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Background: The objective of this study was to investigate whether an isolated abnormal 1-hour glucose challenge test (GCT) among patients without gestational diabetes (GDM) is associated with adverse outcomes., Methods: This is a retrospective cohort study of patients who underwent GDM screening at ≥ 24 weeks' gestation with a 1-hour GCT and delivered a singleton fetus at > 35 weeks' gestation at an urban tertiary hospital from 1/2013 to 10/2021. Data were extracted from an electronic medical record data warehouse using standardized billing/diagnosis codes. Individuals were categorized into 3 groups: normal screening (1-hour GCT value < 140 mg/dL), intermediate screening (1-hour GCT value ≥ 140 and < 200 but normal 3-hour glucose tolerance test (GTT)), and GDM (1-hour GCT ≥ 200 mg/dL or abnormal 3-hour GTT). The primary composite perinatal morbidity outcome included any of the following: large for gestational age (LGA) birthweight, birth injury, hypoglycemia with neonatal intensive care unit (NICU) admission, respiratory distress syndrome, transient tachypnea of the newborn, apnea, NICU admission, or perinatal death. Multiple secondary outcomes were also evaluated. Bivariable analyses and multivariable logistic regression modeling were performed., Results: Of 37,277 eligible patients, 29,698 (79.7%) had normal screening results, 5092 (13.7%) had intermediate screening results, and 2487 (6.6%) were diagnosed with GDM. There were significant differences in baseline characteristics between the three groups, including age, parity, race and ethnicity, payer-type, obesity, and pre-pregnancy metformin use. Compared to normal screening, intermediate screening was associated with an increased risk for the composite perinatal morbidity outcome (OR 1.23, 95% CI 1.15-1.32), cesarean (OR 1.37, 95% CI 1.28-1.46), and hypertensive disorders of pregnancy (OR 1.30, 95% CI 1.20-1.40). Associations for these outcomes were further pronounced in those with GDM compared to normal screening (OR 1.86, 95% CI 1.70-2.03; OR 1.69, 95% CI 1.56-1.84; and OR 1.57, 95% CI 1.42-1.74, respectively). After adjusting for potential confounders, increased risks for the composite perinatal morbidity outcome persisted for those with intermediate screening (aOR 1.18, 95% CI 1.10-1.26)., Conclusions: In addition to patients with GDM, individuals an isolated abnormal 1-hour GCT without GDM were also at increased risks for adverse pregnancy outcomes. Further investigation is needed to understand if patients with mild dysregulation may still benefit from other interventions., Competing Interests: Declarations. Ethical approval: This study and experimental protocol were approved by the Yale New Haven Hospital Institutional Review Board (IRB). The need for individual participant informed consent was waived by the Yale IRB. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Background: Insulin autoimmune syndrome (IAS), characterized by endogenous hypoglycemia associated with insulin autoantibodies, is a rare cause of hypoglycemia in pediatric patients. Here, we report a case of the youngest patient with IAS in China, and summarize the clinical characteristics of the disease through a narrow review of pediatric cases., Case Presentation: A 3-year-10-month-old Chinese boy presented with unconsciousness. Initially, he was misdiagnosed with hyperinsulinemic hypoglycemia (HH) due to non-ketotic hypoglycemia. Whole exome sequencing (WES) was negative, and no pancreatic space-occupying lesions were identified. He continued to have intermittent episodes of symptomatic hypoglycemia. During an extended oral glucose tolerance test (OGTT), his insulin to C-peptide molar ratio was greater than 1, and anti-insulin antibodies (IAAs) measurements were as high as 54.38 COI (normal range 0-1 COI). High-resolution human leukocyte antigen (HLA) test showed a DRB1*08:03/*12:02 genotype. He was eventually diagnosed with IAS. Hypoglycemic episodes were not observed as long as the patient adhered to the low and frequent carbohydrate diet. Six months later, the patient's anti-insulin antibody had decreased to 10.17 COI, and mildly symptomatic hypoglycemia occasionally occurred in the case of noncompliance with the diet. Based on 11 studies from a literature review and our own case, a total of 12 pediatric patients were analyzed. Most of these patients presented with unconsciousness initially and their episodes of hypoglycemia do not follow a definitive pattern. Adjustments in diet serve as an effective intervention, and spontaneous remission is relatively common., Conclusion: When differentiating the causes of HH in pediatric patients, IAS should not be overlooked. Elevated levels of IAAs and an inappropriate insulin to C-peptide molar ratio during an extended OGTT are critical indicators., Clinical Trial Number: Not applicable., Competing Interests: Declarations. Ethics approval and consent to participate: This study’s ethical principles align with Helsinki’s declarations. The patient’s identity was protected. This study was approved by the Ethics Committee of Beijing Children’s Hospital. Consent for publication: Written informed consent for publication was obtained from the patient’s parents. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Background: Continuous glucose monitoring (CGM) improves glycemic control and quality of life. Data on glycemic indices and fear of hypoglycemia (FoH) in newly diagnosed T1DM patients are limited., Aim: To assess the impact of initiating intermittently scanned CGM (isCGM) within 1-6 months of diagnosis on glycemic control and FoH in adults with T1DM., Subjects and Methods: After wearing a blinded sensor for 14 days, participants were randomized (1:1) to either isCGM (intervention) or self-monitoring blood glucose (SMBG) with glucometers and blinded CGM (control). Primary outcomes were changes in time below 70 mg/dl (TB70) and FoH, assessed in the Hypoglycemia Fear Survey (HFS). Main secondary outcomes included changes in mean glucose and time in range (TIR) from baseline to 4 weeks after randomization., Results: The full analysis set included 23 patients (12 from the intervention group and 11 from the control group), aged 25.6 ± 5.1 years (14 men, 9 women). All participants were on multiple daily insulin injections. TB70 changed from 2.42% to 2.25% in the intervention, and from 2.81% to 1.82% in the control group, and the between-therapy difference of 0.83% was insignificant. No difference between intervention and control groups in change in HFS-worry and HFS-behavior subscales between baseline and after 4 weeks was found (-1.6 ± 3.2 and 1.0 ± 2.2, respectively). The mean glucose levels changed from 7.03 mmol/l to 6.73 mmol/l and from 7.07 mmol/l to 7.43 mmol/l, in the intervention and control groups, respectively, which resulted in a between-therapy significant glucose difference of -0.66 mmol/l. The mean TIR changed from 88.0% to 90.0% in the intervention group and from 85.2 to 84.1% in the control group-the between-therapy difference was insignificant (3,1%). The study ended early due to CGM reimbursement policy changes, after which most patients eligible for the study could have isCGM reimbursed., Conclusions: In newly diagnosed T1DM adults, TIR is high and hypoglycemia risk is low. The study group was small; however, the data suggest that the use of isCGM soon after T1DM diagnosis could result in mean glucose decrease, but not in change in TB70 and FoH., Competing Interests: DZ-Z and MM have received lecture honoraria and serve on advisory boards for Abbott Diabetes Care. IK serves on advisory boards for Abbott Diabetes Care. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2025 Hohendorff, Grzelka-Wozniak, Wrobel, Kania, Lapinska, Rokicka, Stoltny, Kowalska, Strojek, Zozulinska-Ziolkiewicz and Malecki.)

Purpose: To investigate the impact of clinical and socio-economic factors on glycaemic control and construct statistical models to predict optimal glycaemic control (OGC) after implementing intermittently scanned continuous glucose monitoring (isCGM) systems., Methods: This retrospective study included 1072 type 1 diabetes patients (49.0% female) from three centres using isCGM systems. Clinical data and net income from the census tract were collected for each individual. OGC was defined as time in range > 70%, with time below 70 mg/dL < 4%. The sample was randomly split in two equal parts. Logistic regression models to predict OGC were developed in one of the samples, and the best model was selected using the Akaike information criterion and adjusted for Pearson's and Hosmer-Lemeshow's statistics. Model reliability was assessed via external validation in the second sample and internal validation using bootstrap resampling., Results: Out of 2314 models explored, the most effective predictor model included annual net income per person, sex, age, diabetes duration, pre-isCGM HbA1c, insulin dose/kg, and the interaction between sex and HbA1c. When applied to the validation cohort, this model demonstrated 72.6% specificity, 67.3% sensitivity, and an area under the curve (AUC) of 0.736. The AUC through bootstrap resampling was 0.756. Overall, the model's validity in the external cohort was 80.4%., Conclusions: Clinical and socio-economic factors significantly influence OGC in type 1 diabetes. The application of statistical models offers a reliable means of predicting the likelihood of achieving OGC following isCGM system implementation., (© 2024 The Author(s). Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.)

Objectives: The purpose of this study was to develop a valid and reliable instrument for assessing patients' behavior toward the risk of hypoglycemia through self-assessment. Insufficient education and supervision of type 2 diabetes mellitus (DM) outpatients by healthcare providers is a significant concern, affecting their behavior during the treatment process. Additionally, inappropriate behavior typically increases the risk of hypoglycemia. To mitigate this risk, several studies have recommended evaluating patients' behavior, necessitating the development of a new instrument., Methods: The study procedures were conducted in 3 stages: instrument development (face and content validity, stage I), construct validity and reliability test (stage II), and criterion validity (stage III). Stage I involved 5 healthcare practitioners, including internal medicine doctors, nurses, dietitians, and pharmacists in hospitals and community health centers. Stage II included 20 respondents using a 1-shot test method. Stage III involved 237 type 2 DM outpatients at Central General Hospital (RSUP) in Jakarta, employing a cross-sectional design and consecutive sampling., Results: The results indicated that the developed instrument was valid and reliable, comprising 9 domains (29 questions). These domains included behavior toward blood glucose monitoring, diet, physical activity, medication, assistance from healthcare providers, hypoglycemia management, self-care, family support, and insulin use. Furthermore, poor behavior was found to increase the risk of hypoglycemia by 2.36 times., Conclusions: Based on these results, the developed instrument could be effectively used to evaluate behavior toward hypoglycemia among type 2 DM outpatients, confirming its validity and reliability.

Background: There is a lack of data on the validation and diagnostic performance of the Freestyle Optium Neo-H (Freestyle) and Centrivet GK (Centrivet) devices for the diagnosis of hypoglycaemia, hyperglycaemia and hyperketonaemia in goats., Objectives: The aim of the present study was to validate the Freestyle and Centrivet for the analysis of whole blood beta-hydroxybutyric acid (BHBA) and to validate the Freestyle for the analysis of whole blood glucose concentrations using the reference method (RM) in goat blood collected from the jugular and ear veins., Methods: Venous blood samples were utilised to assess glucose and BHBA concentrations using the Freestyle, Centrivet and RM. The cut-off point of BHBA was ≥ 0.8 mmol/L for hyperketonaemia. A total of 198 paired blood samples (vena jugularis and ear vein) were collected from 99 hair goats. The cut-off point for hypoglycaemia diagnosis was < 49 mg/dL., Results: There were proportional but no constant errors between RM and Freestyle and Centrivet for BHBA, and both proportional and constant errors were observed for glucose analysis. The mean bias for BHBA analysis was 0.14 and 0.06 mmol/L (Freestyle-RM) 0.51 and 0.16 mmol/L (Centrivet-RM) for jugular and ear veins, respectively. The mean bias for blood glucose analysis was 0.0 and 5.6 mg/L between Freestyle and RM in the jugular and ear veins, respectively. The sensitivity (Centrivet: 50%-61.3%; Freestyle: 93.6%-75.8%) and specificity (Centrivet GK: 75.7%-73%; Freestyle: 37.8%-70.3%) were determined in jugular and ear vein blood for hyperketonaemia diagnostics, respectively. The AUC of Freestyle was 0.89 and 0.95 in the jugular and ear vein for hypoglycaemia, respectively. The sensitivity of Freestyle was 60.3% and 96.8% in the jugular and ear vein for hypoglycaemia. The specificity of Freestyle was 100.0% and 76.7% for hypoglycaemia in jugular and ear veins, respectively., Conclusions: Freestyle demonstrated acceptable diagnostic performance for hypoglycaemia in ear veins, but neither Freestyle nor Centrivet showed sufficient diagnostic performance for hyperketonaemia. Both analysers were not interchangeable with RM in BHBA and glucose analysis., (© 2025 The Author(s). Veterinary Medicine and Science published by John Wiley & Sons Ltd.)

Pediatric diabetes I is an endemic and an especially difficult disease; indeed, at this point, there does not exist a cure, but only careful management that relies on anticipating hypoglycemia. The changing physiology of children producing unique blood glucose signatures, coupled with inconsistent activities, e.g., playing, eating, napping, makes "forecasting" elusive. While work has been done for adult diabetes I, this does not successfully translate for children. In the work presented here, we adopt a reinforcement approach by leveraging the de Bruijn graph that has had success in detecting patterns in sequences of symbols-most notably, genomics and proteomics. We translate a continuous signal of blood glucose levels into an alphabet that then can be used to build a de Bruijn, with some extensions, to determine blood glucose states. The graph allows us to "tune" its efficacy by computationally ignoring edges that provide either no information or are not related to entering a hypoglycemic episode. We can then use paths in the graph to anticipate hypoglycemia in advance of about 30 minutes sufficient for a clinical setting and additionally find actionable rules that accurate and effective. All the code developed for this study can be found at: https://github.com/KurbanIntelligenceLab/dBG-Hypoglycemia-Forecast ., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics statement: The study methodology, consent, and assent forms were approved by the Institutional Review Boards of Texas A &M University (IRB2019-0378F) and Sidra Medicine (1536095). After being informed about the study’s specifics, adolescents and their parents/guardians signed written informed consent and parental permission forms. All participants were recruited from T1D patients getting treatment at Sidra Medicine’s Endocrinology and Diabetic Clinic in Qatar. All methods were performed in accordance with relevant guidelines and regulations., (© 2024. The Author(s).)

Patients with diabetes mellitus (DM) and chronic kidney disease (CKD) exhibit an elevated risk for cardiac arrhythmias, such as bradycardia, which may potentially lead to sudden cardiac death (SCD). While hypoglycemia, defined as a critical drop in glucose levels below the normal range, has long been associated with adverse cardiovascular events, recent studies have highlighted the need for a comprehensive reevaluation of its direct impact on cardiovascular outcomes, particularly in high-risk populations such as those with DM and CKD. In this study, we investigated the association between glucose levels and bradycardia by simultaneously monitoring interstitial glucose (IG) and ECG for 7 days in insulin-treated patients with DM and CKD. We identified bradycardia episodes in 19 of 85 patients (22%) and associated these episodes with personalized low, medium, and high relative glucose levels. Our analysis revealed a significant increase in bradycardia frequency during periods of lowest relative glucose, particularly between 06:00-09:00 and 12:00-15:00. Furthermore, leveraging a Random Forests classifier, we achieved a promising area under the curve (AUC) of 0.94 for predicting bradyarrhythmias using glucose levels and heart rate variability features. Contrary to previous findings, only 4% of bradycardia episodes in our study population occurred at glucose levels of 70 mg/dL or lower, with 28% observed at levels exceeding 180 mg/dL. Our findings not only highlight the strong correlation between relative glucose levels, heart rate parameters, and bradycardia onset but also emphasize the need for a more personalized definition of hypoglycemia to understand its relationship with bradyarrhythmias in high-risk DM and CKD patient populations., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The insulin tolerance test (ITT) is the gold standard for the diagnosis of cortisol and growth hormone (GH) deficiencies. Once hypoglycemia is detected whether patients should receive carbohydrates to recover faster from hypoglycemia is controversial. The aim of our study was to assess the impact of shortening the duration of hypoglycemia by providing a sugar drink on patient comfort and hormonal responses. This prospective, single-center, crossover, single-blind study enrolled 15 healthy participants. Each subject performed two ITT: one with normal Cola and the other with Cola Zero. Glucose and hormone levels were measured at baseline and after the induction of insulin-induced hypoglycemia. Patient tolerance to ITT was evaluated using reported hypoglycemia side effects, visual analog scale scores, and quality-of-life questionnaire. Normal Cola shortened the period of hypoglycemia (plasma glucose < 40 mg/dl) from 30 to 15 min (p = 0.005), allowing a higher proportion of participants to recover from potentially dangerous values after 45 min (12 vs. 5; p = 0.008). Cola also improved patient comfort, as evaluated using a visual analog scale (VAS score 2.6 vs 3.7, p = 0.016). Sugar did not significantly change the median cortisol and GH peaks. Body mass index was the only factor determining the cortisol peak, independent of the injected insulin dose. The time to reach hormone peaks was similar between the two protocols. Cortisol and GH values were significantly higher at 120 min in the Cola Zero group, suggesting the prolongation of hypothalamic-pituitary stress in the absence of sugar. Our study confirmed that rapid correction of hypoglycemia during ITT improves subject comfort, reduces the duration of hypoglycemia and associated symptoms, while guaranteeing unchanged cortisol and GH peaks., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

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.

Background: This meta-analysis was performed to obtain a comprehensive overview of the differences between once-weekly basal insulin (including icodec and basal insulin Fc) and once-daily basal insulin (including glargine and degludec) in patients with type 1 and type 2 diabetes mellitus., Methods: PubMed, EMBASE, and Cochrane Library were systematically searched for eligible studies up to 2 January 2024., Results: A total of 12 studies were included, comprising 5,895 patients, with 3,104 (52.7%) using once-weekly insulin and 2,791 (47.3%) using once-daily insulin. In the pooled data, glycated hemoglobin (HbA1c) change from baseline [mean difference (MD) -0.11%; 95% confidence interval (CI) -0.20 to -0.01%] and the odds of achieving an end-of-trial HbA1c <7% (OR 1.41, 95% CI 1.13, 1.77) demonstrated a significantly good glycemic control in the once-weekly insulin group, especially in insulin-naïve type 2 diabetics or patients using icodec. Body weight increase for once-weekly insulin was 0.43 kg compared to controls (95% CI 0.09 to 0.76 kg). In addition, once-weekly insulin was correlated with a higher risk of level 1 hypoglycemia (OR 1.42, 95% CI 1.26 to 1.6). There was no significant difference in fasting plasma glucose (MD 2.46 mg/dL; 95% CI -2.60 to 7.52 mg/dL), time in range (MD 2.03%; 95% CI -0.50 to 4.56%), and level 2 or 3 hypoglycemic events (OR 1.19; 95% CI 0.93 to 1.53)., Conclusions: Once-weekly basal insulin is safe and effective in modestly reducing HbA1c with similar level 2 or 3 hypoglycemic events compared to once-daily insulin, although the risk of level 1 hypoglycemia and weight gain was slightly increased., Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO, Identifier CRD42024496812., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Xue, Shen, Tang, Deng and Dai.)

Background: Hypoglycemic episodes cause varying degrees of damage in the functional system of elderly inpatients with type 2 diabetes mellitus (T2DM). The purpose of the study is to construct a nomogram prediction model for the risk of hypoglycemia in elderly inpatients with T2DM and to evaluate the predictive performance of the model., Methods: From August 2022 to April 2023, 546 elderly inpatients with T2DM were recruited in seven tertiary-level general hospitals in Beijing and Inner Mongolia province, China. Medical history and clinical data of the inpatients were collected with a self-designed questionnaire, with follow up on the occurrence of hypoglycemia within one week. Factors related to the occurrence of hypoglycemia were screened using regularized logistic analysis(r-LR), and a nomogram prediction visual model of hypoglycemia was constructed. AUROC, Hosmer-Lemeshow, and DCA were used to analyze the prediction performance of the model., Results: The incidence of hypoglycemia of elderly inpatients with T2DM was 41.21% (225/546). The risk prediction model included 8 predictors as follows(named ADOCHBIU): duration of diabetes ( OR =2.276, 95% CI 2.097˜2.469), urinary microalbumin( OR =0.864, 95% CI 0.798˜0.935), oral hypoglycemic agents ( OR =1.345, 95% CI 1.243˜1.452), cognitive impairment ( OR =1.226, 95% CI 1.178˜1.276), insulin usage ( OR =1.002, 95% CI 0.948˜1.060), hypertension ( OR =1.113, 95% CI 1.103˜1.124), blood glucose monitoring ( OR =1.909, 95% CI 1.791˜2.036), and abdominal circumference ( OR =2.998, 95% CI 2.972˜3.024). The AUROC of the prediction model was 0.871, with sensitivity of 0.889 and specificity of 0.737, which indicated that the nomogram model has good discrimination. The Hosmer-Lemeshow was χ 2 = 2.147 ( P =0.75), which meant that the prediction model is well calibrated. DCA curve is consistently higher than all the positive line and all the negative line, which indicated that the nomogram prediction model has good clinical utility., Conclusions: The nomogram hypoglycemia prediction model constructed in this study had good prediction effect. It is used for early detection of high-risk individuals with hypoglycemia in elderly inpatients with T2DM, so as to take targeted measures to prevent hypoglycemia., Trial Registration: ChiCTR2200062277. Registered on 31 July 2022., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Liu, Sun, Wu, Guo, Wang, Lin, Wang and Bai.)

Diabetes mellitus is the main cause of end-stage renal disease (ESKD), and most patients need hemodialysis (HD) treatment after they progress to uremia. Patients with diabetes and HD have obvious blood glucose fluctuation, hyperglycemia and hypoglycemia may both related to the higher mortality. Therefore, maintaining blood glucose stability is the main treatment strategy to improve the prognosis of patients. It is challenging to evaluate the blood glucose control of patients with diabetes and HD. The traditional blood glucose detection methods have certain limitations, they may be affected by many factors in HD patients. The application of continuous glucose monitoring (CGM) system is gradually recognized, CGM can monitor blood glucose real-time, timely, and predictive capabilities, there are fewer factors that are affected blood glucose in HD patients., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Diagnosing post-gastrectomy hypoglycemia is challenging, often relying on medical history with documented low plasma glucose levels. Here, we present three cases of patients who presented a high probability of post-gastrectomy hypoglycemia diagnosed and managed successfully using "theragnostic" continuous glucose monitoring and alpha-glucosidase inhibitors. In the first week, patients maintained their current lifestyle without medical intervention; in the second week, voglibose 0.2 mg before meals was prescribed. Continuous glucose monitoring data from the first week confirmed the diagnosis with multiple hypoglycemic events after postprandial peaks, whereas data from the second week showed reduced hypoglycemic events and lower glycemic variability, demonstrating voglibose's therapeutic effect. This report highlights the effective management of post-gastrectomy hypoglycemia using voglibose and theragnostic continuous glucose monitoring, showing its potential benefits and safety for similar cases., (© 2024 The Author(s). Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.)

A woman in her 60s presented with a small pancreatic head tumor. Imaging studies revealed a 13-mm well-defined pancreatic head tumor. A neuroendocrine neoplasm was suspected, and the patient opted for observation at that time. After 8 months, the patient began experiencing sweating while fasting, and blood tests during regular follow-up visits showed hypoglycemia. Hypoglycemia was induced during fasting test. The tumor exhibited clear features of an insulinoma during follow-up observation. While small neuroendocrine neoplasms are often managed through observation, caution should be exercised regarding their transformation into functional neuroendocrine tumors.

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., (© 2024 The Author(s). Nursing Open published by John Wiley & Sons Ltd.)

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., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

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., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

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., Competing Interests: Competing interests: LC, P-OC and DE have co-founded the company OneTwo Analytics AB of which JD is an employee. OneTwo Analytics AB is developing a commercial product (PRIO Scoring) based on the results presented here., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aromatic L-amino acid decarboxylase (AADC) deficiency is a disease in which neurological findings are dominant due to deficiencies in neurotransmitter synthesis. Hypoglycemia caused by autonomic dysfunction is one of the symptoms that may be encountered. Here we report a case of mild AADC deficiency presenting with hypoglycemia without any neurological signs. A 4-year-old girl presented with recurrent hypoglycemia. Her growth and development were normal. Plasma insulin and cortisol values were normal in the sample at the time of hypoglycemia. C8:1-Carnitine elevation was detected in the acylcarnitine profile. A clinical exome panel was performed with the suggestion of a fatty acid oxidation defect. However, a homozygous variant in the DDC gene was detected. Furthermore, cerebrospinal fluid neurotransmitter analysis revealed low 5-hydroxyindolacetic acid and homovanillic acid and high 3-O-methyl-dopa and methyltetrahydrofolate (5 MTHF) consistent with AADC deficiency. Plasma AADC enzyme activity was low. The episodes of hypoglycemia were treated with uncooked cornstarch. This case suggests that AADC deficiency should be considered in some patients with hypoglycemia., Competing Interests: Conflict of interest: None declared., (©Copyright 2024 by Turkish Society for Pediatric Endocrinology and Diabetes / The Journal of Clinical Research in Pediatric Endocrinology published by Galenos Publishing House.)

Background: Solitary fibrous tumor (SFT) is a rare fibroblastic mesenchymal tumor that mostly involves the pleura and infrequently involves extra-pleural sites. De novo SFT of the kidney is uncommon, and malignant SFT is extremely rare., Case Presentation: We report a case of a 51-year-old man with a large malignant SFT in the left kidney. Pathological examination confirmed the diagnosis of SFT based on typical morphology, nuclear STAT6 expression, and NAB2-STAT6 gene fusion. The malignant subtype was determined by a large tumor size (≥ 15 cm) and high mitotic counts (8/10 high-power fields). KRAS mutation was identified by DNA sequencing. Insulin-like growth factor 2 (IGF2) was diffusely and strongly expressed in tumor cells, however, hypoglycemia was not observed. Hyperglycemia and high adrenocorticotropic hormone (ACTH) concentration were observed one month after surgery. Hormone measurements revealed normal blood cortisol and aldosterone levels, and increased urinary free cortisol level. A pituitary microadenoma was identified using brain magnetic resonance imaging, which may be responsible for the promotion of hyperglycemia., Conclusions: We report a case of renal malignant SFT with a KRAS mutation, which was previously unreported in SFT and may be associated with its malignant behavior. Additionally, we emphasize that malignant SFT commonly causes severe hypoglycemia due to the production of IGF2. However, this effect may be masked by the presence of other lesions that promote hyperglycemia. Therefore, when encountering a malignant SFT with diffuse and strong IGF2 expression and without hypoglycemia, other lesions promoting hyperglycemia need to be ruled out., (© 2024. The Author(s).)

Objective: To examine the relationship between gestational glucose intolerance (GGI) and neonatal hypoglycemia., Research Design and Methods: This was a secondary analysis of 8,262 mother-infant dyads, with delivery at two hospitals between 2014 and 2023. We categorized maternal glycemic status as normal glucose tolerance (NGT), GGI, or gestational diabetes mellitus (GDM). We defined NGT according to a normal glucose load test result, GGI according to an abnormal glucose load test result with zero (GGI-0) or one (GGI-1) abnormal value on the 100-g oral glucose tolerance test, and GDM according to an abnormal glucose load test result with two or more abnormal values on the glucose tolerance test. Neonatal hypoglycemia was defined according to blood glucose <45 mg/dL or ICD-9 or ICD-10 diagnosis of neonatal hypoglycemia. We used logistic regression analysis to determine associations between maternal glucose tolerance category and neonatal hypoglycemia and conducted a sensitivity analysis using Δ-adjusted multiple imputation, assuming for unscreened infants a rate of neonatal hypoglycemia as high as 33%., Results: Of infants, 12% had neonatal hypoglycemia. In adjusted models, infants born to mothers with GGI-0 had 1.28 (95% 1.12, 1.65), GGI-1 1.58 (95% CI 1.11, 2.25), and GDM 4.90 (95% CI 3.81, 6.29) times higher odds of neonatal hypoglycemia in comparison with infants born to mothers with NGT. Associations in sensitivity analyses were consistent with the primary analysis., Conclusions: GGI is associated with increased risk of neonatal hypoglycemia. Future research should include examination of these associations in a cohort with more complete neonatal blood glucose ascertainment and determination of the clinical significance of these findings on long-term child health., (© 2024 by the American Diabetes Association.)

BACKGROUND Hypoglycemia is a common complication following total gastrectomy, primarily caused by dumping syndrome and severe malnutrition, with late dumping syndrome being particularly significant. However, for recurrent fasting hypoglycemia, the possibility of insulinoma should be considered. Hypoglycemia caused by insulinoma can lead to severe consequences, including seizures and even death. Thus, it is crucial to differentially diagnose hypoglycemia occurring after total gastrectomy. CASE REPORT In this report, we present the case of a 36-year-old Chinese woman who underwent total gastrectomy for gastric cancer and subsequently received chemotherapy. Four months after surgery, she began experiencing recurrent seizures, and multiple tests confirmed hypoglycemia. A series of laboratory and imaging examinations ultimately led to a diagnosis of insulinoma. After surgical resection of the tumor, the patient's hypoglycemic symptoms resolved, and pathology results confirmed an insulinoma. CONCLUSIONS This case report highlights the rapid weight loss and severe hypoglycemia observed in a patient only 4 months after total gastrectomy for gastric cancer. Although dumping syndrome was initially suspected based on the clinical course, the final diagnosis turned out to be insulinoma. The case underscores the importance of comprehensive evaluation and appropriate diagnostic investigations for patients experiencing hypoglycemia after total gastrectomy. Furthermore, the case suggests that the increased levels of enteroglucagon following changes in the gastrointestinal tract resulting from total gastrectomy may promote the development of insulinomas. This case report also contributes to the existing literature regarding atypical presentations of insulinomas and their association with gastric resection.

Fulminant type 1 diabetes (FT1D) is a unique subtype of type 1 diabetes, characterized by acute absolute insulin deficiency, severe ketosis, and increased risk of hypoglycemia, glycemic variability and microvascular complications. Seven people with FT1D were identified from two tertiary centers in Singapore. Six were Chinese, the mean age was 35 years and all were lean (mean body mass index 20.3 kg/m 2 ). All presented with diabetes ketosis or ketoacidosis and low C-peptide. All but one had low glutamic acid decarboxylase antibodies. Nearly half had a missed/delayed diagnosis of FT1D. Three had frequent hypoglycemia, which improved after transition to continuous subcutaneous insulin infusion therapy. Individuals with FT1D experience unique diagnostic and management challenges associated with rapid absolute insulin deficiency. Greater awareness about this clinical entity is required., (© 2024 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.)

Introduction: Introduction and objective: neonatal hypoglycemia persistently offers multiple diagnostic controversies. This study aims to present the current situation regarding neonatal hypoglycaemia detection, and to gain insiht into the most widely used portable glucometers in neonatal units today. Methods: an online questionnaire was prepared and sent to the members of the Spanish Society of Neonatology; a total of 75 hospitals participated. Results: portable glucometers continue to be widely used in the neonatal population. More than 75 % of units perform neonatal hypoglycemia screening in specific clinical circumstances, and 13 % of units continue to perform protocolized screening on all newborns at neonatal units. The higher the level of care, the higher the percentage of hypoglycaemia detection by other tests (such as blood gas analysis): chi2, p = 0.019. Multiple models of portable glucometers are currently used, with differences according to level of care (chi2, p = 0.01). Nova Biomedical, Abbott, and Roche Diagnostics models are most commonly used. Conclusions: differences in the performance of neonatal hypoglycaemia screening are observed, so standardised procedures and limiting the neonatal population at risk are important to reduce variability in clinical practice, and to improve the quality of neonatal care. [ABSTRACT FROM AUTHOR]

We herein report a case in which diazoxide was effective in treating reactive hypoglycemia caused by late dumping syndrome in a patient with end-stage renal disease (ESRD). A 50-year-old man with ESRD and a history of gastrectomy underwent hemodialysis. Although he was administered voglibose to treat recurrent reactive hypoglycemia caused by late dumping syndrome, he had difficulty continuing treatment because of gastrointestinal side effects. When he began diazoxide treatment, the reactive hypoglycemia improved. The dose was gradually increased with no apparent side effects, and the hypoglycemic attacks disappeared one year after the start of treatment.

Glycogen storage disease type 1 is a congenital abnormality of metabolism caused by the deficiency of the glucose-6-phosphatase enzyme, essential in glucose homeostasis. Patients with this disease are at high risk of developing hypoglycemia, hyperlipidemia, lactic acidemia, growth retardation, neutropenia, inflammatory bowel disease, and many other severe complications, such as hepatic adenomas converting into hepatocellular carcinomas. To prevent these complications, a liver transplant is the ultimate method of treatment. We present the successful anesthesia management for a 21-year-old man who had gross hepatomegaly, severe hypoglycemia, and hyperlactatemia and who received a liver transplant from his mother, which is a substantial challenge for anesthesiologists. Anesthesiologists should know the underlying pathophysiological condition and perform a comprehensive preoperative evaluation to determine the correct anesthesia plan in patients with glycogen storage disease type 1 who will undergo an orthotopic liver transplant due to multiple system disorders. Successful perioperative management of patients with glycogen storage disease type 1 relies on effective communication and collaboration between specialists through a multidisciplinary team approach.

Background: Sepsis is a life-threatening condition for which critically important antimicrobials are often indicated. The value of blood culture for sepsis is indisputable, but appropriate guidelines on sampling and interpretation are currently lacking in cattle., Objective: Compare the diagnostic accuracy of 2 blood culture media (pediatric plus [PP] and plus aerobic [PA]) and hypoglycemia for bacteremia detection. Estimate the contamination risk of blood cultures in critically ill calves., Animals: One hundred twenty-six critically ill calves, 0 to 114 days., Methods: Retrospective cross-sectional study in which the performance of PP, PA and hypoglycemia to diagnose sepsis was assessed using a Bayesian latent class model. A Cox proportional hazards model was used to compare time to positivity (TTP). Potential contamination was descriptively analyzed. Isolates were considered relevant when they were; member of the Enterobacterales, isolated from both blood cultures vials, or well-known, significant bovine pathogens., Results: The sensitivities for PP, PA, and hypoglycemia were higher when excluding assumed contaminants; 68.7% (95% credibility interval = 30.5%-93.7%), 87.5% (47.0%-99.5%), and 61.3% (49.7%-72.4%), respectively. Specificity was estimated at 95.1% (82.2%-99.7%), 94.2% (80.7%-99.7%), and 72.4% (64.6%-79.6%), respectively. Out of 121 interpretable samples, 14.9% grew a presumed contaminant in PA, PP, or both. There was no significant difference in the TTP between PA and PP., Conclusions and Clinical Importance: PA and PP appear to outperform hypoglycemia as diagnostic tests for sepsis. PA seems most sensitive, but a larger sample size is required to verify this. Accuracy increased greatly after excluding assumed contaminants. The type of culture did not influence TTP or the contamination rate., (© 2024 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals LLC on behalf of American College of Veterinary Internal Medicine.)

Pyruvate dehydrogenase complex (PDHC) deficiency is a common genetic disorder leading to lactic acidosis, which can also result from several nongenetic conditions, such as septic shock. The present study reports a case of PDHC deficiency masked by septic shock-induced lactic acidosis. This case involved a 16-year-old adolescent with poor exercise tolerance compared with his peers, and no underlying diseases. The disease onset was characterized by cough, fever, and dyspnea, with hypotension and elevated lactate levels, which indicated septic shock. However, severe hypoglycemia and lactic acidosis persisted despite resolution of a pulmonary infection and correction of septic shock, requiring continuous intravenous infusion of 50% glucose. Although the patient did not experience acute kidney injury and had normal urine output, continuous renal replacement therapy was used to regulate the internal environment owing to the severity of the acidosis. The diagnosis of PDHC deficiency was considered on the basis of the persistent hypoglycemia and hyperlactatemia, before genetic mutation testing was completed. The clinical thinking process required a rich accumulation of pathophysiological knowledge. This article reports a case of PDHC deficiency masked by septic shock-induced lactic acidosis to raise awareness of the disease and avoid misdiagnosis and missed diagnosis., Competing Interests: Declaration of conflicting interestThe authors declare that there are no conflicts of interest.

Objective: To determine the diagnostic yield of the critical sample and fast-tests as dynamic function tests for the work-up of hypoglycemia in children., Methods: A retrospective record review of children (0-18 years) with a diagnosis of hypoglycemia (glucose ≤ 50 mg/dL) was performed. A comparison of results of critical sample (obtained during an episode of hypoglycemia) and fast-test (performed to induce hypoglycemia in fasting state) was done., Results: In 317 patients with hypoglycemia, data of 89 critical samples and 52 fast-tests were taken. Only 7 (7.8%) patients who underwent critical sample testing received an endocrine or metabolic diagnosis. No confirmatory diagnoses were made using the fast-tests. Idiopathic ketotic hypoglycemia was detected in 33/89 (37.1%) of critical samples and 21/52 (40.4%) of fast-tests. The completeness of workup including the hormonal and metabolic profile was <80% in both tests., Conclusion: The confirmatory yield of critical sample was better than fast-test. The processing of metabolic analytes was incomplete in a few, suggesting the need to rationalize the dynamic function testing.

Background: Hypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting., Materials and Methods: Fifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day., Results: Exercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6., Conclusion: Physical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia., Competing Interests: SE is currently employed by Novo Nordisk and holds stock in Novo Nordisk. UP-b has served on advisory boards for and/or received lecture fees from Novo Nordisk and Sanofi. FK has served on advisory panels at, been part of speaker’s bureaus for, served as a consultant to, and/or received research support from AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly, Gubra, MSD/Merck, Novo Nordisk, Sanofi, ShouTi, Zealand Pharma and Zucara. TV has served on scientific advisory panels at, been part of speaker’s bureaus for, served as a consultant to, and/or received research support from Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Gilead, GSK, Mundipharma, MSD/Merck, Novo Nordisk, Sanofi, and Sun Pharmaceuticals. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Maytham, Hagelqvist, Engberg, Forman, Pedersen-Bjergaard, Knop, Vilsbøll and Andersen.)

Background: Older adults with diabetes are at high risk of severe hypoglycemia (SH). Many machine-learning (ML) models predict short-term hypoglycemia are not specific for older adults and show poor precision-recall. We aimed to develop a multidimensional, electronic health record (EHR)-based ML model to predict one-year risk of SH requiring hospitalization in older adults with diabetes., Methods and Findings: We adopted a case-control design for a retrospective territory-wide cohort of 1,456,618 records from 364,863 unique older adults (age ≥65 years) with diabetes and at least 1 Hong Kong Hospital Authority attendance from 2013 to 2018. We used 258 predictors including demographics, admissions, diagnoses, medications, and routine laboratory tests in a one-year period to predict SH events requiring hospitalization in the following 12 months. The cohort was randomly split into training, testing, and internal validation sets in a 7:2:1 ratio. Six ML algorithms were evaluated including logistic-regression, random forest, gradient boost machine, deep neural network (DNN), XGBoost, and Rulefit. We tested our model in a temporal validation cohort in the Hong Kong Diabetes Register with predictors defined in 2018 and outcome events defined in 2019. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC) statistics, and positive predictive value (PPV). We identified 11,128 SH events requiring hospitalization during the observation periods. The XGBoost model yielded the best performance (AUROC = 0.978 [95% CI 0.972 to 0.984]; AUPRC = 0.670 [95% CI 0.652 to 0.688]; PPV = 0.721 [95% CI 0.703 to 0.739]). This was superior to an 11-variable conventional logistic-regression model comprised of age, sex, history of SH, hypertension, blood glucose, kidney function measurements, and use of oral glucose-lowering drugs (GLDs) (AUROC = 0.906; AUPRC = 0.085; PPV = 0.468). Top impactful predictors included non-use of lipid-regulating drugs, in-patient admission, urgent emergency triage, insulin use, and history of SH. External validation in the HKDR cohort yielded AUROC of 0.856 [95% CI 0.838 to 0.873]. Main limitations of this study included limited transportability of the model and lack of geographically independent validation., Conclusions: Our novel-ML model demonstrated good discrimination and high precision in predicting one-year risk of SH requiring hospitalization. This may be integrated into EHR decision support systems for preemptive intervention in older adults at highest risk., Competing Interests: JCNC has received research grants and/or honoraria for consultancy or giving lectures, from AstraZeneca, Bayer, Bristol-Myers Squibb, Boehringer Ingelheim, Daiichi-Sankyo, Eli-Lilly, GlaxoSmithKline, Merck Serono, Merck Sharp & Dohme, Novo-Nordisk, Pfizer and Sanofi. APSK has received honoraria for consultancy or giving lectures from Abbott, Astra Zeneca, Bayer, Boehringer Ingelheim, Dexcom, Eli-Lilly, Kyowa Kirin, Merck Serono, Merck Sharp & Dohme, Nestle, Novo-Nordisk, Pfizer and Sanofi. RCWM has received research grants and/or honoraria for consultancy or giving lectures, from AstraZeneca, Boehringer Ingelheim, Bayer, Kyowa Kirin, Merck, Novo Nordisk, Pfizer, Roche Diagnostics and Tricida Inc. The proceeds have been donated to the Chinese University of Hong Kong, American Diabetes Association and other charity organizations to support diabetes research and education. RCWM is an Academic Editor on PLOS Medicine’s editorial board. Other authors declared no conflict of interests with this work., (Copyright: © 2024 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

A patient without a diagnosis of diabetes mellitus presented to the hospital due to a fall and hypoglycaemia on admission. The patient was found to have recurrent nocturnal fasting hypoglycaemia. CT revealed a large lung mass consistent with a solitary pleural fibroma, a rare tumour associated with insulin-like growth factor 2 (IGF-2) production. This case is an important reminder that potential causes of hypoglycaemia should be considered in non-diabetic patients., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Importance: The circumstances under which neonatal hypoglycemia leads to brain damage remain unclear due to a lack of long-term data on the neurodevelopment of affected children. As a result, diagnostic strategies and treatment recommendations are inconsistent., Objective: To evaluate whether the occurrence of severe transitional neonatal hypoglycemia (defined as having at least 1 blood glucose measurement of 30 mg/dL or below) is associated with adverse neurodevelopment in midchildhood., Design, Setting, and Participants: This cohort study using neurodevelopmental testing of a retrospectively recruited cohort was conducted at a single-center tertiary hospital in Germany between March 2022 and February 2023. Children with neonatal blood glucose screening data were randomly selected from all births between 2010 and 2015. Frequency matching for sex, birth weight, gestational age, socioeconomic status, and primary risk factors for neonatal hypoglycemia was performed. Children with persistent hypoglycemia diseases or any risk factor for adverse neurodevelopment except hypoglycemia were excluded. Data were analyzed between February 2023 and March 2023., Exposure: At least 1 neonatal hypoglycemia measurement with blood glucose measuring 30 mg/dL or below vs all measured blood glucose levels above 30 mg/dL during postnatal blood glucose screening starting on the first day of life., Main Outcomes and Measures: Cognitive function measured by full-scale IQ test. Secondary outcomes included standardized scales of motor, visual, and executive functions, and child behavior, each measured at ages 7 to 11 years., Results: A total of 140 children (mean [SD] age 9.1 [1.3] years; 77 male [55.0%]) participated in the study. Children with severe neonatal hypoglycemia had a 4.8 points lower mean full-scale IQ than controls (107.0 [95% CI, 104.0-109.9] vs 111.8 [95% CI, 108.8-114.8]). They showed a 4.9-fold (95% CI, 1.5-15.5) increased odds of abnormal fine motor function and a 5.3-fold (95% CI, 2.1-13.3) increased odds of abnormal visual-motor integration. Significantly higher T scores for attention problems (58.2 [95% CI, 56.1-60.2] vs 54.6 [95% CI, 52.6-56.6]) and attention-deficit/hyperactivity disorder symptoms (58.2 [95% CI, 56.2-60.2] vs 54.7 [95% CI, 52.8-56.7]) were reported by parents., Conclusions and Relevance: Neonatal hypoglycemia with blood glucose levels of 30 mg/dL or below was associated with an increased risk for suboptimal neurodevelopmental outcomes in midchildhood. These findings imply that treatment strategies should aim to prevent episodes of hypoglycemia at these severely low levels.

Introduction: Severe hypoglycemia (SH) in older adults (OAs) with type 1 diabetes is associated with profound morbidity and mortality, yet its etiology can be complex and multifactorial. Enhanced tools to identify OAs who are at high risk for SH are needed. This study used machine learning to identify characteristics that distinguish those with and without recent SH, selecting from a range of demographic and clinical, behavioral and lifestyle, and neurocognitive characteristics, along with continuous glucose monitoring (CGM) measures., Research Design and Methods: Data from a case-control study involving OAs recruited from the T1D Exchange Clinical Network were analyzed. The random forest machine learning algorithm was used to elucidate the characteristics associated with case versus control status and their relative importance. Models with successively rich characteristic sets were examined to systematically incorporate each domain of possible risk characteristics., Results: Data from 191 OAs with type 1 diabetes (47.1% female, 92.1% non-Hispanic white) were analyzed. Across models, hypoglycemia unawareness was the top characteristic associated with SH history. For the model with the richest input data, the most important characteristics, in descending order, were hypoglycemia unawareness, hypoglycemia fear, coefficient of variation from CGM, % time blood glucose below 70 mg/dL, and trail making test B score., Conclusions: Machine learning may augment risk stratification for OAs by identifying key characteristics associated with SH. Prospective studies are needed to identify the predictive performance of these risk characteristics., Competing Interests: Competing interests: RW participated in multicenter clinical trials through her institution, sponsored by Insulet, Medtronic, Eli Lilly, Novo Nordisk, and Boehringer Ingelheim, and has used donated DexCom CGMs and Tandem insulin pumps in projects sponsored by the NIH and the Leona M and Harry B Helmsley Charitable Trust., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Hypoglycaemia has been shown to induce a systemic pro-inflammatory response, which may be driven, in part, by the adrenaline response. Prior exposure to hypoglycaemia attenuates counterregulatory hormone responses to subsequent hypoglycaemia, but whether this effect can be extrapolated to the pro-inflammatory response is unclear. Therefore, we investigated the effect of antecedent hypoglycaemia on inflammatory responses to subsequent hypoglycaemia in humans., Methods: Healthy participants (n = 32) were recruited and randomised to two 2-h episodes of either hypoglycaemia or normoglycaemia on day 1, followed by a hyperinsulinaemic hypoglycaemic (2.8 ± 0.1 mmol/L) glucose clamp on day 2. During normoglycaemia and hypoglycaemia, and after 24 h, 72 h and 1 week, blood was drawn to determine circulating immune cell composition, phenotype and function, and 93 circulating inflammatory proteins including hs-CRP., Results: In the group undergoing antecedent hypoglycaemia, the adrenaline response to next-day hypoglycaemia was lower compared to the control group (1.45 ± 1.24 vs 2.68 ± 1.41 nmol/l). In both groups, day 2 hypoglycaemia increased absolute numbers of circulating immune cells, of which lymphocytes and monocytes remained elevated for the whole week. Also, the proportion of pro-inflammatory CD16 + -monocytes increased during hypoglycaemia. After ex vivo stimulation, monocytes released more TNF-α and IL-1β, and less IL-10 in response to hypoglycaemia, whereas levels of 19 circulating inflammatory proteins, including hs-CRP, increased for up to 1 week after the hypoglycaemic event. Most of the inflammatory responses were similar in the two groups, except the persistent pro-inflammatory protein changes were partly blunted in the group exposed to antecedent hypoglycaemia. We did not find a correlation between the adrenaline response and the inflammatory responses during hypoglycaemia., Conclusion: Hypoglycaemia induces an acute and persistent pro-inflammatory response at multiple levels that occurs largely, but not completely, independent of prior exposure to hypoglycaemia. Clinical Trial information Clinicaltrials.gov no. NCT03976271 (registered 5 June 2019)., (© 2024. The Author(s).)

Hypoglycemia is a common clinical finding, especially in the inpatient setting. However, laboratory testing may show falsely low blood glucose levels. It is crucial for clinicians to recognize the existence of pseudohypo- glycemia and know when and how to test for it.

Introduction: Impaired awareness of hypoglycemia (IAH) refers to a diminished capacity to detect hypoglycemia. IAH can result in severe and even life-threatening outcomes for individuals with diabetes, especially those in advanced stages of the disease. This study aimed to assess the prevalence of IAH in people with diabetes on hemodialysis., Research Design and Methods: We conducted a single-center audit to assess the prevalence of IAH using the Clarke questionnaire. Simultaneously, we measured fear of hypoglycemia with an adapted version of the Hypoglycemia Survey and recorded the incidence of severe hypoglycemia. Data were presented as mean±SD or counts/percentages. Logistic regression was then employed to analyze the association between IAH and various sociodemographic and clinical factors., Results: We included 56 participants with diabetes on hemodialysis, with a mean age of 67.2 years (±12.9), of whom 51.8% were male. The ethnic distribution was 23.2% white, 23.2% black, 19.6% Asian, and 33.9% unspecified. The mean HbA1c was 52 mmol/mol (±18.6). The majority (91.1%) had a diagnosis of type 2 diabetes, and 55.4% of those were treated with insulin. The use of diabetes technology was low, with 2.8% of the participants using a continuous glucose monitor. IAH prevalence was 23.2%, and among the 57 participants, 23.6% had a history of severe hypoglycemia, and 60.6% reported fear of hypoglycemia. There were no significant differences in sociodemographic and clinical characteristics between those with IAH and normal hypoglycemia awareness., Conclusions: We observed that 23.2% of individuals with diabetes undergoing hemodialysis had IAH. IAH was more prevalent in people who reported a fear of hypoglycemia and had a history of severe hypoglycemia episode. The study highlights the unmet needs and disparities in access to diabetes technology within this population., Competing Interests: Competing interests: HHH-A received speaker honoraria from AstraZeneca and Bayer. MR received speaker honoraria from AstraZeneca. DCW has an ongoing consultancy contract with AstraZeneca. He has received payments for consultancy working and/or speaking activities from Amgen, Astellas, Bayer, Boehringer Ingelheim, Eledon, GSK, Galderma, Gilead, Janssen, Mundipharma, Menarini, MSD, Novo Nordisk, Pharmacosmos, Tricida and Vifor., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The use of continuous glucose monitors (CGMs) in individuals living without diabetes is increasing. The purpose of this study was to profile various CGM metrics around nutritional intake, sleep and exercise in a large cohort of physically active men and women living without any known metabolic disease diagnosis to better understand the normative glycemic response to these common stimuli. A total of 12,504 physically active adults (age 40 ± 11 years, BMI 23.8 ± 3.6 kg/m 2 ; 23% self-identified as women) wore a real-time CGM (Abbott Libre Sense Sport Glucose Biosensor, Abbott, USA) and used a smartphone application (Supersapiens Inc., Atlanta, GA, USA) to log meals, sleep and exercise activities. A total of >1 M exercise events and 274,344 meal events were analyzed. A majority of participants (85%) presented an overall (24 h) average glucose profile between 90 and 110 mg/dL, with the highest glucose levels associated with meals and exercise and the lowest glucose levels associated with sleep. Men had higher mean 24 h glucose levels than women (24 h-men: 100 ± 11 mg/dL, women: 96 ± 10 mg/dL). During exercise, the % time above >140 mg/dL was 10.3 ± 16.7%, while the % time <70 mg/dL was 11.9 ± 11.6%, with the remaining % within the so-called glycemic tight target range (70-140 mg/dL). Average glycemia was also lower for females during exercise and sleep events ( p < 0.001). Overall, we see small differences in glucose trends during activity and sleep in females as compared to males and higher levels of both TAR and TBR when these active individuals are undertaking or competing in endurance exercise training and/or competitive events.

Background: Hypoglycemia is a frequent and acute complication in type 1 diabetes mellitus (T1DM) and is associated with a higher risk of car mishaps. Currently, hypoglycemia can be detected and signaled through flash glucose monitoring or continuous glucose monitoring devices, which require manual and visual interaction, thereby removing the focus of attention from the driving task. Hypoglycemia causes a decrease in attention, thereby challenging the safety of using such devices behind the wheel. Here, we present an investigation of a hands-free technology-a voice warning that can potentially be delivered via an in-vehicle voice assistant., Objective: This study aims to investigate the feasibility of an in-vehicle voice warning for hypoglycemia, evaluating both its effectiveness and user perception., Methods: We designed a voice warning and evaluated it in 3 studies. In all studies, participants received a voice warning while driving. Study 0 (n=10) assessed the feasibility of using a voice warning with healthy participants driving in a simulator. Study 1 (n=18) assessed the voice warning in participants with T1DM. Study 2 (n=20) assessed the voice warning in participants with T1DM undergoing hypoglycemia while driving in a real car. We measured participants' self-reported perception of the voice warning (with a user experience scale in study 0 and with acceptance, alliance, and trust scales in studies 1 and 2) and compliance behavior (whether they stopped the car and reaction time). In addition, we assessed technology affinity and collected the participants' verbal feedback., Results: Technology affinity was similar across studies and approximately 70% of the maximal value. Perception measure of the voice warning was approximately 62% to 78% in the simulated driving and 34% to 56% in real-world driving. Perception correlated with technology affinity on specific constructs (eg, Affinity for Technology Interaction score and intention to use, optimism and performance expectancy, behavioral intention, Session Alliance Inventory score, innovativeness and hedonic motivation, and negative correlations between discomfort and behavioral intention and discomfort and competence trust; all P<.05). Compliance was 100% in all studies, whereas reaction time was higher in study 1 (mean 23, SD 5.2 seconds) than in study 0 (mean 12.6, SD 5.7 seconds) and study 2 (mean 14.6, SD 4.3 seconds). Finally, verbal feedback showed that the participants preferred the voice warning to be less verbose and interactive., Conclusions: This is the first study to investigate the feasibility of an in-vehicle voice warning for hypoglycemia. Drivers find such an implementation useful and effective in a simulated environment, but improvements are needed in the real-world driving context. This study is a kickoff for the use of in-vehicle voice assistants for digital health interventions., (©Caterina Bérubé, Vera Franziska Lehmann, Martin Maritsch, Mathias Kraus, Stefan Feuerriegel, Felix Wortmann, Thomas Züger, Christoph Stettler, Elgar Fleisch, A Baki Kocaballi, Tobias Kowatsch. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 09.01.2024.)

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC., (© 2024 by the American Diabetes Association.)

People with Alzheimer's disease or related dementias and diabetes mellitus (ADRD-DM) are at high risk for hypoglycemic events. Their cognitive impairment and psychosocial situation often hinder detection of hypoglycemia. Extending use and benefits of continuous glucose monitoring (CGM) to people with ADRD-DM could improve hypoglycemia detection, inform care, and reduce adverse events. However, cognitive impairment associated with ADRD presents unique challenges for CGM use. This commentary proposes applying the human-centered design process to CGM, investigating design solutions or interventions needed to integrate CGM into the health care of patients with ADRD-DM. With this process, we can identify and inform CGM designs for people with ADRD-DM, broadening CGM access, increasing detection and treatment of the silent threat posed by hypoglycemia., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Michael Weiner reports stock ownership in AbbVie Inc, Amgen Inc, Boston Scientific Corporation, Bristol-Myers Squibb Company, IBM, Integer Holdings Corp, Johnson & Johnson, Mallinckrodt PLC, Mead Johnson & Company, LLC, Medtronic, Mylan N.V., Novo Nordisk A/S, Perspecta Inc, Pfizer Inc, Roche Pharmaceuticals, Senseonics, Stryker Corp, Teva Pharmaceutical Industries Ltd, and Walgreens Boots Alliance, Inc. Rich Holden provides paid scientific advising to Cook Medical. April Savoy reports stock ownership in Pfizer Inc. and GSK (GlaxoSmithKline) Plc. David Klonoff is a consultant to Eoflow, Fractyl Health, Lifecare, Integrity, Rockley Photonics, and Thirdwayv. All other authors report no conflicts of interest.

Background: The occurrences of acute complications arising from hypoglycemia and hyperglycemia peak as young adults with type 1 diabetes (T1D) take control of their own care. Continuous glucose monitoring (CGM) devices provide real-time glucose readings enabling users to manage their control proactively. Machine learning algorithms can use CGM data to make ahead-of-time risk predictions and provide insight into an individual's longer term control., Methods: We introduce explainable machine learning to make predictions of hypoglycemia (<70 mg/dL) and hyperglycemia (>270 mg/dL) up to 60 minutes ahead of time. We train our models using CGM data from 153 people living with T1D in the CITY (CGM Intervention in Teens and Young Adults With Type 1 Diabetes)survey totaling more than 28 000 days of usage, which we summarize into (short-term, medium-term, and long-term) glucose control features along with demographic information. We use machine learning explanations (SHAP [SHapley Additive exPlanations]) to identify which features have been most important in predicting risk per user., Results: Machine learning models (XGBoost) show excellent performance at predicting hypoglycemia (area under the receiver operating curve [AUROC]: 0.998, average precision: 0.953) and hyperglycemia (AUROC: 0.989, average precision: 0.931) in comparison with a baseline heuristic and logistic regression model., Conclusions: Maximizing model performance for glucose risk prediction and management is crucial to reduce the burden of alarm fatigue on CGM users. Machine learning enables more precise and timely predictions in comparison with baseline models. SHAP helps identify what about a CGM user's glucose control has led to predictions of risk which can be used to reduce their long-term risk of complications., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: To explore the value of umbilical artery cord blood glucose (UACBG) in predicting hypoglycemia in gestational diabetes mellitus (GDM) and other at-risk newborns, and to provide a cut-off UACBG value for predicting hypoglycemia occurrence., Methods: In this prospective study, we enrolled at-risk infants delivered vaginally, including neonates born to mothers with GDM, premature, macrosomic, and low birth weight. We separated the infants into GDM group and other at-risk group. All subjects underwent UACBG measurement during delivery. Neonatal peripheral blood glucose measurement was performed at 0.5 and 2 h after birth. The predictive performance of UACBG for neonatal hypoglycemia was assessed using receiver operating characteristic curve (ROC), area under curve (AUC), sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV)., Results: 916 newborns were included, with 538 in GDM group and 378 in other at-risk group. 85 neonates were diagnosed hypoglycemia within 2 h after birth, including 36 belonging to GDM group and 49 to other at-risk group. For hypoglycemia prediction within 2 h, the best cut-off of UACBG was 4.150 mmol/L, yielding an AUC of 0.688 (95% CI 0.625-0.751) and a NPV of 0.933. In detail, the AUC was 0.680 in GDM group (95% CI 0.589-0.771), with the optimal cut-off of 4.150 mmol/L and a NPV of 0.950. In other at-risk group, the AUC was 0.678(95% CI 0.586-0.771), the best threshold was 3.950 mmol/L and the NPV was 0.908. No significant differences were observed between GDM group and other at-risk group in AUC at 0.5 h, 2 h and within 2 h., Conclusions: UACBG has a high NPV for predicting neonatal hypoglycemia within 2 h after birth. It was implied that individuals with cord blood glucose levels above the threshold were at lower risk for hypoglycemia. UACBG monitoring provides evidence for subsequent classified management of hypoglycemia., (© 2023. The Author(s).)

Rationale: Hypoglycemia is common in patients with glucose regulation disorders and related diabetic treatments but is rare in nondiabetic patients. Severe hypoglycemia can cause harm to patients' cognition, consciousness, central nervous system, cardiovascular and cerebrovascular system, and even death. However, the most fundamental way to control hypoglycemia is to identify the cause and deal with the primary disease. This article introduces 3 cases of nondiabetic hypoglycemia with different causes, aiming to improve our understanding of nondiabetic hypoglycemia and improve the ability of early diagnosis and differential diagnosis., Patient Concerns: Case 1 is a 19-year-old female with a history of recurrent coma, and magnetic resonance imaging and endoscopic ultrasound of the pancreas suggest insulinoma. Case 2 is a 74-year-old male with a history of viral hepatitis, and computerized tomography shows multiple nodules in the liver, which is diagnosed as liver cancer. Case 3 is a 39-year-old female with a history of taking methimazole, who tested positive for insulin antibodies, and was diagnosed with insulin autoimmune syndrome., Diagnosis: All 3 patients were diagnosed with nondiabetic hypoglycemia, but the causes varied, and included insulinoma, non-islet cell tumor-induced hypoglycemia, and insulin autoimmune syndrome., Interventions: Case 1 underwent pancreatic tail resection; case 2 refused anti-tumor treatment and received glucose injections for palliative treatment only; and case 3 stopped taking methimazole., Outcomes: After surgery, the blood sugar in case 1 returned to normal, and the blood sugar in case 2 was maintained at about 6.0 mmol/L. The symptoms of hypoglycemia gradually improved in case 3 after stopping the medication., Lessons: Non-diabetic hypoglycemia requires further examination to clarify the cause, and the correct differential diagnosis can provide timely and effective treatment, improving the patient's prognosis., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.)

Adrenal insufficiency encompasses a group of congenital and acquired disorders that lead to inadequate steroid production by the adrenal glands, mainly glucocorticoids, mineralocorticoids and androgens. These may be associated with other hormone deficiencies. Adrenal insufficiency may be primary, affecting the adrenal gland's ability to produce cortisol directly; secondary, affecting the pituitary gland's ability to produce adrenocorticotrophic hormone (ACTH); or tertiary, affecting corticotrophin-releasing hormone (CRH) production at the level of the hypothalamus. Congenital causes of adrenal insufficiency include the subtypes of Congenital Adrenal Hyperplasia, Adrenal Hypoplasia, genetic causes of Isolated ACTH deficiency or Combined Pituitary Hormone Deficiencies, usually caused by mutations in essential transcription factors. The most commonly inherited primary cause of adrenal insufficiency is Congenital Adrenal Hyperplasia due to 21-hydroxylase deficiency; with the classical form affecting 1 in 10,000 to 15,000 cases per year. Acquired causes of adrenal insufficiency can be subtyped into autoimmune (Addison's Disease), traumatic (including haemorrhage or infarction), infective (e.g. Tuberculosis), infiltrative (e.g. neuroblastoma) and iatrogenic. Iatrogenic acquired causes include the use of prolonged exogenous steroids and post-surgical causes, such as the excision of a hypothalamic-pituitary tumour or adrenalectomy. Clinical features of adrenal insufficiency vary with age and with aetiology. They are often non-specific and may sometimes become apparent only in times of illness. Features range from those related to hypoglycaemia such as drowsiness, collapse, jitteriness, hypothermia and seizures. Features may also include signs of hypotension such as significant electrolyte imbalances and shock. Recognition of hypoglycaemia as a symptom of adrenal insufficiency is important to prevent treatable causes of sudden deaths. Cortisol has a key role in glucose homeostasis, particularly in the counter-regulatory mechanisms to prevent hypoglycaemia in times of biological stress. Affected neonates particularly appear susceptible to the compromise of these counter-regulatory mechanisms but it is recognised that affected older children and adults remain at risk of hypoglycaemia. In this review, we summarise the pathogenesis of hypoglycaemia in the context of adrenal insufficiency. We further explore the clinical features of hypoglycaemia based on different age groups and the burden of the disease, focusing on hypoglycaemic-related events in the various aetiologies of adrenal insufficiency. Finally, we sum up strategies from published literature for improved recognition and early prevention of hypoglycaemia in adrenal insufficiency, such as the use of continuous glucose monitoring or modifying glucocorticoid replacement., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lee, Baranowski, Sakremath, Saraff and Mohamed.)

Competing Interests: Competing interests: Stewart B. Harris reports research support from AstraZeneca, Eli Lilly, Novo Nordisk and Sanofi. He has also received honoraria or consulting fees from and has participated on advisory boards for Abbott, AstraZeneca, Bayer, Dexcom, Eli Lilly, HLS Therapeutics, Janssen, Novo Nordisk and Sanofi. He has participated in clinical trials for Abbott, Applied Therapeutics, Boehringer Ingelheim, Novartis, Novo Nordisk and Sanofi. Basel Bari has been a member of advisory boards for Novo Nordisk, Sanofi, Boehringer Ingelheim, Astra-Zeneca and Eli Lilly. He has also received grants and honoraria from Master Clinician Alliance, CCRN, Dexcom, Merck, Novo Nordisk, Sanofi, Boehringer Ingelheim, AstraZeneca, Eli Lilly, CPD Network and BD. Jeremy Gilbert reports consulting fees and honoraria from Abbott, Astra Zeneca, Amgen, Boehringer Ingelheim, Dexcom, Eli Lilly, Janssen, Sanofi, Novo Nordisk and HLS Therapeutics, and honoraria from Roche and Master Clinician Alliance. No other competing interests were declared.

Background/aim: Pancreatic neuroendocrine tumors (PNETs) are pancreatic neoplasms with neuroendocrine features, divided into functioning and non-functioning. The non-functioning PNETs are the largest group, and their morbidity is the result of their potential to invade surrounding tissues and metastasize. The functioning PNETs produce hormonal symptoms due to over-secretion of specific hormones. They constitute 1% to 2% of all pancreatic tumors. The use of novel imaging methods has rendered their detection more frequent. Insulinoma, the most common functioning PNET, comprises 35-40% of all functioning PNETs. Its clinical presentation is due to hyperinsulinemia and the subsequent hypoglycemia. Glucagonoma accounts for 5% of all PNETs and is the fourth most frequent functioning PNET, following insulinoma, gastrinoma, and vipoma. Its symptoms are due to the massive secretion of glucagon and ensuing hyperglycemia. The co-existence of two PNETs is a very rare entity. This report aimed to describe cases of concomitant insulinomas and glucagonomas., Materials and Methods: A review of the literature was performed using the PubMed database and Cochrane library aiming to identify reported cases of concomitant pancreatic insulinoma and glucagonoma. Specifically, the research was conducted using the keywords, separately and in various combination, including insulinoma, glucagonoma, cystic, pancreatic neuroendocrine tumors and hypoglycemia. Only publications in English were included in the present study., Results: A total of 8 cases of concomitant pancreatic insulinoma and glucagonoma were identified, corresponding to the period 1992-2021., Conclusion: Concomitant insulinoma and glucagonoma are rare and challenging. A multidisciplinary approach is necessary for diagnosis, prognosis, and therapy., (Copyright © 2023, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Timely diagnosis of persistent neonatal hypoglycemia is critical to prevent neurological sequelae, but diagnosis is complicated by the heterogenicity of the causes. We discuss two cases at separate institutions in which clinical management was fundamentally altered by the results of molecular genetic testing. In both patients, critical samples demonstrated hypoketotic hypoglycemia and a partial glycemic response to glucagon stimulation, thereby suggesting hyperinsulinism (HI). However, due to rapid genetic testing, both patients were found to have deoxyguanosine kinase (DGUOK)-related mitochondrial DNA depletion syndrome, an unexpected diagnosis. Patients with this disease typically present with either hepatocerebral disease in the neonatal period or isolated hepatic failure in infancy. The characteristic features involved in the hepatocerebral form of the disease include lactic acidosis, hypoglycemia, cholestasis, progressive liver failure, and increasing neurologic dysfunction. Those with isolated liver involvement experience hepatomegaly, cholestasis, and liver failure. Although liver transplantation is considered, research has demonstrated that for patients with DGUOK-related mitochondrial DNA depletion syndrome and neurologic symptoms, early demise occurs. Our report advocates for the prompt initiation of genetic testing in patients presenting with persistent neonatal hypoglycemia and for the incorporation of mitochondrial DNA depletion syndromes in the differential diagnosis of HI., Competing Interests: NM is currently on the advisory board of BioMarin and Pfizer; there is no conflict of interest in relation to this current paper or topic. KC is on the advisor board of Travere Therapeutics and PI for the HERO trial by HemoShear Therapeutics and her institution is reimbursed for her time; there is no conflict of interest in relation to this current paper or topic. BV is a consultant for Mirum Pharmaceuticals; there is no conflict of interest in relation to this current paper or topic. DL has received consulting fees from Eiger Biopharmaceuticals, Crinetics Pharmaceuticals, Hanmi Pharmaceuticals, and Zealand Pharma. She has also received research funding/contracts from Zealand Pharma, Hanmi Pharmaceuticals, Twist Pharma, Crinetics Pharmaceuticals, Rezolute, and Ultragenyx. There is no conflict of interest in relation to this current paper or topic. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Guzman, Yazdani, Harmon, Chapman, Vitola, Pyle, McKnight, Sigal, Lord, De Leon, Merchant and Ganetzky.)