Accuracy and performance of continuous glucose monitors in athletes. (February 2017)

• Record Type: Journal Article
• Authors: Thomas, Felicity; Pretty, Christopher G.; Signal, Matthew; Shaw, Geoffrey; Chase, J. Geoffrey
• Is Part Of: Biomedical signal processing and control. Volume 32(2017)
• Page Start: 124
• Page End: 129
• Publication Date: 2017-02
• Subjects: Continuous glucose monitoring -- Accuracy -- Correlation -- Exercise -- Athlete; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2016.08.007
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: During steady state exercise CGM devices perform with high accuracy in athletes. Error between CGM values and blood glucose increased when a bolus was given. CGM devices agree very well with each other during rigorous exercise. Further investigation of using CGM to enhance athlete nutrition is justified. Abstract: Continuous glucose monitoring (CGM) devices, with their 1–5 min measurement interval, allow blood glucose dynamics to be captured more frequently and less invasively than traditional measures of blood glucose concentration (BG). These devices are primarily designed for the use in type 1 and type 2 diabetic patients to aid BG regulation. However, because of their increased measurement frequency and reduced invasiveness CGM devices have been recently applied to other subject cohorts, such as intensive care patients and neonates. One unexamined cohort is athletes. Continuous monitoring of an athlete's BG has the potential to increase race performance, speed recovery, and aid training. However, before these benefits can be realised the accuracy and performance of CGM devices in active athletes must be evaluated. Two Ipro2 and one Guardian Real-time CGM devices (Medtronic Minimed, Northridge, CA, USA) were inserted into 10 subjects (resting HR < 60 beats per minute (bpm), training 6–15 h per week). For each participant a fasting continuous exercise test was carried out until failure, ∼90 min, and glucoses boluses were given at 30 min (0.5 g/kg) and failure (1 g/kg). Reference BG measurements were taken every 10 min for the first 60 min, every 5 min until failure + 30 min and every 10 min until failure + 60 min with an Abbott Optimum Xceed glucometer. Pre-glucose bolus, all sensors perform better compared to results seen in diabetic cohorts with median mean absolute relative difference (MARD) of 9.7%, 9.6% and 11.1% for the two Ipro2's and the Real-time, respectively. However, there is increased error post-bolus likely due to the gradient of BG change being higher, so the delay in transport to interstitial fluid and sensor results in a larger discrepancy from reference values. CGM devices agree very well with each other during rigorous exercise with median cross-correlation coefficients between 0.88 and 0.97 for the different sensor pairings. This good correlation between all three signals suggests the error between glucose measured by CGM and from blood is not random, but likely due to transport/uptake effects. As the interstitial fluid is the medium from which glucose enters muscle cells, this CGM value might be more useful than BG in determining glucose availability for athletes.