading every few minutes, or insulin pumps, allowing more personalized therapies. With the increasing number of available closed-loop systems, new challenges appear regarding algorithms and functionalities. Several of the analysed systems in this paper try to adapt to changes in some patients’ conditions and, in several of these systems, other variables such as basal needs are considered fixed from day to day to simplify the control problem. Therefore, these systems require a correct adjustment of the basal needs profile which becomes crucial to obtain good results. In this paper a novel approach tries to dynamically determine the insulin basal needs of the patient and use this information within a closed-loop algorithm, allowing the system to dynamically adjust in situations of illness, exercise, high-fat-content meals or even partially blocked infusion sites and avoiding the need for setting a basal profile that approximately matches the basal needs of the patient. The insulin sensitivity factor and the glycemic target are also dynamically modified according to the situation of the patient. Basal insulin needs are dynamically determined through linear regression via the decomposition of previously dosed insulin and its effect on the patient’s glycemia. Using the obtained value as basal insulin needs and other mechanisms such as basal needs modification through its trend, ISF and glycemic targets modification and low-glucose-suspend threshold, the safety of the algorithm is improved. The dynamic basal insulin needs determination was successfully included in a closed-loop control algorithm and was simulated on 30 virtual patients (10 adults, 10 adolescent and 10 children) using an open-source python implementation of the FDA-approved (Food and Drug Administration) UVa (University of Virginia)/Padova Simulator. Simulations showed that the proposed system dynamically determines the basal needs and can adapt to a partial blockage of the insulin infusion, obtaining similar results in terms of time in range to the case in which no blockage was simulated. The proposed algorithm can be incorporated to other current closed-loop control algorithms to directly estimate the patient’s basal insulin needs or as a monitoring channel to detect situations in which basal needs may differ from the expected ones.

Controller takes an important role for artificial pancreas (AP) to regulate insulin infusion rate according variable requirements of diabetic patients. In this research, an adaptive model predictive control (MPC) algorithm is proposed to overcome the parameter uncertainty induce by inter and intra variability. Firstly, a glucose-insulin dynamic model is established to describe the integrated metabolism of glucose and insulin, in which the time-varying parameters can be extended to observable state variables. Then, particle filtering technology is introduced to track and adjust the parameters. Meanwhile, the glucose and insulin concentration in plasma (PGC and PIC) are also estimated. Finally, imbedding the dynamic model with personalized parameters, an adaptive MPC algorithm is proposed based on the estimated PIC and PGC. For validation, the in-silico experiments are carried out on the 30 virtual patients of the UVa/Padova simulator. The proposed algorithm shows promising performances. It shows that the proposed method has the potential for artificial pancreas in clinical treatment.