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.
Subject(s)
Diabetes Mellitus, Type 1 , Hypoglycemia , Animals , Blood Glucose , Blood Glucose Self-Monitoring/methods , Diabetes Mellitus, Type 1/complications , Dogs , Humans , Hypoglycemia/chemically induced , Hypoglycemia/diagnosis , Hypoglycemia/prevention & control , Hypoglycemic Agents/therapeutic use , Insulin/therapeutic use , Insulin Infusion SystemsABSTRACT
Almost 45 000 patients with type 1 diabetes are concerned in France by outpatient insulin pump therapy. The first systems of insulin pump therapy guided by glycaemia have evolved driven by the work carried out by multi-disciplinary research teams. Today, the outpatient treatment of type 1 diabetes by an artificial pancreas is on the point of becoming reality.
Subject(s)
Diabetes Mellitus, Type 1/surgery , Pancreas, Artificial , Humans , Therapies, InvestigationalABSTRACT
BACKGROUND: Meal lipids (LIP) and proteins (PRO) may influence the effect of insulin doses based on carbohydrate (CHO) counting in patients with type 1 diabetes (T1D). We developed a smartphone application for CHO, LIP, and PRO counting in daily food and assessed its usability in real-life conditions and potential usefulness. METHODS: Ten T1D patients used the android application for 1 week to collect their food intakes. Data included meal composition, premeal and 2-hour postmeal blood glucose, corrections for hypo- or hyperglycemia after meals, and time for entering meals in the application. Meal insulin doses were based on patients' CHO counting (application in blinded mode). Linear mixed models were used to assess the statistical differences. RESULTS: In all, 187 meals were analyzed. Average computed CHO amount was 74.37 ± 31.78 grams; LIP amount: 20.26 ± 14.28 grams and PRO amount: 25.68 ± 16.68 grams. Average CHO, LIP, and PRO contents were significantly different between breakfast and lunch/dinner. The average time for meal entry in the application moved from 3-4 minutes to 2.5 minutes during the week. No significant impact of LIP and PRO was found on available blood glucose values. CONCLUSION: Our study shows CHO, LIP, and PRO intakes can be easily captured by an application on smartphone for meal entry used by T1D patients. Although LIP and PRO meal contents did not influence glucose levels when insulin doses were based on CHO in this pilot study, this application could be used for further investigation of this topic, including in closed-loop conditions.