| Title: | Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments |
| Author(s): | Diouri O; Cigler M; Vettoretti M; Mader JK; Choudhary P; Renard E; Consortium HR; |
| Address: | "Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France. Department of Physiology, Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, Montpellier, France. Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria. Department of Information Engineering, University of Padova, Padova, Italy. Department of Diabetes and Nutritional Sciences, King's College London, London, UK. Diabetes Research Centre, University of Leicester, Leicester, UK" |
| ISSN/ISBN: | 1520-7560 (Electronic) 1520-7552 (Print) 1520-7552 (Linking) |
| Abstract: | "The main objective of diabetes control is to correct hyperglycaemia while avoiding hypoglycaemia, especially in insulin-treated patients. Fear of hypoglycaemia is a hurdle to effective correction of hyperglycaemia because it promotes under-dosing of insulin. Strategies to minimise hypoglycaemia include education and training for improved hypoglycaemia awareness and the development of technologies to allow their early detection and thus minimise their occurrence. Patients with impaired hypoglycaemia awareness would benefit the most from these technologies. The purpose of this systematic review is to review currently available or in-development technologies that support detection of hypoglycaemia or hypoglycaemia risk, and identify gaps in the research. Nanomaterial use in sensors is a promising strategy to increase the accuracy of continuous glucose monitoring devices for low glucose values. Hypoglycaemia is associated with changes on vital signs, so electrocardiogram and encephalogram could also be used to detect hypoglycaemia. Accuracy improvements through multivariable measures can make already marketed galvanic skin response devices a good noninvasive alternative. Breath volatile organic compounds can be detected by dogs and devices and alert patients at hypoglycaemia onset, while near-infrared spectroscopy can also be used as a hypoglycaemia alarms. Finally, one of the main directions of research are deep learning algorithms to analyse continuous glucose monitoring data and provide earlier and more accurate prediction of hypoglycaemia. Current developments for early identification of hypoglycaemia risk combine improvements of available 'needle-type' enzymatic glucose sensors and noninvasive alternatives. Patient usability will be essential to demonstrate to allow their implementation for daily use in diabetes management" |
| Keywords: | "Animals Blood Glucose Blood Glucose Self-Monitoring/methods *Diabetes Mellitus, Type 1/complications Dogs Humans *Hypoglycemia/chemically induced/diagnosis/prevention & control Hypoglycemic Agents/therapeutic use Insulin/therapeutic use Insulin Infusion S;" |
| Notes: | "MedlineDiouri, Omar Cigler, Monika Vettoretti, Martina Mader, Julia K Choudhary, Pratik Renard, Eric eng Research Support, Non-U.S. Gov't Review Systematic Review England 2021/03/26 Diabetes Metab Res Rev. 2021 Oct; 37(7):e3449. doi: 10.1002/dmrr.3449. Epub 2021 Mar 24" |
