Predicting age at onset of type 1 diabetes in children using regression, artificial neural network and Random Forest: A case study in Saudi Arabia.

The rising incidence of type 1 diabetes (T1D) among children is an increasing concern globally. A reliable estimate of the age at onset of T1D in children would facilitate intervention plans for medical practitioners to reduce the problems with delayed diagnosis of T1D. This paper has utilised Multiple Linear Regression (MLR), Artificial Neural Network (ANN) and Random Forest (RF) to model and predict the age at onset of T1D in children in Saudi Arabia (S.

Adipsic Diabetes Insipidus in Children: A Case Report and Practical Guide.

BACKGROUND Diabetes insipidus (DI) is a clinical syndrome characterized by polyuria and polydipsia that result from a deficiency of antidiuretic hormone (ADH), central DI, or resistance to ADH, nephrogenic DI. In otherwise healthy patients with DI, normal thirst mechanism, and free access to water, the thirst system can maintain plasma osmolality in the near-normal range. However, in cases where DI presents with adipsia, cognitive impairment, or restricted access to water, true hypernatremia may occur, leading to severe morbidity and mortality.

Mean glycosylated hemoglobin in children with type 1 diabetes at King Fahad Medical City, Riyadh, Saudi Arabia.

Background: Type 1 diabetes is the third most common chronic disease among teenagers. In Saudi Arabia, there is a gap of knowledge regarding hemoglobin A1C (HbA1c) concentration levels, and adherence to regular follow-up visits by patients. The aim of this study was to determine the mean glycosylated hemoglobin (HbA1c) levels in diabetic children who have been diagnosed with type 1 diabetes and were being followed up at a tertiary care center in Saudi Arabia.