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Objective: To evaluate the clinical efficacy and comparison of potassium lowering effect of insulin infusion alone and insulin infusion with salbutamol nebulization. Methods: This interventional study was conducted in a tertiary care hospital, for a period of one year. A total of 190 patients with hyperkalemia were divided into two groups. Group-A (diabetic [D] and non-diabetic [ND] patients) received salbutamol 20 mg three times daily (TDS) (nebulizer 5mg/2.5mL) administered over a period of 15 minutes with 10 units of regular insulin (diluted with 25% dextrose in non-diabetic only) over 30 minute TDS via infusion. Group-B (diabetic and non-diabetic patients) received 10 units of regular insulin (diluted with 25% dextrose in non-diabetic patients only) administered over 30 minute TDS via infusion. Potassium and glucose level was measured in patient blood sample after 0, 6, 12 and 24 hrs of treatment. Results: The potassium level was decreased by 30.09% (D) and 31.98% (ND) in Group-A, whereas by 31.98% (D) and 20.49% (ND) in Group-B, after 24 hrs. Whereas blood glucose level in diabetic patients of Group-A and Group-B was found to decrease up to 28.85 % and 40.78 % respectively after 6 hours. Both the treatments were found to be effective without any complication i.e. hypoglycaemia and hypokalaemia. Moreover, renal, liver, cardiac and respiratory function test also did not show significant changes after treatments when recorded bihourly Conclusion: From the results, salbutamol nebulizer with insulin is more effective in the treatment of hyperkalemia in diabetic and non-diabetic patients.

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.

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.

Objective: Most insulin infusion sets (ISs) are labeled for 2- or 3-days use. The Medtronic EWIS is designed to increase wear time up to 7 days. This study reports on EWIS survival and performance during the pivotal trial (ClinicalTrials.gov: NCT04113694). Method: This multi-center (15), single-arm, non-randomized, non-inferiority trial in 259 participants (18-80yrs) with T1D using the MiniMed™ 670G system (with Humalog™ or Novolog™ insulin) involved wearing a 2- or 3-day IS for 2 weeks (run-in) followed by 12 consecutive EWIS wears (study phase). The latter was worn for ≥174 hours or until set failure. Safety and performance (i.e., a priori target of Result: The EWIS survival rate was 74.8% versus the 67.7% rate of 2- or 3-day ISs (p Conclusion: The 7-day EWIS was safe and its performance was superior at ≥174 hours compared to the performance observed for 2- or 3-day infusion sets. Disclosure B. A. Buckingham: Advisory Panel; Self; Medtronic, Tolerion, Inc., Research Support; Self; Beta Bionics, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. B. Horowitz: Research Support; Self; Abbott Laboratories, BD, Celgene, Crinetics Pharmaceuticals, Gan & Lee Pharmaceuticals, Medtronic, Speaker’s Bureau; Self; AstraZeneca, Lilly Diabetes, Merck & Co., Inc., Novo Nordisk Inc. K. B. Kaiserman: Advisory Panel; Self; Medtronic, Consultant; Self; Medtronic, Employee; Self; MannKind Corporation, Research Support; Self; Medtronic, Speaker’s Bureau; Self; Medtronic, Stock/Shareholder; Self; MannKind Corporation. S. Huang: None. V. Chen: Employee; Self; Medtronic. G. Zhang: Employee; Self; Medtronic. S. Chattaraj: Employee; Self; Medtronic. J. Shin: Employee; Self; Medtronic. R. Vigersky: Employee; Self; Medtronic. R. L. Brazg: Research Support; Self; Abbott Diabetes, Ascensia Diabetes Care, Lexicon Pharmaceuticals, Inc., Lilly Diabetes, Medtronic, Pfizer Inc., Roche Diagnostic USA, Senseonics. T. S. Bailey: Consultant; Self; Abbott Diabetes, LifeScan, Novo Nordisk, Sanofi, Research Support; Self; Abbott, Abbott Diabetes, Biolinq, Capillary Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Kowa Research Institute, Inc., Lexicon Pharmaceuticals, Inc., Livongo, Medtronic, Medtrum Technologies, Novo Nordisk, REMD Biotherapeutics, Sanofi, Sanvita, Viacyte, Inc., vTv Therapeutics, Zealand Pharma A/S, Speaker’s Bureau; Self; BD, Medtronic, Sanofi. Y. C. Kudva: Research Support; Self; Dexcom, Inc. S. K. Garg: Advisory Panel; Self; Eli Lilly and Company, Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Medtronic. G. Grunberger: Research Support; Self; Medtronic, Speaker’s Bureau; Self; Abbott Diabetes, Eli Lilly and Company, Novo Nordisk. J. Thrasher: Advisory Panel; Self; Medtronic, Board Member; Self; Medtronic, Consultant; Self; Medtronic, Research Support; Self; Eli Lilly and Company, Lexicon Pharmaceuticals, Inc., Medtronic, Mylan N. V., Novo Nordisk, Sanofi, Speaker’s Bureau; Self; AstraZeneca, Janssen Pharmaceuticals, Inc., Medtronic, Sanofi. A. Cavale: Research Support; Self; Eli Lilly and Company, Medtronic. A. Bhargava: Research Support; Self; Abbott, AbbVie Inc., Amgen Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Boston Therapeutics, Inc., Covance Inc., Dexcom, Inc., Eli Lilly and Company, Gan & Lee Pharmaceuticals, Insulet Corporation, Janssen Research & Development, LLC, Kowa Pharmaceuticals America, Inc., Madrigal Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Mylan N. V., Novo Nordisk, Poxel SA, Quintiles, Sanofi, Senseonics, Tolerion, Inc., Viking Therapeutics.

Objective: A combination insulin infusion and glucose-sensing device will dramatically improve the ease of use for automated insulin delivery systems. The objective of this preclinical study was to collect safety and efficacy data during 7-day wear of a combined insulin-delivery and glucose-sensing device called the “Duo” set. Method: In a type 1 diabetes (T1D) porcine model, each animal (N=6) wore the Duo set multiple times (on the abdomen) while receiving Novolog® insulin subcutaneously via a pump for one week or until set failure, determined by (1). blood glucose (BG) value not decreasing by at least 50 mg/dL an hour after a correction bolus for a BG level >350 mg/dL, or (2). evidence of infection at the infusion site. Blood glucose was measured five times/day with a BG meter, and pigs also wore a Guardian™ Sensor (3) glucose sensor (GS3) distant from the Duo-set site. Additionally, physical examination and serum panel tests were conducted for safety evaluation. Result: There were 15 wears, with 10 wears lasting more than 7 days. Survival rate (67%) was similar to that of the Medtronic 7-day Extended Wear Infusion Set (EWIS) previously tested in the same porcine model (64%). There was no significant difference in total daily insulin dose (TDD) between the Duo set and the EWIS during the entire 7-day wear. There was no significant difference in glucose values between the Duo-set sensor and the GS3 (p>0.10), which agreed with the measured BG values in the range of 70-300 mg/dL (p>0.10). There was no significant device safety concern identified. Conclusion: The results indicated that no interference of sensor signals was observed from insulin infused though the cannula of the same Duo set in the near proximity or from mechanical inference from the infusion-set movements. These data confirm the feasibility of a combined 7-day set which simultaneously infuses insulin and senses glucose subcutaneously in a T1D porcine model. Disclosure G. Zhang: Employee; Self; Medtronic. E. Anselmo: Employee; Self; Medtronic. L. To: None. S. Chattaraj: Employee; Self; Medtronic.

Automated Insulin Delivery (AID) hybrid closed-loop systems have not been well studied in the context of psychological and physiological stress. We evaluated our interoperable artificial pancreas system with in-clinic stress challenges in a randomized crossover trial. Fourteen adults with type 1 diabetes were randomized to 2 weeks of AID-based control and two weeks of sensor augmented pump (SAP)l therapy at home in random order. The AID system used the Zone-Model Predictive Control algorithm with a continuous function of glucose velocity and insulin-on-board to gradually increase insulin infusion under conditions of sustained hyperglycemia. During each two-week period, in-clinic stress assessments for psychological stress (TSST and SECPT) and pharmacological stress (hydrocortisone 40-20-20 mg) were performed. Ten subjects completed the study per protocol, with 48 stress sessions completed in 12 subjects. AID increased time 70-180mg/dL from 63.1 to 74.4% (p=0.001), decreased time 180mg/dL from 35.4 to 24.8% (p=0.001) during the 2 weeks outpatient use. AID decreased glycemic variability as measured by CV (p=0.037) and time Disclosure R. Kaur: None. Y. C. Kudva: Research Support; Self; Dexcom, Inc. S. Deshpande: None. J. E. Pinsker: Advisory Panel; Self; Medtronic, Consultant; Self; Eli Lilly and Company, Tandem Diabetes Care, Research Support; Self; Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care. S. K. Mccrady-spitzer: None. D. Desjardins: None. M. Church: None. W. K. Kremers: Research Support; Self; AstraZeneca, Biogen, Roche Pharma. F. J. Doyle: Advisory Panel; Self; Mode AGC, Other Relationship; Self; Dexcom, Inc., Insulet Corporation, Roche Diabetes Care. E. Dassau: Consultant; Self; Eli Lilly and Company, Employee; Self; Eli Lilly and Company, Research Support; Self; Dexcom, Inc., Tandem Diabetes Care, Speaker’s Bureau; Self; Dexcom, Inc., Roche Diabetes Care, Stock/Shareholder; Self; Eli Lilly and Company. Funding JDRF (2-SRA-2017-503-M-B); The Leona M. and Harry B. Helmsley Charitable Trust; Dexcom, Inc. (IIS-2019-017)

During the first phase of the COVID-19 pandemic, we modified our insulin infusion protocol (IIP) for use in COVID-19 patients with severe hyperglycemia, in order to reduce entry into patient rooms and minimize viral exposure for healthcare workers (HCW), and preserve personal protective equipment (PPE). Blood glucose (BG) monitoring was less frequent (Q2h vs. Q1h in our standard IIP) and the BG target higher (150-199 mg/dl vs. 120-160 mg/dl). We sought to validate the safety and effectiveness of the COVID-19 IIP. We reviewed the medical records of 40 adult patients admitted with COVID-19 from 3/2020-5/2020 who were treated with either standard IIP (n=20) or COVID-19 IIP (n=20) to compare safety (hypoglycemia) and effectiveness (achievement of BG target, mean BG.) All results (Table) are reported as mean ± SD. Four patients in the standard IIP group and 2 in the COVID-19 IIP did not achieve target BG before IIP discontinuation. Preliminary results using our modified COVID-19 IIP show that it is safe and effective in controlling severe hyperglycemia, achieving its distinct BG target in a similar timeframe and without any increased risk of hypoglycemia despite reduced BG monitoring frequency. We conclude that our COVID-19 IIP can be used to safely manage hyperglycemia while protecting patients and HCWs as the pandemic continues. Disclosure D. Athonvarangkul: None. L. B. Bak: None. C. Zheng: None. J. D’ambrosi: None. J. Siner: None. S. Honiden: None. S. E. Inzucchi: Consultant; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Esperion, Merck & Co., Inc., Novo Nordisk.

Hyperglycemia (BG>140 mg/dl) and hypoglycemia (BG 180 mg/dl. All patients were on an eGMS to titrate IV insulin and followed Glucommander IV order set initiation recommendations for renal failure. The results were compared to published data from other eGMS. See Table for complete results. Conclusions: When using Glucommander proprietary nonlinear IV insulin infusion software and an appropriate order set, renal impaired patients had low hypoglycemia rates and acceptable glycemic control. There were few large comparator studies, all with higher hypoglycemic rates and none of which reported outcomes in patients with renal impairment. Disclosure B. W. Bode: Advisory Panel; Self; Eli Lilly and Company, Consultant; Self; Bigfoot Biomedical, Inc., Companion Medical, Lexicon Pharmaceuticals, Inc., Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Abvance Therapeutics, Dexcom, Inc., Diasome Pharmaceuticals, Inc., Dompe, Eli Lilly and Company, Eyenuk, Inc., Insulet Corporation, Jaeb Center for Health Research, Medtronic, Nova Biomedical, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanofi, Senseonics, Viacyte, Inc., vTv Therapeutics, Xeris Pharmaceuticals, Inc., Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, MannKind Corporation, Medtronic, Novo Nordisk, Sanofi, Stock/Shareholder; Self; AgaMatrix, Aseko, Inc., Glytec, LLC. J. Clarke: Employee; Self; Aseko, Inc., Stock/Shareholder; Self; Aseko, Inc. J. Messler: Employee; Self; Glytec, LLC. R. Booth: Employee; Self; Glytec, LLC.

The Federal University of Sao Paulo is developing a low-cost insulin infusion pump in cooperation with a Brazilian company to provide an affordable treatment option for individuals with type 1 diabetes, especially from low-incoming countries. Risk management according to standard ISO 14971 is required for certification and safe use of the insulin pump. This paper describes the risk management performed to include safeguards in the architectural design of the insulin pump in development. The risk management process activities were carried out simultaneously and integrated with equipment development, generating requirements to protect against adverse effects on safety due to physical components failures, development errors, and user errors. Design solutions for the safety requirements, implemented in hardware and software, were incorporated in the low-cost insulin pump architecture. Comparison with applicable standards and certified insulin infusion pumps showed that these safeguards align with the best practices adopted for this type of equipment.

Objective: Most insulin infusion sets (ISs) are labeled for 2- or 3-days use. The Medtronic EWIS is designed to increase wear time up to 7 days, and demonstrated a 74.8% survival rate (77.8%, excluding inadvertent early removal) in the pivotal trial (ClinicalTrials.gov: NCT04113694). This study reports on study participant satisfaction during the EWIS pivotal trial. Method: This multi-center (15), single-arm, non-randomized, non-inferiority trial in 259 participants (18-80yrs) with T1D using the MiniMed™ 670G system (with Humalog™ or Novolog™ insulin) involved wearing a 2- or 3-day IS for 2 weeks (run-in) followed by 12 consecutive EWIS wears (study phase). The latter was worn for ≥174 hours or until set failure. Participants completed a Medtronic Likert-based questionnaire at baseline and study exit. The averaged paired change in score at study-baseline was determined (Wilcoxon signed-rank test). Result: Reported satisfaction data during 2- or 3-day IS versus EWIS wear (Figure) show that ease and convenience of use, comfort, wear duration and time required to change a set were significantly improved with EWIS (p Conclusion: These findings point to significantly greater satisfaction with the EWIS when compared with a 2- or 3-day IS, which may result in reduced care burden and improved adherence. Disclosure R. L. Brazg: Research Support; Self; Abbott Diabetes, Ascensia Diabetes Care, Lexicon Pharmaceuticals, Inc., Lilly Diabetes, Medtronic, Pfizer Inc., Roche Diagnostic USA, Senseonics. B. Horowitz: Research Support; Self; Abbott Laboratories, BD, Celgene, Crinetics Pharmaceuticals, Gan & Lee Pharmaceuticals, Medtronic, Speaker’s Bureau; Self; AstraZeneca, Lilly Diabetes, Merck & Co., Inc., Novo Nordisk Inc. K. B. Kaiserman: Advisory Panel; Self; Medtronic, Consultant; Self; Medtronic, Employee; Self; MannKind Corporation, Research Support; Self; Medtronic, Speaker’s Bureau; Self; Medtronic, Stock/Shareholder; Self; MannKind Corporation. S. Huang: None. V. Chen: Employee; Self; Medtronic. G. Zhang: Employee; Self; Medtronic. S. Chattaraj: Employee; Self; Medtronic. J. Shin: Employee; Self; Medtronic. R. Vigersky: Employee; Self; Medtronic. T. S. Bailey: Consultant; Self; Abbott Diabetes, LifeScan, Novo Nordisk, Sanofi, Research Support; Self; Abbott, Abbott Diabetes, Biolinq, Capillary Biomedical, Inc., Dexcom, Inc., Eli Lilly and Company, Kowa Research Institute, Inc., Lexicon Pharmaceuticals, Inc., Livongo, Medtronic, Medtrum Technologies, Novo Nordisk, REMD Biotherapeutics, Sanofi, Sanvita, Viacyte, Inc., vTv Therapeutics, Zealand Pharma A/S, Speaker’s Bureau; Self; BD, Medtronic, Sanofi. Y. C. Kudva: Research Support; Self; Dexcom, Inc. S. K. Garg: Advisory Panel; Self; Eli Lilly and Company, Medtronic, Novo Nordisk Inc., Zealand Pharma A/S, Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Medtronic. G. Grunberger: Research Support; Self; Medtronic, Speaker’s Bureau; Self; Abbott Diabetes, Eli Lilly and Company, Novo Nordisk. A. Cavale: Research Support; Self; Eli Lilly and Company, Medtronic. J. Thrasher: Advisory Panel; Self; Medtronic, Board Member; Self; Medtronic, Consultant; Self; Medtronic, Research Support; Self; Eli Lilly and Company, Lexicon Pharmaceuticals, Inc., Medtronic, Mylan N. V., Novo Nordisk, Sanofi, Speaker’s Bureau; Self; AstraZeneca, Janssen Pharmaceuticals, Inc., Medtronic, Sanofi. A. Bhargava: Research Support; Self; Abbott, AbbVie Inc., Amgen Inc., Boehringer Ingelheim Pharmaceuticals, Inc., Boston Therapeutics, Inc., Covance Inc., Dexcom, Inc., Eli Lilly and Company, Gan & Lee Pharmaceuticals, Insulet Corporation, Janssen Research & Development, LLC, Kowa Pharmaceuticals America, Inc., Madrigal Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Mylan N. V., Novo Nordisk, Poxel SA, Quintiles, Sanofi, Senseonics, Tolerion, Inc., Viking Therapeutics. B. A. Buckingham: Advisory Panel; Self; Medtronic, Tolerion, Inc., Research Support; Self; Beta Bionics, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care.

Background Severe insulin resistance is an uncommon finding in patients with type 2 diabetes but is often associated with difficult to managing blood glucose. While severe insulin resistance is most frequently seen in the setting of medication side effects or rare genetic conditions, this report of two cases highlights the presence of severe insulin resistance in the setting of severe COVID-19 and explores how this may contribute to the poor prognosis of patients with diabetes who become infected with SARS-CoV-2. Case presentation Here we present the cases of two African-American women with pre-existing type 2 diabetes who developed severe COVID-19 requiring mechanical ventilation and concurrent severe insulin resistance with total daily insulin dose requirements of greater than 5 unit/kg. Both patients received aggressive insulin infusion and subcutaneous insulin therapy to obtain adequate glucose management. As their COVID-19 clinical course improved, their severe insulin resistance improved as well. Conclusions The association between critical illness and hyperglycemia is well documented in the literature, however severe insulin resistance is not commonly identified and may represent a unique clinical feature of the interaction between SARS-CoV-2 infection and type 2 diabetes.

Since 2001, various glycemic control (GC) studies have been conducted to reduce dysglycemia in critically ill patients. To prove their effectiveness, each proposed GC approach requires not only patient clinical results, but also users assessments. This paper presents International Islamic University Malaysia Medical Centre intensive care unit (ICU) staff perceptions and assessments of human factors of Stochastic Targeted (STAR) protocol usage based on a Malaysian pilot trial to analyze the users responses to the protocol in the Malaysian set-up. STAR protocol is a model-based and automated GC that accounts for the individual patient s metabolic variability. The ICU staff feedback on STAR trial was based on 13 survey questions. The survey demonstrated that 87.5% of ICU staff agreed that STAR protocol improved patient s outcome, and is user friendly. Human factor assessment quantifies the different interventions recorded from STAR historical and manual bedside records for a total of 31 diabetes mellitus (DM) and non-diabetes mellitus (NDM) patients. During a total of 6168 hours in ICU stays, the percentage of compliance in blood glucose (BG) measurements, insulin infusion, and nutrition administered for DM and NDM cohorts were 97.3%/97.2%, 74.1%/70.3% and 65%/71.2%, respectively. © 2019 Institute of Electronics and Information Engineers. All rights reserved.

To evaluate the effectiveness of predictive low glucose suspend (PLGS) systems within sensor-augmented insulin infusion pumps at preventing nocturnal hypoglycemia in patients with type 1 diabetes (DM1), we performed a systematic review and meta-analysis of randomized crossover trials. Pubmed and Google Scholar were searched for randomized crossover trials, published between January 2013 and July 2018, in nonpregnant outpatients with DM1, which compared event rates during PLGS overnight periods and non-PLGS overnight periods. The primary outcome was the proportion of overnight periods with one or more hypoglycemic measurement. When available, individual patient data were used to assess the effect of clustering measurements within patients. Four studies (272 patients, 10,735 patient-nights: 5422 PLGS and 5313 non-PLGS) were included in the meta-analysis. Two studies reported patient-level data that permitted assessment of the effect of clustering measurements within patients. The effect on the risk difference was minimal. The proportion of overnight periods with one or more episodes of hypoglycemia was 19.6% for the PLGS periods and 27.8% for the non-PLGS periods. Based on the pooled estimate, PLGS overnight periods were associated with an 8.8% lower risk of hypoglycemia (risk difference -0.088; 95% CI -0.119 to -0.056

In patients admitted to a neurocritical care (NCC) unit, management of blood glucose concentration (BGC) is a challenging clinical task. Several studies have shown that episodes of hypo- and hyperglycemia and high BGC variability are associated with poor short- and long-term outcomes. Optimal BGC target-range and BGC management in NCC patients have dramatically evolved in the past decades and new insulin infusion and adequate nutrition protocols are now available. The aim of this narrative review is to report the state-of-the-art on clinical relevance on BGC and hyperglycemia management in NCC patients.

ContextLittle is known about the individual response of glucose-regulating factors to administration of exogenous insulin infusion in extremely preterm infants.ObjectiveTo evaluate longitudinal serum concentrations of insulin, C-peptide, and plasma glucose levels in a high-frequency sampling regimen in extremely preterm infants treated with insulin because of hyperglycemia.DesignProspective longitudinal cohort study.SettingTwo university hospitals in Sweden between December 2015 and September 2016.Patients and InterventionSerum samples were obtained from nine extremely preterm infants, gestational age between 22 (+3) and 26 (+5) weeks (+ days), with hyperglycemia (plasma-glucose >10 mmol/L) at the start of insulin infusion, at 12, 24, and every 24 hours thereafter during ongoing infusion, and 12, 24, and 72 hours after the end of insulin infusion.Main outcome measuresLongitudinal serum concentrations of insulin and C-peptide and plasma glucose levels.ResultsDuring insulin infusion, the serum C-peptide concentrations decreased compared with at start of infusion (P = 0.036), and then increased after ending the infusion. Individual insulin sensitivity based on the nonfasting plasma glucose/insulin ratio at the start of insulin infusion correlated with the initial decrease in serum ΔC-peptide[after 12h] (P = 0.007) and the degree of lasting decrease in serum ΔC-peptide[after end of infusion] (P = 0.015).ConclusionExogenous insulin infusion suppressed the C-peptide concentration to individually different degrees. In addition, the effect of insulin infusion on β cells may be linked to individual insulin sensitivity, where a low insulin sensitivity resulted in a more pronounced decrease in C-peptide during insulin infusion.

People with type 1 diabetes must control their blood glucose level through insulin infusion either with several daily injections or with an insulin pump. However, estimating the required insulin dose is not easy. Recommender systems, mainly based on Case-Based Reasoning (CBR), are being developed to provide recommendations to users. These systems are designed to keep the experiences or cases of the user in a case-base, which requires maintenance to keep system's response accurate and efficient. This paper proposes a case-base maintenance methodology that combines case-base redundancy reduction and attribute weight learning. Contrary to previous approaches designed for classification problems, the maintenance methodology presented in this paper deals with numerical recommendations. It can manage a potentially huge case-base due to the combinatorial derived from the number of attributes used to represent a case. The proposed approach has been tested using the UVA/PADOVA type 1 diabetes simulator and the results demonstrate that it can accomplish better levels of accuracy than other insulin recommender systems mentioned in the literature, when a large number of attributes is considered This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No. 689810, www.pepper.eu.com/, PEPPER, and the grant of the University of Girona 20162018 (MPCUdG2016). The work has been developed with the support of the research group SITES awarded with distinction by the Generalitat de Catalunya (SGR 20142016)

Recent work, Goodwin et al. (2015, 2018), has established that, subject to an assumption regarding the relative blood glucose response times of meal and insulin, it is optimal for the minimisation of the peak blood glucose excursion to apply a bolus of insulin at the time of (or slightly prior to) meal ingestion. A key assumption underlying this result is that the impact of an impulse of insulin “lasts longer” than the impact of an impulse of food. The result is consistent with clinical trials reported in Lopez et al. (2014) . In the current paper we consider the converse situation where the response of the meal lasts longer than the response of an insulin impulse. The latter situation is known to arise in certain circumstances e.g., when low glycaemic index and/or hi-fat/hi-protein meals are consumed (Bell et al., 2015; Lodefalk et al., 2008; van der Hoogt et al., 2017). We consider the same set-up as in Goodwin et al. (2015). However, here we show that, when the response of the meal lasts longer than the response of an insulin impulse, it is optimal to use an open-loop policy combining an insulin bolus (applied with the meal) and a specific form of decaying insulin flow thereafter. This gives support to results for clinical trials, reported in Lopez et al. (2017). However, as far as we are aware, no earlier work has given a methodology to quantify the best insulin flow after the initial bolus nor the best split between bolus and post-bolus insulin flow. In support of the theory, we apply the results to a model obtained from clinical trials on a real subject with Type 1 diabetes and include a discussion of open-loop versus closed-loop policies.

Background and objective: The effects of age and related factors on insulin sensitivity have not been definitively evaluated in East Asian populations. We proposed a reference range for the glucose disposal rate (M-value) on hyperinsulinemic-euglycemic study and its association with other parameters. Methods: Healthy, non-diabetic young (n=10) and elderly (n=13) male subjects with normal body mass index were eligible for this study. Subjects who passed the oral glucose tolerance test (OGTT) underwent hyperinsulinemic-euglycemic clamp with high-dose (80 mU/m2·min) insulin infusion. Results: M-values were normalized to body weight (MBW) and fat-free mass (MFFM). Neither M-value was significantly different between age groups (P=0.458 and P=0.900, respectively). An inverse correlation was observed between MFFM and baseline insulin (r=-0.418; P=0.047), baseline C-peptide (r=-0.426; P=0.043) and OGTT 2-hour glucose (r=-0.452; P=0.030). Regarding correlations with other insulin sensitivity indices, M-values were positively associated with the Matsuda index but not with homeostasis model assessment of insulin resistance. Conclusion: Our results suggest that age is not a critical determinant of insulin sensitivity, while fasting insulin and C-peptide levels, OGTT 2-hour glucose level, and Matsuda index are predictable markers of insulin sensitivity in healthy Koreans.

Insulin infusion pump, continuous glucose monitoring (CGM), and insulin infusion set (IIS) have been developed to be increasingly feasible for people with type 1 diabetes (T1D). Several recently approved CGMs are transitioning from 7-day to 10-day wear time without the need for fingerprick recalibration. Nevertheless, studies and improvements on IIS, a critical part of insulin pump therapy, have been limited. In particular, the recommended wear time of IIS is still 2-3 days, which can hardly match the current duration of CGM for potential closed-loop system development. It is generally believed that both the inserted catheter and the subsequent infused insulin drug could induce particular subcutaneous tissue response and skin-related complications at the infusion site. In certain cases, poor glycaemic control, increased risk of hypoglycemia, and serious cosmetic impact on people with diabetes were observed. Skin complication has also been attributed as an important factor resulting users to discontinue insulin pump therapy. This article provides the rare systematic review of IIS induced subcutaneous tissue responses and skin complications, including the impacts from the inserted catheters, the subcutaneous infused insulin, and the adhesive or tape used to immobilize the catheter. The FDA’s recommendation for the frequency of IIS change was further discussed. Future studies on this topic are required to further understand the IIS-related problems, and future strategies could be developed accordingly to significantly reduce the incidence of these problems, extend the wear time, and increase the acceptance of insulin pump based therapy.

People with type 1 diabetes (T1D) must estimate the carbohydrate (CHO) content in meals to compute the bolus insulin correctly. To release T1D patients from the cumbersome task of counting CHO, we develop a method for detecting meals that can be used in blood glucose (BG) control. The algorithm detects a meal and estimates the meal onset and the amount of CHO. The inputs of the meal detector are the continuous glucose monitoring (CGM) data and the insulin infusion rate. We use second-order linear input-output models for insulin to subcutaneous glucose dynamics and for CHO to subcutaneous glucose dynamics. The models are converted to a linear discrete-time state-space model. A white noise double integrator models the unknown meal disturbances. The state-space model is augmented with the unknown meal disturbance (CHO ingestion rate) and a Kalman filter (KF) estimates the CHO rate (g/min). The algorithm uses two tests to announce a meal. The first test is a cumulative sum algorithm that detects changes in the KF innovation and estimates the onset of change. The second test is comparison of the estimated CHO rate with a threshold to detect a change in the rate. If both tests simultaneously detect a change, an optimal smoother estimates the meal-size. If the estimated meal-size reaches a certain amount, the algorithm announces a meal. Furthermore, we integrate a bolus calculator (BC) with the meal detector. We test the algorithm for nine virtual T1D patients. In total, the patients eat 45 meals in 13.5 days. The detection sensitivity is 93% and the detection delay has a median of 40 min. The median of the meal onset estimation bias is 5 min. Out of 42 detected meals, the algorithm underestimates 26 meals with a median bias of −19 g, and it overestimates 16 meals with a median bias of 21 g. The meal detector with the BC reduces the BG postprandial peak from 274 mg/dL (unbolused meals) to 207 mg/dL, and it increases the mean time in euglycemia from 50% to 79%. The meal detector combined with the BC improves glycemia for the virtual patients in this study.

Objective: Trans-catheter Aortic Valve Replacement/Aortic Valve Implantation (TAVR) are increasingly performed today. We compared insulin requirements between TAVR and Surgical Aortic Valve Replacement (SAVR) patients with and without diabetes mellitus (DM) to determine optimal glucose management strategies during the perioperative period (POP). Methods: Charts of consecutive patients undergoing aortic procedures were retrospectively reviewed for glucose ranges, insulin requirements and routes of insulin administration (subcutaneous vs. intravenous) for patients with and without DM to maintain BG < 180 mg/dl and compared between the surgical and trans-catheter groups. Results: Patients with SAVRs without DM and A1C < 6.5%, needed low dose insulin infusions and could be transitioned to subcutaneous insulin by 1.5 postoperative days. Patients with SAVR and DM had higher insulin requirements and were transitioned by 2.5 postoperative days. Patients with TAVR with no known DM did not need an insulin infusion in the perioperative period. Patients with TAVR with DM and an HbA1C < 6.5% did not require insulin infusions during the procedure but only postoperatively for short periods. Patients with DM and A1C ≥ 6.5%, required higher doses of insulin infusion and transitioned to subcutaneous insulin by postoperative day 1. Conclusions: TAVR patients have different insulin requirements compared to SAVRs (p < 0.05). This information helps build a glucose management algorithm for a procedure which is increasingly performed.

This paper presents an active disturbance rejection control scheme to automatically regulate the glucose level in type 1 diabetic patients. Although the blood glucose system is nonlinear, in this control approach, it is represented as a linear perturbed system, whose lumped disturbance input is estimated by an Extended State Observer (ESO) and then compensated by an robust controller tuned with Quantitative Feedback Theory (QFT). The robust control scheme uses a Smith predictor for the time delay compensation and allows taking into account the inter-patient variability presented in the glucose control problem. In order to validate the effectiveness of this approach, the controller is tested in silico on a cohort of adult patients of the UVA/Padova metabolic simulator, which has been accepted by the Food and Drug Administration (FDA). In silico results indicate that safe blood glucose control can be achieved by the proposed controller.

Aims Although diabetic ketoacidosis (DKA) commonly presents as a pure diabetic ketoacidosis (PDKA), up to 30% of cases may be associated with a mixed hypochloremic metabolic alkalosis (HMA). It is unknown whether there is a difference in treatment outcomes between these two entities. We evaluated an insulin infusion protocol (IIP), previously validated for hyperglycemia management in ICU's, for the management of PDKA and HMA. Materials and methods A retrospective case series/cohort study of 41 DKA admissions was further characterized as having PDKA or HMA. HMA was defined in those having an elevated delta-delta gradient (ΔAG-ΔHCO3) ≥ 5 mmol/L and base excess chloride (BECl) > 2.7 mmol/L. The main outcome measures were times to recovery of glucose levels to ≤250 mg/dL and of anion gap to ≤12 mmol/L. Results The initial serum glucose was 553 ± 265 mg/dL, serum bicarbonate of 8.8 ± 5.1 mmol/L, and venous pH 7.13 ± 0.2). Recovery of glucose occurred in 5 h: 25 min (±3 h:39min), and for anion gap in 11 h:25 min (±6 h:56min). HMA compared with PDKA had a delayed recovery of serum glucose (7 h: 23min ± 3 h: 35min vs. 4 h: 31min ± 3:h:21min, p = 0.017), which was due to the higher initial level of glucose (p = 0.02) rather than level of BECl (p = 0.17). There was no difference in time to anion gap closure between the PDKA and HMA. Conclusions Correction of hyperglycemia and acidosis in PDKA as well as in HMA was managed through the IIP. The simultaneous fluid and electrolyte management corrected the hypochloremic alkalosis.

Background: Patients with Diabetes Mellitus (DM) are required to have long-term treatment regimen and strict selfmanagement, which thus might lead to the Diabetes Distress (DD). Patients’ DD varies in different regions with different levels of medical conditions. For improving the treatment effect of the patients with the Type-2-Diabetes-Mellitus (T2DM), this study explores the influencing factors of the patients’ DD in the regions where the medical treatment are at low level. Subjects and methods: In this study, 167 adult patients with T2DM were selected from the People’s Hospital of Jinhua city, an A-grade hospital of a small-mid-sized city in Eastern China. Based on these samples, the Diabetes Distress Scale with 17 items (DDS17) was adopted to measure the degree of patients’ DD, and then regression analyses were carried out to investigate the influencing factors for their DD. Results: The T2DM patients with moderate and high levels of DD take up 54.5% of the samples investigated in this study. According to the Spearman correlation analysis, sleep time, physical exercise, diet control, treatment regimen, TG and HbA1c significantly affect the patients’ DD. Through the multivariate linear regression analysis, this study shows that (1) sleep time significantly influences the T2DM patients’ DD (????=-0.213, P=0.034); (2) sleep time also impacts emotional burden (????=-0.379, P=0.027); (3) physical exercise (????=-0.195, P=0.002), treatment regimen (????=0.158, P=0.026) and diet control (????=0.158, P=0.026) are the three major influencing factors for regimen-related distress. Conclusion: In the small-mid-sized city where the treatment regimen is not highly advanced, to alleviate the T2DM patients’ DD, the medical staff should suggest the patients to improve sleep quality and exercise more, help them positively understand the insulin infusion therapy and take proper diet control.

Adults with metabolic syndrome (MetS) have increased fasting arterial stiffness and altered central hemodynamics that contribute, partly, to increased cardiovascular disease (CVD) risk. Although insulin affects aortic wave reflections in healthy adults, the effects in individuals with MetS are unclear. We hypothesized that insulin stimulation would reduce measures of pressure waveforms and hemodynamics in people with MetS. Thirty-five adults with obesity (27 women; 54.2 ± 6.0 yr; 37.1 ± 4.8 kg/m(2)) were selected for MetS (ATP III criteria) following an overnight fast. Pulse wave analysis was assessed using applanation tonometry before and after a 2-h euglycemic-hyperinsulinemic clamp (90 mg/dL, 40 mU/m(2)/min). Deconvolution analysis was used to decompose the aortic waveform [augmentation index corrected to heart rate of 75 beats/min (AIx@75); augmentation pressure (AP)] into backward and forward pressure components. Aerobic fitness (V̇o(2max)), body composition (DXA), and blood biochemistries were also assessed. Insulin significantly reduced augmentation index (AIx@75, 28.0 ± 9.6 vs. 23.0 ± 9.9%, P < 0.01), augmentation pressure (14.8 ± 6.4 vs. 12.0 ± 5.7 mmHg, P < 0.01), pulse pressure amplification (1.26 ± 0.01 vs. 0.03 ± 0.01, P = 0.01), and inflammation [high-sensitivity C-reactive protein (hsCRP): P = 0.02; matrix metallopeptidase 7 (MMP-7): P = 0.03] compared to fasting. In subgroup analyses to understand HTN influence, there were no insulin stimulation differences on any outcome. V̇o(2max), visceral fat, and blood potassium correlated with fasting AIx@75 (r = −0.39, P = 0.02; r = 0.41, P = 0.03; r = −0.53, P = 0.002). Potassium levels were also associated with insulin-mediated reductions in AP (r = 0.52, P = 0.002). Our results suggest insulin stimulation improves indices of aortic reflection in adults with MetS. NEW & NOTEWORTHY This study is one of the first to investigate the effects of insulin on central and peripheral hemodynamics in adults with metabolic syndrome. We provide evidence that insulin infusion reduces aortic wave reflection, potentially through a reduction in inflammation and/or via a potassium-mediated vascular response.

Continuous subcutaneous insulin infusion (CSII) is becoming increasingly used for achieving target glycemic control as well as providing flexibility in lifestyle. In a widely used version of CSII, the insulin pump itself is attached to one end of an insulin infusion set (IIS), which delivers insulin via a thin flexible plastic tube to the patient’s body via a cannula or needle that is inserted under the skin at the other end of the IIS. Despite the increased use of CSII by patients with diabetes, there have been few recent advances in IIS technology, especially when compared to the many recent advances made in insulin pump technology and in insulin pharmacokinetics. To discuss recent developments in, and future plans for IIS development, Diabetes Technology Society virtually hosted the Advances in Insulin Pump Infusion Sets Symposium on December 1, 2020. This symposium featured experts in the field of IISs, including representatives from Medtronic and ConvaTec (which are two manufacturers that are currently developing IISs), Stanford University, Steno Diabetes Center Copenhagen, and Science Consulting in Diabetes. The webinar’s six speakers covered (1) patient burden, (2) extended wear technology, and (3) future directions in IIS development.

Insulin infusion protocol based on the sliding scale is the standard protocol implemented in Malaysia's Intensive Care Unit (ICU) for controlling the patient's glycemic level. However, patients have a different dynamic and sensitivity toward insulin infusion, which needs close monitoring. The objective of this study is to compare the performance of two sliding scale-based glycemic control protocols (Protocols X and Y) on two different cohorts (cohorts A and B). Insulin sensitivity and patient variability of the patients were modelled using retrospective data, and an established glucose-insulin model. The sliding scale-based was further compared with a model-based glycemic control, Stochastic TARgeted (STAR) to investigate the patient variability and dynamic factors. The results obtained from this study showed that cohort A had more dynamics metabolism with lower mean of insulin sensitivity (50.0 L/mU.min) than cohort B. Protocol X had highest blood glucose (BG) measurements within their target range (6.0-10.0 mmol/L). However, there is no significant mean difference ( $\mathrm{p} > 0.05$ ) in BG level between Protocol X and Protocol Y. The median Acute Physiology and Chronic Health II (APACHE II) score showed the cohort A (26) had more severe patients than cohort B (20) that possibly not responding well towards the insulin therapy. The findings of this study show that the sliding scale-based results in a better BG level than the model-based. Nevertheless, patient variability and dynamics play an essential role in achieving a blood glucose target.

OBJECTIVE: In this review, we address a few key issues and the challenges faced in the management of severe diabetic ketoacidosis (DKA) in children, highlighting the existing standard of care, supported by evidence and bench studies. BACKGROUND: The classic triad of DKA namely hyperglycemia, metabolic acidosis and ketonemia warrants immediate attention with fluids and insulin. Correction of dehydration in DKA is of utmost priority and the calculation of fluid volume and choice of fluid have remained a matter of debate. Insulin therapy, to halt the ketone production, in DKA has undergone wide variations in dose and preparation since its discovery. Although the mortality due to severe DKA has remarkably decreased, complications like cerebral edema and acute kidney injury (AKI) continue to haunt the intensivists and endocrinologists on a few occasions. METHODS: We have selected a few important questions in the management of severe DKA in children, addressing the challenges, reviewing the studies, guidelines and bedside practices with evidence in this narrative review. CONCLUSIONS: The focus of management should be to understand and normalise the deranged physiology rather than trying to get normal laboratory reports. This needs careful understanding of the pathogenesis and deriving conclusion from bench studies. With newer studies and evidence, guidelines are revised every few years. There is a trend towards more conservative therapy, with continuous and advanced monitoring. Switching to subcutaneous insulin and oral hydration is done as early as possible with clinical monitoring and resolution of DKA. Management of severe DKA in children can vary from simple fluid titration and insulin infusion in mild cases to a scenario with multiorgan dysfunction requiring intensive monitoring and advanced organ support. Individualisation of therapy to suit the needs with the available evidence and expertise is extremely essential.

Internet of Things (IoT) technologies aim at creating a better world for human beings and are widely adopted in several industries, including healthcare. One area within the healthcare industry where humans are directly impacted by the use of IoT, is in monitoring of patients with chronic diseases, such as diabetes. The number of patients living with diabetes has increased drastically in recent years and is predicted to keep rising. The use of IoT technologies in monitoring diabetic’s health, such as continuous glucose monitoring (CGM) and Insulin infusion pumps, is believed to improve the life-quality of diabetic patients. Although IoT offers numerous benefits within monitoring diabetes, however there are several challenging issues concerning privacy and security. Existing reports show that, out of those using IoT in healthcare, 89% have suffered an IoT-related security breach, yet more than 80% of consumers are willing to wear technology to monitor their health. In this study, we have conducted a review of literature, and we complimented it with semi-structured interviews. Our findings suggest that diabetics consider their data not to be valuable to privacy violators and consider that the life-improving qualities by using those devices as more rewarding than the potential harm or abuse of their data may cause.