Using a stochastic model to detect unusual continuous glucose monitor behaviour in newborn infants (2012)
Type of ContentConference Contributions - Published
PublisherUniversity of Canterbury. Mechanical Engineering
Abnormal blood glucose (BG) concentrations have been associated with negative outcomes in critically ill adults and infants. Diagnosis of hyperglycaemia and hypoglycaemia is by BG measurements, which are typically taken several hours apart due to the clinical effort required. Continuous glucose monitoring (CGM) devices, which take measurements every 5 minutes, have the potential to improve the detection and diagnosis of these glycaemic abnormalities. There have been relatively few successful investigations of CGM devices in the ICU, and one study reported significant sensor noise. If CGM devices are going to be used in the clinical setting to monitor, diagnose and potentially help treat glycaemic abnormalities, clinicians need to know data are reliable and accurate. This study uses CGM data from neonatal infants to develop a tool that will aid clinicians in identifying unusual CGM behaviour. A stochastic model was created to classify CGM measurements with the aim of highlighting unusual CGM behaviour. In addition, the method uses a colour coded CGM trace to convey the information quickly and efficiently, either retrospectively or in real-time. The method has been used to detect unusual hypoglycaemic events and potential sensor degradation, both of which need to be interpreted with care. Overall, while BG measurements are required to make definitive conclusions about glycaemic events, the stochastic model provides another level of information to aid users in interpretation and decision making.
CitationSignal, M., Le Compte, A.J., Harris, D.L., Weston, P.J., Harding, J.E., Chase, J.G. (2012) Using a stochastic model to detect unusual continuous glucose monitor behaviour in newborn infants. Budapest, Hungary: 8th IFAC Symposium on Biological and Medical Systems (BMS12), 29-31 Aug 2012. Biological and Medical Systems, 8, 1, 248-253.
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Keywordshypoglycaemia; continuous glucose monitoring; modelling; detection; critically ill; infant; preterm
ANZSRC Fields of Research32 - Biomedical and clinical sciences::3202 - Clinical sciences::320208 - Endocrinology
40 - Engineering::4003 - Biomedical engineering::400305 - Biomedical instrumentation
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Impact of calibration algorithms on hypoglycaemia detection in newborn infants using continuous glucose monitors Signal, M.; Le Compte, A.J.; Harris, D.L.; Weston, P.J.; Harding, J.E.; Chase, Geoff (University of Canterbury. Mechanical Engineering, 2012)Neonatal hypoglycaemia is a common condition that can cause seizures and serious brain injury in infants. It is diagnosed by blood glucose (BG) measurements, often taken several hours apart. Continuous glucose monitoring ...
Continuous glucose monitoring in newborn infants: Effect of calibration measurements and detected hypoglycaemia Thomas, F.; Signal, M.K.; Harris, D.L.; Weston, P.J.; Harding, J.E.; Shaw, Geoff; Chase, Geoff (University of Canterbury. Mechanical Engineering, 2013)Neonatal glycaemia is highly variable and can cause serious brain injury if uncontrolled . However, monitoring infants’ blood glucose (BG) levels via frequent BG measurements is not achievable due to a lack of blood and ...
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