Search Results (726)

Background: The ketogenic diet has gained substantial popularity in recent years, and an increasing number of caregivers of children with type 1 diabetes are considering it as a nutritional strategy to improve glycemic control. Reported benefits include fewer postprandial glucose fluctuations, lower insulin requirements, and reduced insulin-associated weight gain. However, the use of this diet in children with type 1 diabetes remains highly debated, and scientific evidence regarding its safety and long-term effects in the pediatric population is limited. This narrative review aims to explore the motivations that lead parents to initiate a ketogenic diet in their children with type 1 diabetes and to summarize current knowledge on its potential metabolic and developmental consequences. Methods: A narrative review of the literature was conducted, including original research articles, case reports, and existing reviews addressing the use of ketogenic diets in children with type 1 diabetes. Clinical observations and published accounts of family experiences were also examined to contextualize emerging concerns and motivations. Results: Parents most commonly adopt a ketogenic diet for their children due to the desire for tighter glucose control, concerns about insulin-related weight gain, and the influence of information shared on social media. Some observational data suggest improvements in glycemic stability and reduced insulin requirements under ketogenic dietary regimens, while available evidence also highlights several potential risks, including dyslipidemia, increased susceptibility to hypoglycemia, slowed linear growth, and possible neurocognitive and psychosocial effects. Long-term safety data remain scarce, and current findings are insufficient to establish clear clinical recommendations. Conclusions: Interest in ketogenic diets among families of children with type 1 diabetes is growing, yet existing evidence suggests that the diet may pose significant metabolic and developmental risks in this population. Further well-designed studies are needed to evaluate its safety and efficacy. This review may assist clinicians in counseling families and underscores the need for evidence-based guidelines regarding restrictive dietary patterns in youth with type 1 diabetes. Full article

Background: Severe hypoglycemia is a major reason for emergency medical service (EMS) activation among patients with diabetes. However, real-world epidemiology, including onset location, timing, caller identity, and prehospital management, remains insufficiently described. This study aimed to characterize these cases and assess prehospital interventions and patient outcomes. Methods: We conducted a retrospective, descriptive study using EMS transport records and emergency department (ED) data from two core hospitals and their regional EMS systems in Japan between January 2018 and December 2023. Included patients were those transported by EMS for hypoglycemia with a corresponding ED diagnosis. Extracted data included patient characteristics, episode location and time, EMS caller identity, prehospital interventions, and clinical outcomes. Results: Among 237 episodes, the median age was 74 years and 59.9% were male. Most events occurred at home (78.1%) and during evening or nighttime hours (51.9%). Family members were the most frequent EMS callers (67.5%), yet 12.5% of patients received bystander medical intervention. EMS teams performed most prehospital interventions (68.8%), primarily intravenous glucose administration (65.2%). At EMS arrival, 16.0% were fully conscious and 21.1% were comatose. Hospitalization occurred in 44.3%. The hospitalization rate was 34.2% among patients who received prehospital intervention and 53.2% among those who did not. Conclusions: Most hypoglycemia episodes were discovered by family members, but bystander intervention was uncommon. Differences in hospitalization rates were observed according to the presence and timing of prehospital intervention. Full article

Background: Carbohydrate quality and culinary processing can meaningfully alter postprandial glycemia in people with type 1 diabetes (T1D). Cooling gelatinized starch promotes retrogradation and increases resistant starch (RS), potentially attenuating postprandial glucose excursions. Objectives: We investigated whether pasta cooled after cooking (24 h at 4 °C) and reheated before consumption improves postprandial glycemia in adults with T1D without increasing hypoglycemia risk under routine insulin pump bolus-calculator dosing. Methods: In this randomized, single-blind, crossover study, 32 adults with T1D treated with continuous subcutaneous insulin infusion (CSII) consumed two standardized pasta-based meals (50 g of available carbohydrate): freshly cooked pasta and cooled/reheated pasta. Participants administered rapid-acting insulin boluses calculated by their pump bolus calculator 10 min before the meal. Interstitial glucose was recorded for 180 min using flash glucose monitoring. Results: Compared with freshly cooked pasta, cooled/reheated pasta produced lower maximum glycemia (10.7 vs. 12.6 mmol/L, p = 0.0001), lower maximum glycemic rise (2.8 vs. 4.7 mmol/L, p < 0.0001), lower incremental area under the curve (iAUC; 211.9 vs. 524.8 mmol/L × 180 min, p < 0.0001), and a shorter time-to-peak (65 vs. 125 min, p = 0.014). Resistant starch content increased after cooling (12.88 ± 0.06 vs. 8.03 ± 0.08 g/100 g). The number of hypoglycemic episodes did not differ between conditions. Conclusions: Cooling and reheating pasta therefore increased RS and attenuated postprandial glycemia in adults with T1D without increasing early postprandial hypoglycemia in the studied setting. Full article

Background/Objectives: Diabetes threatens independent living among elderly individuals. However, the effects of glycemic management on the severity of functional impairment are unclear. This study aimed to elucidate the relationship between glycemic management and functional impairment severity in elderly individuals with type 2 diabetes (T2D). Methods: We used data from the Japanese National Health Insurance Database from 2017 to 2024. The database included 11,411 elderly individuals (≥65 years) with Long-Term Care Insurance evaluations. Functional status was classified into three categories based on independence—Group A (non-mild impairment), Group B (moderate impairment), and Group C (severe impairment). The factors associated with the severity of functional impairment in patients with T2D were elucidated. Results: The severity of functional impairment was significantly greater in patients with T2D than in those without T2D. In participants with T2D, low glycated hemoglobin (HbA1c) levels were associated with the severity of functional impairment (odds ratio [OR]: 0.78; p < 0.001). In contrast, the use of antidiabetic drugs that could induce severe hypoglycemia (high-risk drugs) was positively associated with the severity of functional impairment (Group A vs. B/C: OR: 1.42; p < 0.001; Group C vs. A/B: OR: 1.90; p < 0.001). The frequency of high-risk drug use increased as functional impairment increased. Conclusions: The use of high-risk drugs is associated with the severity of functional impairment in elderly individuals with T2D. Elucidating the factors associated with the severity of functional impairment in elderly individuals with T2D may contribute to maintaining their quality of life and reducing the economic burden on healthcare and long-term care systems. Full article

Proportional–integral–derivative (PID) controllers are always a preferred choice of control strategy in industrial and biomedical systems due to their simplicity, reliability, and easy implementation. However, the systematic tuning of PID parameters for nonlinear, constrained, and safety-critical systems remains challenging, particularly in the presence of disturbances and actuator limitations. This paper presents a unified surrogate-based optimization framework for tuning PID controllers for linear and nonlinear dynamical systems. The tuning problem is formulated as a constrained optimization task, where performance objectives and safety requirements are explicitly incorporated into the cost function. A surrogate-based optimization via clustering (SBOC) approachis employed to efficiently explore the PID parameter space while reducing the number of expensive closedloop simulations. The proposed framework is first applied to the first- and second-order linear time-invariant systems to check its feasibility and then to the nonlinear systems to demonstrate its robustness under nonlinearity and saturation. The approach is further applied to safety-critical systems considering the case of glucose regulation in type 1 diabetes under realistic meal disturbances and insulin delivery constraints. The simulation results show that the surrogate-optimized PID controller achieves stable regulation with improved tracking performance while strictly satisfying safety requirements, including control effort penalties to limit actuator wear and the avoidance of hypoglycemia and hyperglycemia in glucose regulation problems. Full article

Background/Objectives: Patients with hepatic glycogen storage disease (GSD) require frequent nighttime intake of uncooked corn starch (UCCS) to prevent fasting hypoglycemia, which imposes a substantial burden. Glycosade, an extended-release cornstarch, was developed to prolong overnight glucose availability. However, data regarding South Korean patients are limited. Therefore, we aimed to evaluate the efficacy and safety of Glycosade in South Korean patients with hepatic GSD. Methods: In this single-center prospective observational study, patients with hepatic GSD underwent laboratory evaluations before and 1 month after Glycosade administration. Continuous glucose monitoring (CGM) was performed during UCCS and Glycosade administration periods. The nocturnal mean glucose, coefficient of variation, time in range (70–180 mg/dL), and time below the range (<70 and <54 mg/dL) were compared between the periods using paired analyses. Results: No significant differences were observed in the nocturnal CGM metrics between the treatment periods. However, time-aligned CGM profiles revealed distinct temporal patterns, with a decline in glucose levels approximately 3–4 h after UCCS intake, whereas Glycosade showed a more sustained glucose profile over an extended period. Liver enzyme and lipid levels improved significantly after 1 month of Glycosade supplementation. Conclusions: In a cohort of South Korean patients with hepatic GSD, Glycosade maintained nocturnal glycemic stability comparable to that of conventional cornstarch without increasing the risk of hypoglycemia. Glycosade was also associated with improved biochemical parameters, supporting its role in nighttime dietary management. Full article

Objectives: Gestational diabetes is linked to increased inflammatory and metabolic stress during the neonatal period. Among the biomarkers elucidating the relationship between diabetes and inflammation, the interleukin-33 (IL-33)/ST2 signaling pathway is of particular interest. Research on the IL-33/sST2 axis in pregnancies complicated by diabetes indicates that these biomarkers are associated with maternal metabolic disorders and inflammation. Therefore, evaluating sST2 levels in infants of diabetic mothers is essential for identifying a biological marker of systemic inflammation resulting from intrauterine hyperglycemia and for clarifying the specific risks associated with this condition. The objective of this study was to examine sST2 levels in infants born to diabetic mothers and to assess their association with perinatal inflammation, metabolic stress, and clinical outcomes. Methods: This prospective observational study included term infants born at Pamukkale University Medical Faculty Hospital. The study group comprised term infants whose mothers had gestational diabetes, while the control group consisted of term infants born to healthy mothers without diabetes. sST2 levels were measured from serum samples obtained from cord blood at birth using the ELISA method. Factors influencing sST2 levels were analyzed using regression analyses. Results: sST2 levels were significantly higher in the diabetic group than in the control group (p < 0.001). The incidences of large for gestational age (LGA), small for gestational age (SGA), hypoglycemia, postnatal respiratory distress, and both the frequency and duration of neonatal intensive care unit admissions were also significantly elevated in the diabetic group. Multivariate analysis identified gestational diabetes as independent predictor. Conclusions: This study is among the first to demonstrate increased sST2 levels at birth in infants of diabetic mothers. The results indicate that intrauterine exposure to hyperglycemia due to gestational diabetes may be associated with heightened inflammation and metabolic stress in the neonatal period, and that sST2 may serve as a potential biomarker reflecting fetal exposure. Full article

Accurate perioperative glucose monitoring is essential in dogs undergoing general anesthesia, yet most validation studies of handheld glucometers have been performed under stable outpatient conditions. This prospective clinical validation study evaluated the analytical agreement, diagnostic performance, and ISO 15197 compliance of a human-calibrated (Accu-Chek) and a veterinary-specific (Centrivet GK) handheld glucometer compared with a laboratory spectrophotometric reference method in 34 anesthetized dogs (99 paired measurements per device). Linear mixed-effects modeling demonstrated significant method effects (p < 0.001), with the veterinary-specific device overestimating glucose concentrations relative to the reference method (β = 20.79 mg/dL; 95% CI: 8.08–33.50; p = 0.001), whereas the human-calibrated device did not differ significantly (β = 7.18 mg/dL; 95% CI: −5.53–19.89; p = 0.267). Bland–Altman analysis showed mean bias of 4.44 mg/dL (95% CI: 0.73–8.16) for the human-calibrated device and 22.72 mg/dL (95% CI: 18.22–27.21) for the veterinary-specific device. Passing–Bablok regression identified proportional bias only for the veterinary-specific device (slope 1.19; 95% CI: 1.01–1.34). ISO compliance was 69.7% and 39.4%, respectively. For hyperglycemia detection, AUC values were 0.9566 (95% CI: 0.8955–1.0000) and 0.9757 (95% CI: 0.9479–1.0000); for hypoglycemia, 0.8567 (95% CI: 0.7557–0.9578) and 0.7376 (95% CI: 0.6056–0.8697). In anesthetized dogs, the human-calibrated device demonstrated superior analytical robustness, whereas the veterinary-specific device showed greater bias and variability. Full article

Type 1 diabetes (T1D) constitutes a chronic metabolic disorder attributed to the autoimmune destruction of insulin-producing pancreatic β cells, which most frequently occurs in childhood. Long-term complications of T1D are expected to occur mainly in adult life, whereas cognitive dysfunction can also occur in children and adolescents with T1D. Most studies demonstrate mild cognitive impairment, especially in the domains of memory, attention and executive functions, all of which affect academic performance, which may also negatively influence adherence to appropriate glucose monitoring and insulin treatment in children and adolescents with T1D. As a result, mild cognitive dysfunction can be an obstacle to both optimal glycemic control during childhood and adolescence and academic achievements for young individuals with T1D. The major metabolic changes occurring around the onset of diabetes, such as severe hyperglycemia and diabetic ketoacidosis, may have a negative impact on brain plasticity during this vulnerable period of neurodevelopment, especially in children diagnosed at a younger age. The pathophysiological mechanisms involved are closely related to increased oxidative stress and the accumulation of advanced glycation end products in the brain, thus leading to neuron cell damage and apoptosis. On the other hand, hypoglycemic episodes and glucose fluctuations may also impair neuronal integrity. The aim of the current narrative review is therefore to present the existing literature data on the clinical aspects, risk factors and molecular mechanisms associated with cognitive dysfunction in children and adolescents with T1D. Full article

High-intensity interval training (HIIT) is presented as a safe, effective, and time-efficient strategy for individuals with type 1 diabetes, offering benefits for glycemic control, cardiovascular function, and physical fitness, with a lower risk of hypoglycemia than other exercise modalities. However, substantial variability exists among protocols, and there is no consensus on optimal dosage. This study reviewed 18 investigations to identify key parameters for safe and effective implementation. Results emphasize the importance of individualized programming, adherence to protocols, frequent glucose monitoring, and professional supervision. A preliminary framework is proposed to guide personalized HIIT programs for people with type 1 diabetes. Full article

Metabolic and bariatric surgery (MBS) has evolved into a highly effective neurohormonal intervention for severe obesity; however, it introduces unique long-term vulnerabilities, particularly regarding alcohol (AUD) and substance use disorders (SUD). This review synthesizes the epidemiological, pharmacokinetic, and neurobiological drivers of postoperative substance misuse. Procedures like Roux-en-Y gastric bypass (RYGB) radically alter ethanol metabolism, eliminating first-pass metabolism and accelerating gastric emptying, while simultaneously recalibrating reward pathways, creating a “reward gap” that facilitates addiction transfer. These physiological shifts exacerbate critical micronutrient deficiencies (thiamine, B12, iron), increase the risk of post-bariatric hypoglycemia, and correlate with higher rates of liver cirrhosis and suicide. Furthermore, substance use is a primary driver of suboptimal weight loss trajectories and weight regain. Mitigation requires a lifelong, multidisciplinary framework involving preoperative risk stratification, validated screening (e.g., AUDIT-C), and targeted nutritional supplementation to safeguard the long-term metabolic and psychological benefits of MBS. Full article

Background and Objectives: Diabetes mellitus represents one of the most prevalent chronic metabolic disorders worldwide, necessitating precise insulin dose management to prevent both acute and long-term complications. The optimization of insulin dosing remains a significant clinical challenge, as inappropriate dosing can lead to hypoglycemia or hyperglycemia, each carrying substantial morbidity risks. Machine learning approaches have emerged as promising tools for developing clinical decision support systems; however, their practical implementation requires both high predictive accuracy and model interpretability. This study aimed to develop and evaluate an explainable machine learning framework for predicting insulin dose adjustments in diabetic patients. We sought to compare multiple ensemble learning approaches and identify the optimal model configuration that balances predictive performance with clinical interpretability through comprehensive SHAP and LIME analyses. Materials and Methods: A comprehensive dataset comprising 10,000 patient records with 12 clinical and demographic features was utilized. We implemented and compared nine machine learning models, including gradient boosting variants (XGBoost, LightGBM, CatBoost, GradientBoosting), AdaBoost, and four ensemble strategies (Voting, Stacking, Blending, and Meta-Learning). Model interpretability was achieved through SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) analyses. Performance was evaluated using accuracy, weighted F1-score, area under the receiver operating characteristic curve (AUC-ROC), precision-recall AUC (PR-AUC), sensitivity, specificity, and cross-entropy loss. Results: The Meta-Learning Ensemble achieved superior performance across all evaluation metrics, attaining an accuracy of 81.35%, weighted F1-score of 0.8121, macro-averaged AUC-ROC of 0.9637, and PR-AUC of 0.9317. The model demonstrated exceptional sensitivity (86.61%) and specificity (91.79%), with particularly high performance in detecting dose reduction requirements (100% sensitivity for the ‘down’ class). SHAP analysis revealed insulin sensitivity, previous medications, sleep hours, weight, and body mass index as the most influential predictors across different insulin adjustment categories. The meta-model feature importance analysis indicated that LightGBM probability estimates contributed most significantly to the ensemble predictions. Conclusions: The proposed explainable Meta-Learning Ensemble framework demonstrates robust predictive capability for insulin dose adjustment recommendations while maintaining clinical interpretability. The integration of SHAP-based explanations facilitates clinician understanding of model predictions, supporting transparent and informed decision-making in diabetes management. This approach represents a significant advancement toward the clinical implementation of artificial intelligence in personalized insulin therapy. Full article

Background/Objectives: Insulin and glucagon are key hormones in metabolic regulation. There are limited comparative data on how common rodent anesthetic regimens influence hormone secretion, leading to misinterpretation of results. We aimed to compare the effects of several anesthetic regimens on insulin and glucagon secretion using the physiologically relevant isolated perfused rat pancreas model. Methods: Six commonly used rodent anesthetic regimens were assessed for their ability to induce surgical depth of anesthesia. Once achieved, the pancreas was vascularly isolated and perfused. After euthanasia, the pancreas was stimulated with glucose and glucagon-like peptide-1 (GLP-1). Insulin and glucagon were measured in the effluent using radioimmunoassay. Results: Anesthesia with Hypnorm^® (fentanyl/fluanisone)/midazolam produced the most physiological responses, meaning that insulin was secreted in response to hyperglycemia and GLP-1, and glucagon was secreted under hypoglycemia. Ketamine/dexmedetomidine anesthesia abolished insulin dynamic secretion and blunted glucagon secretion. Isoflurane/buprenorphine anesthesia partially suppressed insulin secretion, but it still followed a physiological pattern in response to glucose fluctuations. However, it abolished the dynamic glucagon responses to glucose. Three additional anesthetic regimens failed to produce surgical depth anesthesia and were therefore not further analyzed. Conclusions: Different anesthetic regimens altered pancreatic hormone secretion. Fentanyl/fluanisone/midazolam was associated with dynamic insulin and glucagon secretion, whereas ketamine/dexmedetomidine and isoflurane/buprenorphine altered the pattern and/or magnitude of hormone secretion. Overall, the choice of anesthesia is a critical variable in animal experimentation for metabolic studies and may confound the interpretation of results. Full article

Background: Understanding patient-specific patterns of medication intensification and de-intensification is essential for personalizing diabetes management and minimizing hypoglycemia risk in patients with type 2 diabetes. Objectives: To assess treatment changes in hypoglycemia-associated medications over five years and explore patient characteristics associated with these changes. Methods: We conducted a longitudinal cohort study using the IADB.nl database containing prescription data from Dutch community pharmacies. Individuals aged ≥35 years with at least two dispensations of glucose-lowering medications were identified. We estimated transition probabilities of changes in hypoglycemia-associated medications (sulfonylureas and/or insulin) using a Markov model for each year of follow-up. Associations with age, sex, and estimated hypoglycemia risk were explored with regression analysis. Results: Overall, 25,057 patients were included. Medication remained unchanged for the majority of the patients in the follow-up period. De-intensification increased from 4.7% (Year 1) to 6.5% (Year 5), while intensification decreased from 7.7% to 6.9% over the same period. Markov models showed that patients predominantly remained in a no change state over 5 years (transition probabilities: 0.92–0.94). High estimated hypoglycemia risk, age and being female were associated with intensification and/or de-intensification. Conclusions: While treatment regimens remained unchanged for most patients, de-intensification of hypoglycemia-associated medications increased modestly over five years. Factors like hypoglycemia risk, age and sex influenced changes. These findings support the need for personalized, risk-stratified approaches to diabetes medication management. Full article

Objective: Individuals with reactive hypoglycemia (RH) may be more likely to develop obesity and type 2 diabetes, but the ability to identify RH has been hampered by the lack of clear criteria. This study used calculus-based curve parameters from a mixed macronutrient liquid meal test (MMTT) to define RH in men and women with obesity. Methods: A total of 69 non-diabetic adults aged 35 ± 8.3 years with obesity (BMI 32.3 ± 4.2 kg/m²) underwent a 4 h MMTT to define RH, and an intravenous glucose tolerance test (IVGTT) to characterize RH (via insulin sensitivity, the acute insulin response to glucose (AIRg), insulin clearance, and the disposition index). Perceived hunger and fullness were assessed by visual analog scale. Results: RH was defined using curve properties of the MMTT. A total of 19 of the 69 participants had a reactive hypoglycemic response to the MMTT. Glucose AUC and nadir were lower, timing of glucose nadir was earlier, and insulin sensitivity was higher in RH compared to non-RH. Sex (female) and race (AA) were significant predictors of RH presence. Conclusions: Among individuals with obesity, RH is characterized by greater sensitivity to insulin and greater disposition index. We introduce a novel and reproducible method to define RH using curve-based criteria from a mixed meal test integrated with gold-standard IVGTT-derived outcomes. Full article