Lack of consideration of socioeconomic factors in transition programme of adolescents with type 1 diabetes: A systematic review.

The transition of adolescents with type 1 diabetes should be organized such that loss of follow-up and deterioration of patients' metabolic control are minimized. OBJECTIVE: Our study aimed to ascertain whether socioeconomic status is featured in the characteristics of adolescents with type 1 diabetes in transition programmes and their inclusion in transition programmes. RESEARCH DESIGN AND METHODS: A systematic review of the literature was performed according to PRISMA recommendations. All articles published between 2010 and 2023 were considered. Studies that described a transition programme for adolescents or young adults with T1DM were included. RESULTS: After screening, 18 studies were included. Different transition programmes were proposed (exchanges between professionals, coordinators, and transition clinics). Nine articles described socio-economic factors. The educational level was the most frequently reported. Only three studies evaluated the impact of one parameter on transition success: a lower education level was associated with more hospital visits for hyperglycaemia, and the other did not report any socioeconomic factor associated with clinic attendance. CONCLUSIONS: The socioeconomic status of type 1 diabetes is poorly described in transition programmes, and the few that do make mention of it, offer little information about patient management.

[The value of assessing the socioeconomic context during the transition of adolescents with type 1 diabetes]. / Intérêt de l'évaluation du contexte socio-économique lors de la transition des adolescents diabétiques de type 1.

The follow-up of diabetic patients is marked by a period of transition from pediatric care to adult services. The major challenge of this transition is to ensure continuity of care under the best possible conditions. Socio-economic factors must be taken into account to ensure that care is adapted to patients' needs.

Evaluation of the transition program at the University Hospital of Reims from 2015 to 2020.

The transition of young type 1 diabetic (T1D) patients from pediatric to adult healthcare is a high-risk period of loss to follow-up. Since 2015, we have implemented a transition program, involving both pediatric and adult clinicians. The main objective was to evaluate the number of patients who had succeeded this transition program at 1 year. We found that 86% of patients underwent the complete transition program. However, adverse outcomes occurred in 19.1% of patients at 1 year but decreased to 2.9% after 3 years. In 63% of patients their HbA1c level had deteriorated 1 year after the transition day and this level stabilized at around 8% in the following 2 and 3 years. In patients who had improved HbA1c levels the body mass index was lower (P = 0.03) and they lived alone (P = 0.04). Although our program seemed to allow a better follow-up than previously described, this study highlights the importance of further supporting this transition period.

Temporal deep learning framework for retinopathy prediction in patients with type 1 diabetes.

The adoption of electronic health records in hospitals has ensured the availability of large datasets that can be used to predict medical complications. The trajectories of patients in real-world settings are highly variable, making longitudinal data modeling challenging. In recent years, significant progress has been made in the study of deep learning models applied to time series; however, the application of these models to irregular medical time series (IMTS) remains limited. To address this issue, we developed a generic deep-learning-based framework for modeling IMTS that facilitates the comparative studies of sequential neural networks (transformers and long short-term memory) and irregular time representation techniques. A validation study to predict retinopathy complications was conducted on 1207 patients with type 1 diabetes in a French database using their historical glycosylated hemoglobin measurements, without any data aggregation or imputation. The transformer-based model combined with the soft one-hot representation of time gaps achieved the highest score: an area under the receiver operating characteristic curve of 88.65%, specificity of 85.56%, sensitivity of 83.33% and an improvement of 11.7% over the same architecture without time information. This is the first attempt to predict retinopathy complications in patients with type 1 diabetes using deep learning and longitudinal data collected from patient visits. This study highlighted the significance of modeling time gaps between medical records to improve prediction performance and the utility of a generic framework for conducting extensive comparative studies.

Characteristics of newly diagnosed type 1 diabetes in paediatric and adult population from Reims University Hospital, France from 1997 to 2019.

French health insurance data showed that the incidence of type 1 diabetes mellitus (T1DM) in children increased over the years to 2015. The objective of our study was to assess the evolution of the number of incident cases of paediatric and adult type 1 diabetes in our institution, and to describe their clinical presentation and its evolution. All patients with T1DM managed at diagnosis at Reims University Hospital between 1997 and 2019 were included. The clinical and biological data were extracted from the Champagne-Ardenne Diabetes Network database. Included were 847 patients with a median age of 10.3 years. Diagnosis was established in 71% of cases before 15 years, 7.4% after 35 years. The number of newly diagnosed cases was 3.6-times higher in 2019 compared to 1997. Ketoacidosis, the frequency of which decreased with age (P < 0.0001), revealed diabetes in a total of 32% of cases and in 46% of children under 5 years. It was more severe in children than in adults (P = 0.03), and its frequency increased over the study period. Hypotrophy was found in 23% of children under 15 years of age, and was more pronounced before 5 years of age, with no improvement over time. We saw an increase in the frequency of obesity or overweight among adults. Our study showed an increase in incident cases of diabetes in our hospital that continued over time for both children and adults. Clinical features at diagnosis deteriorated during this period for those under 15 years of age with an increase in ketoacidosis frequency.

Presenting features and molecular genetics of primary hyperparathyroidism in the paediatric population.

AIM: To describe the presenting features and molecular genetics of primary hyperparathyroidism (PHPT) in the paediatric population. METHODS: Retrospective study of 63 children diagnosed with primary PHPT from 1998 to 2018. RESULTS: Compared to older children, infants were often asymptomatic (54% vs 15%, P = 0.002) with a milder form of PHPT. When symptomatic, children and adolescents mostly presented with non-specific complaints such as asthenia, depression, weight loss, vomiting or abdominal pain. A genetic cause of PHPT was identified in about half of this cohort (52%). The infancy period was almost exclusively associated with mutation in genes involved in the calcium-sensing receptor (CaSR) signalling pathway (i.e. CaSR and AP2S1 genes, 'CaSR group'; 94% of infants with mutations) whereas childhood and adolescence were associated with mutation in genes involved in parathyroid cell proliferation (i.e. MEN1, CDC73, CDKN1B and RET genes, 'cell proliferation group'; 69% of children and adolescents with mutations). Although serum calcium levels did not differ between the two groups (P = 0.785), serum PTH levels and the urinary calcium/creatinine ratio were significantly higher in 'cell proliferation group' patients compared to those in the 'CaSR group' (P = 0.001 and 0.028, respectively). CONCLUSION: Although far less common than in adults, PHPT can develop in children and is associated with significant morbidity. Consequently, this diagnosis should be considered in children with non-specific complaints and lead to monitoring of mineral homeostasis parameters. A genetic cause of PHPT can be identified in about half of these patients.