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The lecture deals with the topical issues of treating elderly and senile patients with diabetes mellitus (DM). The number of such people with type 2 DM is steadily increasing. The management of this category of patients should be individual and include adequate correction of hyperglycemia to prevent microvascular complications, as well as hypoglycemic episodes, to reduce cardiovascular mortality and to maintain the quality of life. The basic data about clinical features of DM and application of antihyperglycemic preparations in elderly and senile patients are presented. Special attention is paid to the target levels of glycemic control.

Accurate prediction of blood glucose variations in type 2 diabetes (T2D) will facilitate better glycemic control and decrease the occurrence of hypoglycemic episodes as well as the morbidity and mortality associated with T2D, hence increasing the quality of life of patients. Owing to the complexity of the blood glucose dynamics, it is difficult to design accurate predictive models in every circumstance, i.e., hypo/normo/hyperglycemic events. We developed deep-learning methods to predict patient-specific blood glucose during various time horizons in the immediate future using patient-specific every 30-min long glucose measurements by the continuous glucose monitoring (CGM) to predict future glucose levels in 5 min to 1 h. In general, the major challenges to address are (1) the dataset of each patient is often too small to train a patient-specific deep-learning model, and (2) the dataset is usually highly imbalanced given that hypo- and hyperglycemic episodes are usually much less common than normoglycemia. We tackle these two challenges using transfer learning and data augmentation, respectively. We systematically examined three neural network architectures, different loss functions, four transfer-learning strategies, and four data augmentation techniques, including mixup and generative models. Taken together, utilizing these methodologies we achieved over 95% prediction accuracy and 90% sensitivity for a time period within the clinically useful 1 h prediction horizon that would allow a patient to react and correct either hypoglycemia and/or hyperglycemia. We have also demonstrated that the same network architecture and transfer-learning methods perform well for the type 1 diabetes OhioT1DM public dataset.

Background and aims To determine the efficacy of i-Port Advance system on patients satisfaction and glycemic control among patients with type 1 diabetes (T1D). Methods This prospective study was performed among 73 patients with T1D (13–29 years) at Prince Sultan Military Medical City, Riyadh, Saudi Arabia. Demographic data were collected at baseline and clinical characteristics were collected at baseline and 12 weeks. Patients’ responses to Morisky Medication Adherence Scale (MMAS-8) and Insulin Delivery Satisfaction Survey (IDSS) were recorded at baseline and 12 weeks after initiating the i-Port Advance system. Results At 12 weeks, significant improvement was evident in the IDSS subscales, which comprises the IDSS effective (p = 0.048), burdensome (p = 0.032), and IDSS inconvenient (p = 0.001), with the total baseline IDSS score being 2.6 ± 0.42, and at 12 weeks being 3.7 ± 0.72 (p = 0.037). The MMAS total score at baseline was 4.6 ± 1.2, and at 12 weeks, it increased to 6.4 (p = 0.028). HbA1c level was 8.4% at baseline and decreased to 7.9% (p = 0.001) at 12 weeks. The total daily dose of insulin at baseline registered 0.9 ± 0.13, which declined to 0.8 ± 0.12 (p = 0.048) at 12 weeks. Fasting blood sugar value was 197 ± 23.4 at baseline, which dropped to 182 ± 24.5 at 12 weeks (p = 0.01); and the postprandial glucose at baseline was 195 ± 21.4 and declined to 177 ± 19.2 at 12 weeks (p = 0.01). The hypoglycemic episodes revealed a noteworthy reduction after the i-Port Advance system usage. Conclusion Use of i-Port Advance system was found to raise the patients’ satisfaction levels and lower both the hypoglycemic episodes as well as the HbA1c levels.

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.

Dear Dr. Martin Hovland, We learned from the literature that premixed insulins are short-acting insulin or rapid-acting insulin analogue mixed with intermediate-acting insulin in a fixed ratio, addressing FBG and PPBG in one injection. There are two categories; high-mix and low-mix premixed insulins. We, a Saudi task force, gathered to develop an explicit, evidence-based consensus for the use of the low-mix premixed insulin for better glycemic control. The treatment with premixed aspart 30 was non-inferior to treatment with premixed insulin lispro 25. In addition, Self-monitored blood glucose levels were comparable. Safety profiles were similar between both treatments, as was the incidence of hypoglycemic episodes. The switch between both products of the low-mix family can be carried out without any problem. Both products of the low-mix premixed insulin analogues aspart 30/70 and premixed insulin lispro 25/75 have comparable efficacy and safety as shown from the medical literature. Therefore, we can change from one to another safely as demonstrated by the US FDA statement. In addition, the ergonomic features of KwikPen’s design and function may offer important advantages for the user during insulin administration.

We present a patient with intractable and debilitating pain secondary to chronic pancreatitis who was effectively treated with total pancreatectomy with islet autotransplantation (TPIAT). Islets engrafted into his liver significantly contributed to improved blood glucose control and quality of life. Subsequently, the patient developed alcohol related acute liver failure and en bloc liver and pancreas transplantation was performed to replace the failing liver with engrafted islets. Pancreas transplantation was required to resolve his life-threatening severe hypoglycemic episodes. Herein, we detail an innovative and multidisciplinary management of this complex medical problem.

Objective: To delineate the effect of self-gained information through internet on glycemic control and overall QoL in type 1 diabetes patient. Methodology: 35 type 1 diabetes patients, who had reasonably good glycemic control were classified by a single clinician into net- savvy and ordinary based on their behaviour towards use of internet to gather information regarding health queries and their glycemic control and QoL analysed.WHO-5 questionnaire which is used in clinical practise was applied. Result: Of net savvy group (n=18), 14 (82%) had WHO-5 score greater than 13 while among ordinary (n=17) only 7 had WHO5 of same range. Thus, those who surfed internet were in general likely to have better QoL. Among net savvy group all had individual smart phones and used google as search engine. Among ordinary, 40% (9/17) had smart phones. The mean HbA1c of net savvy group was 7.2 which was lower than that of ordinary group mean HbA1c of 7.6. Those of net savvy group were more likely to agree to increase in number of s.c. insulin injections (12/18) as compared to ordinary group (4/17). The self-reported hypoglycemia episodes were also more in net savvy group (6/ person-week) as compared to ordinary (2/ person- week). Conclusion: Use of smart search engines like google (with strong in-built Artificial Intelligence (AI) systems), even if unsupervised, should be encouraged as part of DSME in type 1 Diabetes patients for optimizing glycemic control and detecting hypoglycemic episodes.

OBJECTIVE The aim of the study was to evaluate efficacy of chemoembolization and radioembolization in treating patients with recurrent hypoglycemia secondary to metastatic insulinoma. METHODS A retrospective review was performed of all patients with metastatic insulinoma treated with liver-directed therapy (LDT) at a large academic medical center from January 1998 to August 2017. Primary outcomes included blood glucose levels, occurrence of symptomatic hypoglycemic episodes, and tumor imaging response rates. RESULTS Seven patients were identified (4 male patients). The mean age at the first LDT was 60.9 (standard deviation [SD], 9.2) years. The median follow-up was 1.8 years. Thirty-three sessions of LDT were performed including 30 sessions of chemoembolization and 3 sessions of radioembolization. Technical success rate was 97% (32/33 procedures) with an initial clinical success rate of 100%, defined as absence of recurrent symptomatic hypoglycemia within 1 month after first cycle of LDT and overall clinical success rate of 85%. Random daytime glucose levels increased from 75.0 (SD, 26) mg/dL to 152.8 (SD, 52.4) mg/dL after LDT. The mean time to recurrence of intractable hypoglycemia was 21 (SD, 9) months. No severe complications were reported. CONCLUSIONS Liver-directed therapy with chemoembolization or radioembolization is effective for treatment of symptomatic hypoglycemia secondary to malignant insulinoma metastatic to liver.

Glycogen storage diseases (GSDs) are a group of genetic disorders that occur in approximately 1 in 100,000 individuals depending on the subtype. Patients with GSD type I lack glucose-6 phosphate, 1 of the enzymes needed to convert glycogen to glucose during times of fasting. GSD type I is the most severe form because of the risk of life-threatening hypoglycemic episodes. Patients with GSDs require a team of professionals who specialize in metabolic disorders to monitor and manage their disease because of its complex nature. However, many of these patients live a distance from a GSD center and require episodic/sporadic care. Nurse practitioners need to be aware of this special subset of patients in the event they arrive for care at their local hospital’s emergency room. This article presents information on the pathophysiology of GSDs and outlines the recognition and management of these rare diseases.

The aim of the present study was to examine whether an elderly subject without diabetes experiences hypoglycemia during his daily life or after an oral glucose tolerance test (OGTT), and investigate whether hypoglycemic episodes affect cognitive function. The 85-year-old healthy subject, who is a sports enthusiast, showed lower than normal (

BACKGROUND Severe hypoglycemic episodes are life-threatening events demanding rapid administration of glucagon by a caregiver or bystander. The glucagon analog dasiglucagon is stable in aqueous formulation and therefore suitable for delivery in a ready-to-use autoinjector, potentially increasing speed and ease of use compared with standard glucagon emergency kits (GEKs). METHODS In an open-label, randomized, crossover, comparative device handling study, trained caregivers and untrained bystanders administered the dasiglucagon autoinjector or Eli Lilly GEK to manikins in a simulated emergency hypoglycemia situation. RESULTS In total, 54 participants were randomized (18 patient-caregiver pairs and 18 bystanders). Overall, 94% of trained caregivers were able to administer the dasiglucagon autoinjector successfully within 15 minutes, compared with 56% for the GEK (P

Type 1 diabetes mellitus (T1DM) is caused by autoimmune destruction of pancreatic β cells, which results in little or no insulin production. Islet transplantation plays an important role in the treatment of T1DM, with the improved glycometabolic control, the reduced progression of complications, the reduction of hypoglycemic episodes when compared with traditional insulin therapy. The results of phase III clinical trial also demonstrated the safety and efficacy of islet allotransplantation in T1DM. However, the shortage of pancreas donors limits its widespread use. Animals as a source of islets such as the pig offer an alternative choice. Because the architecture of the pig pancreas is different from the islets of mice or humans, the pig islet isolation procedure is still challenging. Since the translation of alternative porcine islet sources (xenogeneic) to the clinical setting for treating T1DM through cellular transplantation is of great importance, a cost-effective, standardized, and reproducible protocol for isolating porcine islets is urgently needed. This manuscript describes a simplified and cost-effective method to isolate and purify adult porcine islets based on the previous protocols that have successfully transplanted porcine islets to non-human primates. This will be a beginners guide without the use of specialized equipment such as a COBE 2991 Cell Processor.

Persistent hypoglycemia in infants with congenital hyperinsulinism (CHI) can be challenging in approximately half of these cases, even after undergoing a near-total pancreatectomy. While maltodextrin has been recommended in the nutritional management of CHI cases younger than six months, facts about its efficacy in managing hypoglycemia are not yet clear. Here, we present a male infant with CHI who experienced persistent hypoglycemia even after undergoing a near-total pancreatectomy and despite multiple medical treatments. The infant's hypoglycemic episodes were successfully controlled by adding maltodextrin to his diet.

Navigating safely towards euglycemia in type 2 diabetes mellitus (T2DM) is a real challenge in the current clinical practice despite availability of a number of glucose-lowering drugs; major barriers are hypoglycemia and weight gain. Sulfonylureas (SUs) have been recommended as one of the most common choice of add-on therapy to metformin (used as first line therapy). They are used extensively in Southeast Asia due to their high efficacy and low cost. However, there have been concerns regarding hypoglycemia, weight gain and cardiovascular safety with SUs. There is a need for an oral molecule that does not cause weight gain, has low risk of causing hypoglycemia, which can be used to navigate safely towards euglycemia with minimal constraints. Literature has shown that gliclazide provides consistent glycemic control with fewer hypoglycemic episodes and has long-term micro- and macrovascular benefits. This expert opinion was developed to highlight the role of SUs, and gliclazide in particular, in navigating effectively and safely towards the desired glycemic control in T2DM.

The primary goal of this study was to explore physical activity (PA) levels, hypoglycemia fear scores and hypoglycemia episodes according to insulin administration and blood glucose monitoring methods in youth with type 1 diabetes (T1D). A self-administered questionnaire was completed by 28 children and 33 adolescents with T1D, and their PA was assessed. Hypoglycemia episodes, fear of hypoglycemia scores, insulin therapy (pump vs. injection) and blood glucose monitoring (continuous blood glucose monitors [CGMs] vs. blood glucose meters) methods are reported in the present work. There were no significant differences in the number of hypoglycemic episodes, child hypoglycemia fear survey behavior or total scores, or any components of the PA profile between youth using injections and those using a pump. However, these variables differed significantly when compared according to blood glucose monitoring method (CGMs vs. blood glucose meters): 41.2 vs. 81.8, pvs. 2.6 ± 0.63, pvs. 2.94 ± 0.22, pvs. 49 ± 11, p

Acute to subacute onset chorea is commonly due to stroke, metabolic, post-infectious, and autoimmune disorders. Chorea in diabetes (DM) patient is mostly due to hyperglycemia, and few cases were reported due to hypoglycemia. The mechanism at the cellular level is still evolving. The MRI changes in diabetic chorea patients are variably reported. It is important to discuss our patient with hypoglycemic hemichorea because of unique features like low BMI, recently diagnosed DM on sulphonylurea with a history of hypoglycemic episodes, and acute left hemichorea that was controlled with neuroleptics, and her MRI brain showed reversible lentiform nucleus T1 hyperintensity without diffusion restriction and blooming on SWI.

Introduction: The ADEMOLUS HYPOGLYCEMIC INDEX (AHI) is proposed in this article as a mathematical representation of a hypoglycemic episode in a patient with recurrent hypoglycemia over a three-month period. Methodology: This is a retrospective analysis of 65 hypoglycemia episodes (HE) that occurred in six randomly selected diabetes mellitus patients from 86 case files analysed at the Lagos State University Teaching Hospital in Ikeja, Lagos, Nigeria. The data was examined using the Ademolus Hypoglycemia Classification and the 2018 ADA/EASD Hypoglycemia Classification to determine hypoglycemia. The proposed mathematical formula was used to derive AHI from the HE. The data was analysed using SPSS version 23. Results: The ADEMOLUS HYPOGLYCEMIC INDEX was used to investigate 65 hypoglycemic episodes in six diabetic patients. All six individuals experienced a succession of hypoglycemic episodes over the course of three months. Using both the ACH and the ADA/EASD classifications, Patient 1 had an AHI of 0.53. Discussion: In patient 1 her AHI was not in the severe range. In patient 3, in the last quarter of 2016, her AHI was 0.60, in the first quarter of 2017, her AHI was zero, then between June, July and August 2017 her AHI was 0.64. At this point in the patient's care, it would be prudent to assess the aetiological reasons in this diabetic patient with chronic kidney disease who suffers recurrent hypoglycemia, as it was six months ago. The formula can be programmed or computerized into a device like a calculator and/or a designed webpage calculator on ADEMOLUS HYPOGLYCEMIC INDEX can be developed. Conclusion: The Ademolus Hypoglycemic Index (AHI) is useful for tracking chronic or long-term recurrent HE in diabetic and non-diabetic patients.

A 48-year-old man, a case of metastatic insulinoma, who failed transarterial chemoembolization of liver metastases underwent multiple cycles of peptide receptor radionuclide therapy with 177Lu-DOTATATE, following which a complete morphologic and metabolic response was demonstrated on 68Ga-DOTATATE PET/CT. Patient had a remarkable improvement in his quality of life as intractable hypoglycemic episodes resolved after treatment. Peptide receptor radionuclide therapy is a promising targeted radionuclide therapy in patients of metastatic insulinomas that can result in reduced tumor burden and improved quality of life, particularly those who fail the conventional treatment modalities as seen in the present case.

Aims Ramadan is a holy month for the Muslim community. Fasting Ramadan is directed by a systematic alteration in eating habits, sleeping times, and daily physical activities that optimize blood glucose levels. This study aims to evaluate the effects of structured education on safe fasting among diabetic patients. Methods This study included diabetic patients with eligibility for the Ramadan fast. The control group included 494 patients who received standard diabetes education, while the intervention group included 407 patients who attained structured diabetes education. The patients were required to register their responses following the written, structured questionnaires before and after Ramadan fasts. In addition, patients were advised to keep a log of their hypoglycemic episodes. Result This study showed that structured diabetes education improved the blood glucose levels/glycemic control and outcomes of patients during their Ramadan fasting. The structured diabetes education helped reduce the incidence of hypoglycemic events and hyperglycemic crises. It also increased the acceptance and frequency of blood sugar level measurements among patients during Ramadan. Conclusion The standard diabetes management plan should include structured diabetes education measures to improve outcomes effectively. The providers should screen the patients with diabetes before Ramadan and educate them to improve their safe fasting practices.

DPP-4 inhibitors may prevent hypoglycemic episodes in insulin-treated type 2 diabetes (T2D), but mechanisms are unclear. 20 T2D patients treated with basal insulin and metformin (± other agents) were recruited for two randomized treatments (placebo or 100 mg/d sitagliptin) in addition to insulin glargine/metformin; 17 completed (3 women, 14 men; age 57 ± 7 yrs.; BMI 28.8 ± 3.9 kg/m2; HbA1c 7.4 ± 0.7 %). After titrating fasting plasma glucose (PG) to 90-110 mg/dl, patients were observed during a 3-day (d) inpatient period with exposure to oral glucose or lipid loads, strenuous exercise and fasting, while increasing insulin doses to 110, and 120 % of the titrated dose before d 2 and 3, respectively. Hypoglycemic episodes (PG < 70 mg/dl) were identified by measuring venous plasma glucose or symptoms, and prompted the determination of counter-regulatory hormones at the glucose nadir and 30 and 60 min later. After titrating insulin glargine, fasting PG was 112 ± 5 and 107 ± 5 mg/dl with placebo and sitagliptin treatment, respectively. Concentrations of insulin, C-peptide and counterregulatory hormones were similar during both treatments. Hypoglycemic episodes were mainly nocturnal (10 p.m. to 7 a.m.), with a similar PG nadir (65 ± 4 mg/dl) and incidence with placebo and sitagliptin (4.5 ± 3.2 vs. 4.6 ± 3.6 episodes per patient, respectively, p = 0.96). With a similar incidence of daytime (7 a.m. to 10 p.m.) chemical hypoglycemia, the incidence of symptomatic episodes was higher with sitagliptin (0.2 ± 0.4 vs. 0.0 ± 0.0, p = 0.028). Counter-regulatory responses were suppressed by sitagliptin for cortisol (p = 0.022), unchanged for glucagon, HGH, noradrenaline and prolactin, and accentuated for adrenaline (p = 0.022). Our results suggest that sitagliptin treatment augments counter-regulatory responses of adrenaline at minimal degrees of hypoglycemia. This may increase symptoms, in particular during daytime, and may offer opportunities for earlier treatment. Disclosure M. A. Nauck: Advisory Panel; Self; Berlin-Chemie AG, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk, Consultant; Self; Eli Lilly and Company, Novo Nordisk, Research Support; Self; Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk, Speaker’s Bureau; Self; Berlin-Chemie AG, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk. A. Feldmann: None. J. J. Meier: Advisory Panel; Self; AstraZeneca, MSD Corporation, Novo Nordisk, Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Lilly Diabetes, MSD Corporation, Novo Nordisk, Sanofi. M. Nauck: None. C. Kapitza: Research Support; Self; ADOCIA, Afon Technology, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Gan & Lee Pharmaceuticals, Johnson & Johnson, Julphar, Mylan N. V., Nestlé, Novo Nordisk A/S, Sanofi, Zealand Pharma A/S. Funding Merck Sharp & Dohme Corp

Idiopathic ketotic hypoglycemia (IKH) is characterized by recurrent neurohypoglycemic symptoms with ketosis. Hypoglycemic episodes typically occur during early mornings, especially either with illness and/or prolonged fasting. We reported a case of IKH which presented with recurrent episodes of seizures during early morning with intercurrent illness and which was labeled as epilepsy and started on antiepileptic medication. The purpose of this case report is to alert clinicians about this condition, which is not an uncommon entity, but rarely thought of. Therefore, in view of keeping the IKH in mind, which can be prevented with proper diet advice during illness, unnecessary long-term antiepileptic therapy can be avoided.

IN BRIEF Automated insulin delivery (AID; also known as artificial pancreas) has improved the regulation of blood glucose concentrations, reduced the frequency of hyperglycemic and hypoglycemic episodes, and improved the quality of life of people with diabetes and their families. Three different types of algorithms—proportional-integral-derivative control, model predictive control, and fuzzy-logic knowledge-based systems—have been used in AID control systems. This article will highlight the foundations of these algorithms and discuss their strengths and limitations. Multivariable artificial pancreas and dual-hormone (insulin and glucagon) systems will be introduced.

Background/aim Prevention of hypoglycemia remains a major challenge in diabetic management, despite the introduction of modern insulin pumps in daily clinical practice. The Low Glucose Suspend (LGS) and the newer Predictive Low Glucose Management (PLGM) systems incorporated in the Medtronic insulin pumps have shown promising results in prevention of hypoglycemia. Our aim was to evaluate the effect of the 2 systems relative to the frequency of clinically significant hypoglycemia in Type 1 diabetes (T1DM). In addition, we investigated the events preceding clinically significant hypoglycemia episodes. Methods A cross-sectional study was conducted in 30 T1DM patients using the MiniMed 640G vs. 30 using the MiniMed Veo sensor-augmented insulin pump. All data was recorded during patients’ normal daily activity and living conditions. The patients were matched for age and duration of diabetes. Results PLGM use was associated with lower incidence of clinically significant hypoglycemia (1.9±1.4 vs. 3.6±1.9 episodes per week), along with reduced exposure to hypoglycemia. The data indicated that both pump systems are effective in preventing severe hypoglycemic episodes. In both groups the most common events preceding hypoglycemic episodes included adjustment of hyperglycemia, basal rate increase and miscalculation of carbohydrates. Conclusions The results indicated that the use of the Minimed 640G pump system can help reduce the frequency of clinically significant hypoglycemia. Management of hyperglycemia must be addressed in diabetes education programs in order to encourage proper adjustment of high blood glucose levels. Future studies would be useful in exploring the details of the events preceding hypoglycemia episodes in insulin pump users.

Beta‐ketothiolase (T2, mitochondrial acetoacetyl‐CoA thiolase) deficiency is an autosomal recessive disorder of isoleucine catabolism and ketone body metabolism that is characterized by increased urinary excretion of 2‐methylacetoacetate, 2‐methyl‐3‐hydroxybutyrate, and tiglylglycine. Most patients with T2 deficiency develop their first severe ketoacidotic events between 5 and 24 months of age. We encountered a case of T2 deficiency who developed the first hypoglycemic crisis without ketosis during her neonatal period and repeated such nonketotic hypoglycemic crisis during her infancy and early childhood. This is a very atypical clinical phenotype in T2 deficiency. We finally realized that she also has severe carnitine deficiency which might suppress beta‐oxidation resulting in nonketotic hypoglycemia. After carnitine supplementation, she actually developed episodes with ketonuria. Her carnitine deficiency was probably a secondary deficiency which is rare in T2 deficiency but if present, may modify the clinical manifestation of T2 deficiency from ketoacidotic events to hypoketotic hypoglycemic events.

[EN] Nowadays, diabetes mellitus remains as a public health worldwide problem. In this work, control strategies are proposed to maintain the blood glucose levels of diabetic type 1 patients in the ideal ranges for the sake of its health and quality of life. The first strategy is based on a state feedback but respecting positivity constraints, which in medical terms, is a guaranty of elimination of hypoglycemic episodes for prolonged fasting periods. Besides, an extension of this strategy is developed to achieve disturbance rejection (meal intake) in diurnal periods by coupling it with a proportional, integral and derivative control. The second strategy is a model-based predictive control with impulsive input and regulation towards a target zone. Finally, the performance of both control strategies is assessed in 50 virtual patients extracted from the literature and in the UVa/Padova Simulator approved by the Food and Drug Administration from the United States., [ES] Actualmente la diabetes mellitus es un problema de salud pública mundial. En este trabajo, se proponen estrategias de control para mantener los niveles de glucosa en sangre de pacientes diabéticos tipo 1 en los rangos ideales en pro de la salud del paciente y su calidad de vida. La primera estrategia propone una retroalimentación de estados con restricciones de positividad, que en términos médicos representa la eliminación de episodios de hipoglucemia durante períodos prolongados de ayuno. Posteriormente, se realiza una extensión para lograr el rechazo de las perturbaciones por ingesta de alimentos, mediante el acoplamiento de un control proporcional, integral y derivativo. La segunda estrategia es un control predictivo con entrada impulsiva y regulación hacia una zona objetivo. Finalmente, el desempeño de las estrategias es evaluado en 50 pacientes virtuales extraídos de la literatura y en el Simulador UVa / Padova aprobado por la Food and Drug Administration de EEUU.

There are as yet no cohort studies of hypoglycemia in type 1 diabetes before starting insulin therapy. Our aim was to determine the frequency and clinical features of hypoglycemia in patients with type 1A diabetes prior to commencing insulin therapy.Eighty-seven patients with type 1A diabetes were enrolled, and a retrospective chart review of the patients was conducted.Hypoglycemia before insulin therapy occurred in six of 87 patients (6.9%). The HbA1c levels at the diagnosis of type 1A diabetes in the hypoglycemia group were lower than in the non-hypoglycemia group (median: 7.3% (56 mmol/mol) vs. 11.9% (106 mmol/mol), p 0.0001). Similarly, the 24-hour urinary C-peptide (UCPR) levels of the former group were higher than those of the latter group (16.5 μg/day/mWe demonstrated that some patients with type 1A diabetes experience hypoglycemic episodes before insulin therapy. Patients with early-stage type 1A diabetes with relatively low HbA1c or high UCPR have a risk of hypoglycemia. These findings may impact when and how insulin is introduced in the treatment of early-stage type 1A diabetes.

Introduction: Glycemic variability (GV) has been associated with worse prognosis in critically ill patients. We sought to evaluate the potential association between GV indices and clinical outcomes in acute stroke patients. Methods: Consecutive diabetic and nondiabetic, acute ischemic or hemorrhagic stroke patients underwent regular, standard-of-care finger-prick measurements and continuous glucose monitoring (CGM) for up to 96 h. Thirteen GV indices were obtained from CGM data. Clinical outcomes during hospitalization and follow-up period (90 days) were recorded. Hypoglycemic episodes disclosed by CGM but missed by finger-prick measurements were also documented. Results: A total of 62 acute stroke patients [48 ischemic and 14 hemorrhagic, median NIHSS score: 9 (IQR: 3–16) points, mean age: 65 ± 10 years, women: 47%, nondiabetic: 79%] were enrolled. GV expressed by higher mean absolute glucose (MAG) values was associated with a lower likelihood of neurological improvement during hospitalization before and after adjusting for potential confounders (OR: 0.135, 95% CI: 0.024–0.751, p = 0.022). There was no association of GV indices with 3-month clinical outcomes. During CGM recording, 32 hypoglycemic episodes were detected in 17 nondiabetic patients. None of these episodes were identified by the periodic blood glucose measurements and therefore they were not treated. Conclusions: Greater GV of acute stroke patients may be related to lower odds of neurological improvement during hospitalization. No association was disclosed between GV indices and 3-month clinical outcomes.

Background: Type 1 Diabetes Mellitus (T1DM) is a chronic autoimmune disease, which is characterized by an increased prevalence worldwide, which, in fact, tends to take extensive dimensions. The recent rapid development of science and technology has significantly contributed to the improvement of the management of type 1 diabetes mellitus, both in achieving the required euglycaemic regulation and reducing the psychological burden associated with the disease, consequently improving the quality of life of the patients with type 1 diabetes mellitus. Methods: A literature review from 2010, related to the contribution of the modern insulin analogues, continuous glucose monitoring and the insulin pump, was performed using Scopus, ScienceDirect and PubMed databases. Results: Studies included in the review support a direct and indirect association of technological innovations with the quality of life. The use of type 1 diabetes mellitus technology was negatively associated with the frequency of the hypoglycaemias and the value of the glycosylated hemoglobin, while at the same time, the development and use of the related technology were highly associated with an improvement in the quality of life. Conclusion: Patients’ quality of life is an indicator of the management of type 1 diabetes mellitus, and it is just as important as glycaemic regulation. Through this review, it was concluded that a better quality of life of T1DM patients was associated with the improvement of glycosylated hemoglobin and hypoglycemic episodes.

Hypoglycemic episodes are associated with worse hospital outcomes. All adult patients admitted to our burn center from 2015 to 2019 were retrospectively reviewed. Patient demographics and burn characteristics were recorded. The primary outcome was mortality, and secondary outcomes were total length-of-stay and intensive care unit length-of-stay. All patients experiencing at least one hypoglycemic episode were compared to patients who did not experience hypoglycemia. There were 914 patients with acute burns admitted during the study period, 33 of which (4%) experienced hypoglycemic episodes. Of these, 17 patients (52%) experienced a single hypoglycemic episode, while the remainder experienced multiple hypoglycemic episodes. Patients with one or more hypoglycemic events were matched to non-hypoglycemic controls using propensity matching. Patients that experienced hypoglycemia had significantly less TBSA involvement (5% vs. 13%,median, p < 0.0002), higher prevalence of diabetes (48% vs. 18%, p < 0.0001), higher mortality (18% vs. 7%, p = 0.01), longer total length-of-stay (22 vs. 8 days, median, p < 0.0001), and longer ICU length-of-stay (12 vs. 0 days, median, p < 0.0001). A single hypoglycemic episode was associated with prolonged total (IRR = 1.91, p < 0.0001) and ICU length-of-stay (IRR = 3.86, p < 0.0001). Hypoglycemia was not associated with higher mortality in the survival analysis (p = 0.46).

In type 1 diabetes management, the availability of algorithms capable of accurately forecasting future blood glucose (BG) concentrations and hypoglycemic episodes could enable proactive therapeutic actions, e.g., the consumption of carbohydrates to mitigate, or even avoid, an impending critical event. The only input of this kind of algorithm is often continuous glucose monitoring (CGM) sensor data, because other signals (such as injected insulin, ingested carbs, and physical activity) are frequently unavailable. Several predictive algorithms fed by CGM data only have been proposed in the literature, but they were assessed using datasets originated by different experimental protocols, making a comparison of their relative merits difficult. The aim of the present work was to perform a head-to-head comparison of thirty different linear and nonlinear predictive algorithms using the same dataset, given by 124 CGM traces collected over 10 days with the newest Dexcom G6 sensor available on the market and considering a 30-min prediction horizon. We considered the state-of-the art methods, investigating, in particular, linear black-box methods (autoregressive, autoregressive moving-average, and autoregressive integrated moving-average, ARIMA) and nonlinear machine-learning methods (support vector regression, SVR, regression random forest, feed-forward neural network, fNN, and long short-term memory neural network). For each method, the prediction accuracy and hypoglycemia detection capabilities were assessed using either population or individualized model parameters. As far as prediction accuracy is concerned, the results show that the best linear algorithm (individualized ARIMA) provides accuracy comparable to that of the best nonlinear algorithm (individualized fNN), with root mean square errors of 22.15 and 21.52 mg/dL, respectively. As far as hypoglycemia detection is concerned, the best linear algorithm (individualized ARIMA) provided precision = 64%, recall = 82%, and one false alarm/day, comparable to the best nonlinear technique (population SVR): precision = 63%, recall = 69%, and 0.5 false alarms/day. In general, the head-to-head comparison of the thirty algorithms fed by CGM data only made using a wide dataset shows that individualized linear models are more effective than population ones, while no significant advantages seem to emerge when employing nonlinear methodologies.

The economic and psychological consequences of diabetes-related hypoglycemic events are multifold and shared across various parties, including patients and their family or caregivers, payors, and employers. Hypoglycemic events contribute to increased morbidity, mortality, and a substantial portion of diabetes economic burden. Both severe and non-severe hypoglycemic episodes contribute to economic and psychological burden, and can have short-term consequences, such as emergency services, hospitalization, clinic visits, and increased use of diabetes supplies. Severe hypoglycemic events also generate additional follow-up costs, and are likely to occur again. Left untreated, hypoglycemia can have long-term consequences including, death, cardiovascular events, and cognitive issues. Costs vary geographically based on the treatment protocols which focus on outpatient treatment versus increased in-patient hospitalization. Certain types of medications are also associated with increased hypoglycemia, which requires closer monitoring of the patient, such as with basal insulin initiation. Some individuals with diabetes may be more vulnerable to hypoglycemia, such as the elderly, postoperative bariatric patients, and adolescent females. Measures to mitigate hypoglycemia are essential to ease the economic burden of these events. Medication management, optimal glucose control, lifestyle modifications and frequent glucose monitoring are some interventions which may help prevent hypoglycemia.

Background We intended to estimate the proportion hypoglycemic/hyperglycemic emergency episodes in treated diabetes mellitus (DM) patients admitted to a hospital ward, and calculate the prevalence of risk factors for hypoglycemia and diabetic complications. Methods In this cross-sectional, multicentered study, the observational data was collected by physicians from patient’s hospitalization to discharge/death. Statistical tests were 2-tailed considering 5% significance level. Results There were 646 ward admissions due to hyperglycemic emergencies and 176 hypoglycemic episodes with a ratio hypoglycemia/hyperglycemia 0.27 for all DM patients. In T2DM patients the ratio was 0.38. These were mainly female (55.1%), functionally dependent (61.4%) and retired/disabled (73.1%). Median age was 75 years and median duration of disease 11 years. Half the patients were on insulin-based therapy and 30.1% on secretagogue-based therapy. Approximately 57% of patients needed occasional/full assistance to manage the disease. The most frequent risk factor for hypoglycemia was polypharmacy (85.0%). Hypoglycemia in the 12 months before admission was higher in insulin-based therapy patients (66.1%; p = 0.001). Conclusions Hyperglycemic emergencies are the most frequent cause of hospitalization in Portugal, although severe hypoglycemic events represent a health and social problem in elderly/frail patients. There is still the need to optimize therapy in terms of the potential for hypoglycemia in this patient group and a review of anti-hyperglycemic agents to add on to insulin.

Background Noninsulinoma pancreatogenous hypoglycemia syndrome (NIPHS) is a rare syndrome characterized by postprandial hypoglycemia with neuroglycopenic symptoms occurring 1 to 3 h after a meal. Diagnosis can be elusive, as the vast majority of patients have normal fasting blood glucose levels, and onset of hypoglycemic episodes can be a late complication of gastric surgery. Case Report We report the case of a 45-year-old woman presenting to the Emergency Department (ED) with new-onset seizures and hypoglycemia worsened by glucose administration. Surgical history is pertinent for a Roux-en-Y gastric bypass approximately 10 years prior to presentation. Why Should an Emergency Physician Be Aware of This? Although rare, it is important for emergency physicians to be vigilant of this disease process as a traditional treatment approach for hypoglycemia may be detrimental. Although cases of NIPHS have been documented in literature, its presence in emergency medicine-specific literature is seemingly nonexistent. Noninvasive imaging techniques will be normal, and diagnosis is dependent on awareness of this disease entity coupled with a detailed history.

Here, we present a case that required a supplemental “old school” islet purification for a safe intraportal infusion. Following pancreas procurement from a brain-dead 26-year-old male donor (body mass index: 21.9), 24.6 ml of islet tissue was isolated after continuous density gradient centrifugation. The islet yield was 504,000 islet equivalent (IEQ), distributed among the following three fractions: 64,161 IEQ in 0.6 ml of pellet, 182,058 IEQ in 10 ml, and 258,010 IEQ in 14 ml with 95%, 20%, and 10% purity, respectively. After a 23-h culture, we applied supplemental islet purification, based on the separation of tissue subfractions during unit gravity sedimentation, a technique developed over 60 years ago (“old school”). This method enabled the reduction of the total pellet volume to 11.6 ml, while retaining 374,940 IEQ with a viability of over 90%. The final islet product was prepared in three infusion bags, containing 130,926 IEQ in 2.6 ml of pellet, 108,079 IEQ in 4 ml of pellet, and 135,935 IEQ in 5 ml of pellet with 65%, 40%, and 30% purity, respectively, and with the addition of unfractionated heparin (70 units/kg body weight). Upon the islet infusion from all three bags, portal pressure increased from 7 to 16 mmHg. Antithrombotic prophylaxis with heparin was continued for 48 h after the infusion, with target activated partial thromboplastin time 50–60 s, followed by fractionated heparin subcutaneous injections for 2 weeks. β-Cell graft function assessed on day 75 post-transplantation was good, according to Igls criteria, with complete elimination of severe hypoglycemic episodes and 50% reduction in insulin requirements. Time spent within the target glucose range (70–180 mg/dl) improved from 42% to 98% and HbA1c declined from 8.7% to 6.7%. Supplemental “old school” islet purification allowed for the safe and successful utilization of a robust and high-quality islet preparation, which otherwise would have been discarded.

Objective: To evaluate the effect of anti-IL-21 and liraglutide, alone and in combination, compared to placebo, on preservation of β-cell function after 54 weeks of treatment in adults with recently diagnosed type 1 diabetes. Methods: This was a multicenter, double-dummy, double-blind, efficacy, safety and pharmacokinetic randomized control trial (NCT02443155) in adults recently diagnosed with type 1 diabetes and non-fasting C-peptide peak ≥0.2 nmol/L, comprising a 54-week treatment period followed by a 26-week observation period. Primary endpoint: area under the curve (AUC)0-4h for meal-stimulated C-peptide at week 54 relative to baseline. Results: At week 54, combination treatment was associated with a significant improvement of 48% in meal-stimulated C-peptide secretion versus placebo (Table). The insulin requirement was significantly lowered by 0.13 U/kg. Trends for better glycemic control and lower risk of hypoglycemic episodes at 54 weeks compared to placebo were also observed. No safety concerns were identified. Treatment benefits were not sustained at 26 weeks after end of treatment. Conclusion: Treatment with anti-IL-21 and liraglutide for 54 weeks was safe and resulted in sustained insulin secretion and lower insulin dose. Trends for improved glucose control and fewer hypoglycemic episodes compared to placebo were observed. Disclosure M.G. von Herrath: Employee; Self; Novo Nordisk A/S. S.C. Bain: Advisory Panel; Self; Boehringer Ingelheim International GmbH, Lilly Diabetes, Merck Sharp & Dohme Corp., Napp Pharmaceuticals, Novo Nordisk A/S, Sanofi. Research Support; Self; Novo Nordisk A/S, Sanofi. Speaker’s Bureau; Self; AstraZeneca. B.W. Bode: Advisory Panel; Self; InPen, Medtronic. Consultant; Self; ADOCIA, Eli Lilly and Company, Lexicon Pharmaceuticals, Inc., Novo Nordisk A/S, Pfizer Inc. Research Support; Self; Dexcom, Inc., Diasome Pharmaceuticals, Inc., Eli Lilly and Company, Gan & Lee Pharmaceuticals, Medtronic, Novo Nordisk A/S, Provention Bio, Inc., Senseonics, Xeris Pharmaceuticals, Inc. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., InPen, Janssen Pharmaceuticals, Inc., MannKind Corporation, Medtronic, Novo Nordisk A/S, Sanofi, Sanofi, Senseonics, Xeris Pharmaceuticals, Inc. Stock/Shareholder; Self; Glytec. J. Clausen: Other Relationship; Self; Novo Nordisk A/S. K. Coppieters: Other Relationship; Self; Novo Nordisk A/S. L. Gaysina: None. J. Gumprecht: Consultant; Self; Astra, Bioton, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Merck Sharp & Dohme Corp., Mundipharma International, Novo Nordisk A/S, Polfa Tarchomin S.A., Sanofi, Servier. Speaker’s Bureau; Self; Astra, Bioton, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Merck Sharp & Dohme Corp., Mundipharma International, Novo Nordisk A/S, Polfa Tarchomin S.A., Sanofi, Servier. T.K. Hansen: None. C. Mathieu: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Intrexon, MannKind Corporation, Medtronic, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk Inc., Pfizer Inc., Roche Diagnostic USA, Sanofi. Research Support; Self; Intrexon, Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis AG, Novo Nordisk Inc., Sanofi. C. Morales Portillo: Board Member; Self; Novo Nordisk, Lilly, MSD, Astra, Sanofi, Abbot. Research Support; Self; Novo Nordisk, Sanofi, AstraZeneca, Pzifer, Lilly, Merck, Lexicon, FPS, Hanmi, Janssen, Boehringer, Takeda, Roche, Theracos. Speaker’s Bureau; Self; Sanofi, Novo Nordisk, AstraZeneca, Roche, Lilly, Boehringer, MSD, Ferrer, Janssen, Abbot. O. Mosenzon: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi. Research Support; Self; AstraZeneca, Novo Nordisk A/S. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi, Teva Pharmaceutical Industries Ltd. S. Segel: Employee; Self; Novo Nordisk A/S. Employee; Spouse/Partner; Novo Nordisk A/S. Stock/Shareholder; Self; Novo Nordisk A/S. Stock/Shareholder; Spouse/Partner; Novo Nordisk A/S. G.M. Tsoukas: Advisory Panel; Self; Amgen, Novo Nordisk Inc. Speaker’s Bureau; Self; Amgen Canada. T. Pieber: Advisory Panel; Self; ADOCIA, Arecor, AstraZeneca, Eli Lilly and Company, Novo Nordisk A/S, Sanofi. Research Support; Self; AstraZeneca, Novo Nordisk A/S. Speaker’s Bureau; Self; Novo Nordisk A/S, Roche Diagnostics K.K. Funding Novo Nordisk A/S

Background: Patient-driven innovation has led to the development of do-it-yourself artificial pancreas systems (DIYAPS) for the management of type 1 diabetes (T1D). There have been few studies comparing glycemic outcomes for DIYAPS compared to conventional sensor-augmented pump (SAP) therapy. Methods: A retrospective double cohort study was performed. The DIY group consisted of people with T1D using DIYAPS (OpenAPS, Loop, and AndroidAPS) who contributed data to the OpenAPS Data Commons. The SAP group included age-matched SAP users whose sensor data was obtained through the Tidepool Big Data Donation Project. The primary outcome of percent of sensor glucoses (SG) in low glucose range (=15-minute hypoglycemic episodes (=180 mg/dL) and in target range (70-180 mg/dL). Results: The DIY group included 90 days of data from 74 individuals with mean age of 36 ± 15 years and 24 ± 16 years since T1D diagnosis. The SAP group had 98 individuals with mean age of 35 ± 14 years and 20 ± 13 years since diagnosis. There was no significant difference in percent of SG =180 mg/dL was lower (16.9% for DIY vs. 26.1% for SAP, p Conclusion: Users of DIYAPS had a comparable amount of hypoglycemia to those using SAP and had less hyperglycemia. This study suggests that the glycemic benefit of DIYAPS is in reducing hyperglycemia without compromising the low occurrence of hypoglycemia. Disclosure J. Zabinsky: None. H. Howell: None. A. Ghezavati: None. D.M. Lewis: Research Support; Self; JDRF. A. Nguyen: None. J.C. Wong: Consultant; Self; pH Pharma. Research Support; Self; Dexcom, Inc. Funding JDRF

An exploratory subgroup analysis of the 52-week, double-blind PIONEER 8 trial (NCT03021187) evaluated the effect of background insulin regimen (basal, premixed, or basal-bolus) with or without metformin on the efficacy and safety of oral semaglutide (sema). Patients (pts) (N=731) with type 2 diabetes and treated with insulin were randomized to once-daily oral sema (3, 7, or 14 mg) or placebo (pbo). Endpoints included change from baseline in HbA1c, body weight (BW), and total daily insulin dose at week 52. Baseline age and HbA1c were similar across insulin regimen subgroups whereas BW was greater and diabetes duration was longer in pts on basal-bolus vs. basal and premix subgroups. There were greater dose-dependent HbA1c and BW reductions with oral sema vs. pbo; these were generally similar across all insulin subgroups (Table). Total daily insulin dose at week 52 was decreased for pts on basal (oral sema 7 and 14 mg), premix (oral sema 14 mg), and basal-bolus (oral sema 3, 7, and 14 mg), mainly driven by the bolus component for pts on basal-bolus (Table). Most hypoglycemic episodes were in pts on basal-bolus insulin. Fewer pts had hypoglycemia with oral sema vs. pbo except in the basal-bolus subgroup (Table). In conclusion, oral sema reduced HbA1c and BW in a dose-dependent manner, and reduced insulin dose regardless of background insulin regimen, with a safety profile similar to other glucagon-like peptide-1 receptor agonists. Disclosure O. Mosenzon: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi. Research Support; Self; AstraZeneca, Novo Nordisk A/S. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Sanofi, Teva Pharmaceutical Industries Ltd. V.R. Aroda: Consultant; Self; Duke, Novo Nordisk Inc., Sanofi. Employee; Spouse/Partner; Merck & Co., Inc. Research Support; Self; Applied Therapeutics, Fractyl Laboratories, Inc., Novo Nordisk Inc., Sanofi. Other Relationship; Self; IMNE, Medscape. E. Christiansen: None. S.B. Harris: Advisory Panel; Self; Abbott, AstraZeneca, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Consultant; Self; Abbott, AstraZeneca, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk Inc., Sanofi. Research Support; Self; AstraZeneca, Canadian Institutes of Health Research, Eli Lilly and Company, Health Canada/First Nations and Inuit Health Branch, Janssen Pharmaceuticals, Inc., JDRF, Lawson Foundation, Novo Nordisk Inc., Sanofi. Other Relationship; Self; AstraZeneca, Eli Lilly and Company, Novo Nordisk Inc., Sanofi. K. Pedersen: Employee; Self; Novo Nordisk A/S. M. Tarp-Johansen: Employee; Self; Novo Nordisk A/S. B. Zinman: Advisory Panel; Self; Abbott, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Novo Nordisk Inc., Sanofi-Aventis. Funding Novo Nordisk A/S