Living Donor Liver Transplantation for Congenital Portosystemic Shunt Presenting With Hyperinsulinemic Hypoglycemia.

BACKGROUND: A congenital portosystemic shunt (CPSS) is defined as abnormal vascular communications between the portal vein and the systemic vein. Encephalopathy, hepatopulmonary syndrome, and portopulmonary hypertension are manifestations in patients with CPSS. Hyperinsulinemic hypoglycemia is also one of the manifestations of CPSS. Hyperinsulinemic hypoglycemia secondary to CPSS is caused by a lack of hepatic first-pass elimination of insulin, which is secreted from pancreatic beta cells. CASE PRESENTATION: A 7-month-old boy had hypergalactosemia detected by newborn mass screening. Enhanced abdominal computed tomography showed the absence of the portal vein trunk and extrahepatic portosystemic communication between the superior mesenteric vein and the inferior vena cava. He had suffered from uncontrollable hyperinsulinemic hypoglycemia under protein and lactose restriction. We performed living donor liver transplantation (LDLT) using a left lateral segment graft from his father. The postoperative course was uneventful and the hypoglycemic attacks disappeared. CONCLUSION: We believe that uncontrolled hyperinsulinemic hypoglycemia secondary to CPSS is an indication of LDLT.

Development and Validation of a Nocturnal Hypoglycaemia Risk Model for Patients With Type 2 Diabetes Mellitus.

AIM: To develop and test different machine learning algorithms for predicting nocturnal hypoglycaemia in patients with type 2 diabetes mellitus. DESIGN: A retrospective study. METHODS: We collected data from dynamic blood glucose monitoring of patients with T2DM admitted to the Department of Endocrinology and Metabolism at a hospital in Shanghai, China, from November 2020 to January 2022. Patients undergone the continuous glucose monitoring (CGM) for ≥ 24 h were included in this study. Logistic regression, random forest and light gradient boosting machine algorithms were employed, and the models were validated and compared using AUC, accuracy, specificity, recall rate, precision, F1 score and the Kolmogorov-Smirnov test. RESULTS: A total of 4015 continuous glucose-monitoring data points from 440 patients were included, and 28 variables were selected to build the risk prediction model. The 440 patients had an average age of 62.7 years. Approximately 48.2% of the patients were female and 51.8% were male. Nocturnal hypoglycaemia appeared in 573 (14.30%) of 4015 continuous glucose monitoring data. The light gradient boosting machine model demonstrated the highest predictive performances: AUC (0.869), specificity (0.802), accuracy (0.801), precision (0.409), recall rate (0.797), F1 score (0.255) and Kolmogorov (0.603). The selected predictive factors included time below the target glucose range, duration of diabetes, insulin use before bed and dynamic blood glucose monitoring parameters from the previous day. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

A Case of Neonate Hypoglycemia.

BACKGROUND: There has been no unified definition for neonatal hypoglycemia. Generally, neonatal hypoglycemia is diagnosed when the whole blood glucose concentration is below 2.2 mmol/L. The reasons are numerous. This case report presents an instance of a newborn with extremely low blood glucose levels immediately after birth from a diabetic mother, referred to as the "Infants of Diabetic Mothers", providing a practical case reference for early monitoring and timely intervention for Infants of Diabetic Mothers (IDMs). METHODS: The glucose concentrations in whole blood and serum were measured using a fingerstick glucometer and a fully automatic biochemical analyzer, respectively. The levels of insulin and C-peptide were detected using a fully automatic chemiluminescence method. The glycated hemoglobin was measured using a glycated hemoglobin analyzer. RESULTS: The mother's blood glucose value before delivery was 8.28 mmol/L. After delivery, the fingerstick blood glucose and serum glucose concentrations of the newborn were 2.6 mmol/L and 0.11 mmol/L, respectively. The levels of insulin and C-peptide were 805.55 pmol/L and 2,312.64 pmol/L, respectively. The value of glycated hemoglobin was 7.5%. Intravenous nutrition with a 100 mL of 10% glucose at an infusion rate of 12.7 mL/d was maintained. Then, 10% glucose was given to the neonate at an infusion rate of 7.7 mL/minute for 30 minutes. Eventually, the blood glucose levels were raised to 5.2 mmol/L. CONCLUSIONS: Diabetes has a profound impact on both the mother and the newborn. Close monitoring and timely intervention are necessary to reduce neonatal complications and promote longterm healthy growth and development.

Continuous glucose monitoring (Dexcom g6) in people with diabetes after kidney transplantation.

OBJECTIVES: Use of continuous glucose monitoring-CGM in patients on kidney replacement therapy including kidney transplant recipients, may improve glycemic control and detection of hypoglycemia. However, studies in this population in particular in kidney transplant recipients are very limited. METHODS: The study aimed to evaluate glycemic profiles using the Dexcom G6 CGM system for 30 d a personal smartphone in people with diabetes after kidney transplantation and to assess the impact of monthly use of the CGM system on glycemic control and quality of life in this group. RESULTS: Over 8 months, 9 people after kidney transplantation were included in the study (7 women, median age 57 years), 8 people with new-onset diabetes after transplantation (NODAT), and 1 person with diabetes mellitus type 1. The time since kidney transplantation in each of the study participants was less than 2 years. In 7 people with NODAT, the time in range was above 70%. In all study participants, hyperglycemia was observed mainly in the afternoon (2-6 pm). In some patients, pressure-induced sensor attenuations (PISAs) were noted. There was no effect of the use of Dexcom G6 on the HbA1c value. There was no impact of the use of the Dexcom G6 system on the perception of overall quality of life, but monthly use had a positive impact on the perception of the quality of health. CONCLUSIONS: CGM systems seem to be a promising method for assessing glycemic control in people with diabetes after kidney transplantation. More extensive research is needed to assess safety and usefulness in everyday practice.

[Continuous glucose monitoring for better glucose control in type 2 diabetes?] / Diabète de type 2 : vers un contrôle opti­mal grâce au ­suivi continu du glucose ?

This article reviews the use of continuous glucose monitoring (CGM) devices in the management of type 2 diabetes (T2D). Study results show that continuous CGM use improves glycemic control, lowers glycated hemoglobin (HbA1c) levels, and reduces hypoglycemic episodes compared with traditional monitoring methods. -Observational studies also suggest a reduction in diabetes-related emergencies and hospitalizations. In addition, sporadic use of CGM appears to be beneficial for certain groups of people with T2D. However, more research is needed to fully understand the long-term effects and limitations of this technology. This article discusses -innovative perspectives on T2D management.

Cet article explore l'impact des dispositifs de mesure continue du glucose (MCG) dans la gestion du diabète de type 2 (DT2). Les ­résultats des études démontrent que l'utilisation régulière de la MCG améliore le contrôle de la glycémie, réduit les taux d'hémoglobine glyquée (HbA1c) et diminue les épisodes hypoglycémiques par rapport à la surveillance traditionnelle. Les données issues d'études observationnelles mettent également en évidence une réduction des événements aigus liée au diabète et des hospitalisations. De plus, l'emploi occasionnel de la MCG semble davantage bénéfique pour certains groupes de patients DT2. Toutefois, des recherches supplémentaires sont nécessaires pour clarifier les effets à long terme et les limites de cette technologie. Cet article discute les perspectives innovantes pour la gestion du DT2.

Hypoglycemia and hyperglycemia in neonatal encephalopathy: A narrative review.

Neonatal encephalopathy (NE) is a serious condition with various neurological dysfunctions in newborns. Disruptions in glucose metabolism, including both hypoglycemia and hyperglycemia, are common in NE and can significantly impact outcomes. Hypoglycemia, defined as blood glucose below 45 mg/dL, is associated with increased mortality, neurodevelopmental disabilities, and brain lesions on MRI. Conversely, hyperglycemia, above 120 to 150 mg/dL, has also been linked to heightened mortality, hearing impairment, and multiorgan dysfunction. Both aberrant glucose states appear to worsen prognosis compared to normoglycemic infants. Therapeutic hypothermia is the standard of care for NE that provides neuroprotection by reducing metabolic demands and inflammation. Adjunct therapies like glucagon and continuous glucose monitoring show promise in managing dysglycemia and improving outcomes. Glucagon can enhance cerebral blood flow and glucose supply, while continuous glucose monitoring enables real-time monitoring and personalized interventions. Maintaining balanced blood sugar levels is critical in managing NE. Early detection and intervention of dysglycemia are crucial to improve outcomes in neonates with encephalopathy. Further research is needed to optimize glycemic management strategies and explore the potential benefits of interventions like glucagon therapy.

Novel ABCC8 mutation in the genetic diagnosis of familial hyperinsulinaemic hypoglycaemia.

Familial hyperinsulinaemic hypoglycaemia-1 arises from mutations within the genes of pancreatic beta cells, resulting in unregulated insulin secretion from pancreatic beta cells. A 4.06 kg female neonate, born to a second-degree consanguineously married couple, presented with repeated asymptomatic hypoglycaemia. There was a significant history of a previous sibling's death from nesidioblastosis. Despite treatment with intravenous glucose, diazoxide, hydrochlorothiazide and octreotide, she continued to experience hypoglycaemic episodes. Despite efforts to manage sepsis, including antibiotics, antifungals and intravenous immunoglobulin/granulocyte-macrophage colony-stimulated factor, her condition worsened. She succumbed on day 34. This case underscores the complexities of managing congenital hyperinsulinaemic hypoglycaemia, especially in the context of concurrent infections and the need for multidisciplinary care. Early genetic diagnosis proved invaluable in facilitating timely and effective treatment. Furthermore, the genetic results enabled us to counsel the parents regarding the recurrence risk in subsequent pregnancies and the necessity for antenatal diagnosis.

Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes.

INTRODUCTION: Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort. RESEARCH DESIGN AND METHODS: Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB). RESULTS: The dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of ≥80 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%). CONCLUSIONS: Our scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.

Continuous glucose monitoring metrics in people with liver glycogen storage disease and idiopathic ketotic hypoglycemia: A single-center, retrospective, observational study.

BACKGROUND: Cohort data on continuous glucose monitoring (CGM) metrics are scarce for liver glycogen storage diseases (GSDs) and idiopathic ketotic hypoglycemia (IKH). The aim of this study was to retrospectively describe CGM metrics for people with liver GSDs and IKH. PATIENTS AND METHODS: CGM metrics (descriptive, glycemic variation and glycemic control parameters) were calculated for 47 liver GSD and 14 IKH patients, categorized in cohorts by disease subtype, age and treatment status, and compared to published age-matched CGM metrics from healthy individuals. Glycemic control was assessed as time-in-range (TIR; ≥3.9 - ≤7.8 and ≥3.9 - ≤10.0 mmol/L), time-below-range (TBR; <3.0 mmol/L and ≥3.0 - ≤3.9 mmol/L), and time-above-range (TAR; >7.8 and >10.0 mmol/L). RESULTS: Despite all patients receiving dietary treatment, GSD cohorts displayed significantly different CGM metrics compared to healthy individuals. Decreased TIR together with increased TAR were noted in GSD I, GSD III, and GSD XI (Fanconi-Bickel syndrome) cohorts (all p < 0.05). In addition, all GSD I cohorts showed increased TBR (all p < 0.05). In GSD IV an increased TBR (p < 0.05) and decreased TAR were noted (p < 0.05). In GSD IX only increased TAR was observed (p < 0.05). IKH patient cohorts, both with and without treatment, presented CGM metrics similar to healthy individuals. CONCLUSION: Despite dietary treatment, most liver GSD cohorts do not achieve CGM metrics comparable to healthy individuals. International recommendations on the use of CGM and clinical targets for CGM metrics in liver GSD patients are warranted, both for patient care and clinical trials.

[Association between anthropometric indices with the risk of hypoglycemia in elderly patients with type 2 diabetes mellitus].

Almost 90% of patients with type 2 diabetes mellitus (DM2) are obese. Obesity increases the risk of developing DM2 several times. The calculation of anthropometric indices is used to diagnose the severity of obesity, as well as to assess the risk associated with obesity. The aim of the study is to study the relationship between Body Mass Index (BMI), waist circumference to hip circumference ratio (waist-to-hip ratio, WC/HR), Body Roundness Index (BRI) and Visceral Adiposity Index (VAI) with the risk of hypoglycemia in elderly and senile patients with DM2. The study included 122 elderly and senile patients (mean age 71±6,18 years) with DM2. The study participants were divided into 2 groups: patients with cases of hypoglycemia (n=65) and patients without a history of hypoglycemia (n=57). We have found that lower BMI, WC/HR, BRI, and VAI values are significantly associated with an increased risk of hypoglycemia in patients with DM2 of older age groups.

Clinical evidence for high-risk CE-marked medical devices for glucose management: A systematic review and meta-analysis.

AIMS: To conduct a systematic review and meta-analysis, within the Coordinating Research and Evidence for Medical Devices (CORE-MD) project, evaluating CE-marked high-risk devices for glucose management. MATERIALS AND METHODS: We identified interventional and observational studies evaluating the efficacy and safety of eight automated insulin delivery (AID) systems, two implantable insulin pumps, and three implantable continuous glucose monitoring (CGM) devices. We meta-analysed randomized controlled trials (RCTs) comparing AID systems with other treatments. RESULTS: A total of 182 studies published between 2009 and 2024 were included, comprising 166 studies on AID systems, six on insulin pumps, and 10 on CGM devices; 26% reported industry funding; 18% were pre-market; 37% had a comparator group. Of the studies identified, 29% were RCTs, 24% were non-randomized trials, and 47% were observational studies. The median (interquartile range) sample size was 48 (28-102), age 34.8 (14-44.2) years, and study duration 17.5 (12-26) weeks. AID systems lowered glycated haemoglobin by 0.5 percentage points (absolute mean difference [MD] = -0.5; 21 RCTs; I2 = 86%) and increased time in target range for sensor glucose level by 13.4 percentage points (MD = 13.4; 14 RCTs; I2 = 90%). At least one safety outcome was assessed in 71% of studies. CONCLUSIONS: High-risk devices for glucose monitoring or insulin dosing, in particular AID systems, improve glucose control safely, but evidence on diabetes-related end-organ damage is lacking due to short study durations. Methodological heterogeneity highlights the need for developing standards for future pre- and post-market investigations of diabetes-specific high-risk medical devices.

Fear of Hypoglycemia and Diabetes Distress: Expected Reduction by Glucose Prediction.

BACKGROUND: Extended glucose predictions are novel in diabetes management. Currently, there is no solution widely available. People with diabetes mellitus (DM) are offered features like trend arrows and limited predictions linked to predefined situations. Thus, the impact of extended glucose predictions on the burden of diabetes and person-reported outcomes (PROs) is unclear. METHODS: In this online survey, 206 people with type 1 and type 2 diabetes (T1D and T2D), 70.9% and 29.1%, respectively, who participated in the dia·link online panel and were current continuous glucose monitoring (CGM) users, were presented with different scenarios of hypothetical extended glucose predictions. They were asked to imagine how low glucose predictions of 30 minutes and overnight as well as glucose predictions up to 2 hours would influence their diabetes management. Subsequently, they completed the Hypoglycemia Fear Survey II (HFS-II) and the T1 Diabetes Distress Scale (T1-DDS) by rating each item on a 5-point scale (-2: strong deterioration to +2: strong improvement) according to the potential change due to using glucose predictions. RESULTS: For all glucose prediction periods, 30 minutes, up to 2 hours, and at nighttime, the surveyed participants expected moderate improvements in both fear of hypoglycemia (HFS-II: 0.57 ± 0.49) and overall diabetes distress (T1-DDS = 0.44 ± 0.49). The T1-DDS did not differ for type of therapy or diabetes. CONCLUSIONS: People with T1D and T2D would see glucose predictions as a potential improvement regarding reduced fear of hypoglycemia and diabetes distress. Therefore, glucose predictions represent a value for them in lowering the burden of diabetes and its management.

Nocturnal Hypoglycemia in the Era of Continuous Glucose Monitoring.

Nocturnal hypoglycemia is a common acute complication of people with diabetes on insulin therapy. In particular, the inability to control glucose levels during sleep, the impact of external factors such as exercise, or alcohol and the influence of hormones are the main causes. Nocturnal hypoglycemia has several negative somatic, psychological, and social effects for people with diabetes, which are summarized in this article. With the advent of continuous glucose monitoring (CGM), it has been shown that the number of nocturnal hypoglycemic events was significantly underestimated when traditional blood glucose monitoring was used. The CGM can reduce the number of nocturnal hypoglycemia episodes with the help of alarms, trend arrows, and evaluation routines. In combination with CGM with an insulin pump and an algorithm, automatic glucose adjustment (AID) systems have their particular strength in nocturnal glucose regulation and the prevention of nocturnal hypoglycemia. Nevertheless, the problem of nocturnal hypoglycemia has not yet been solved completely with the technologies currently available. The CGM systems that use predictive models to warn of hypoglycemia, improved AID systems that recognize hypoglycemia patterns even better, and the increasing integration of artificial intelligence methods are promising approaches in the future to significantly minimize the risk of a side effect of insulin therapy that is burdensome for people with diabetes.

Clinical Usage and Potential Benefits of a Continuous Glucose Monitoring Predict App.

Continuous glucose monitoring (CGM) has become an increasingly important tool for self-management in people with diabetes mellitus (DM). In this paper, we discuss recommendations on how to implement predictive features provided by the Accu-Chek SmartGuide Predict app in clinical practice. The Predict app's features are aimed at ultimately reducing diabetes stress and fear of hypoglycemia in people with DM. Furthermore, we explore the use cases and potential benefits of continuous glucose prediction, predictions of low glucose, and nocturnal hypoglycemia.

Relationship Between Sensor-Detected Hypoglycemia and Patient-Reported Hypoglycemia in People With Type 1 and Insulin-Treated Type 2 Diabetes: The Hypo-METRICS Study.

OBJECTIVE: Use of continuous glucose monitoring (CGM) has led to greater detection of hypoglycemia; the clinical significance of this is not fully understood. The Hypoglycaemia-Measurement, Thresholds and Impacts (Hypo-METRICS) study was designed to investigate the rates and duration of sensor-detected hypoglycemia (SDH) and their relationship with person-reported hypoglycemia (PRH) in people living with type 1 diabetes (T1D) and insulin-treated type 2 diabetes (T2D) with prior experience of hypoglycemia. RESEARCH DESIGN AND METHODS: We recruited 276 participants with T1D and 321 with T2D who wore a blinded CGM and recorded PRH in the Hypo-METRICS app over 10 weeks. Rates of SDH <70 mg/dL, SDH <54 mg/dL, and PRH were expressed as median episodes per week. Episodes of SDH were matched to episodes of PRH that occurred within 1 h. RESULTS: Median [interquartile range] rates of hypoglycemia were significantly higher in T1D versus T2D; for SDH <70 mg/dL (6.5 [3.8-10.4] vs. 2.1 [0.8-4.0]), SDH <54 mg/dL (1.2 [0.4-2.5] vs. 0.2 [0.0-0.5]), and PRH (3.9 [2.4-5.9] vs. 1.1 [0.5-2.0]). Overall, 65% of SDH <70 mg/dL was not associated with PRH, and 43% of PRH had no associated SDH. The median proportion of SDH associated with PRH in T1D was higher for SDH <70 mg/dL (40% vs. 22%) and SDH <54 mg/dL (47% vs. 25%) than in T2D. CONCLUSIONS: The novel findings are that at least half of CGM hypoglycemia is asymptomatic, even below 54 mg/dL, and many reported symptomatic hypoglycemia episodes happen above 70 mg/dL. In the clinical and research setting, these episodes cannot be used interchangeably, and both need to be recorded and addressed.

Glycemic Outcomes and Nurse Perceptions of Continuous Glucose Monitoring for Hospitalized Patients.

BACKGROUND: Continuous glucose monitoring (CGM) can decrease hypoglycemic events and health care costs; however, barriers and facilitators that influence CGM use are unknown. PURPOSE: The purpose of this study was to evaluate hypoglycemic events and cost outcomes after CGM implementation and describe associated barriers and facilitators. METHODS: A mixed-methods study design was used to evaluate CGM implementation on 2 pulmonary units within an academic health center. Hypoglycemic events were evaluated before and after CGM implementation, and nurses were interviewed about facilitators and barriers that influence CGM use. RESULTS: Hypoglycemic events decreased from a rate of 0.0906 per 1000 patient days to 0.0503 postimplementation, P < .0001. A $105 766 cost avoidance was recognized. Barriers and facilitators to CGM use are described. CONCLUSIONS: Findings support CGM implementation, while uniquely contributing financial impact and device use barriers and facilitators. Hospitals may consider CGM use to improve timely identification and treatment of hypoglycemia.

Hypoglycemia and Multivitamins.

Insulin autoimmune syndrome (IAS) is a rare condition triggered by exposure to various drugs containing sulfhydryl compounds, proton pump inhibitors, supplements, plasma proteins, viral infections like measles, influenza, hepatitis C, and autoimmune conditions like Graves' disease and systemic lupus erythematosus.1,3 We report two patients with recurrent episodes of hypoglycemia who were then diagnosed with IAS due to the consumption of α-lipoic acid (ALA) present in a multivitamin supplement. Eating small, frequent meals containing complex carbohydrates and steroids helps normalize blood glucose levels and reduce the insulin autoantibodies (IAA) to undetectable levels.3.