Treatment of Hypothalamic Obesity With GLP-1 Analogs.

Introduction: Congenital and acquired damage to hypothalamic nuclei or neuronal circuits controlling satiety and energy expenditure results in hypothalamic obesity (HO). To date, successful weight loss and satiety has only been achieved in a limited number of affected patients across multiple drug trials. Glucagon-like peptide-1 (GLP-1) acts via central pathways that are independent from the hypothalamus to induce satiety.

Opportunities for digitally-enabled personalization and decision support for pediatric growth hormone therapy.

Smart technologies and connected health are providing opportunities for improved healthcare for chronic conditions. Acceptance by healthcare professionals (HCPs) and patients is crucial for successful implementation. Evidence-based standards, technological infrastructure and regulatory processes are needed to integrate digital tools into clinical practice.

Children and young people's preferences and needs when using health technology to self-manage a long-term condition: a scoping review.

Background: The use of patient-facing health technologies to manage long-term conditions (LTCs) is increasing; however, children and young people (CYP) may have preferences about health technologies which they interact or engage with, that influence their decision to use these technologies.

Aims: To identify CYP's reported preferences about health technologies to self-manage LTCs.

Methods: We undertook a scoping review, searching MEDLINE, PsycINFO and CINAHL in July 2021.

Artificial intelligence in paediatric endocrinology: conflict or cooperation.

Artificial intelligence (AI) in medicine is transforming healthcare by automating system tasks, assisting in diagnostics, predicting patient outcomes and personalising patient care, founded on the ability to analyse vast datasets. In paediatric endocrinology, AI has been developed for diabetes, for insulin dose adjustment, detection of hypoglycaemia and retinopathy screening; bone age assessment and thyroid nodule screening; the identification of growth disorders; the diagnosis of precocious puberty; and the use of facial recognition algorithms in conditions such as Cushing syndrome, acromegaly, congenital adrenal hyperplasia and Turner syndrome. AI can also predict those most at risk from childhood obesity by stratifying future interventions to modify lifestyle.