Editorial: Diabetic complications in children and adolescents: From low resources to advanced technical countries

Pediatric diabetes is a global health concern with significant inequality and unmet needs in healthcare infrastructure, technology access and funding (1). Diabetic ketoacidosis (DKA), neuropathy, and severe hypoglycemia are diabetes-related complications that carry a significant cost and burden on patients, families, and health care systems (diabetes-related complications)2–4). An increased incidence of type 1 diabetes (T1D) exacerbates this situation (5). Therefore, it is important to create solutions that address acute and long-term complications in a variety of situations. Those with access to advanced technology have a hard time incorporating cutting-edge technology into everyday care.6). People in the country where resource-restricted struggle with basic diabetes management. The topic of this study aims to bridge the gap between resource inequality and innovative solutions in the context of diabetes complications in children.

Research by Lazar et al. We propose anion gap normalization time (AGNT) as a more reliable marker of diabetic ketoacidosis (DKA) resolution in pediatric patients, challenging the traditional dependence on pH and bicarbonate levels. Their findings indicate that AG normalizes considerably faster than these markers. The median AGNT is 8 hours, with PICU ejection 15 hours ahead. Particularly, severe acidosis (pH) <7.1）および高血糖（> 500 mg/dL) was a strong predictor of delayed AGNT and strengthened its potential as a clinically relevant indicator. By adopting AGNT as a criterion for intensive care escalation, clinicians can reduce unnecessary PICU stays, minimize patient burden, and optimize hospital resource utilization. However, the retrospective nature of this study and the lack of ketone body measurements require further prospective validation before fully integrating AGNT into the DKA management protocol. This study raises important questions. Normalization of the anion gap should replace traditional DKA resolution markers, paving the way for a more efficient, patient-centered approach. (Lazar et al.).

Research by Tinti et al. We explore long-term neurological dysfunction in adolescents with type 1 diabetes and highlight early asymptomatic changes in nerve conduction. Using the Neuroconductivity Study (NCS) and a follow-up Neuropathy Screening Questionnaire, in this study, 11.8% of patients showed signs of somatic dysfunction, while 41% of significant 41% were hypoglycemic recognition reduced and suggested early self-economic disorders. Importantly, the abnormal NCS results correlated with a 97-fold increased risk of severe hypoglycemia after 6 years, highlighting the potential effects of diabetic autonomic neuropathy (DAN) on metabolic control . Despite the small sample size and lack of comprehensive metabolic data, this finding suggests that, particularly through electrophysiological assessments, which may identify risk factors before clinical symptoms appear, can be used to determine pediatric diabetes. It strengthens the need for early screening for neuropathy. This study proposes an increased evidence that early autonomic neuropathy in diabetes may lead to increased blood glucose variability and increased risk of hypoglycemia, and a more aggressive approach in pediatric neuropathy screening. It advocates improving diabetes management (Tinti et al.).

Research by Leutheuser et al. We investigate predictions of nocturne hypoglycemia in children with type 1 diabetes after daytime physical activity using machine learning models applied to continuous glucose monitoring (CGM) and physiological data. This study, conducted in a structured sports camp setting, evaluated logistic regression, random forests, and deep neural networks to predict hypoglycemia between 9 hours. The results showed that random forest models achieved the highest prediction accuracy using only glucose data (F2 score: 64.4%). Despite variation in model efficacy, this finding highlights the clinical importance of early hypoglycemia risk prediction, so caregivers can use aggressive measures such as adjusting insulin and carbohydrate intake. Do it to prevent overnight complications. However, small sample sizes (13 children, 66 nights) and dataset constraints highlight the need for large-scale validation studies. Although this study contributes to the growing field of AI-driven diabetes management, further improvements, including personalized modeling and real-world verification, are essential prior to clinical implementation (Leutheuser et al.).

Research by López-Lópezetal. We assess the real-world efficacy and safety of a minimised 780G advanced hybrid closed-loop (AHCL) system in children under the age of 7 with type 1 diabetes (T1D). In an analysis of data from 61 pediatric patients across three endocrine centres in the Canary Islands, this study showed a significant increase in the range (TIR) ​​(up to 13%-15%) and time beyond the range (TAR) It was found to decrease without decreasing. risk. These metabolism improvements can be maintained for up to 12 months, supporting the long-term benefits of AHCL therapy in young children. Importantly, this study assessed children who require low daily insulin doses (<8 units less than one day) and found that they did not adversely affect safety or efficacy, and the AHCL system suggests that it may be suitable for people with minimal insulin needs. Despite the retrospective design and small sample size, this finding strengthens the role of automated insulin delivery in achieving optimal glycemic control in very young children with T1D, and in a larger cohort We advocate for use and further verification (López-Lópezetal.).

Impact on global diabetes care

These studies highlight the need for adaptable solutions to address disparities in diabetes care across different health systems. Complex technologies may not be feasible in low-resource settings, but simple and effective tools such as anion gap normalization time (AGNT) and scalable neuropathy screening methods can significantly improve results It may be. These approaches allow early intervention and better complication management without the need for high-cost infrastructure. Cost-effective evidence-based strategies tailored to resource-limited environments are key to ensuring equitable access to quality diabetes care (7).

Advances in machine learning (ML)-based prediction and advanced hybrid closed-loop (AHCL) systems have transformed diabetes management in technologically developed settings. These innovations help optimize glycemic control, reduce variability, reduce the risk of complications, and improve the overall quality of life in people with type 1 diabetes (quality of life for people with type 1 diabetes) will improve.8). However, the high cost and limited availability of these technologies create barriers for many individuals, especially in low- and middle-income countries. Filling this gap requires collaboration between healthcare providers, policymakers and industry leaders, developing policies that ensure these life-changing innovations become affordable and widely accessible I will.

Equitable diabetes care relies on global cooperation. High-resource institutions need to play an active role in capacity building efforts by investing in training programs, telehealth support and knowledge sharing initiatives for healthcare providers in underresourced regions. Strengthening local expertise and improving access to essential technologies such as continuous glucose monitoring (CGM) and AHCL systems will help clinicians provide better care for children with type 1 diabetes . Policymakers should prioritize investing in diabetes-related healthcare policies and ensure affordability and accessibility remain at the forefront of decision-making.

Future research should also consider socioeconomic, cultural and regional differences to create scalable and practical solutions. Interventions should be designed to meet the specific needs of different populations and to account for variations in health infrastructure, patient education, and treatment accessibility. Sustainable advances in diabetes management rely on balancing innovation and real feasibility, providing the care that every child needs to thrive, regardless of their location or financial background. I guarantee you will receive it.

Conclusion

This research topic highlights how innovation and research can help manage diabetes complications in children and adolescents. By reducing resource gaps and using technology, the global diabetic community can improve care for all young patients. Achieving this goal requires a strong commitment to teamwork, advocacy and health equity.

Author's contribution

GF: Writing – Original draft, Writing – Reviews and Editing. MMAT: Written – Reviews and Editing. RF: Writing – Original draft, Writing – Reviews and Editing. EM: Writing – Original draft, writing – Reviews and editing. MMAR: Writing – Original draft, writing – Reviews and editing.

Conflict of interest

The authors declare that this study was conducted in the absence of commercial or financial relationships that could be interpreted as a potential conflict of interest.

The author declared upon submission that he was a member of the Frontier Editorial Board. This had no impact on the peer review process and final decisions.

Publisher's Notes

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