Annals of Pediatric Endocrinology & Metabolism最新文献

Purpose: Continuous glucose monitoring (CGM) is recommended by clinical guidelines for pediatrics and adults with type 1 diabetes (T1D) to improve clinical outcomes. In Thailand, CGM was incorporated into the Universal Healthcare Coverage (UHC) program just over a year ago. This study aimed to evaluate preliminary clinical outcomes and device adoption at a single tertiary care center. To assess glycemic outcomes before and after CGM use following the UHC reimbursement program and compare results across four groups: Self-Monitoring Blood Glucose (SMBG), CGM, Open Loop Insulin Pump, and Hybrid Closed-Loop (HCL) System. CGM adherence and parameters were also analyzed.

Methods: This retrospective-prospective study collected and analyzed demographic data, HbA1c levels, and CGM parameters.

Results: A total of 142 T1D patients (median age: 17.3 years, range 3.5-69.2) were included. Baseline HbA1c was 8.1 ± 1.5%, with no significant differences between groups (P=0.223). The HCL group showed the largest HbA1c reduction at 12 months (-0.99%, P=0.001), particularly in patients <18 years (-1.21%, P=0.014). CGM users showed improvements in HbA1c (-0.29%) and increase in the proportion achieving TIR ≥ 70% at 12 months (69.2% vs. 47.1%, P = 0.08), though not statistically significant. Preliminary CGM uptake was 12% (17/142). HCL users exhibited higher TIR and better sensor adherence (P<0.05), while other groups showed no significant changes.

Conclusion: The Hybrid Closed-Loop system significantly improved glycemic outcomes, particularly in younger patients. However, CGM adoption remains low, highlighting the need for expanded access, enhanced reimbursement policies, and improved adherence strategies.

Purpose: Given the limitations of glycated hemoglobin (HbA1c), continuous glucose monitoring (CGM) metrics have been proposed as complementary indicators of glycemic control. This study evaluated the association between CGM metrics and HbA1c and developed HbA1c prediction models in Korean pediatric patients with type 1 diabetes (T1D).

Methods: We retrospectively analyzed CGM data from 85 patients aged 2-18 years using real-time CGM systems (G6 or G7, Dexcom, USA). CGM records over 12 weeks were segmented into five intervals (0-2, 0-4, 4-8, 8-12, and 0-12 weeks) prior to HbA1c measurement. Metrics included time-in-range (TIR), time-above-range (TAR), time-below-range (TBR), time-in-normoglycemia (TING), coefficient of variation (CV), and average glucose. HbA1c prediction models were constructed using ridge regression and validated in a separate test dataset.

Results: TIR consistently showed the strongest negative association with HbA1c, while TAR and average glucose showed the strongest positive associations. Among all intervals, 0-4 week CGM data demonstrated the strongest relationship with HbA1c (all P<0.05). Average glucose achieved the best explanatory power among all metrics (R²=0.83, AIC=84.34), and prediction models incorporating average glucose and TAR yielded the lowest mean squared error (MSE=0.15) and highest R² (0.83), with robust results in the test dataset.

Conclusion: Short-term CGM metrics, particularly average glucose during the 0-4 week preceding HbA1c testing, are strong predictors of HbA1c. These findings support the clinical utility of recent CGM data in optimizing the individualized glycemic management in pediatric patients with T1D.

Purpose: Psychiatric conditions are common in children and adolescents with diabetes and can hinder disease management. In this study, we examined whether mental health status at diagnosis predicts glycemic control at one year.

Methods: We included 57 patients aged 6–18 years diagnosed with type 1 diabetes or type 2 diabetes between 2019 and 2023 at Seoul National University Bundang Hospital. Mental health was assessed within three months of diagnosis using the Eating Disorder Inventory-2, Children's Depression Inventory, and Child Behavior Checklist (CBCL) for ages 6-18. Poor glycemic control was defined as glycated hemoglobin > 6.5% at one year. Associations between screening results and glycemic control were analyzed using Fisher's exact test and multivariate logistic regression.

Results: Of the 57 patients, 32 (56.1%) had type 1 diabetes, and the mean age at diagnosis was 12.9 ± 3.1 years; 31 (54.4%) were male. Poor glycemic control at one year was observed in 16 (28.1%) patients. While individual subscale positivity was not significantly associated with glycemic control, borderline somatic complaints on the CBCL were significantly associated with poor control (p = 0.022). In multivariate analysis, having two or more positive CBCL subscales showed a trend toward association with poor control (adjusted odds ratio = 21.47, p = 0.054).

Conclusion: Early psychological screening, especially for somatic symptoms or multiple psychological problems, may help identify pediatric patients with diabetes at risk for poor glycemic control. These findings underscore the importance of early detection and intervention in optimizing diabetes management.

Diabetic ketoacidosis (DKA) is present in about 30% of pediatric patients diagnosed with new-onset type 1 diabetes. Among such patients, cerebral oedema is relatively uncommon (<1%), representing about 0.1%-0.3% of deaths. However, 25% of these survivors of cerebral oedema suffer permanent neurologic deficits. Clinical presentation may be nonspecific, but the laboratory parameters of hyperglycaemia and ketosis are present in almost all cases, and treatment mainstay depends on intravenous fluids and insulin. The pathophysiology of cerebral oedema and related injury to the brain cells is not fully understood. Different modalities have been used to manage cerebral oedema related to DKA. Here we will review such targeted management options to allow immediate treatment regardless of cause. Such techniques could include fluid restriction, ABC, neuroprotective measures, and osmotherapy with mannitol and/or hypertonic saline.

Purpose: This study aims to estimate the incidence and examine the clinical and laboratory characteristics of newly diagnosed type 1 diabetes (T1D) in Vietnamese children at a tertiary referral pediatric hospital.

Methods: A retrospective cross-sectional analysis was conducted on 64 children newly diagnosed with T1D at Vietnam National Children's Hospital in 2023. Data on the children were analyzed, including demographics, family history, symptoms, anthropometric measurements, hemoglobin A1c levels, and pancreatic islet autoantibodies.

Results: The average age at diagnosis was 9.1±3.7 years, with a male predominance (53.1%). The incidence rate of T1D in these northern Vietnamese children was 0.77 per 100,000 children. Diabetic ketoacidosis (DKA) was present in 57.8% of children at diagnosis, and 75% tested positive for autoantibodies. The Red River Delta reported the highest proportion of children with T1D (43.5%), but the incidence rate was highest in Hanoi, the capital city (0.91 per 100,000 children).

Conclusion: This study underscores the considerable diagnostic delays in T1D in a tertiary pediatric center in Vietnam, with a high prevalence of DKA. The results highlight the need for an enhanced network of satellite hospitals to enable early diagnosis and treatment for patients.

The integration of large language models (LLMs) in academic research has transformed traditional research methodologies. This review investigates the current state, applications, and limitations of LLMs, particularly ChatGPT, in medical and scientific research. I performed a systematic review of recent literature and LLM development reports in artificial intelligence-assisted research tools, including commercial LLM services (GPT-4o, Claude 3, Gemini Pro) and specialized research platforms (Genspark, Scispace). I evaluated their performance, applications, and limitations across stages of the research process. Recent advancements in LLMs shows potential for improving research efficiency, particularly in literature review, data analysis, and manuscript preparation. Performance comparison revealed varying strengths: GPT-4o and o1 outperformed in the overall area, Claude 3 in writing and coding, and Gemini Pro in multimodal processing. Therefore, it is important to choose and use each model wisely according to its advantages. However, hallucination risks, inherent biases, plagiarism concerns, and privacy issues are concerns in LLMs. The emergence of Retrieval-Augmented Generation models and specialized research tools has improved accuracy and current information access. LLMs offer effective support for research productivity, but they should serve as complementary tools rather than primary research drivers. The successful application of these tools depends on a thorough understanding of their limitations, strict adherence to ethical guidelines, and preservation of researcher autonomy.

Purpose: Metabolic syndrome (MetS) is increasingly prevalent among adolescents, and thyroid-stimulating hormone (TSH) levels influence metabolic health. This study investigates whether TSH levels are associated with MetS and its components in euthyroid adolescents.

Methods: We used data from the Korean National Health and Nutrition Examination Survey between 2013 and 2015. The study included 940 euthyroid adolescents aged 10-18 years, who were divided into 2 groups: high-normal TSH group (top 25% of euthyroid TSH levels) and nonhigh TSH group (remaining 75%). We analyzed the association between high-normal TSH levels and MetS and its components.

Results: TSH quartiles were related to MetS (P for trend=0.006). The prevalence of MetS was 3.5% in the high-normal TSH group and 1.9% in the nonhigh group (P=0.1929). Abdominal obesity was more prevalent in the high-normal TSH than in the nonhigh TSH group (16.2% vs. 9.6%, P=0.0153). Other MetS components were more prevalent in the high-normal TSH group, but the difference was not significant. High-normal TSH was significantly associated with abdominal obesity (adjusted odds ratio, 1.975; 95% confidence interval, 1.104-3.531, P=0.0218).

Conclusion: In euthyroid adolescents, a significant trend was observed between TSH quartile and MetS. Specifically, high-normal TSH levels showed a significant association with abdominal obesity, a key component of MetS.

Purpose: Continuous glucose monitoring (CGM) technology offers real-time glucose feedback and has shown potential to improve glycemic control. This retrospective study evaluated the effect of CGM on glycemic outcomes in Korean children and adolescents with type 1 diabetes mellitus (T1DM) in a real-world setting.

Methods: We included 66 participants divided into a CGM group (n=22) and a self-monitoring blood glucose (SMBG) group (n=44). We compared changes in hemoglobin A1c (HbA1c) of the 2 groups over 1 year and observed changes in CGM activation time, mean glucose, glucose management indicator (GMI), coefficient of variation (CV), time in range (TIR), and hypoglycemia.

Results: The CGM group had a mean age of 16.63 years and time from diagnosis to the initiation of study of 4.19 years, while those of the SMBG group were 17.85 years and 5.19 years, respectively. In the CGM group, mean HbA1c decreased from 8.68% at baseline to 7.92% at 12 months (P=0.011), whereas HbA1c increased from 8.46% to 8.93% in the SMBG group (P<0.001). The changes in HbA1c at 1 year between the CGM and SMBG groups were significantly different (-0.76%±1.39% vs. 0.47%±1.38%, P=0.001). CGM activation time decreased slightly (89.09% to 79.24%, P=0.093), and there were no significant changes in TIR, mean glucose, GMI, CV, or hypoglycemia over time.

Conclusion: CGM use in Korean children and adolescents with T1DM significantly improves HbA1c levels over 12 months compared to SMBG. The implementation of CGM may provide valuable benefits in glycemic control and potentially reduce the risk of diabetes-related complications.