Standardised practices in the networked management of congenital hyperinsulinism: a UK national collaborative consensus
MG Shaikh, AK Lucas-Herald, A Dastamani… - Frontiers in …, 2023 - frontiersin.org
Congenital hyperinsulinism (CHI) is a condition characterised by severe and recurrent
hypoglycaemia in infants and young children caused by inappropriate insulin over …
hypoglycaemia in infants and young children caused by inappropriate insulin over …
Treatment recommendations for glycogen storage disease type IB-associated neutropenia and neutrophil dysfunction with empagliflozin: Consensus from an …
SC Grünert, TGJ Derks, H Mundy, RN Dalton… - Molecular genetics and …, 2024 - Elsevier
Glycogen storage disease type Ib (GSD Ib, biallelic variants in SLC37A4) is a rare disorder
of glycogen metabolism complicated by neutropenia/neutrophil dysfunction. Since 2019, the …
of glycogen metabolism complicated by neutropenia/neutrophil dysfunction. Since 2019, the …
Current understanding on pathogenesis and effective treatment of glycogen storage disease type Ib with empagliflozin: new insights coming from diabetes for its …
A Maiorana, F Tagliaferri, C Dionisi-Vici - Frontiers in Endocrinology, 2023 - frontiersin.org
Glycogen storage type Ib (GSDIb) is a rare inborn error of metabolism caused by glucose-6-
phosphate transporter (G6PT, SLC37A4) deficiency. G6PT defect results in excessive …
phosphate transporter (G6PT, SLC37A4) deficiency. G6PT defect results in excessive …
The behaviour change behind a successful pilot of hypoglycaemia reduction with HYPO-CHEAT
Background Children with hypoglycaemia disorders, such as congenital hyperinsulinism
(CHI), are at constant risk of hypoglycaemia (low blood sugars) with the attendant risk of …
(CHI), are at constant risk of hypoglycaemia (low blood sugars) with the attendant risk of …
Artificial intelligence in paediatric endocrinology: conflict or cooperation
P Dimitri, MO Savage - Journal of Pediatric Endocrinology and …, 2024 - degruyter.com
Artificial intelligence (AI) in medicine is transforming healthcare by automating system tasks,
assisting in diagnostics, predicting patient outcomes and personalising patient care …
assisting in diagnostics, predicting patient outcomes and personalising patient care …
Hypoglycaemia in adrenal insufficiency
SC Lee, ES Baranowski, R Sakremath… - Frontiers in …, 2023 - frontiersin.org
Adrenal insufficiency encompasses a group of congenital and acquired disorders that lead
to inadequate steroid production by the adrenal glands, mainly glucocorticoids …
to inadequate steroid production by the adrenal glands, mainly glucocorticoids …
The use of CGM to identify hypoglycemia and glycemic patterns in congenital hyperinsulinism
M Gariepy, N Yoosefi, C Silva, JP Chanoine… - Journal of Pediatric …, 2023 - degruyter.com
Objectives Unrecognized hypoglycemia, especially in the neonatal population, is a
significant cause of morbidity and poor neurologic outcomes. Children with congenital …
significant cause of morbidity and poor neurologic outcomes. Children with congenital …
The Utility and Safety of a Continuous Glucose Monitoring System (CGMS) in Asphyxiated Neonates during Therapeutic Hypothermia
L Giordano, A Perri, E Tiberi, A Sbordone, ML Patti… - Diagnostics, 2023 - mdpi.com
Background: The present study was designed to assess the feasibility and reliability of a
Continuous Glucose Monitoring System (CGMS) in a population of asphyxiated neonates …
Continuous Glucose Monitoring System (CGMS) in a population of asphyxiated neonates …
First Accuracy and User-Experience Evaluation of New Continuous Glucose Monitoring System for Hypoglycemia Due to Hyperinsulinism
C Worth, S Worthington, S Auckburally… - Journal of Diabetes …, 2024 - journals.sagepub.com
Introduction: Patients with congenital hyperinsulinism (HI) require constant glucose
monitoring to detect and treat recurrent and severe hypoglycemia. Historically, this has been …
monitoring to detect and treat recurrent and severe hypoglycemia. Historically, this has been …
Machine Learning in Diabetes Modeling
Machine learning (ML) has become an integral component of diabetes research. Its
applications encompass prediction, identification, classification, and diagnosis of diabetes …
applications encompass prediction, identification, classification, and diagnosis of diabetes …